<%BANNER%>

Regional landscape analysis and reserve design to conserve Florida's biodiversity

University of Florida Institutional Repository
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PAGE 1

REGIONAL LANDSCAPE ANALYSIS AND RESERVE DESIGN TO CONSERVE FLORIDAS BIODIVERSITY By THOMAS SCOTT HOCTOR A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2003

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Copyright 2003 by Thomas Scott Hoctor

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ACKNOWLEDGMENTS Many different people have helped shape my thinking and provided support through the long process of completing this work. First, I want to express my sincere gratitude to my parents, Michael and Lorraine Hoctor, for all of their support, love, and understanding throughout the years. They have been very patient throughout my long graduate career but always had the confidence that I would finally finish. I would not have been a graduate student at the University of Florida and I would never have developed the conceptual foundation of my work and expertise without the guidance of Dr. Larry Harris. Larry created the foundation of ecological conservation in Florida upon which this dissertation is built. There would not be a Florida Ecological Network without Larry's blood, sweat, tears, and inspiration; and I and innumerable others are indebted to him for his vision for saving Florida's natural heritage. Larry is a conservation scholar without peer, and I have very much enjoyed all of the challenges and intellectual support that our collaboration has fostered. Peggy Carr and Paul Zwick have provided me with immeasurable support in funds, space, time, guidance, collaboration, and friendship. One of my luckiest moments was when I met Peggy and Paul early in my graduate career, working together on the Cross Florida Greenway Management Plan. Their support and encouragement have been instrumental to my success. Peggy Carr reviewed all chapters in draft and her comments greatly strengthened the clarity of the central message of this work. iii

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I also want to thank the many students and co-workers who helped me along the way. Jason Teisinger provided essential help developing the bear habitat models; and was a valued fishing partner. Karen Whitney helped develop the methods for creating bear connectivity cost surfaces and contributed to my thoughts on the importance of reserve networks. Crystal Goodison, Patty Hernandez, Jessica Green, Christy McCain, and Wendy Robinson Rieth all helped collect and analyze the data for the ecoregional planning analysis. Rich Doty and Juna Papajorgji were instrumental in developing the computer code for the Florida Ecological Network analysis. Dan Smith contributed important information on highway projects and wildlife movement mitigation structures. Maynard Hiss provided almost endless commentary, help, and prodding that expanded my thinking and increased my motivation to finish. The various birding trips with Kurt Leuschner were a welcome respite from job and dissertation obligations. All have been good friends and compatriots along the way. Many others also contributed. Mark Benedict provided conceptual help and much needed organizational skills during the development of the Florida Ecological Network project. Richard Hilsenbeck, Ray Moranz, Wendy Castor, and others at the Florida Chapter of the Nature Conservancy were integral to accomplishing the ecoregional planning analysis. I am also indebted to the many scientists who contributed to the identification of focal species and natural communities. Dave Maehr deserves special praise for his intellectual support and friendship. Dave helped pull me through this process more than once. He contributed instrumental comments on various sections of my dissertation, decreasing its length and increasing its impact. iv

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I also want to thank my committee (Larry Harris, Peggy Carr, Tom Crisman, Joe Schaefer, and Mike Binford) for their support, patience, and perseverance. All helped me at critical times during my graduate program. Their encouragement toward the end of this process was essential. The Florida Ecological Network was funded by the Florida Department of Environmental Protection and the Florida Department of Transportation. Their support was essential and is much appreciated. I also want to thank the staff of the FDEP's Office of Greenways and Trails for their hard work and perseverance through the implementation process for the Florida Ecological Network. The ecoregional planning analysis was funded by The Nature Conservancy; I hope that future collaborations will prove as interesting and fruitful. Randy Kautz from the Florida Fish and Wildlife Conservation Commission provided data and other help that greatly improved the thoroughness of this work. Florida Natural Areas Inventory also provided several datasets that improved the specificity of the Florida Ecological Network and were essential for completing the Florida Peninsula and Tropical Florida ecoregional plans. I also want to thank my two brothers, Jim and Dan. I enjoyed all of the mutual travails Dan and I shared as resident advisors in the old athletic dorm, Yon Hall. Those memories will not fade anytime soon. The occasional fishing trips with Jim provided much-needed relief throughout this process. Finally, I want to thank Kristin Leuschner for her simultaneous support and cajolery. Her friendship, wittiness, sagacity, and keen sense of irony have been very important to me throughout this long, hard journey. v

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TABLE OF CONTENTS page ACKNOWLEDGMENTS...........................................................................................iii ABSTRACT..................................................................................................................x CHAPTER 1 INTRODUCTION...................................................................................................1 Study Area.............................................................................................................10 General Geographic Information System Methods...............................................13 2 THE FLORIDA ECOLOGICAL NETWORK.......................................................17 Introduction............................................................................................................17 Methods..................................................................................................................20 Review Process...................................................................................................20 Analysis Used to Identify the Florida Ecological Network................................20 Results....................................................................................................................34 Comparisons to Other Ecological Inventories....................................................36 Landscape Comparisons.....................................................................................41 Representation....................................................................................................43 Discussion..............................................................................................................47 3 LANDSCAPE CONNECTIVITY FOR THE FLORIDA BLACK BEAR...........54 Introduction............................................................................................................54 Florida Black Bear Ecology...................................................................................59 Methods..................................................................................................................65 Multiple Criteria-Based Cost Surfaces...............................................................69 Simplified Cost Surfaces....................................................................................91 Exponential Function Cost Surfaces...................................................................96 Using Multiple Logistic Regression Modeling to Develop Cost Surfaces.......100 Creation of Analysis Masks to Modify Cost Surfaces......................................107 Sources and Destinations for LCP Analysis.....................................................108 Identifying Florida Black Bear Habitat and Landscape Linkage Opportunities............................................................................................109 Results and Discussion........................................................................................112 vi

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Stepwise Multiple Logistic Regression Habitat Model....................................112 Alternative Model Multiple Logistic Regression Results.................................114 Comparison of LCP Results Using Different Intensive Land Use Masks........118 Least Cost Path Results for Landscape Linkages between Major Populations...............................................................................................122 Assessment of Potential Landscape Linkages between Major Populations and Other Bear Populations or Habitat....................................................129 Statewide Black Bear Habitat and Landscape Linkages..................................132 Habitat, Linkages, Conservation Lands, and the Florida Ecological Network....................................................................................................142 Habitat Connectivity and Potential Bear Population Size................................150 Potential Black Bear Habitat, Landscape Linkages, and Development Pressure....................................................................................................151 Conclusions..........................................................................................................157 Recommendations for Conducting LCP Analyses to Identify Potential Landscape Linkages................................................................................157 Landscape Ecology and a Florida Black Bear Metapopulation........................159 Connectivity Beyond Bears..............................................................................166 Landscape Conservation Opportunities............................................................168 Research Priorities for Protecting a Statewide Florida Black Bear Metapopulation........................................................................................172 4 ECOREGIONAL PLANNING FOR BIODIVERSITY CONSERVATION IN THE FLORIDA PENINSULA.......................................................................175 Introduction..........................................................................................................175 Description of the Florida Peninsula Ecoregion...............................................180 Description of the Tropical Florida Ecoregion.................................................183 Methods................................................................................................................188 Selecting Species and Natural Communities....................................................188 Setting Conservation Goals for Species and Natural Communities.................191 Assessing Viability...........................................................................................200 Portfolio Site Selection.....................................................................................208 Results and Discussion........................................................................................216 Florida Peninsula Ecoregion Portfolio..............................................................216 Tropical Florida Ecoregion Portfolio................................................................218 Goal Achievement............................................................................................220 Conservation Land and Open Water Statistics.................................................228 Comparison with the Florida Ecological Network...........................................228 Comparison with Black Bear Habitat and Landscape Linkages.......................236 Conclusions..........................................................................................................238 5 CONCLUSIONS, POLICY ISSUES, AND RECOMMENDATIONS..............245 Reserve Design Analysis: Landscape Approaches and Methods........................245 Land Conservation Policy Issues and Recommendations...................................254 vii

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Land Protection.................................................................................................254 Land Management ...........................................................................................256 Growth Management........................................................................................261 Transportation Planning....................................................................................262 Ecological Linkages across State Borders...........................................................264 Protecting Biodiversity and Ecosystem Services.................................................265 APPENDIX A DATA FOR FLORIDA BLACK BEAR LANDSCAPE REGRESSION ANALYSIS..........................................................................................................268 B COMPARISON OF MAJOR COST SURFACE VARIATIONS.......................272 Cost Surface 1 and Cost Surface 2: The Influence of Adding Major Roads and Large Water Bodies...........................................................................272 Cost Surface 1 and Cost Surface 3: Testing the Influence of Changing the Range of Cost Surface Value...................................................................275 Cost Surface 3 versus Cost Surface 4: Testing the Influence of Differential Weighting of Input Indices (SUAs).........................................................277 Cost Surface 5 versus Cost Surface 6: Testing the Performance of Simplified Surfaces and the Influence of Habitat Patch Size....................................279 Cost Surfaces 7, 8, and 9: Testing the Performance of Simplified Surfaces.......281 Cost Surfaces 3 and 4 versus Cost Surfaces 10 and 11: Testing the Influence of Drastically Changing the Range of Cost Surface Values....................281 Cost Surfaces 10 and 11 versus Cost Surfaces 12 and 13: Testing the Effect of Adding Major Roads and Large Water Bodies to Expanded Cost Surfaces...........................................................................................283 Cost Surfaces 8 and 9 versus Cost Surfaces 14 and 15: Testing the Influence of Drastically Changing the Range of Cost Surface Values....................286 Cost Surface 16 and Cost Surface 17: Comparing Cost Surfaces Created Using Multiple Logistic Regression........................................................286 C DETAILED COMPARISON OF LEAST COST PATH RESULTS FOR THE BIG CYPRESS NATIONAL PRESERVE TO OCALA NATIONAL FOREST LANDSCAPE LINKAGE...................................................................290 D ASSESSMENT OF POTENTIAL LANDSCAPE LINKAGES BETWEEN MAJOR POPULATIONS AND OTHER BEAR POPULATIONS OR HABITAT.....................................................................................................301 Apalachicola National Forest to the Lower Suwannee National Wildlife Refuge and Goethe State Forest...............................................................301 Ocala National Forest to Twelve Mile Swamp....................................................303 Ocala National Forest to Gulf Coast Destinations...............................................306 Weekiwachee Conservation Area to Green Swamp, Goethe State Forest, and Lower Suwannee River National Wildlife Refuge..................................311 viii

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Big Cypress National Preserve to Myakka River State Park, Green Swamp Conservation Area, and Corbett Wildlife Management Area..................313 E FOCAL SPECIES FOR THE FLORIDA PENINSULA ECOREGION.............318 F FOCAL SPECIES FOR THE TROPICAL FLORIDA ECOREGION................325 G GOAL STATUS FOR FOCAL PLANT SPECIES IN THE FLORIDA PENINSULA ECOREGION...............................................................................331 H GOAL STATUS FOR FOCAL PLANT SPECIES IN THE TROPICAL FLORIDA ECOREGION....................................................................................335 I GOAL STATUS FOR FOCAL ANIMAL SPECIES IN THE FLORIDA PENINSULA ECOREGION...............................................................................340 J GOAL STATUS FOR FOCAL ANIMAL SPECIES IN THE TROPICAL FLORIDA ECOREGION....................................................................................345 K GOAL STATUS FOR NATURAL COMMUNITES IN THE FLORIDA PENINSULA ECOREGION...............................................................................348 L GOAL STATUS FOR NATURAL COMMUNITES IN THE TROPICAL FLORIDA ECOREGION....................................................................................350 LITERATURE CITED..............................................................................................352 BIOGRAPHICAL SKETCH.....................................................................................375 ix

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LIST OF TABLES Table page 2-1 Criteria for selecting Priority Ecological Areas for the Florida Ecological Network...............................................................................................................24 2-2 Landscape unit classification used in landscape linkage identification for the Florida Ecological Network..........................................................................28 2-3 Riverine suitability surface values for the Florida Ecological Network.............30 2-4 Hub-to-hub suitability surface values for the Florida Ecological Network.........31 2-5 Area of land in various land ownership categories within Floridas Ecological Network............................................................................................38 2-6 Comparison of the Florida Ecological Network, other ecological resource inventories, and existing and proposed conservation lands................................39 2-7 Comparison of roadless areas found in existing conservation lands and the those included in the Ecological Network..........................................................44 2-8 Comparison of the total land area of existing ecological community types (habitats) in the state of Florida with area of habitat types found in existing conservation lands and the amount included in the Ecological Network...........46 3-1 Seventeen cost surfaces used to assess landscape linkages for the Florida black bear............................................................................................................70 3-2 SUA ranking land cover types based on preference as habitat............................72 3-3 Ranking of potential habitat based on patch size................................................74 3-4 Habitat diversity rankings....................................................................................75 3-5 Ranking of distance from protected bear habitat 20,000 ha or larger.................77 3-6 Roadless area ranks based on size of the roadless areas and the percentage of bear habitat within roadless areas...................................................................79 x

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3-7 Ranking of road densities....................................................................................80 3-8 Ranking of distances from major roads...............................................................82 3-9 Land use intensity rankings.................................................................................84 3-10 Ranking of distances from major roads...............................................................85 3-11 Conservation land rankings.................................................................................86 3-12 Weighting factors used to create Cost Surface....................................................90 3-13 Cost Surface 5 categories and rankings...............................................................93 3-14 Cost Surface 6 categories and rankings...............................................................94 3-15 Cost Surface 7 categories and rankings...............................................................95 3-16 Cost Surface 8 categories and rankings...............................................................97 3-17 Cost Surface 9 categories and rankings...............................................................98 3-18 Comparison of original values from Cost Surface 3 and the transformed values using an exponential function to create Cost Surface 10.........................99 3-19 Comparison of original values from Cost Surface 8 and the transformed values to create Cost Surface 14.......................................................................101 3-20 Comparison of occurrences and random locations used for multiple logistic regression habitat model validation..................................................................116 3-21 Comparison of occurrences and random locations used for validation of the alternative multiple logistic regression habitat model................................119 3-22 Existing and proposed conservation land statistics for potential black bear habitat and landscape linkages..........................................................................144 3-23 Comparison statistics between potential black bear habitat and landscape linkages and the Florida Ecological Network...................................................146 4-1 Natural community classification and goals for the Florida Peninsula Ecoregion..........................................................................................................192 4-2 Natural community classification and goals for the Tropical Florida Ecoregion..........................................................................................................195 xi

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4-3 Data and criteria used in designing the terrestrial, aquatic and averaged viability indices.................................................................................................204 4-4 Additional data used to identify portfolio sites.................................................214 4-5 Goal achievement by taxonomic group for vertebrate species in the Florida Peninsula Ecoregion..........................................................................................223 4-6 Goal achievement by taxonomic group for vertebrate species in the Tropical Florida Ecoregion...............................................................................224 4-7 Conservation lands and open water statistics for the Florida Peninsula site portfolio......................................................................................................230 4-8 Conservation lands and open water statistics for the Tropical Florida site portfolio.............................................................................................................232 E-1 Focal species for the Florida Peninsula Ecoregion...........................................318 F-1 Focal species for the Tropical Florida Ecoregion.............................................325 G-1 Goal status for focal plant species in the Florida Peninsula Ecoregion.............331 H-1 Goal status for focal plant species in the Tropical Florida Ecoregion...............335 I-1 Goal status for focal animal species in the Florida Peninsula Ecoregion..........340 J-1 Goal status for focal animal species in the Tropical Florida Ecoregion............345 K-1 Goal status for natural communities in the Florida Peninsula Ecoregion.........348 L-1 Goal status for natural communities in the Tropical Florida Ecoregion............350 xii

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LIST OF FIGURES Figure page 2-1 Results of 1991 mapping workshop (charrette) coordinated by The Nature Conservancy........................................................................................................18 2-2 Major steps in the Florida Ecological Network modeling process......................21 2-3 Riverine cost surface example.............................................................................33 2-4 Florida Ecological Network model results..........................................................35 2-5 Comparison of the Ecological Network other statewide ecological resource inventories...........................................................................................................40 3-1 Process used to identify the land area with the potential to support a statewide black bear metapopulation..................................................................66 3-2 Cost Surface 1......................................................................................................88 3-3 Telemetry locations from major Florida black bear populations used in the multiple logistic regression analysis.................................................................105 3-4 Recent bear range map from the Florida Fish and Wildlife Conservation Commission......................................................................................................106 3-5 Comparison between a 3 X 3 and a 5 X 5 neighborhood for analyzing potential bottlenecks.........................................................................................110 3-6 Sources and destinations for assessing best potential landscape linkages.........111 3-7 Results of the primary version of the stepwise multiple logistic regression model.................................................................................................................115 3-8 Results of the alternative version of the multiple logistic regression model.....117 3-9 Comparison of LCP results for the three mask alternatives..............................121 xiii

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3-10 LCP results for the landscape linkage options between Big Cypress National Preserve (BCNP) and the Ocala National Forest...............................124 3-11 The landscape linkage between the Ocala National Forest and Osceola National Forest..................................................................................................127 3-12 LCP results for Osceola National Forest to Apalachicola National Forest landscape linkage..............................................................................................128 3-13 The LCP results for the landscape linkage between the Apalachicola National Forest and Eglin Air Force Base........................................................130 3-14 Forest cover compared to LCP results the Apalachicola National Forest and Eglin Air Force Base landscape linkage....................................................131 3-15 LCP results for landscape linkages between Apalachicola National Forest, Lower Suwannee National Wildlife Refuge (LSRNWR) and Goethe State Forest (GSF).............................................................................................133 3-16 The LCP results for the Ocala National Forest to Twelve Mile Swamp landscape linkage..............................................................................................134 3-17 The LCP results between Ocala National Forest and the Weekiwachee and Green Swamp conservation areas.....................................................................135 3-18 The LCP results for landscape linkages between Weekiwachee Conservation Area and the Green Swamp Conservation Area, Goethe State Forest, and Lower Suwannee National Wildlife Refuge.........................136 3-19 The LCP results between Big Cypress National Preserve and the Green Swamp Conservation Area, Myakka River State Park, and Corbett Wildlife Management Area...............................................................................137 3-20 Black bear habitat and landscape linkages statewide........................................140 3-21 Potential black bear habitat and landscape linkages with population cores and roadkills......................................................................................................141 3-22 Bear habitat and landscape linkages in south Florida........................................143 3-23 Existing and proposed conservation lands are shown on top of potential black bear habitat and landscape linkages........................................................145 3-24 Florida Ecological Network drawn on top of potential black bear habitat and landscape linkages......................................................................................147 xiv

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3-25 Black bear habitat and landscape linkages drawn on top of the Florida Ecological Network..........................................................................................149 3-26 Distribution of large black bear habitat blocks statewide..................................152 3-27 Largest blocks of black bear habitat in Florida.................................................153 3-28 Impact of future development on bear habitat and landscape linkages.............154 4-1 Boundaries of the four ecoregions in Florida....................................................177 4-2 Boundaries of the Florida Peninsula and Tropical Florida Ecoregions.............181 4-3 Process for identifying the site portfolios for the Florida Peninsula and Tropical Florida Ecoregions.............................................................................190 4-4 Subecoregions for the Florida Peninsula and Tropical Florida Ecoregions......201 4-5 The Florida Peninsula Ecoregion site portfolio.................................................217 4-6 The Tropical Florida Ecoregion site portfolio...................................................219 4-7 Conservation lands, open water, and private lands both within and outside the Florida Peninsula Ecoregion...........................................................229 4-8 Conservation lands, open water, and private lands both within and outside the Tropical Florida Ecoregion site portfolio.......................................231 4-9 Overlap between the Florida Ecological Network and the Peninsula Florida and Tropical Florida ecoregional portfolios.........................................234 4-10 Overlap between the Peninsula Florida and Tropical Florida ecoregional portfolios and Florida black bear habitat or landscape linkages.......................237 B-1 Comparison between Cost Surface 1 and Cost Surface 2.................................273 B-2 Comparison of Cost Surface 1 and Cost Surface 2 in central Florida..............274 B-3 Comparison between Cost Surface 1 and Cost Surface 3..................................276 B-4 Comparison between Cost Surface 3 and Cost Surface 4..................................278 B-5 Comparison between Cost Surface 5 and Cost Surface 6..................................280 B-6 Comparison of Cost Surfaces 7, 8, and 9...........................................................282 xv

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B-7 Comparison of Cost Surface 10 and Cost Surface 11........................................284 B-8 Comparison of Coast Surfaces 10, 11, 12, and 13.............................................285 B-9 Comparison of Cost Surfaces 8, 9, 14, and 15...................................................287 B-10 Comparison of Cost Surface 16 and Cost Surface 17.......................................289 C-1 LCP results for for the Big Cypress National Preserve to Ocala National Forest landscape linkage in southwest Florida.................................................291 C-2 Forest cover and LCP results in southwest Florida...........................................293 C-3 LCP results for the Big Cypress National Preserve to Ocala National Forest landscape linkage in south-central Florida............................................294 C-4 LCP results for for the Big Cypress National Preserve to Ocala National Forest landscape linkage through the Kissimmee River basin.........................297 C-5 LCP results for for the Big Cypress National Preserve to Ocala National Forest landscape linkage east of Orlando.........................................................300 D-1 Landscape linkage opportunities in the Big Bend.............................................302 D-2 LCP results for the Ocala National Forest to Twelve Mile Swamp landscape linkage..............................................................................................305 D-3 LCP results between the Ocala National Forest and Gulf Coast destinations.......................................................................................................308 D-4 LCP results from Weekiwachee Preserve to other Gulf Coast destinations......312 D-5 LCP results for the Big Cypress National Preserve and for destinations in central and south Florida...................................................................................315 xvi

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Abstract of Dissertation Presented to the Graduate School Of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy REGIONAL LANDSCAPE ANALYSIS AND RESERVE DESIGN TO CONSERVE FLORIDAS BIODIVERSITY By Thomas Scott Hoctor May 2003 Chair: Lawrence D. Harris Major Department: Wildlife Ecology and Conservation The design and management of reserve networks are driving forces in conservation biology and landscape ecology. Reserve design principles and methods are continually being developed and applied worldwide. Designing functionally integrated reserve networks is now considered essential to conserve biodiversity, ecological functions, and evolutionary processes effectively. The state of Florida has been a leader in adopting systematic, landscape-based reserve design, and thus provides an excellent opportunity to explore regional landscape assessments and reserve design strategies for effective protection of biodiversity. In this study, I develop and compare three such approaches: Identify a connected statewide network of intact landscapes and landscape linkages called the Florida Ecological Network. Identify important habitat blocks and connectivity options for the Florida black bear, Ursus americanus floridanus, which may serve as an umbrella species for many other biodiversity components. xvii

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Develop ecoregional plans for the Florida peninsula that integrate fine filter, coarse filter, and landscape approaches for designing reserve networks. The Florida Ecological Network incorporates 9.3 million ha of large, connected landscapes, over half of which lie within existing conservation lands and public domain waterways. Over 5 million ha were identified as potentially high quality black bear habitat, with an additional 680,000 ha identified as landscape linkages to facilitate connectivity. The Florida Peninsula Ecoregion site portfolio contains 3.4 million hectares (51% within public domain lands and water) and the Tropical Florida Ecoregion site portfolio contains 2 million hectares (89% in public domain lands and waters). Collectively, 85% of the bear habitat and landscape linkages were within the Florida Ecological Network, which also overlaps with 84% and 90% of the Florida Peninsula and Tropical Florida Ecoregions, respectively. The results suggest the following: Even given Florida's rapid urbanization, opportunities remain to protect a statewide reserve network that could protect most biodiversity effectively. Each approach I developed identifies some unique areas for protection not found in the other two analyses. Collectively, the assessments address the primary steps of reserve design including representation analysis, focal species analysis, incorporation of special resource elements, and considerations for maintaining or restoring ecological and evolutionary processes. xviii

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CHAPTER 1 INTRODUCTION If a chance process of reserve selection continues, it may produce a network . in which all but a few species adapted to urban life become extinct. . .The challenge remains to integrate the existing distribution of national parks and wilderness areas with a plan that will ensure the functional integrity of the worlds ecosystems while land use for human purposes increases. (Sullivan and Shaffer 1975, p. 13) Since the science of conserving biological diversity gained significant momentum with the discussions prompted by popularization of island biogeography theory (Preston 1962; MacArthur and Wilson 1963; MacArthur and Wilson 1967; Wilson and Willis 1975), the design and management of reserve networks have been primary driving forces behind conservation biology, and cornerstones of landscape ecology. The importance of analysis and planning at the regional landscape scale for effective conservation has been a central theme in reserve design over the last two decades (Harris 1984; Noss and Harris 1986; Thomas et al. 1990; Wilcove and Murphy 1991; Noss and Cooperrider 1994; Forman 1995; Harris et al. 1996b; Soul and Terborgh 1999; Margules and Pressey 2000; Poiani et al. 2000). Principles guiding reserve design are in continual development, and application of these principles is occurring in various regions to identify areas needed to conserve biodiversity. The state of Florida is a leader in conducting detailed species assessments and the identification of large, intact landscapes needed to protect connectivity and ecological processes. Reserve design efforts continue to evolve, and 1

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2 Florida provides an excellent opportunity to explore regional landscape assessments and reserve design strategies for effectively protecting biodiversity. Awareness of the significance of habitat patch size and isolation on the viability of species and ecological dynamics began as early as the nineteenth century. A French scientist, de Candolle (1855), recognized the importance of patch and sample effects on species richness, and Wallace (1880) wrote about the influence of islands and other geographical factors on speciation (Browne 1983). Development of a national parks system in the United States resulted in observations and research about national parks as viable, natural landscapes. Well before popularization of island biogeography theory, wildlife biologists were noticing that national parks were not of sufficient size to maintain many animal species, especially ones that are wide-ranging (Wright et al. 1933; Wright and Thompson 1934). Additional studies over the next several decades (Shelford 1936, Cahalane 1947, Leopold et al. 1963) demonstrated the inadequacy of what was thought to be extremely large reserves such as Yellowstone National Park. Early suggestions for improving this situation included creation of buffer zones around reserves to provide more space to meet seasonal habitat requirements or to support viable populations (Wright and Thompson 1934; Shelford 1936). However, despite these early recommendations to adopt landscape-scale conservation strategies, most protected areas have become more insularized and impacted by land use changes beyond their boundaries (Leopold et al. 1963; Freemuth 1991). Studies during the last few decades confirm the loss of many species from protected lands, both in Africa and North America, with such losses presumed to be caused by

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3 insufficient size of protected areas, their increasing isolation, and negative edge and boundary effects due to the intensification of land uses outside park boundaries (Miller and Harris 1977; Soul et al. 1979; Newmark 1985, 1987, 1995; Schonewald-Cox 1988; Freemuth 1991). Articulation of island biogeography theory has also had a significant role in the evolving science of designing reserve networks (Preston 1962; McArthur and Wilson 1967; Wilson and Willis 1975; Browne 1983; Harris 1984; Shafer 1990; Noss and Cooperrider 1994; Soul and Terborgh 1999). When island biogeography was popularized by McArthur and Wilson in the 1960s, its influence over the nascent discipline of conservation biology was particularly strong. Island biogeography theory helped spur much discussion about the relevance of insularity to habitat fragments in continental landscapes through the 1970s and early 1980s (Wilson and Willis 1975; Harris 1984; Shafer 1990). During the 1970s, reserve design rules based on the principles of island biogeography were proposed (Sullivan and Shaffer 1975; Terborgh 1975; Diamond 1975; Wilson and Willis 1975; Diamond 1976; Diamond and May 1976; Terborgh 1976; Wilcox 1980). Such rules included the importance of reserve size, avoidance of habitat fragmentation effects, and the need for functional connectivity among reserves. Debates regarding the rationale and applicability of island biogeography to conservation raged in the scientific literature throughout the late 1970s and into the mid 1980s (Shafer 1990), but they included what are now considered to be fallacious arguments such as SLOSS (Single Large Or Several Small reserves) (Soul and Simberloff 1986; Noss and Cooperrider 1994).

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4 Conservation biologists and ecologists now generally agree that it will be necessary to have many large and strategically located reserves to conserve biodiversity effectively (Wilcox and Murphy 1985; Soul and Simberloff 1986; Noss and Cooperrider 1994; Harris et al. 1996b; Soul and Terborgh 1999). The solidity and importance of reserve design guidelines increased with the development of conservation biology and additional research on habitat fragmentation effects on population viability and genetic integrity (Soul 1986; Meffe and Carroll 1997). Furthermore, both the emerging disciplines of conservation biology and landscape ecology tended to substantiate many of the reserve design principles proposed initially through application of island biogeography and provided new principles as well (Harris 1984; Forman and Godron 1986; Noss and Cooperrider 1994; Forman 1995). Effective protection of biodiversity and ecological integrity is dependent on research and planning efforts at a variety of scales (Poiani et al. 2000). This includes research on species, natural communities, and landscapes. Effective conservation requires analysis and planning at large scales in order to understand functional relations between landscapes and to integrate efforts. One of the primary lessons of landscape ecology is that spatial context matters (Harris 1984; Harris et al. 1996a), and natural resource conservation and land use planning must consider the effects of actions within their largest spatial and temporal perspectives (Forman 1987). Within both landscape ecology and conservation biology, habitat loss and fragmentation are the primary threats to biodiversity and functional ecological processes and services (Wilcox and Murphy 1985; Harris and Silva-Lopez 1992). Strategies are needed that help to protect and restore natural levels of spatial and temporal heterogeneity that are necessary for

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5 maintaining intact ecosystems and biodiversity while minimizing the effects of fragmentation (Harris et al. 1996a). The need for regional landscape approaches to conservation has resulted in increasing attention to the design of reserve networks that incorporate landscapes apportioned into reserves, multiple-use buffer zones, and landscape linkages (Harris 1984; Noss and Harris 1986; Noss and Cooperrider 1994; Harris et al. 1996b; Soul and Terborgh 1999; Margules and Pressey 2000). Buffers provide protection to core reserves, provide additional habitat, and can potentially link reserves (Harris 1984; Noss and Harris 1986; Noss and Cooperrider 1994). Reserve networks that are functionally connected by buffers, landscape linkages, and corridors are more likely to maintain viable populations, functional ecological processes, and flexibility to respond to environmental changes (Harris 1984; Noss and Harris 1986; Williams 1986; Harris and Scheck 1991; Noss and Cooperrider 1994; Forman 1995; Harris et al. 1996b; Noss et al. 1996). The overarching goals for such systems include those described by Noss (1996, p. 95-96): 1) Represent, in a system of protected areas, all native ecosystem types and seral stages; 2) Maintain viable populations of all native species in natural patterns of abundance and distribution; 3) Maintain ecological and evolutionary processes, such as disturbance regimes, hydrological processes, nutrient cycles, and biotic interactions; 4) Design and manage the system to be responsive to short-term and long-term environmental change and to maintain the evolutionary potential of lineages. Along with these 4 goals, there are 4 primary components of a comprehensive reserve design process: identification of special elements such as roadless areas and high quality natural community sites; representation analysis to identify biodiversity elements (especially natural communities) that are not well protected; focal species habitat

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6 assessments; and consideration of functional ecological and evolutionary processes (Noss and Cooperrider 1994; Harris et al. 1996a; Noss 1996; Margules and Pressey 2000; Sanderson and Harris 2002). By the late 1980s and early 1990s, reserve design principles, or guidelines, for conserving biodiversity were generally accepted in conservation biology and were being applied to cases such as the Spotted Owl (Strix occidentalis) (Wilcove and Murphy 1991). The most commonly accepted "rules of thumb" for reserve design include the following (Harris 1984; Thomas et al. 1990; Soul 1991; Noss and Cooperrider 1994; Noss et al. 1997): Large reserves (or blocks or habitat) are preferable to smaller reserves. Such reserves will tend to have larger blocks of habitat and larger populations, more potential for supporting various ecological communities and therefore more diversity, are more likely to be both resistant and resilient to disturbances and potentially support natural, functional disturbance regimes and other ecological processes, and will be better insulated from incompatible land uses outside the reserve (Harris 1984; Soul and Simberloff 1986; Thomas et al. 1990; Soul 1991; Noss and Cooperrider 1994; Noss et al. 1997). Functionally interconnected reserves are generally preferable over isolated reserves. Depending on the situation and species, connectivity can be provided by establishing corridors or landscape linkages or through compatibly managed multiple-use landscapes surrounding and connecting reserves. Reserves that are close together may also provide functional connectivity for species that are either able to fly or traverse the matrix surrounding the reserves (Harris 1984; Noss and Harris 1986; Harris and Scheck 1991; Soul 1991; Noss 1993; Noss and Cooperrider 1994; Noss et al. 1996; Noss et al. 1997; Beier and Noss 1998; Soul and Terborgh 1999). Reserves in contiguous or consolidated blocks are preferable over fragmented blocks. Examples of fragmentation within reserves include roads, inholdings with incompatible land uses, or clear cuts (Harris and Silva-Lopez 1992; Noss and Cooperrider 1994; Noss et al. 1997). Reserves that are roadless and less accessible to human disturbance are preferable to areas with high road density and access (Noss and Cooperrider 1994; Noss et al. 1996). This principle is born out of the established relation between areas of high road density and avoidance of such areas by a number of wide-ranging species

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7 sensitive to humans in general or vulnerable to hunting, poaching, and roadkills including grizzly bear (Ursus arctos) (Mattson et al. 1987; McLellan and Shackleton 1988), wolf (Canis lupus) (Thiel 1985; Mech et al. 1988; Mladenoff 1995), elk (Cervus elaphus) (Lyon 1983), cougar (Puma concolor) (Van Dyke et al. 1986), and black bear (Ursus americanus) (Brody 1984; Brody and Pelton 1989). Reserves that include native carnivores especially, and wide ranging species generally, are preferred to reserves without these guilds (Terborgh 1988; Bolger et al. 1991; Soul 1991; Noss et al. 1996; Soul and Terborgh 1999). There are sound ecological reasons for maintaining and restoring such species. Carnivores are often keystone species that effect the structure of entire communities ranging from genetics to species abundance. Keystone functions of carnivores include: controlling tree seed predators in tropical forests (Terborgh 1988), controlling herbivore and neotropical migrant bird abundance in the Greater Yellowstone Ecosystem (Berger et al. 2001a; Berger et al. 2001b), or meso-mammals in southern California chaparral fragments that benefits native ground/shrub dwelling and nesting bird species (Bolger et al. 1991; Soul 1991); and wolves providing carrion for other species in Yellowstone including grizzly bears, eagles, and other species (MacNulty et al. 2001). Carnivores can also be important for maintaining functional evolutionary relations between predator and prey (Maehr et al. 2001b). Reserves that are well distributed across the native range of a species provide a better opportunity to maintain genetic variation and adaptive responses to local conditions and temporal environmental changes (Thomas et al. 1990; Wilcove and Murphy 1991; Harris 1992; Noss and Cooperrider 1994; Noss et al. 1997). Although exceptions are always possible and options must be weighed carefully when addressing specific situations (Noss et al. 1997), these guidelines have played an important role in the development of conservation science and planning. Regional landscape analysis and reserve design are now part of a new natural resource management strategy that can be termed regional conservation planning." The goal of such efforts is to conduct research and planning at sufficiently large spatial scales to account for the interactions of competing land uses and protect and restore landscapes that will effectively conserve biological diversity while providing important ecological services and other natural resources needed to sustain healthy human communities. Efforts to involve local people in conservation efforts are also a critical part of regional

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8 conservation planning (Jacobson 1995; Meffe and Carroll 1997; Benedict 2000). By identifying a large scale, regional conservation framework, it is possible to provide a foundation on which protection of the important ecological properties and processes can be optimized for multiple benefits at local to regional scales (Noss 1996; Hoctor et al. 2002). Various efforts to design reserve or ecological networks began in the United States in the 1990s. The state of Maryland has developed a green infrastructure assessment to identify areas of highest conservation significance and opportunities to maintain and restore ecological connectivity (Maryland Greenways Commission 2000; Weber and Wolf 2000; Weber 2001). The Wildlands Project (Soul and Terborgh 1999) is engaged in various regional reserve design projects with special focus on wide-ranging species. Defenders of Wildlife recently completed an analysis of areas most significant for conserving Oregons biodiversity and developed policy strategies and incentives to effect protection (Heagerty et al. 1998). The Nature Conservancy, which until the late 1980s (Noss 1987a) embraced site-specific strategies for conserving biological diversity, has begun an ambitious biodiversity planning effort called ecoregional planning (Groves et al. 2000; Groves et al. 2002). All of these projects are based on the fact that regional landscape assessment is essential to protect biodiversity and ecological integrity. However, such efforts had already gained momentum in Florida in the 1980s in response to rapid human population growth and habitat fragmentation (Harris 1984; Harris 1985; Noss and Harris 1986; Noss 1987b; Harris and Gallagher 1989; Harris and Scheck 1991; Harris and Atkins 1991). Since then, Florida has completed several statewide assessments to identify strategic habitats and landscapes that can be integrated

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9 into an integrated reserve network that effectively protects biodiversity and ecological processes (Millsap et al. 1990; Cox et al. 1994; Florida Greenways Commission report 1994; Cox and Kautz 2000). Although reserve design has become an important part of conservation practice, methods for conducting analyses to identify areas of ecological significance and design reserve networks at regional scales are still in their early stages of development. Strategies and methods are constrained by funding, time, data availability, data quality, and software limitations. Because Florida remains at the forefront of applying regional landscape assessments for identifying and conserving biodiversity, it provides an excellent opportunity to explore developments and issues in designing reserve networks. This dissertation develops three comparative and potentially complementary approaches to regional landscape analysis and reserve design to conserve Floridas biodiversity effectively. They include identification of a connected statewide network of intact landscapes and landscape linkages called the Florida Ecological Network; identification of connectivity options and important habitat blocks for the Florida black bear (Ursus americanus floridanus), which may serve as an umbrella species for many other biodiversity components; and development of ecoregional plans for the Florida peninsula that integrate fine filter, coarse filter, and landscape approaches for designing reserve networks. Collectively the three approaches address the four goals and primary components of reserve design (Noss and Copperrider 1994; Noss 1996; Noss et al. 1999; Margules and Pressey 2000). The three approaches are discussed in detail to compare their relative advantages and develop recommendations for additional steps in the

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10 biodiversity reserve design process in Florida and beyond. Policy considerations for protecting regional ecological networks are also discussed. Study Area Florida is an ecologically diverse region ranging in climate and biota from the temperate to tropical. It is relatively flat with a maximum elevation in the north of approximately 100 m, and much of the state below elevations of 30 m. There are approximately 14 million ha in the state with approximately two-thirds of that area occurring as a long peninsula. Northern Florida is within the southern temperate zone and harbors broad alluvial riparian habitats, and upland flats and modest "ridges" once dominated by longleaf pine (Pinus palustris) communities. The central peninsula consisted (until recent development) of broad flatlands dominated by longleaf and slash pine (Pinus elliottii), dry and wet prairies, and sandy ridges with scrub and sandhill communities harboring numerous rare and endemic species (Myers 1990). The southern tip of the peninsula, though heavily modified by development, still contains tropically-influenced hammocks, swamps, rocklands, and marshes of the Big Cypress Swamp, Everglades, and the Florida Keys. Rivers originating in the southern Appalachians and Piedmont are an important ecological component in north Florida that harbor increasingly rare mollusk and fish species. Lakes are very common in the Florida peninsula, and Lake Okeechobee in south Florida is one of the largest lakes in North America. Numerous springs are also characteristic of the vast limestone regions of north and central Florida. Springs and limestone caves and sinks also support many rare aquatic invertebrates (Deyrup and

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11 Franz 1994). Estuarine ecosystems include productive saltmarsh communities dominating the northern half of the state and mangrove and seagrass dominating the southern half of the peninsula. The extensive Gulf of Mexico and Atlantic coastlines of Florida significantly influence a climate that is generally warm and humid. Summer thunderstorms are frequent, and lightning-caused fires have been an extremely important ecological process shaping many upland and wetland communities across the state for millennia (Myers and Ewel 1990). Rains vary from highly seasonal patterns in south Florida with heavy rains occurring mainly in the summer to more even rainfall year round in northern Florida due to more frequent precipitation in winter from continental frontal systems (Chen and Gerber 1990). Freezes occur every year in north Florida but are extremely rare in south Florida. Freeze events have a strong influence on the range of tropical species up the Florida peninsula, with such species typically found further north along the coasts, which are better buffered from freeze events than interior areas because of the warm waters of the Atlantic and Gulf of Mexico (Harris and Cropper 1992). Florida's biota is a mixture of southern temperate, neotropical, and even southwestern species. Sea level rise and fall have been a dominating biogeographic force controlling the evolution of Florida's biota. The Florida Scrub-Jay (Aphelocoma coerulescens), eastern diamondback rattlesnake (Crotalus adamanteus), and gopher tortoise (Gopherus polyphemus) are all closely related to species found in southwestern U. S. biomes, which were directly connected to Florida during the much lower sea levels of Pleistocene glacial periods (Webb 1990). Tropical species have colonized by flying across the Gulf of Mexico or by riding Gulf Stream currents and include numerous

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12 plants, wading bird species, Snail Kite (Rostrhamus sociabilis plumbeus), and Short-tailed Hawk (Buteo brachyurus) (Rodgers et al. 1996). In fact, Florida is a premier birding destination due to the various tropical species that can only be seen or are best seen in Florida within the United States (Kale and Maehr 1990). Temperate species include the Red-cockaded Woodpecker (Picoides borealis), and various amphibians, fish, and mollusk species (Gilbert 1992; Moler 1992; Deyrup and Franz 1994; Rodgers et al. 1996). Characteristic vertebrate species that has been either extirpated or have gone extinct since the arrival of Europeans in Florida include the red wolf (Canis rufus), monk seal (Monachus tropicalis), bison (Bos bison), Ivory-billed Woodpecker (Campephilus principalis), Carolina Parakeet (Conuropsis carolinensis), Passenger Pigeon (Ectopistes migratorius), and Bachman's Warbler (Vermivora bachmanii). Extant megafauna include the Florida panther (Puma concolor coryi), Florida black bear, West Indian manatee (Trichechus manatus), American alligator (Alligator mississippiensis), and American crocodile (Crocodylus acutus). Urgency is the key word for Florida conservation planning. The state is rapidly developing with a human population of over 16 million and approximately 250,000 additional residents each year (U. S. Bureau of the Census 1996). As a state Florida has the fourth largest human population in the United States, but its population density is approximately double that of the largest state, California. Vast urban areas including southeast Florida, Orlando, Tampa, and Jacksonville continue to incorporate more area at a rapid rate supported by a dense network of highways with extensive planned expansions. The rate of rural land loss is approximately 60,000 ha per year, which

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13 represents approximately 1% of the unprotected rural land remaining (Reynolds 1999). In addition, habitat fragmentation due to expanding urban areas and rapid growth along major highways threatens to disrupt ecological connectivity and landscape function even more rapidly in the very near future. Based on the rate of habitat fragmentation and ever-increasing land costs, the future of Florida's biodiversity will likely be determined by the conservation planning conducted and policies enacted over the next ten to twenty years. However, with more than 20% of the state in public conservation land and large wetland, timberland, and rangeland tracts still remaining in private ownership, conservation efforts still have the potential to effectively protect much of Florida's natural heritage. Land acquisition and conservation easement programs at the federal, state, and local levels will be an essential component to protect the lands identified in reserve design assessments, and effective means to manage public and private lands in ways that are compatible with biodiversity conservation will be an additional challenge. General Geographic Information System Methods A Geographic Information System (GIS) consists of integrated hardware and software that captures, stores, retrieves, analyzes, and displays spatially explicit data. Geographic data are generally stored in layers, each representing a particular theme, such as land use, roads or hydrology. Data layers are overlain spatially for analysis of overlapping features, such as finding residential areas within 100-year floodplains. Geographic information systems are increasingly being used to assist in analysis and synthesis of information in environmental planning and design.

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14 GIS applications include conservation as well as other forms of land use planning. The Florida Fish and Wildlife Conservation Commission (FWC) used GIS to identify Strategic Habitat Conservation Areas for selected species and communities of conservation interest (Cox et al. 1994). The federal Gap Analysis Program (GAP) methodology is dependent on GIS to analyze vegetative communities and identify potential habitat for all selected species (Scott et al. 1993). Although GIS is now considered to be extremely useful or even essential for conservation or land use planning, there have been impediments to its wider application: thematic data accuracy, data handling and management issues, positional accuracy, lack of data and unwieldy software. These are gradually being eliminated, ensuring increased future application of GIS to reserve design and regional conservation planning. There are two main types of geographic information systems data, vector and raster. The primary difference between the two types is the way in which geographic information (features and attributes) is stored. In vector GIS, features are always represented with either points, lines, or polygons, and associated attributes (information about the features) are stored with each feature. Raster-based GIS is a way of storing geographic information in a matrix that is divided into a grid of equally sized cells. Grid cells are most typically square. Each cell represents an area on the Earth's surface, for example a cell could represent 1 m 2 or 10 m 2 or any other convenient multiple. In raster GIS, attribute information is stored with each cell. Each cell is assigned a value that corresponds to what it contains on the ground. Cell size is defined by the user and corresponds to the length of one side of one grid cell.

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15 The cell size determines the grid's resolution, or the finest level of detail that can be depicted by the data layer. For example, if a cell size of 10 m is chosen, then the finest level of detail for that map will be 10 m in width and height, and 100 m 2 in area. Features smaller than the cell size can be shown, but they will be represented larger than their actual size. For example, a road that is approximately 5 m wide (actual width) can be represented on a 10 m grid, but its width will appear as 10 m. Smaller cell sizes correspond to higher resolutions. When working with raster-based GIS, choosing an appropriate cell size is an important issue that involves consideration of the features being represented/modeled, the geographic extent of the area of interest, and any existing input data that are already in raster format. Cell size is important because it determines the level of accuracy in the features represented (resolution) and dictates (along with study area extent) the computer processing time needed to run analyses. Of course, the computer hardware being used also dictates the processing time, but cell size is critical. Furthermore, when choosing a cell size for a raster GIS analysis, it is important to consider any existing raster data sets to be used. The cell size chosen would ideally be compatible with, if not equal to the cell size of existing raster data sets. Depending on the geographic area and subject of interest, data can be abundant or scarce. Data can be from various sources, including state and federal agencies, research institutions, and Data Clearing House websites that compile and organize data for distribution. In any GIS-based project or analysis, the first step is to frame the question, develop goals, and create a list of necessary data. Florida is blessed with a large quantity of detailed GIS information, much of which is stored at the University of Florida's

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16 GeoPlan Center, a primary GIS data repository for the state. The second step involves taking an inventory of existing data. Thereafter, data gaps can be evaluated and decisions can be made as to whether there is time or resources to create primary data that may be necessary, or whether there is a surrogate data source available. Data availability is often the limiting factor in GIS-based research projects, and sometimes less than ideal data must be used in order to complete an analysis. However, the availability of GIS data is increasing, as it has quickly become a popular tool for various planning and management applications. Environmental Systems Research Institute's Arc-Info 7.2 and ArcView 3.2 software packages were used to do all of the analysis and modeling for this dissertation. Although some vector analysis was conducted, the majority of the work used raster analytical tools in ESRIs Grid module in the Arc-Info software package. Grid utilizes a map-algebra spatial language that is particularly useful both for conditional combinations of multiple GIS data layers and conducting quantitative spatial modeling.

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CHAPTER 2 THE FLORIDA ECOLOGICAL NETWORK Introduction The protection of an integrated reserve system has been proposed in Florida since the 1980s (Harris 1984; Harris 1985; Noss and Harris 1986; Noss 1987b; Harris and Gallagher 1989; Harris and Scheck 1991; Harris and Atkins 1991). These proposals provided critical momentum for the importance of landscape-level planning. They helped establish that effective biodiversity conservation requires spatial considerations at large scales to ensure the restoration and maintenance of functional ecological and evolutionary processes (Harris et al. 1996a; Sanderson and Harris 2002). Included in this process was a Florida reserve design proposal by Noss (1987b; Noss and Cooperrider 1994) and the results of a mapping workshop coordinated by The Nature Conservancy that involved a variety of experts to identify conservation priorities and areas of conservation interest (Figure 2-1). Building on these proposals, the Conservation Fund and 1000 Friends of Florida began the Florida Greenways Program in 1991 with the goal of public endorsement and adoption of a greenways initiative. Next, the Florida Greenways Commission was appointed by the Governor to explore the utility of creating a statewide greenways program. It recommended (Florida Greenways Commission 1994) the development and protection of a statewide greenways system that would include an ecological network functionally connecting existing conservation lands and other large areas of ecological 17

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18 Figure 2-1. Results of 1991 mapping workshop (charrette) coordinated by The Nature Conservancy. The charrette identified conservation priority areas and areas of conservation interest with some emphasis on ecological connectivity. Natural resource and biodiversity conservation experts from state, federal, regional agencies, universities, and NGOs participated to identify the priorities for the Preservation 2000 state land acquisition program that began in 1990.

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19 significance. These recommendations were adopted by the state legislature, and the Florida Department of Environmental Protection was chosen as the lead state agency to develop an implementation plan. Identification of the best opportunities for protecting a Florida ecological greenways network was the first step in the implementation process. I conducted a statewide GIS-based analysis to identify large areas of ecological significance and landscape linkages to serve as the ecological component of the Florida greenways program. Florida has a good foundation of GIS data on species habitats, land uses, hydrology, roads, etc. that are all relevant for developing landscape-based reserve design analyses to delineate a statewide ecological network. This chapter covers the methodology developed to conduct the GIS assessment, the significance of the identified ecological network for conserving Floridas biodiversity, and some policy considerations for protecting the ecological network. The goal of this reserve design analysis was to use a regional landscape-based approach to design a statewide reserve network that accomplishes the following: Conserves critical elements of Floridas native ecosystems and landscapes Restores and maintains essential connectivity among diverse native ecological systems and processes Facilitates the ability of these ecosystems and landscapes to function as dynamic systems Maintains the evolutionary potential of the biota of these ecosystems and landscapes to adapt to future environmental changes (Florida Greenways Commission 1994) Such a network would result in the protection of an integrated reserve system protecting ecological processes and biodiversity that would not necessarily be achieved by individual reserves (Harris 1984; Noss 1992). Identification of the reserve network

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20 was accomplished by incorporating assays of ecological significance, such as locations of rare and listed species, intact ecological communities, habitat areas needed to maintain viable populations of sensitive species, and land use data, into a reserve design process that integrates them. The result is the first iteration of an interconnected Florida reserve system called the Ecological Network (based on the definition by Forman 1995). Methods Review Process Numerous assumptions and decisions about specific parameters and the step sequence had to be made because of the complexity of the modeling process and the breadth of goals and objectives. To ensure appropriateness of the assumptions and modeling decisions and to seek input on the use and application of available statewide data, technical input was obtained from 1995 through 1997 from the Florida Greenways Commission, the Florida Greenways Coordinating Council, scientists, university personnel, conservation groups, planners and others in federal, state, and regional environmental agencies, and the general public in more than 20 meetings. Those attending these sessions reviewed the progress of the modeling process and provided input on the relevant data and thresholds for identifying areas of ecological significance and landscape linkages. Analysis Used to Identify the Florida Ecological Network The GIS decision support model used consisted of four steps (Figure 2-2). The cell, or pixel, size for the analysis was 180 x 180 m (approximately 3 ha). Use of 180 x 180 m cell size resulted from the necessity to reduce data storage requirements and model simulation speed. Three ha cells provided enough resolution to identify large connected

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21 Figure 2-2. Major steps in the Florida Ecological Network modeling process

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22 landscapes while allowing reasonable computing times on the hardware available when this analysis was conducted. Step 1, identification of areas of ecological significance, derived from queries and re-classification of various GIS data layers including Strategic Habitat Conservation Areas; priority natural communities; existing conservation lands; roadless areas; and information on significant aquatic ecosystems. Each of the layers was evaluated to identify areas with ecological significance, and then all areas with the highest ecological significance were combined into a single layer called Priority Ecological Areas (PEAs). The data and thresholds used to identify PEAs are contained in Table 2-1. An area was included if it met one of the criteria, and no special significance was ascribed to areas meeting multiple criteria. These areas represented the primary building blocks of the linked reserve network. Step 2, selection of hubs, involved the identification of potential core areas for protection of biological diversity and ecological processes. This process began with the PEAs layer (Step 1), then identified the areas with the highest ecological integrity potential through the application of a five part process: Intensive land uses ranging from improved pastures and croplands to residential, commercial, and industrial lands were excluded from consideration. This helped to rectify potential inconsistencies or errors in data used to determine areas of ecological priority. Land use data created by each of Floridas 5 water management districts (WMD) based on both satellite imagery and aerial photography ranging from 1988-1994 were used for this purpose. Data on the most intensive land uses (urban) were also updated by using SPOT imagery from 1995-1996 to ensure exclusion of areas that were no longer suitable. Areas of high road density ( > 3km/km 2 ) that greatly exceed general road density standards for protecting sensitive species were excluded from consideration (Noss 1992).

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23 Areas with the greatest potential for negative edge effects, which were modeled coarsely as areas within 180 m of urban land uses, were excluded from consideration. This distance was the minimum edge effect that could be modeled given our cell size and it was selected as a minimal estimate for the most intensive potential negative edge effects (Meffe et al. 1997). Priority Ecological Areas that remained after this exclusion process that were > 2,000 contiguous ha were selected as Hubs. Reviewers recommended this size threshold during model development. Such areas are potentially large enough to support many species and ecological processes while still capturing most areas of ecological significance (Forman 1995). Resulting hubs were consolidated by smoothing edges and filling in internal gaps by adding lower priority native habitat and potentially compatible land uses such as pine plantations and rangelands, which were identified by using a combination of the FWC land cover and WMD land use data. Step 3, identification of linkages, was the most complicated portion of the GIS modeling. First, the National Wetlands Inventory classification system (Cowardin et al. 1979) was used as the starting point for deriving three native landscape units or type (Table 2-2): Upland dominated Riverine and large wetland basins Coastal. These landscape units served as a logical, broad basis for identifying various potential landscape linkage types. The landscape units were used to partition hubs into the three general landscape classes and to develop linkage types. Next, five linkage types for hubs partitioned into the three landscape types were identified, including coastal to coastal, riverine to riverine, upland to upland, riverine to coastal, and cross-basin hub to hub. Linkages between hubs of like types were modeled before linkages between hubs of different types. The last linkage type, cross-basin (or

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24 Table 2-1. Criteria for selecting Priority Ecological Areas for the Florida Ecological Network Data layer Priority area criterion Explanation FWCa Strategic Habitat Conservation Are a (SHCA) All SHCAs Includes lands outside existing protected areas needed to maintain or restore minimally viable populations of 30 foca l vertebrate species, rare natural community types, important wetlands for wading birds, and globally rare plant species (Cox et al. 1994; Kautz and Co x 2001). Many focal species used in this analysis are umbrella species, whose conservation requirements meet the needs of other species. The natural communities identified represent a coarse filter approach to protect suites of species. FWCa Hotspots Areas containing p otential habitat fo r 7 or more focal species Areas containing potential habitat for 7 or more of the focal species analyzed in the identification of SHCAs. FWC staf f recommended the threshold of 7. FWCa Wetland Hotspots Areas containing p otential habitat fo r 7 or more wetland-dependent species or 4 or more species requiring both wetland and upland habitat Areas represent wetlands in Florida with habitat to support additional wetland-dependent and partially wetlanddependent vertebrate species. FWC staff recommended the thresholds FNAIb Areas of Conservation Interest (ACIs) All ACIs ACIs were identified outside existing p ublic lands using aerial photos, natural heritage data, and expert knowledge. ACIs are high-quality, relatively pristin e sites that contain occurrences of rare species. FNAIb Potential Natural Areas (PNAs) All PNAs except those receiving the lowest rank due to significant disturbance Includes most of the remaining sites available to conserve native ecosystems in Florida, though some disturbance ma y be present and status of tracked species may not be completely known.

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25 Table 2-1. Continued Data layer Priority area criterion Explanation Rare and priority natural communit y types based on FWC habitat data and rankings by Florida Natural Areas Inventory (FNAI) All community types ranked S2 or higher that could be identified using the 22 class FWC landcover map that included coastal strand, dry prairie, sand pine and oak scrub, sandhill, tropical hardwood hammocks, freshwater marsh, and wet prairie FNAI "S" ranks are state ranks based on The Nature Conservancy's global rankings (G1 G5, 1 being most imperiled). The FWC landcover data are classified LANDSAT TM imager y from 1985-1989, but due to the coarse scale of the classification, some S1 communities were not identified in thidata set. However, these communitie s were represented in the SHCA, ACI and PNA analyses. Existing public conservation lands and private preserves (e.g., Audubon, The Nature Conservancy) All such lands Approximately 20% of the state are now contained in conservation lands. Though management practices vary widely, all sites are potentially significant building blocks for a statewide reserve system. Proposed public conservation lands and easements All such lands Approximately 6% of the state have been identified for purchase through Floridas aggressive conservation lan d acquisition program. These parcels were selected based on the presence of high quality natural communities, habitat for rare species, opportunities to protect connectivity, or other conditions supportive of conservation objectives. Lands identified as p art of the Coastal Barrier Resources Act All such lands These areas are typically coastal barrier islands identified by the federal government as undeveloped. Such sites are significant for conserving coastal ecosystems.

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26 Table 2-1. Continued Data layer Priority area criterion Explanation Roadless areas Areas 2,000 ha or larger containing n o roads of any kind Roadless areas are important to species sensitive to humans, are typically buffered from disturbance and provide connectivity for species isolated by roads. A 2,000 ha area was used based on federal roadless standards, average home range size for the Florida black bear (Ursus americanus floridanus), and recommendations by reviewers. Roadless areas without major roads Areas 40,000 ha or larger containing n o major roadways such as interstate, federal, or state highways, and larg e capacity county roads Large areas containing no high-volume roads may be critical for maintaining many sensitive species especially wide-ranging animals such as the Florida black bear and the Florida panther (Puma concolor coryi). The threshold is consistent with the FWCs objective to prevent major road construction in areas greater than 40,000 ha currently without major roads. State Aquatic Preserves, National EstuarineResearch Reserve s Outstanding Florida Waters, Shellfish Harvesting WatersWild and Scenic Rivers All such designated aquatic ecosystems The greatest dearth in information about Floridas natural communities and species is in aquatic ecosystems. I n the absence of such data, these designated aquatic areas, all indicating a level of quality that could support functional aquatic ecosystems, were used as a surrogate for a more comprehensive identification of significant aquatic features.

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27 Table 2-1. Continued Data layer Priority area criterion Explanation Overlap Criteria Moderately ranked FWC focal species, FWC wetland species hotspots, and lower ranked FNAI PNAs, smaller roadless areas (1000 ha or greater and 20,000 ha or greater respectively) that overlap with 100 year floodplains or areas of significant aquifer recharge Moderately ranked habitat areas and roadless areas that overlap with areas significant for maintaining aquatic ecosystems and processes are also significant conservation features. a The Florida Fish and Wildlife Conservation Commission was previously named the Florida Game and Fresh Water Fish Commission. b Florida Natural Areas Inventory

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28 Table 2-2. Landscape unit classification used in landscape linkage identification for the Florida Ecological Network Landscape Unit Ecosystems Coastal open coastal waters; coastal strand; coastal salt marsh; mangrove inshore marine habitats; all other native habitats within contiguous 100-year coastal flood zone Riverine and large wetland basins Open waters of major Florida rivers (FREAC 1990), plus the following when contiguous to major rivers or 400 ha: bottomland hardwood forest mixed hardwood swamp cypress swamp shrub swamp freshwater marsh and wet prairie freshwater aquatic habitats bay swamp open lake waters Upland dominated dry prairie; flatwoods; xeric scrub; sandill; mixed hardwood-pine forest hardwood forest; tree plantations; wetland/isolated aquatic habitats when less tha n 400 ha

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29 general hub to hub), was a broad category that permitted exploration of linkage feasibility between, for example, an upland ridge system and a neighboring river corridor or through agricultural landscapes where some restoration may be needed to restore connectivity. An algorithmic function called least cost path was used to identify landscape linkages. Suitability surfaces (cost surfaces in Arc-Info parlance) were created to represent the relative suitability of each cell for potential inclusion in a linkage. Five different suitability surfaces were created with one for each linkage type. The value assigned to each cell was inversely proportional to its relative suitability for that linkage type, (e.g., a cell with the value of 1 is most suitable, 2 next, etc.) (Figure 2-3, Table 2-3, Table 2-4). The function also allows for identification of unsuitable cells where a potential linkage cannot be located. The relative suitability of each cell was determined by querying original data layers and data layers derived in Steps 1 and 2. Suitability surfaces ranged from simple for the same type linkages such as riverine to riverine (Table 2-3) to complex for the general hub linkages that required a much broader range of suitability values to discriminate between highly suitable and much less suitable areas (Table 2-4). The least cost path function was then run to find the optimal path for selected hub pairs for each linkage type. Accepted paths were widened to include all contiguous cells of native habitat or lower intensity land uses, up to 25% of the linkage length. Such landscape linkages are more likely provide functional movement corridors, maintain habitat gradients from aquatic to upland ecosystems, and buffer aquatic ecosystems in riverine and coastal landscapes (Harris and Scheck 1991; Noss 1993; Forman 1995).

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30 Table 2-3. Riverine suitability surface values for the Florida Ecological Network Category Value Criteria for highly suitable areas Open water associated with major Florida rivers classified as Priority Ecological Area (PEA) 1a Freshwater wetland ecosystems classified as PEAs 1 Open water associated with major Florida rivers classified as SEAb 2 Freshwater wetland ecosystems classified as SEAb 2 Criteria for moderately suitable areas Open water associated with major Florida rivers not classified as PEA or SEAb 3 Freshwater wetland ecosystems not classified as PEAs or SEAsb 3 Open water and areas with high road density or negative edge effect 4 Areas with high road density or negative edge effect that meet the riverine open water or freshwater wetland criteria for this linkage type 4 Criteria for unsuitable areas Intensive agriculture and urban lands No value All other cells No value a The lower the value the higher the suitability. b SEA or Significant Ecological Area, was an area meeting criteria for moderate significance such as moderately ranked FWC hotspots and FNAI Potential Natural Areas.

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31 Table 2-4. Hub-to-hub suitability surface values for the Florida Ecological Network Category Value Priority Ecological Areas (PEAs) that meet all but the 2,000 hectare size criteria for hubs and are contiguous to significant coastal and/or inland aquatic features 1a Other PEAs that meet the 2,000 hectare size filter 2 SEAsb that are contiguous to significant coastal and/or inland aquatic features 2 Native habitat contiguous to significant coastal and/or inland aquatic features 3 All remaining SEAsb 3 All other native habitat 4 Low intensity land use/land cover contiguous to significant coastal and/or inland aquatic features 4 All other low intensity land use/land cover 5 Native habitat lands with areas of negative edge effects or areas of high road density 600 Lands with low intensity use and areas of negative edge effects or areas of high road density 700 Improved pasture contiguous to significant coastal and/or inland aquatic features 7,000 Cropland contiguous to significant coastal and/or inland aquatic features 8,000 All other lands in moderate intensity use, contiguous to significant coastal and/or inland aquatic features 9,000 Improved pasture 70,000 Cropland 80,000 All other lands with moderate intensity use 90,000

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32 Table 2-4. Continued Category Value Open water 100,000 Urban lands No value All other cells No value a The lower the value the higher the suitability. b SEA or Significant Ecological Area, was an area meeting criteria for moderate significance such as moderately ranked FWC hotspots and FNAI Potential Natural Areas.

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33 Figure 2-3. Riverine cost surface example. This example from south central Florida and the Kissimmee River basin (headwaters of the Everglades) of a suitability surface used for identifying potential riverine and large wetland basin landscape linkages and corridors where only wetlands and fresh water ecosystems are considered suitable and are valued based on their resource significance.

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34 Step 4, creation of the Ecological Network, was achieved by combining the identified hubs and linkages. Results Florida still supports large areas of intact native ecological systems and potentially compatible land uses that can serve as a connected statewide reserve system. The Ecological Network links the larger public conservation lands, while also incorporating other important landscape features of each region (Figure 2-4). In the Florida Panhandle, the numerous rivers that flow north to south (such as the Apalachicola) form a network from the Blackwater River State Forest and Eglin Air Force Base to the Apalachicola National Forest. North-central Florida is dominated by the Suwannee River corridor, which links the lowlands of the Big Bend on the Gulf Coast to the Osceola National Forest--Pinhook Swamp--Okefenokee National Wildlife Refuge complex, and a large landscape linkage parallel to the western shore of the St. Johns River that connects the Ocala and Osceola National Forests. In central Florida, river and swamp basins including the Kissimmee, Peace, St. Johns, Myakka, and Withlacoochee Rivers join the sandhills and scrub of the Lake Wales Ridge and Brooksville Ridge and provide the primary elements of a network that includes the Ocala National Forest, Green Swamp, Three Lakes Wildlife Management Area, and Avon Park Bombing Range. Southern Florida is dominated by the Everglades National Park--Big Cypress National Preserve complex. This complex is linked to landscapes in central Florida via Okaloacoochee Slough and Fisheating Creek west of Lake Okeechobee, and via the Corbett Wildlife

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35 Figure 2-4. Florida Ecological Network model results. The results include existing and proposed conservation lands within the ecological network. Existing conservation includes all public lands with some conservation management and private preserves. Proposed conservation lands include all projects within official federal, state, regional and local land acquisition/protection programs. Although the ecological network includes water within all of the major rivers and most intact estuarine systems, these features have not been differentiated from other areas of open water in this figure.

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36 Management Area and ranchlands containing flatwoods, prairies, and sloughs northeast of Lake Okeechobee. Of the approximately 9.3 million ha (57.5% of the state) incorporated into the Ecological Network, 4.8 million ha (52.2% of the network) are within existing public conservation lands of various federal, state, regional, and local designations, private preserves (such as those owned by The Nature Conservancy), or open water (considered public domain by Florida statute). Thus, less than half of the identified Ecological Network occurs on private land that may need protection (Table 2-5). Of the private land included in the Ecological Network, more than 50% occurs within an existing conservation project, wetlands, or in 100-year floodplains. Although these areas may be more easily protected than the 2 million ha of uplands occurring in private ownership, approximately 4.5 million ha of private land is still identified in the model results. Comparisons to Other Ecological Inventories For Florida, good analyses and data indicate priority areas for conserving biological diversity. Two key analyses used in the ecological model are the Strategic Habitat Conservation Areas identified by the Florida Fish and Wildlife Conservation Commission (FWC) (Cox et al. 1994; Kautz and Cox 2001) and Florida Natural Areas Inventorys (FNAI) Areas of Conservation Interest and Potential Natural Areas (FNAI 2001) (Table 2-1). Although many other data were used in this study, the FWC and FNAI data were integral to identifying a connected statewide reserve system. Because of the details and sequence of the modeling process, not all areas contained within the FWC or FNAI data were included in the Ecological Network. For example:

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37 The lowest ranking FNAI Potential Natural Areas were not automatically included because of the level of disturbance found on lower priority sites. Areas of intensive land use identified from data sources more current than the FNAI and FWC data were excluded from consideration. Any area included in FNAI and/or FWC results that did not occur within a hub totaling at least 2000 ha was not included in the Ecological Network unless it was incorporated within landscape linkages selected to connect hubs. Comparison between the FWC and FNAI data and the Ecological Network is a useful measures of the significance of the model results for conservation of focal species and natural communities. Over 80% of the Strategic Habitat Conservation Areas and over 68% of the Areas of Conservation Interest and Potential Natural Areas are contained in the Network (Table 2-6). Most of the Strategic Habitat Conservation Areas that did not overlap with the Ecological Network are either isolated wetlands and scrub or areas recommended to conserve the Crested Caracara in south-central Florida that often overlapped with improved pastures that were excluded from consideration in the hub identification process. Moreover, 80% of the Network is at least one of the following: Existing or proposed conservation lands Inland or coastal waters Strategic Habitat Conservation Areas Areas of Conservation Interest and Potential Natural Areas. This suggests that the remaining 20% of the Network contains other suitable areas that integrate these primary ecological features spatially into a statewide ecological network (Figure 2-5).

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38 Table 2-5. Area of land in various land ownership categories within Floridas Ecological Network Land Use Hectares Percentage of state area Percentage of model results Public ownership 3,239,476 20.0 34.8 Open water (outside existing conservation areas) 1,613,418 10.0 17.4 Proposed public conservation lands 985,936 6.1 10.6 Private ownership in wetlandsa 701,650 4.3 7.5 Private ownership in 100 yr. Floodplainab 656,691 4.1 7.1 Private ownership in uplandsa 2,101,559 13.0 22.6 Totals 9,298,742 57.5 100.0 a Ha of private ownership in wetlands, 100 yr. flood plain and uplands is calculated as if all proposed public acquisitions are/will be completed. b Floodplain data were not available for Bradford, Columbia, Dixie, Gilchrist, Hamilton, Jefferson, Lafayette, Madison, Okeechobee, Taylor, and Union Counties, so the statistics shown above underestimate total floodplain.

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39 Table 2-6. Comparison of the Florida Ecological Network, other ecological resource inventories, and existing and proposed conservation lands Comparison categories Area of category within model results (ha ) Percent of model results Percent of category within the model results Area of category in study area (ha) Percent of state State N/A N/A N/A 16,175,928 100.0 Ecological Network model results 9,298,742 100.0 N/A 9,298,742 57.5 FWCa Strategic Habitat Conservation Areas (SHCAs) 1,586,567 17.1 80.6 1,968,587 12.2 FNAIb Areas of Conservation Interest and Potential Natural Areas (ACIs) 1,521,085 16.4 68.7 2,214,813 13.7 Existing or proposed conservation lands; open water; SHCAs; or ACIs 7,539,052 81.1 81.4 9,259,270 57.2 a Florida Game and Fresh Water Fish Commission (renamed Florida Fish and Wildlife Conservation Commission in 1999) b Florida Natural Areas Inventory

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40 Figure 2-5. Comparison of the Ecological Network other statewide ecological resource inventories. Though the overlap of the Florida Ecological Network with the Florida Fish and Wildlife Conservation Commissions Strategic Habitat Conservation Areas and the Florida Natural Area Inventorys Areas of Conservation Interest and Potential Natural Areas is high, the Florida Ecological Network identifies additional lands that would help integrate all lands into an integrated network.

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41 Landscape Comparisons Since the Florida Ecological Network is almost three times as large as the total area within existing conservation lands (9.3 million ha versus 3.2 million ha), a logical conclusion or hypothesis is that the Ecological Network would better protect large landscapes. These large landscapes should have a better opportunity to protect functional ecological processes (such as the interplay of flooding and fire in intact landscapes of the southeastern United States) and viable populations of wide-ranging species and most other species of conservation interest (Harris et al. 1996a). Several landscape-level comparisons between existing conservation lands and the Ecological Network help to bring specificity to this conclusion. Wetland-upland adjacencies In Florida, wetland-upland adjacency or juxtaposition is a critical landscape feature that mediates important ecological processes and is essential for providing habitat for many species of conservation interest (Harris 1988; Echternacht and Harris 1993; Harris et al. 1996a). In this comparison, areas containing natural and semi-natural upland patches (all natural upland communities and pine plantation) of 400 ha or larger adjacent to all wetlands 40 ha or larger were identified. Of these areas containing adjacencies of large uplands and wetlands, existing conservation lands contained 32% of the area, whereas the Florida Ecological Network contained 88% of the area. Although this analysis does not include information regarding the intactness of these wetland-upland complexes, degree of interspersion, or other potential measures of significance, it does suggest that the Ecological Network greatly enhances the representation of landscapes containing functional blocks of large wetlands and uplands.

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42 Small or ephemeral wetland complexes Another critical component of landscapes in Florida is the presence of small, often ephemeral, wetlands. Such wetlands provide seasonally important foraging habitat for many species, including various wading birds such as the federally-listed Wood Stork (Mycteria americana); and essential breeding habitat for various, increasingly rare, amphibian and reptile species (Moler 1992; Cox et al. 1994; Burke and Gibbons 1995; Dodd and Cade 1998; Gibbs 1998; Haig et al. 1998; Semlitsch 2000; Snodgrass et al. 2000; Joly et al. 2001; Joyal et al. 2001). To identify landscapes containing significant complexes of isolated wetlands, I conducted a neighborhood or shifting window analysis to identify all areas containing natural and semi-natural uplands that were also comprised of 5% or more isolated wetlands (defined as all wetlands 2 ha or smaller) within a 2 km 2 window. Such areas are more likely to support functional metapopulations of ephemeral pond breeding species and important foraging habitat for many other species (Cox et al. 1994; Dodd and Cade 1998; Semlitsch 2000; Snodgrass et al. 2000; Joyal et al. 2001). Existing conservation lands contain only 18% of such areas, whereas the Ecological Network contains 61%. Wetland biodiversity in general, and ephemeral pond breeding amphibians in particular, are very sensitive to impacts associated with roads and increasing road densities (Gibbs 1998; Findlay and Bourdages 2000). Therefore, I also identified landscapes containing 5% or more isolated wetlands (as identified above) that were within 400 ha or larger roadless blocks (defined as areas containing no paved roads). Existing conservation lands encompass 23% of such areas, whereas the Ecological Network contains 78%. Although more specific analysis is needed regarding landscape

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43 integrity (such as differentiating areas with well-managed upland forests from low integrity forests), this comparison suggests that the Ecological Network provides much greater opportunity for protecting functional complexes of small wetlands. Roadless areas The importance of roadless areas for conserving landscapes with high integrity cannot be overstated. Roads have a myriad of impacts including fragmentation, isolation, mortality, disturbance effects, and pollution that can severely impact biodiversity (Noss and Cooperrider 1994; Reed et al. 1996; Reijnen et al. 1997; Findlay and Bourdages 2000; Jones et al. 2000; Trombulak and Frissell 2000; Develice and Martin 2001; Strittholt and Dellasala 2001; Heilman et al. 2002). Another important comparison between existing conservation lands and the Florida Ecological Network is the number of roadless areas with each. I identified roadless areas using different subsets of Floridas roads system and different roadless area sizes. In all cases, the Florida Ecological Network contains substantially more roadless areas and total roadless area than contained in existing conservation lands (Table 2-7). Representation Representation analysis involves comparing features of ecological significance (usually natural communities or species) with existing protected areas to determine which features require greater protection (Scott et al. 1993; Noss 1996). I conducted a coarse analysis of habitat representation by comparing total existing ha of major natural communities (Cox et al. 1994) with the amount found in existing conservation areas and the Ecological Network. Although some important elements are not included in the Ecological Network, it is clear that the identified Ecological Network enhances the

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44 Table 2-7. Comparison of roadless areas found in existing conservation lands and the those included in the Ecological Network. Comparisons include the total number of roadless patches and total roadless areas for two road class types (major roads versus all roads) and various roadless patch sizes. Roadless area type Existing conservation lands number of patches Florida Ecological Network number of patches Existing conservation lands total area (ha) Florida Ecological Network total area (ha) Intrastate Highway System (contains all major paved roads) 40,000 ha or larger 25 52 2,597,989 5,479,562 20,000 ha or larger 37 100 2,919,142 6,832,500 4,000 ha or larger 130 274 3,777,137 8,551,438 All Roads (including unpaved) 40,000 ha or larger 8 15 1,230,823 1,887,800 20,000 ha or larger 15 26 1,417,061 2,175,800 4,000 ha or larger 104 190 2,099,166 3,394,887

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45 protection of each community type (Table 2-8). The increases for sand pine scrub, xeric oak scrub, and longleaf pine sandhill are of particular significance. These community types are endangered globally; and provide habitat for many endangered, threatened, and endemic species, as well as a host of species that are candidates for listing (Myers 1990; Noss et al. 1995; Platt 1998). Conserving most of the intact natural and semi-natural landscapes in Florida may prove to be an effective coarse filter strategy (Noss 1996) for protecting most of Floridas biological diversity, but this strategy must be complemented by more focused analyses for specific rare natural communities and species that may not be well represented by focal species analyses (Caro and ODoherty 1999) or coarse habitat classifications (Noss 1996). I compared the Ecological Network to element occurrence information for natural communities and rare species from the Florida Natural Areas Inventory (FNAI 1997). Of 69 natural communities contained in the FNAI data, all 69 had at least one occurrence in the Ecological Network, and only 4 had less than 50% of their occurrences within the Ecological Network. Analysis of rare species occurrences showed there are 32 species (mostly plants) not known to be found on existing conservation lands or within the Ecological Network. These taxa represent only 6% of the species and subspecies analyzed. Therefore, most rare natural communities and species are represented in existing conservation areas and the Ecological Network, but more work needs to be done to assess whether this representation is sufficient and to identify other areas needed to viably protect those that are not adequately protected.

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46 Table 2-8. Comparison of the total land area of existing ecological community types (habitats) in the state of Florida with area of habitat types found in existing conservation lands and the amount included in the Ecological Network. Ecological community type Total area (ha) Area in existing conservation lands (ha) Total habitat in existing conservation lands (ha) Area in Ecological Network (ha) Habitat in Ecological Network (ha) Increase in protected area (ha) Percent increase in protected area Coastal strand 4,281 3,145 73.4 3,475 81.2 330 7.7 Dry prairie 519,895 133,334 25.6 422,050 81.2 288,716 55.5 Pinelands 1,651,235 413,066 25.0 1,076,578 65.2 663,512 40.2 Sand pine scrub 131,708 105,501 80.1 117,500 89.2 11,999 9.1 Sandhill 390,056 146,250 37.5 248,888 63.8 102,638 26.3 Xeric oak scrub 52,628 22,272 42.3 38,967 74.0 16,695 31.7 Mixed hardwood-pine forests 387,889 46,532 12.0 197,300 50.9 150,767 38.9 Hardwood forest 818,030 185,651 22.7 530,194 64.8 344,544 42.1 Tropical hardwood forest 5,872 3,313 56.4 4,210 71.7 897 15.3 Saltmarsh 195,710 121,584 62.1 182,616 93.3 61,032 31.2 Freshwater marsh/wet prairie 1,153,285 778,923 67.5 1,023,724 88.8 244,801 21.2 Cypress 621,504 253,454 40.8 546,964 88.0 293,509 47.2 Mixed hardwood swamp 1,076,484 276,915 25.7 864,698 80.3 587,783 54.6 Bay swamp 57,968 16,763 28.9 47,102 81.3 30,339 52.3 Shrub swamp 252,327 152,976 60.6 222,950 88.4 69,974 27.7 Mangrove swamp 229,012 198,100 86.5 221,703 96.8 23,603 10.3 Bottomland hardwoods 40,033 23,532 58.8 39,926 99.7 16,394 41.0

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47 Discussion The Florida Ecological Network, identified as part of the Florida Statewide Greenways planning process, is another significant step toward protecting an integrated state reserve system for biodiversity conservation. Harris (1985), Noss (1987b), and The Nature Conservancy recommended connected reserve systems through intuitive representations of networks and mapping charrettes. The Strategic Habitat Conservation Area analysis by the Florida Fish and Wildlife Conservation Commission and the natural areas identification by the Florida Natural Areas Inventory provided systematic assays to identify priority areas for conservation (Mann 1995). The progress represented by the design and execution of the Ecological Network delineation process was the combination of a systematic landscape analysis of ecological significance; and the identification of critical landscape linkages; in a way that can be replicated, enhanced with new data, or applied at different scales. The Ecological Network connects and integrates existing conservation areas and unprotected areas of high ecological significance. The network can be used in concert with other information on conservation priorities to develop a more integrated landscape protection strategy. Such an integrated reserve network will more thoroughly protect important ecological functions, community and landscape juxtapositions, and biotic connectivity than the present collection of isolated conservation areas (Noss and Harris 1986; Harris et al. 1996a; Harris et al. 1996b). The Ecological Network also includes most of the intact natural communities and most known occurrences of species tracked by FNAI. These factors suggest that the Ecological Network will be integral to efforts to conserve Floridas biological diversity.

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48 Although the Ecological Network model represents an important step in Floridas conservation strategy, many issues and questions still need to be addressed. Among these is the need for a more thorough analysis of the relation between the model results and specific conservation needs for sensitive species and all communities. In the process of identifying potentially viable reserve networks, Noss (1996) recommended three primary steps: special element mapping, representation analysis, and area-dependent species analysis. Although these steps were incorporated in the Ecological Network delineation process, there are still gaps in the analysis. The model benefited from previous analyses of habitat needed to protect potentially viable populations of 30 focal species. Cox et al. (1994) however, limited the strategic habitat conservation area recommendations for the Florida panther to within or near the area currently occupied by the known breeding population in southwest Florida. Their recommendations for the Florida black bear were limited to expanding the habitat base for the five largest populations left in the state. These recommendations are essential, but a large connected reserve network in Florida will significantly enhance survival prospects for these umbrella species, as well as the ecological integrity of the landscapes they would occupy (Harris et al. 1996b; Maehr 1997b; Maehr et al. 2001a; Maehr et al. 2001b; Maehr et al. 2002b). Although the Ecological Network model has identified connected landscapes that may provide functional connectivity and promote the re-establishment of statewide populations, species-specific analyses should be conducted for both the Florida panther and black bear to establish this possibility better. Broad landscape analyses of connectedness are useful, but species-specific analyses are essential for determining potential for connectivity of particular populations and identifying minimal viable areas

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49 for metapopulations (Beier 1995; Maehr and Cox 1995; Beier 1996; Beier and Noss 1998). One of the most discussed issues in the model development process was determination of minimum hub size. Several reviewers felt that areas at least as small as 400 ha should also be considered because areas need not be 2,000 ha or larger to be ecologically significant and because the completed Ecological Network could draw attention away from the conservation significance of smaller, isolated tracts. Isolated sites can contain critical elements of biodiversity that should be protected as part of a statewide reserve system (Shafer 1995). One of the most important steps within a reserve design process is a thorough representation of all native ecological communities and species (Noss and Cooperrider 1994). Not all important sites and species are contained within the model: results did not include globally imperiled pine rocklands in southeast Florida (Snyder et al. 1990) and oak scrub tracts along the Lake Wales Ridge that support many rare and endemic species. More work is required to assess the needs of specific rare species and natural communities, especially in aquatic systems (Hoehn 1998). Another important consideration in a reserve design process is identification of potential core areas, corridors, and buffers (Harris 1984; Noss and Harris 1986; Noss and Cooperrider 1994; Soul and Terborgh 1999). In the Ecological Network delineation process, hubs were used as destinations, but they cannot typically be considered equivalent to core areas, where core areas are defined as reserves managed exclusively or primarily for conserving biological diversity (Scott et al. 1993; Noss and Cooperrider 1994). The few managed areas in Florida that might meet this definition include The

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50 Nature Conservancy and National Audubon Society preserves, some designated wilderness areas, national parks, and state preserves. Yet, many of these areas allow uses contradictory to core area ideals; or suffer from external threats or disruption of natural ecological processes (including fire suppression) and changes in hydrologic regimes (such as in Everglades National Park). There is a need to identify other areas within the Florida reserve system that might also be managed with greater emphasis on biodiversity. Much of the land identified in the Ecological Network is managed for multiple uses. Except in south Florida, much of public land area in Florida is within National Forests and military reservations where biodiversity is only one of many management objectives (Noss and Cooperrider 1994). Although strides have been made under the rubric of ecosystem management on military reservations (Gordon et al. 1997) and to some extent within the National Forest system (Salwasser et al. 1996). Even though there are extremely important and high quality natural communities found on private lands, much has been converted to conifer plantations or rangelands (Kautz 1993). These areas may be the buffer areas of a future Florida conservation reserve system, but the model did not include the specific identification of buffer areas. In some cases, there may be a need to identify buffers for narrower corridors and potential bottlenecks especially around network components in central and south-central Florida (Figure 2-4). Although these network elements are primarily surrounded by low intensity agriculture currently, their function could be endangered if land uses intensify. Identification of core areas and buffers will be an important part of the reserve design process in Florida. However, the focus for now should be on prioritizing lands for

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51 protection from conversion to more intensive uses because of rapid human population growth and the consequent habitat loss and fragmentation. This raises questions about how much land must be protected to meet biodiversity conservation objectives (Noss 1996; Soul and Sanjayan 1998). Furthermore, guidelines are needed so that the most critical lands are protected first. Although Florida has committed at least $300 million per year since 1990 for land acquisition and related conservation efforts, the approximately 4.4 million ha within the Ecological Network might require at least 3 to 4 decades to protect at current funding levels. Such a need for setting priorities also involves the debate about the importance of protecting corridors versus protecting core areas of high-quality habitat (Simberloff and Cox 1987; Noss 1987c; Simberloff et al. 1992; Hobbs 1993; Beier and Noss 1998). How are state conservation decision-makers to choose between these alternative strategies? The Florida Greenways Project provides some insight. First, these approaches are not mutually exclusive. Prioritization of land protection can include both considerations. Landscape linkages that also contain high quality habitats needed to maintain viable populations of sensitive species can be identified. The high degree of overlap among the ecological greenways network model results, Strategic Habitat Conservation Areas, and priority sites identified by the Florida Natural Areas Inventory suggests that this will occur frequently (Figure 2-7). Then, landscape linkages most significant for facilitating connectivity for wide-ranging species and isolated sites containing critical elements of biodiversity should also be identified as priorities. Though additional debate about landscape linkage and corridor projects is likely, connectivity has been accepted as a critical reserve design principle (Harris et al.

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52 1996b; Beier and Noss 1998). Because natural landscapes are generally connected, the burden of proof for not including connectivity should be on those remaining skeptical about the need to protect landscape linkages and corridors and not vice versa (Noss 1987c: Noss 1991; Beier 1996; Beier and Noss 1998). There would always be the option to sever linkages in the future if deemed necessary, but the opportunity to protect existing landscape linkages or to restore them will diminish rapidly as Floridas human population continues to grow. Another challenge is to retrofit the existing highway system in Florida and to plan future road projects to be as compatible as possible with the protection of a statewide reserve system. The Florida Department of Transportation has made significant progress, including construction of a comprehensive system of underpasses where Interstate 75 crosses the Big Cypress National Preserve that is allowing Florida panthers and many other species to cross under the highway safely (Foster and Humphrey 1992). One underpass has been constructed at a black bear roadkill hotspot in central Florida; and more are planned (Roof and Wooding 1996). A comprehensive assessment of all potential interfaces between major roads and priority ecological conservation areas for future mitigation (e.g., lengthening existing bridges and culverts, constructing new wildlife underpasses) coordinated with the Ecological Network modeling process has also recently been completed (Smith 1999). However, there is still a need to avoid major new road projects, several of which now threaten important elements of the Ecological Network. Reserve design is an iterative process that must continually consider new information. Work on refining and enhancing a Florida reserve network is progressing in

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53 several projects and scales. Floridas federal GAP analysis project was just recently completed, and the Florida Fish and Wildlife Conservation Commission continues to analyze additional species. These and other projects likely will identify priorities that should be addressed in future iterations of a state reserve system plan, and, as always, field assessments of priority sites need to be done as part of the protection process. As land development continues, loss of habitat must be monitored and conservation plans adjusted as necessary. Finally, considering Formans ethics of isolation (1987), work at the next scale is being conducted with Region 4 of the U.S. Environmental Protection Agency to identify a regional ecological conservation network for the southeastern United States (Hoctor et al. 2002), which could lead to coordination with other efforts to identify and protect reserve networks in North America (Soul and Terborgh 1999).

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54 CHAPTER 3 LANDSCAPE CONNECTIVITY FOR THE FLORIDA BLACK BEAR Introduction The Florida black bear is the most common of four documented wide-ranging species found in Florida at the time of Eur opean exploration and settlement of North America. The bison and red wolf disapp eared from Florida before the early 1900s primarily because of persecution (Humphrey 1992 ). The only breeding population of the Florida panther is now relegated to extrem e southwestern Florida in a small population that is threatened by habitat loss and fragmentation caused by residential, commercial, industrial, and agricultural development (Mae hr 1997b; Maehr et al. 2001a; Maehr et al. 2001b; Maehr et al. 2002a). In contrast, the Flor ida black bear remains in five larger and several smaller sub-popu lations across Florida, southern Georgia, and Alabama (Brady and Maehr 1985). Although its range has also been drastically reduced, a regional landscape approach to Florida black bear cons ervation could result in the protection of a statewide metapopulation with a st rong likelihood of survival into the future. Further, it can serve as a flagship and umbrella species for landscape-level conservation in Florida that may greatly enhance the protection and restoration of native biodiversity. Landscape ecology has lead to a significant broadening in the focus of conservation research, planni ng, and management (Forman 1987; Turner 1989; Forman 1995; Pickett et al. 1997). Coupled with the gr owth of this discipline is an increasing awareness of the spatial needs and landscape co nsiderations involved in protecting viable populations of large carnivores and other wide -ranging species (Schoen 1990; Noss et al.

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55 1996; Samson and Huot 1998). Landscape ecolog y is increasingly necessary due to the importance of habitat heterogeneity and the large spatial scales needed to maintain many species. Effective conservation of wide-ran ging species depends on a landscape focus that incorporates natural levels of spatial and temporal heterogeneity, while minimizing the negative effects of artificial edges and barriers (Harris et al. 1996a). Wide-ranging species such as the Florida black bear require large areas to support functional demographics (Maehr et al. 2001b). Black bear are species of the landscape because of their large home ranges and typical dependence on more than one vegeta tion association or ecological community type (Harris and Kangas 1988; Schoen 1990; Maehr 1997a; Samson and Huot 1998). Schoen (1990, p. 146) explicitly linked bear management to landscape ecology: In fact, a narrow concept of habitat ma y be inapplicable for bears, which are wide-ranging creatures of landscapes rather than habitat types per se. . Clearly, the normal movements of bears are so extensive that bear habitat must be evaluated and managed on a landscape scal e often exceeding thousands of square kilometers. . Even in large areas, ma nagers should be as concerned about the composition and status of the surrounding ha bitat as they are about the area they wish to conserve. Habitat loss and fragmentation is anot her key reason for landscape-level management (Wilcox and Murphy 1985; Wilc ove et al. 1986; Harris and Silva-Lopez 1992). Essentially all bear sp ecies have been impacted by habitat loss and fragmentation that has resulted in range cont ractions, smaller populations, and populations that are more isolated from one another (Schoen 1990; Mattson 1990; Noss et al 1996). The direct impact that the outright loss of habitat on black bears is obvious: less habitat means fewer bears. However, the effects of fragmentation are more subtle, yet pernicious. As habitat patche s become smaller, bear populations also are reduced in size, and populations become more isolated or ofte n completely separated. This can lead to

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56 several processes adversely affecting the su rvivability of small populations: demographic stochasticity, inbreeding, nega tive edge effects, and catastr ophic events (Harris and SilvaLopez 1992). Even if a small population doe s persist, it will pr obably lose genetic diversity through genetic drift, and, therefor e, have a reduced ability to survive future environmental changes. Habitat loss and fragmenta tion have resulted in vast reductions in the area occupied by the black bear. It used to be found throughout North America where sufficient forest cover existed (Maehr 1984b; Pe lton 1986). As forests have been cleared for development, occupied black bear range has receded into more remote, inaccessible areas such as mountains, boreal forests, and large swamps. In the eastern United States and especially the southeast, black bear habitat is quickly being relegated to only scattered, large public lands (Pelton 1986). The range of the Florida black bear s hows the same trend of contraction and fragmentation (Hellgren and Maehr 1992; Cox et al. 1994). The Florida black bear is now restricted to approximately 27% of its fo rmer range in seven "more-or-less separate" populations (Kasbohm and Bentzien 1998) incl uding those in southeast Georgia and southwest Alabama. In Florida, the bulk of the former and existing range of the black bear, large forests are being whittled away and fragmented. A lthough approximately 40% of bear habitat in Florida is in public ownership, habitat on private lands are under ever-increasing development pressure as hum an populations continue to grow. Kasbohm and Bentzien (1998) suggest that four of th e existing populations (Apalachicola, OsceolaOkefenokee, Ocala, and Southwest Florida) ar e viable, though they acknowledge that at least two of these (Ocala and Southwest Fl orida) will suffer hab itat loss and population reductions due to continued rapid habitat loss and fragmentation.

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57 Land development trends near Jacksonville and in the panhandle (such as new St. Joe Company residential development) suggest that Kasbohm and Bentzien underestimate the future loss of habitat in the other two populations. Florida currently has 16 million human residents and is project ed to add 3 million more by 2010. In addition, the comprehensive growth manageme nt plans for the entire state would allow approximately 100 million people and at the current growth rate Florida could theoretically reach a human population of 455 million by 2099 (Nicolas and Steiner 2000). Though Florida likely cannot attain su ch a population, the threat of habitat loss and fragmentation over the coming decades is severe. Based on land use trends, the approximate rate of a nnual deforestation has been estimate d as high as 60,000 ha per year (Harris and Scheck 1991). More recent es timates of rural land loss (including both agricultural lands and natural communitie s) using aerial photography and satellite imagery indicate that approximately 52,000 ha are being destroyed each year through conversion to residential, commercial, and industria l development (Reynolds 1999, Florida Division of Forestry 2001). At this ra te, at least 25% of remaining private rural lands (over 2.4 million ha) will be converted to intensive development in the next 50 years. In addition, the pattern of loss is as im portant as the actual amount lost. For instance, depending on where habitat loss actu ally occurs, the smaller bear populations that now exist may become completely isolated and potentially extirpated. New development can sever areas that now serve as links between various bear populations or subpopulations including the Chassahowitz ka, Highlands, St. Johns, Eglin, and Southwestern Alabama populations.

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58 Regardless of the opinion of Kasbohm and Bentzien regarding population viability (1998), Cox et al. ( 1994) determined that a l ong-term, minimally viable population of Florida black bear requires at least approximately 200,000 to 400,000 ha of suitable habitat. Only the Apalachicola, Okefenokee, and Southwest Florida populations currently have protected habitat exceeding the lower end of this threshold. Furthermore, these estimates of viability are based on minimum populations of 200 bears. Other estimates indicate that once widespread species may need effective populations of at least 500 to 5000 to maintain long-term viability and evolutionary potential (Franklin 1980; Lande 1995; Noss et al. 1997). Clearly, no existing contiguous complex of existing protected areas is large enough to support Florida black bear populations of this size. The need for regional landscape approaches to conservation has resulted in increasing attention to the design and protec tion of reserve networks that incorporate landscapes apportioned into func tional networks of reserves multiple-use buffer zones, and landscape linkages (Harris 1984; Noss a nd Harris 1986; Noss and Cooperrider 1994; Harris et al. 1996b; Soul and Terborgh 1999) Although the primary goal of such reserve systems is conserving all biologi cal diversity, landscape ecology and regional conservation strategies are especially releva nt to conservation of carnivores and other wide-ranging species. In a study focused on c onservation strategies for carnivores in the Rocky Mountains, Noss et al. (1996, p. 955-956) elucidate the importance of regional conservation approaches: The overwhelming message from population viability studies of large carnivores is that conservation planning must be unde rtaken at vast spatial scales and must consider connectivity. . If maintaining viable populations of species that have large home ranges and are vulnerable to human activities is an objective, then the conservation planner must grapple with the design and management of entire landscapes. Thus a zoning approach has come to dominate conservation

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59 strategies for large carnivores. Zoned landscapes should include refugia that are strictly protected, but they will often be dominated by multiple-use lands. These principles are directly applicable to conservation and management efforts for the Florida black bear. One of the primary goals for its conservation should be maintenance and restoration of functional connections among bear populations across the state. In this chapter, the best opportunities to maintain or restore such connectivity were explored using a GIS function called least cost path (LCP). These methods are similar to those to delineate the Florida Ecological Netw ork, but in this case were specifically designed to test potential la ndscape connectivity for the Florida black bear. Different methods for conducting LCP analyses are also as sessed. These analyses are then used to identify the highest quality habitat and the best opportunities to maintain and restore connectivity among populations within Florida. Florida Black Bear Ecology Taxonomy and physical characteristics Merriam described the Florida black bear as a full species, Ursus floridanus (1896). It is now considered to be a subspecies, Ursus americanus floridanus (Hall 1981). There is some question about the valid ity of the Florida black bear's taxonomic status as a subspecies. Howe ver, recent investigations by the U.S. Fish and Wildlife Service regarding the validity of the Louisian a black bear, which included comparisons to the Florida black bear, reinforced its subs pecies status (Federal Register 1990). The Florida black bear is almost always black and sometimes has a whitish chest patch. Florida black bears are an apparent exception to Bergmann's rule with females weighing an average of about 82 kg and males weighing an average of about 113 kg (Maehr and Wooding 1992). Florida male s occasionally obtain masses up to 300 kg

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60 (Maehr and Wooding 1992). Both the aver ages and maximum masses are on the upper ends of masses for all North American black bears reported by Pelton (1982). Habitat use and food habits The Florida black bear uses a wide variet y of forest types such as pine flatwoods, hardwood and mixed swamps, cabbage pa lm forests, sand pine scrub, hardwood hammocks, and even mangroves (Maehr and Wooding 1992; Maehr 1997a). Open sandhills are only used occasionally (Wooding and Hardisky 1988). Denning sites are typically ground nests found in areas of dense shrubs such as saw palmetto thickets or w ithin swampy areas on higher ground (Wooding and Hardisky 1992). Tree cavities are important denning sites in other regions and may also be used by Florida bears, although past and present timber practices have greatly reduced the availability of such trees (Pelton 1982; Weav er et al. 1990; Maehr and Wooding 1992). The Florida black bear is omnivorous, but plant matter dominates as a food source. Black bears typically follow the phenology of plants in selecting food items seasonally (Amstrup and Beecham 1976; Land ers et al. 1979; Pelton 1982; Pelton 1986). In spring the major food item is usually new green leaves and shoots of various plant species. Soft mast such as berries and other fruits are the major food items during summer; and hard mast such as acorns usually dominate fall/winter diets. The Florida black bear exhibits similar trends, but the typically mild climate results in soft mast being available over longer periods of time (M aehr and Brady 1984a; Maehr and Wooding 1992; Stratman 1998; Scheic k 1999; Stratman and Pelt on 1999). Saw palmetto ( Seronoa repens ) fruits are heavily used in late summer and fall; with cabbage palm ( Sabal palmetto ) hearts, tupelo ( Nyssa spp.) fruits, acorns ( Quercus spp.), blueberries ( Vaccinium spp.), blackberries ( Rubus spp.), and gallberry ( Ilex glabra ) also important

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61 ( Maehr and Brady 1984a; Maehr and Brady 1984b ; Maehr and Wooding 1992). Animal matter makes up a smaller, but regular, part of the diet and includes wasps ( Vespula spp.), bees ( Apis mellifera ), ants ( Campanotus abdominalis floridanus ), and vertebrates such as armadillos ( Dasypus novemcinctus ) and feral pigs ( Sus scrofa ) in Florida. Social structure and home ranges The black bear is usually solitary except during courtship/mating and when females are with cubs. Depending on the re gion, season, sex, and food availability, home ranges of individual bears can be fairly ex clusive (Young and Ruff; Rogers 1987), but in most situations there is often a great de gree of overlap (Reynolds and Beecham 1977; Garshelis and Pelton 1981; Wharburton a nd Powell 1985; Klenner 1987; Mollohan and Lecount 1989). Data collected on the Florida black bear indicate ex tensive overlap of home ranges in the Ocala and Osceola Nati onal Forests and southwest Florida (Wooding and Hardisky 1988; Maehr 1997a). Home ranges for adult males are considerably larger than for adult females, and male territories will overlap th e ranges of several females (Pelton 1982). Over the black bear's continental distribution, home ranges va ry widely likely in relation to habitat quality (Pelton 1982). Home range size for Fl orida black bear are average compared to other regions: average adult male and female home range size were calculated in recent studies to be 170 km2 and 28 km2 (Wooding and Hardisky 1988) and 283 km2 and 54 km2 (Maehr 1997a) respectively. Reproduction The black bear, like other bear species, has one of the lowest reproductive rates known among terrestrial mammals (Jonkel and Cowan 1971; Bunnell and Tate 1981; Eiler et al. 1989). Sexual maturity is reached at about 3 to 5 years of age, although first

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62 reproduction can be as late as 7 to 8 ye ars (Bunnell and Tait 1981; Pelton 1982). Florida black bear females usually produce their first cubs at 3 or 4 years (Maehr and Wooding 1992). Breeding usually peaks in June and July although in some areas it may begin as early as May or last through early Sept ember (Pelton 1982; Eile r et al. 1989; Maehr 1997a). Females are induced ovulators; and imp lantation is delayed until late fall (Pelton 1982). Parturition occurs in the den during wi nter. Typical cub production is usually 2, although litters of 3 and 4 also occur (P elton 1982; Maehr 1997a). Females normally produce young every other year, although seasonal mast failures may eliminate reproduction in some years (Rogers 1987). Seasonal movements, dispersal, and connectivity Seasonal movements and dispersal are th e most important considerations for a landscape-based approach to conserving the Fl orida black bear. After winter denning and throughout the fall, black bears steadily increase in activity, and home ranges usually expand accordingly (Rogers 1987). In some area s, this can include complete shifts in home ranges as food availability shifts sp atially (Garshelis a nd Pelton 1981; Klenner 1987; Mollohan and Lecount 1989; Maehr 1997a). Florida black bear in the Ocala National Forest usually shift from pine flatw oods during winter and spring to sand pine scrub in the summer and fall; whereas bears in Osceola National Forest mainly utilize swamps (Wooding and Hardisky 1988). Seasonally increasing adult male activity patterns are likely related to both reproductive effort in the summer and foraging requirements in the fall. The greater mobility of male black bears makes them mu ch more susceptible to roadkill or hunting and poaching (Pelton 1982; Rogers 1987). One adult male Florida black bear moved 35-

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63 km out of its normal home range during the breeding season (Wooding and Hardisky 1988). Long distance movements by females are rarer, although one relocated adult female Florida black bear in the panhandl e moved 77 km (Wooding et al. 1992). In Minnesota, black bears (both ma les and females) m oved considerable distances out of normal home ranges to use more abundant f ood resources in the late summer and fall (Rogers 1987). Movements up to 83 km (with an average of 29.5 km) were recorded to reach one particular resource, and one adult male traveled 201 km in 13 weeks, which is the longest movement recorded for a non-dispersing bear (Rogers 1987). Dispersal usually refers to the movement of animals away from their area of origin (Brown and Gibson 1983). Black bear di spersal usually occurs at 2 to 4 years of age (Pelton 1982; Rogers 1987). Subadult fema les usually stay in the immediate area of their mother's home range; whereas subadult males may disperse widely, either in response to social pressure from resident adult males (Pelton 1982), or socially independent reasons (Rogers 1987). In a samp le of 51 subadults in Alaska, all male subadults dispersed, whereas only 3% of th e subadult females disp ersed (Schwartz and Franzmann 1992). In Minnesota, dispersal distances ranged from 13 to 219 km and averaged 61 km (Rogers 1987). There was al so evidence of a dispersal event over 324km (Rogers 1987). In north-central Florida, the dispersal of 4 subadult males ranged from 22 to 56 km (Wooding and Hardisky 1988) Another subadult male moved 140 km in southwest Florida (Maehr et al. 1988). The longest known dispersal distance of a subadult female in Flor ida covered 60 km in south Florida (Maehr 1997a). Dispersal is an important demographic f actor that has a key role in population regulation (Kemp 1974; Bunnell and Tait 1981; Lecount 1982; Beecham 1983; Rogers 1987). In Alberta, 26 adult males were rem oved in an experimental study area, and a

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64 large number of subadult males quickly moved in to take their territories (Kemp 1974). Other studies indicate that many transient sub-adult males routinely travel through occupied territories (Beecham 1983; Rogers 1987 ). This wide-ranging behavior of subadult males is a key factor in linking re gional bear populations. Such dispersal may currently link several populations of the Florida black bear. Habitat protection, restoration, and population re-i ntroduction in key areas could establish a statewide metapopulation. Corridors and landscape linkages (areas that link larger core reserves) are a primary method for designing reserve networ ks to facilitate conn ectivity (Harris 1984; Harris and Scheck 1991; Noss and Cooperride r 1994; Harris et al. 1996b; Soul and Terborgh 1999). For the Florida black bear, th ese landscape features serve at least three purposes related to connectivity: To facilitate daily or seasonal movements To allow dispersal that mi ght facilitate gene flow be tween populations, buffer small populations, or recolonize vacant areas To allow range shifts in response to vagari es of food supply, catastrophic events, or long-term environmental change (Noss 1993). Functional connectivity is more likel y in corridors that not only support movement but home ranges as well (Harri son 1992; Noss and Cooperrider 1994; Noss et al. 1996). Based on the average home range requi rements for a male Florida black bear, a corridor would have to be at least 13 km wide for a square home range or 9 km wide if the home range was twice as long as wide. Landscape linkages could be much bigger. The best regional example of such a linka ge is the Pinhook Swamp, which connects the Osceola National Forest and the Okefenokee National Wildlife Refuge. Though forest and other primary habitat is preferred, landscape linkages for the Florida black bear can

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65 include a mixture of habitats and low-intensity land uses (e.g., most types of agriculture) (Maehr et al. 1988; Maehr 1997a). Methods The potential for protecting functiona l landscape linkage s between bear populations and additional areas of habitat in Florida was assessed using the least cost path (LCP) function. Least cost path resu lts selected from 17 Cost Surfaces were then combined with a black bear habitat model (developed using multiple logistic regression and also used to create several Cost Surfaces) to identify the area with the potential to support a statewide metapopulation (Figure 3-1). LCP function is a raster-based algorithm available in ESRI’s Arc-Info GRID, ArcView Spatial Analyst, or ArcGIS software. It is an optimization function that seeks the least costly route between a source and a destination. Typically this algorithm has been used to find the optimal path for linear infrastructure (including roads and transmission lines). LCP analysis can also be applied to identifyi ng landscape linkages between conservation areas to maintain or restore connectivity between wildlife populations. Identifying LCPs first requires the developm ent of a cost surface, which is a raster map in which every cell (or pixel) is ranked for its potential suitability for accommodating a particular function. In the case of ecological connectivity, a cost surface ranks each cell based on its poten tial to support a functional ecological connection. Cells within the study area can be ranked using as many variables as deemed relevant for determining connectivity potential. These variables can include intrinsic qualities (such as the land use of the cell) or landscape or context values (such as whether the cell is part of a large forest bl ock or near a large urban area).

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66 Figure 3-1. Process used to identify th e land area with the potential to support a statewide black bear metapopulation

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67 There are several issues regarding the use of LCP for identifying landscape linkages to be discussed. The LCP function minimizes the accumulated cost of traveling through cells. Therefore, it attempts to minimize the distance traveled and the number of high cost cells that must be traveled through to get from the source to the destination. Hence, the range of values used in a cost surface may greatly affect the relative significance of distance versus cell cost or vice versa for determining the LCP. For example, if a cost surface was constructed where all cells within the study area were given the same cost (e.g., a value of 1 which correlates to the lowest cost, and therefore, the most suitable cells), the function would re turn an LCP that was a straight line (the shortest distance) between the source and the de stination. In this case, cell suitability has no bearing on the resulting LCP; and therefore distance is the only factor considered. However, if a wider range of values is used to represent the differences among cells with high or low suitability, then cell suitability, or cost, becomes more important for determining the LCP. Thus a primary question when developing cost surfaces is how to incorporate a range of input values that appropriately balances both cell cost and accumulated distance when determining LCPs. Other questions for constructing cost surfaces include the following: How are features such as major roads and la rge water bodies best included within cost surfaces to represent their potential impedance to functional connectivity? Should cost surfaces include more variables that may be relevant to ecological connectivity; or can simpler surfaces including one or a few potentially critical variables result in useful assessments of potential connectivity? When multiple variables are used in cost surfaces, do different methods of weighting variables result in significant differences in LCPs? Could quantitative methods (rath er than qualitative) methods create cost surfaces that enhance the statistical basis of the LCP algorithm?

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68 To evaluate these questions and to expl ore options for creating cost surfaces for identifying opportunities for facilitating connec tivity, seventeen cost surfaces were created and used to run the LCP function to identify the best potential linkages among the five largest Florida black bear populations ac ross the state (Table 3-1). I compared the relative performance of these cost surfaces. Th en three cost surfaces were selected to represent the best landscape linkage options for the five major populations. I also used the three selected cost surfaces to analyze a dditional connectivity betw een the five largest populations, smaller populations, and other areas that could support bear populations in the future. All least cost path and habita t analyses were conducted using the raster functions of ESRI's GIS software, and 90 m ce ll sizes were used because of the size of the study area and because of computin g limitations with various neighborhood and regional analysis functions. I created four major categories of cost surfaces. The first four cost surfaces combine multiple criteria where variables are ranked individually using the same scale, then combined to create one cost surface. Different weighting schemes were also applied to create different versions of these multiple criteria cost surfaces. The next five cost surfaces (Cost Surfaces 5 to 9) were simplified to include only a few variables that were potentially most important for determining suitability for connectivity (landcover type, patch size, proximity to large developed areas, and proximity to roads). Variations include the following: Cost surfaces based primarily on forest All potential bear habitat Incorporation of major roads (h ighways) and open water bodies

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69 Combinations of habitat pa tch size, distance from devel opment, and distance from major roads. The next six cost surfaces (Cost Surfaces 10 to15) are modified versions of the first 9 cost surfaces, where the range of values was expanded to test the influence of cell suitability versus accumulated distance in determining LCPs. The ranges of values were expanded by using various exponential functions. The final two cost surfaces (Cost Surfaces 16 and 17) were created by running a multiple logistic regression model to develop a statewide map of Florida black bear habitat quality statewide. Black bear occurrences collected in radio telemetry studies of four of the major populations, and over sixty landscape variables were compared in the model. The two cost surfaces were based on slightly different models using different sets of random locations in the multiple logistic regression analyses. Multiple Criteria-Based Cost Surfaces Multiple utility assignments (MUAs) are optimization surfaces that represent a combination of more than one single criteria or utility assignments. Each single utility assignment (SUAs) ranks suitability for a particular function based on a single criterion on the same scale as all the other criteria. In these cost surfaces, all SUAs were ranked on a scale from 1 to 10. MUAs are then created by combining all of the SUAs either with or without weighting. Cost Surface 1: multiple utility assignment with major roads and large open water bodies Cost Surface1 was created using 11 variable s relevant to black bear habitat quality and conservation to create an MUA with fi nal ranks of 1 to 100. Major roads (those within the Florida Intrastate Highway Syst em) and large water bodies were included in this cost surface by assigning them specific hi gh costs above the value range of 1 to 100

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70 Table 3-1. Seventeen cost surfaces used to assess landscape linkages for the Florida black bear Cost surface # Description Value range 1 Multiple Utility Assignment (MUA) using 11 bear habitat quality variables, major roads, large water bodies. 1-200 2 Multiple Utility Assignment (MUA) using 11 bear habitat quality variables. 1-100 3 Multiple Utility Assignment (MUA) using 11 bear habitat quality variables, major roads, large water bodies with a compressed value range. 1-20 4 Multiple Utility Assignment (MUA) using 11 weighted bear habitat quality variables, major roads, large water bodies with a compressed value range. 1-20 5 Ranked forest cover a nd other land cover and land uses 1-100 6 Forest cover ranked by size class with other land cover and land uses also ranked 1-100 7 Black bear habitat ranked by size class with other land cover and land us es also ranked 1-100 8 Bear habitat ranked ba sed on patch size, distance from intensive development, and distance from major roads 1-100 9 Bear habitat ranked base d on patch size and distance from intensive development 1-100 10 Cost Surface 3 transformed using the ArcView exponential function 3-22026 11 Cost Surface 4 transformed using the ArcView exponential function 3-22026 12 Cost Surface 10 with major roads and large water bodies added 3-22026 13 Cost Surface 11 with major roads and large water bodies added 3-22026 14 Cost Surface 8 transformed by squaring the original values 1-10000 15 Cost Surface 9 transformed by squaring the original values 1-10000 16 Multiple logistic regressi on bear habitat model 1-100 17 Alternative multiple logistic regression bear habitat model 1-100

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71 (200 and 150 respectively). Each SUA is base d on a factor considered significant to black bear habitat quality or more likely to provide a favorable design option for a landscape linkage. For each SUA, every cell within the study area (the entire state) is given a value from 1 to 10, with 10 indicating that the cell has the highest or best value for that index and 1 indicating lowest value. The eleven indices used were the same as those in Maehr et al. (1999) though minor modifications were made in the ranking of some of the indices. The eleven indices used were as follows: Primary and secondary black bear habitat Using the Florida Fish and Wildlife Conservation Commission (FWC) landc over data (Cox et al. 1994), potential primary habitat was identified. Primary habitat was define d as all patche s of pineland, oak scrub, sand pine scrub, mixed hardw ood, upland hardwood forest, cypress swamp, mixed hardwood swamp, bay swamp and bo ttomland hardwood swamp greater than 14.8 ha (Mykytka and Pelton 1989; Cox et al. 1994) To incorporate smaller patches of potential secondary habitat nearby, a one km buffer was created around primary habitat and additional habitat (smaller blocks of primary habitat as well as dry prairie, sandhill, shrub swamp, and shrub and brus hland) located within the buffer were included (Cox et al. 1994). In the index, primary habitat wa s ranked 10, secondary habitat was ranked 7, and all other cells (areas) in the state were ranked 1. Preferred habitat Using the FWC landcover data as the input, natural and seminatural landcover types were ra nked into three classes and all other land uses as a fourth class based on their relative value as potential bear habitat (Maehr and Wooding 1992; Cox et al. 1994; Maehr 1997a; Table 3-2). Habitat block size This SUA was created to rank areas based on the size of potential habitat patches not fragmented by roads. Roads selected to delineate habitat

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72 Table 3-2. SUA ranking land cover type s based on preference as habitat Habitat type Rank Pineland (including pine plantation) 10 Sand pine scrub 10 Oak scrub 10 Mixed hardwood-pine 10 Upland hardwood forest 10 Cypress swamp 10 Mixed hardwood swamp 10 Bay swamp 10 Sandhill 7 Mangrove swamp 7 Shrub and brushland 7 Coastal strand 3 Dry prairie 3 Freshwater marsh and wet prairie 3 Salt marsh 3 Shrub swamp 3 All other land uses (agric ulture and urban) 1

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73 patches had traffic le vels of 2500 or greater vehicles per day or were highway segments with ten or more documented road kills. Fi rst, primary and secondary habitat from SUA 1 were combined. The highways included we re considered to have high enough traffic levels to serve as barriers or filters for bear movement or important mortality threats (Brody and Pelton 1989; Wooding and Maddrey 1994). Contiguous potential habitat not bisected by such roads were then grouped into ranked size classes (Table 3-3). Habitat diversity Areas with a higher diversity of plant communities will have a higher probability of supporting a diverse arra y of food sources and act as a buffer during mast crop failures (Pelton 1985; Rogers and Allen 1987; Mollohan and LeCount 1989; Schoen 1990; Maehr and Wooding 1992; Sams on and Huot 1998). This index was created by first reclassifying the FWC landcover data into the following four categories: Forested wetlands (hardwood swamp, cypr ess swamp, bay swamp, mangrove swamp, shrub swamp) Forested uplands (pineland, sand pine scr ub, sandhill, upland hardwood forests, and mixed hardwood-pine) Freshwater and saltwater marshes Low stature open brush uplands (xeric oak scrub, dry prairie, coastal strand, and shrub and brushland) (Cox et al. 1994). Each cell was then ranked by the number of different habitat categories found within the surrounding km2 (Table 3-4). Cells that were not considered bear habitat based on the FWC landcover data were given th e lowest value regardless of the diversity of habitats in the surrounding area. Distance from large areas of protected habitat Larger areas of protected conservation lands provide critical core areas to help ma intain breeding populations of black bear (Hellgren and Maehr 1992; Cox et al. 1994; Samson and Huot 1998). Areas

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74 Table 3-3. Ranking of potentia l habitat based on patch size Block size of potential habita t fragmented by high traffic highways and highways with bear roadkills Rank Potential black bear habitat bl ock greater than or equal to 200,000 ha 10 Potential black bear ha bitat less than 200,000 ha and greater than or equal to 100,000 ha 9 Potential black bear ha bitat less than 100,000 ha and greater than or equal to 40,000 ha 8 Potential black bear ha bitat less than 40,000 ha and greater than or equal to 20,000 ha 7 Potential black bear ha bitat less than 20,000 ha and greater than or equal to 4,000 ha 6 Potential black bear ha bitat less than 4,000 ha and greater than or equal to 2,000 ha 5 Potential black bear ha bitat less than 2,000 ha and greater than or equal to 400 ha 4 All other potential bear habitat 3 All other cells in study area 1

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75 Table 3-4. Habitat diversity rankings Habitat diversity/variety Rank Four types of habitat 10 Three types of habitat 8 Two types of habitat 6 One habitat 4 Other cells 1

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76 close to large blocks of protected bear habitat are likely to be used by bears, may provide critical foraging habitat seasonally or durin g mast failures (Samson and Huot 1998), may be critical for providing enough additional ha bitat to support viable populations (Cox et al. 1994), and are more likely to be within di spersal distances of bears and, therefore, more likely either to support part of a f unctional metapopulation or to be re-colonized (Cox et al. 1994; Maehr 1997a). Therefore, in this index, potential habitat (as identified in SUA 1) in blocks of 20,000 ha or greater within existing conserva tion lands (primarily public lands but also include private preserves such as those ow ned by The Nature Conservancy, National Audubon Society, and conservation easements ) were identified (Cox et al. 1994). Potential habitat needs to be emphasized because there are several areas across the state including the Green Swamp Conservation Ar ea and the Corbett Wildlife Management Area that meet the criteria for potential ha bitat but do not currently support breeding black bear populations. Proximity to all such conservation areas was modeled using intervals based on typical dispersal distances for black bear (Rog ers 1987; Maehr et al. 1988, Wooding et al. 1992; Cox et al. 1994; Maehr 1997a; Table 3-5). Roadless areas Roadless areas are more likely to provide optimal black bear habitat by minimizing the chance of roadkills, providing large blocks of intact habitat, and minimizing various forms of disturbance (Lentz et al. 1980; Quigley 1982; Pelton 1986; Brody and Pelton 1989; Kasw orm and Manley 1990; Beringer et al. 1991; Clark et al. 1993; Beecham and Rohlman 1994; W ooding and Maddrey 1994; Heyden 1997; Powell et al. 1997; Martorello 1998; Orlando 2002). In this index, roadless areas were identified using class 1 through class 4 road s found in the 1:24000 roads data for Florida created by the U.S. Geological Survey (U SGS). Class 5 roads, which are unimproved

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77 Table 3-5. Ranking of distance from prot ected bear habitat 20,000 ha or larger Distance from protected bear habitat 20,000 ha or larger Rank Areas < 20 km from core areas 10 Areas 20-40 km from core areas 7 Areas 40-60 km from core areas 3 Areas > 60 km from core areas 1

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78 dirt roads frequently referred to as jeep tra ils, were not included. The identified roadless areas were then broken into size classes and ranked by percentage of potential bear habitat (using the methods from SUA 1 to id entify habitat) found w ithin each roadless area (Table 3-6). Thresholds selected were based on a similar index created by Cox et al. (1994) and recommendations on f unctional sizes of bear hab itat blocks from Hellgren and Maehr (1992). Road density Road densities, though related to roadless areas, more specifically capture the potential intensity of disturbance associated with roads as the number of roads increase. It may be possible for an area to not meet strict standards or definitions of roadlessness yet support low enough road densitie s to provide functiona l habitat with low or no disturbance to sensitive species. However, as road densities increase, the potential for a variety of disturbances including roadkills, poaching, edge effects, and others associated with vehicle traffic and human activity also tend to increase (Lyon 1983; Brody 1984; Thiel 1985; Van Dyke et al. 1986; Mattson et al. 1987; McLellan and Shackleton 1988; Mech et al. 1988; Brody a nd Pelton 1989; Mladenoff 1995; Trombulak and Frissell 2000; Orlando and Maehr 2001). To create a road density index, the linedensity function in the GRID module of ArcInfo was used to calculate road density. Class 1-4 roads from USGS 1:24000 roads were included in the linedensity function to calculate road density in the 2.6 km2 surrounding each cell within the study area. Rankings were based on the recommendation by Pelton (1986) to main tain road densities below 0.33 km/km2 to maintain high quality black bear habitat and the recommendation that road densities should be maintained at least below 0.66 km/km2 to provide habitat for wide-ranging species sensitive to road impact s (Noss and Cooperrider 1994) (Table 3-7).

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79 Table 3-6. Roadless area ranks based on size of the roadless areas and the percentage of bear habitat within roadless areas Roadless area size and percen tage habitat combination Rank Roadless areas 4,000 ha or great er with greater than 70% primary potential black bear habitat 10 Roadless areas 4,000 ha or gr eater with 40-70% primary potential black bear habitat 9 Roadless areas 4,000 ha or gr eater with 10-40% primary potential black bear habitat 8 Roadless areas 2000 ha or greater with greater than 70% primary potential black bear habitat 7 Roadless areas 2000 ha or gr eater with 40-70% primary potential black bear habitat 6 Roadless areas 2000 ha or gr eater with 10-40% primary potential black bear habitat 5 Roadless areas 1000 ha or greater with greater than 70% primary potential black bear habitat 4 Roadless areas 1000 ha or gr eater with 40-70% primary potential black bear habitat 3 Roadless areas 1000 ha or gr eater with 10-40% primary potential black bear habitat 2 Roadless areas below 1000 ha 1

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80 Table 3-7. Ranking of road densities Road density Rank Less than 0.33 km/km2 10 0.33 or greater and < 0.66 km/km2 9 0.66 km/km2 or greater and < 0.99 km/km2 8 0.99 km/km2 or greater and < 1.32 km/km2 7 1.32 km/km2 or greater and < 1.65 km/km2 6 1.65 km/km2 or greater and < 1.98 km/km2 5 1.98 km/km2 or greater and < 2.31 km/km2 4 2.31 km/km2 or greater and < 2.64 km/km2 3 2.64 km/km2 or greater and < 2.97 km/km2 2 2.97 km/km2 or greater 1

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81 Distance from major roads Larger roads with higher traffic levels cause roadkills and can result in road avoidance and habitat fragmentation (Wooding and Brady 1987; Brody and Pelton 1989; Gilbert and Wooding 1994; Wooding and Maddrey 1994; Maehr 1997a; Orlando and Maehr 2001). In this analysis, proximity to major roads was modeled such that areas closer to such roads were ranked lower for corridor suitability. As a conservative estimate, all roads with tr affic levels of 2500 vehicles per day or greater and additional road segments with 10 or more bear roadkills were included as major roads. Ranking thresholds were created by using a sliding scale, where the most intensive zones of potential impacts near roads were assigned the smallest intervals, and other ranks were given equal intervals (Table 3-8). Land use intensity Intensity of land use is assumed to affect the potential quality of areas as bear habitat (Mattson 1990; Schoen 1990). In this index, 1995 land use data from each of Florida’s five Water Management Districts were reclassified into the following four general land use categories to depict level of land use intensity: All native or natural habitat including wetland and upland forests of all types, marshes, prairies, etc. Low-intensity land use such as unimpr oved pastures, woodland pastures, pine plantations, and areas that have been platted for development but still retain natural cover types Moderate intensity land use including impr oved pastures, row crops, citrus groves, etc. High intensity uses including all residentia l, commercial, and i ndustrial land uses. Though some natural communities included in the native category may not be used frequently by bears, and some land uses in high er intensity classes such as pine plantation can provide black bear habitat, these categ ories serve as a general indication for the

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82 Table 3-8. Ranking of distances from major roads Distance from major roads Rank > 7001 m 10 6001 m to 7000 m 9 5001 m to 6000 m 8 4001 m to 5000 m 7 3001 m to 4000 m 6 2001 m to 3000 m 5 1001 m to 2000 m 4 501 m to 1000 m 3 101 m to 500 m 2 0 m to 100 m 1

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83 potential of disturbance to bears, management activities that may conflict with bear habitat needs, and the potential suitability of areas to serve as bear corridors (Table 3-9). Distance from larger areas of intensive land use Intensive land uses can disturb bears and increase mortality through human-bear conflicts and roadkills (Mattson 1990; Schoen 1990). The purpose of this SUA was to identify the potential for lower habitat quality near larger areas of intensive land use. To avoid areas not optimal for bear corridors, the distance from areas of high in tensity land use (using the same classification as SUA 9) 40 ha or larger was ca lculated and ranked (Table 3-10). Conservation lands Protected bear habitat is an essential component of a conservation strategy. The purpose of this index was to identify and prioritize areas based on their land protection status regardle ss of size. Though black bears are found on private lands in various parts of Florid a and some populations may be expanding on private lands, the population cores for the 5 largest populations are on public lands (Brady and Maehr 1985). In addition, landscape linkages would incorporate as much existing and proposed conservation lands as possi ble. Therefore, in this SUA, all cells were ranked based on their la nd conservation status. Cons ervation land status included the following: existing protected areas (national parks, stat e parks, national forests, state forests, water management district lands, The Nature Conservancy Preserves, and conservation easements) proposed conservation lands (Florida Forever projects, Save Our Rivers projects, and official proposals with various county land acquisition programs) all other private lands (Table 3-11). Combination of eleven indices to create Cost Surface 1 All eleven indices, each ranked on a scale of 1 to 10, were added to create a qualitative combined ranking,

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84 Table 3-9. Land use intensity rankings Land use intensity Rank Native habitat 10 Low intensity land use (pine pl antations, rangelands, etc.) 7 Moderate intensity land use (row crops, improved pasture, etc.) 2 High-intensity land use (residential, commercial, industrial) 1

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85 Table 3-10. Ranking of distances from major roads Distance from major roads Rank > 9000 m 10 8001 m to 9000 m 9 7001 m to 8000 m 8 6001 m to 7000 m 7 5001 m to 6000 m 6 4001 m to 5000 m 5 3001 m to 4000 m 4 2001 m to 3000 m 3 1001 m to 2000 m 2 0 m to 1000 m 1

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86 Table 3-11. Conservation land rankings Conservation land status Rank Existing conservation lands 10 Proposed conservation lands 5 All other private lands 1

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87 termed a multiple utility assignment (MUA). In the MUA, every cell within the state is ranked based on its habitat significance or su itability for facilitating connectivity for the Florida black bear. The value range of the combined MUA is 11-110 with 11 representing the least suitable areas and 110 representing the most suitable areas. However, the LCP function attempts to minimize accumulated cost. Therefore, the MUA must be inverted to turn it into a cost surface. This was accomplished by first subtracting 10, then inverting the values so that the high est suitability was a value of 1 and the lowest suitability was now 100 (Figure 3-2). The last step in creating Cost Surface 1 was inclusion of major roads and large water bodies. Though roads have been factored into the development of the cost surface in 4 SUAs (habitat block size, roadless ar eas, distance from major roads, and road densities), bear avoidance of large highways may be important enough to assign major highways a very high cost. In this cost surface, roads within the Florida Intrastate Highway System were assigned a value of 200. In addition, all open water bodies and major rivers were assigned a value of 150 to minimize crossing large water bodies. When these features were added, they were combined with the major roads data so any cells at the intersection of highways and wate rbodies received a value of 150 to delineate locations most suitable for crossing roads. Assigning major roads and large water bodies high values in the cost surface was an attempt to force the LCP function to avoid minimizing path distance that might also result in more major roads and water bodies being traversed versus a longer path th at avoids major roads and water bodies.

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88 Figure 3-2. Cost Surface 1. This cost surface is a cumulative index or multiple utility assignment (MUA) combining eleven individual indices relevant for evaluating Florida black bear habitat significance or suitability for supporting connectivity. A value of 1 re presents the highest suitability and a value of 100 represents the lowest suitability.

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89 Cost Surface 2: cumulative index without adding major roads and large open water bodies This cost surface was created exactly in the same way as Cost Surface 1 except major roads and large water bodies were not a dded to the cost surface so the final value range was 1-100. Cost Surface 3: cumulative index with values of 1-10 Because all eleven individual indices used to create the cumulative index in the first two cost surfaces had value ranges fro m 1 to 10, another means for creating a MUA is to multiply each index by a scaling factor and add the transformed SUAs to create a MUA that also has values from 1 to 10. In th is cost surface, each of the eleven SUAs was multiplied by 0.091, added togeth er, then rounded to the nearest integer to create an unweighted MUA with values from 1 to 10. These values were then inverted to create a cost surface. Major highways and water bodi es were added in the same manner as in Cost Surface 1, except the values assigned were 20 and 15, respectively. The result is the same indices and landscape features used in Cost Surface 2 but with a compressed range of values to test the influence of varying value ranges on LCP results. Cost Surface 4: cumulative index with values of 1-10 created with weighted SUAs The methods used to create Cost Surf ace 3 are also ideal for creating a MUA in which the component indices are weighted to reflect their relative significance for evaluating bear habitat or corri dor quality. In this cost surface, the same eleven SUAs were used to create a MUA with values with 1-10, but in order to weight them each was multiplied by different weights instead of the same scaling factor used in Cost Surface 3 (Table 3-12). To assign weightings, the rela tionship between bear telemetry locations and each of the individual indices was examined using summary tables and scatter plots that

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90 Table 3-12. Weighting factors used to creat e Cost Surface 4. The number after the title of each index refers to the index num ber found above in the description of Cost Surface 1. The higher the value of the weighting factor, the more significance that variable receives in the cumulative MUA. Indices Weighting factor Primary and secondary po tential habitat (1) 0.250 Habitat type preference ranks (2) 0.050 Block size of primary and sec ondary habitat combined (3) 0.200 Habitat diversity (4) 0.025 Distance from large blocks of protected bear habitat (5) 0.075 Roadless areas (6) 0.025 Road density (7) 0.075 Distance from major roads (8) 0.100 Land use intensity (9) 0.025 Distance from intensive land uses (10) 0.150 Land protection status (11) 0.025

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91 demonstrated the number of occurrences within each particular rank for each variable. Weights were chosen using this information combined with consideration of important habitat variables discussed in the black bear literature (Brody and Pelton 1989; Schoen 1990;Cox et al. 1994; Maehr 1997a; van Mane n 1997) and the potential for some redundancy between certain variables. Ther efore, these weights are qualitative because they are not exclusively based on a statis tical relationship between the independent variables and bear occurrences, densities, or known habitat quality. The primary purpose of this weighting scheme is to evaluate how weighting might influence the outcome of LCP modeling in comparison to the unweighted Cost Surface 3. The resulting weighted MUA was inverted to turn it into a cost su rface, and water bodies and major roads were added to the cost surface using the same me thods and values used in Cost Surface 3. Simplified Cost Surfaces The following cost surfaces were created to compare simpler surfaces including only one or a few potentially critical variables with more complex cost surfaces represented by Cost Surfaces 14 and Cost Surfaces 16-17. Cost Surface 5: simplified landcover/landuse-based cost surface This cost surface is based on a simp le ranking of landcover and landuse types without consideration of any landscape-based va riables such as patch size, proximities, or densities. Forest cover was given the highest suitability, other forms of natural cover were given the next highest suitability, and different land use intensities were given varying levels of moderate or low suitability. High intensity land use was converted to “no data”, which means that such cells are excluded from the LCP analyses, and therefore, paths cannot cross them. Finall y, water bodies and major roads were added

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92 using the methods used in Cost Surfaces 24 but with water given the same value as moderate intensity land use ( 50) and major roads assigned a value of 100 (Table 3-13). Cost Surface 6: forest ranked by size class The purpose of this cost surface was to provide a variant of Cost Surface 5 where forest patch size was also cons idered. Forest patches were ra nked by size into ten classes with larger patches ranked as more suitable. Rankings were done by log transforming the patch size to produce size classes that were then ranked. Otherwise, the structure of the cost surface is the same as Cost Surface 5 (Table 3-14). Cost Surface 7: potential habitat ranked by size class The purpose of this surface was to incor porate all bear hab itat ranked in size classes versus using just fore st patches. Potential black bear habitat was ranked using the same size classes as the potential habitat patch size index from Cost Surface 1 (Table 3-15). Cost Surface 8: combination of habitat patch size, distance from intensive development, and distance from major roads This cost surface represents a simplification of Cost Surfaces 1-4, where only 3 SUAs were used versus the 11 used in Cost Surfaces 1-4. The cost surface combines 3 primary factors for locating landscape linkages within large intact areas and distance from intensive development and major roads. Th e potential habitat patch size, distance from intensive development, and distance from majo r road indices from Cost Surface 1 were combined with equal weighting to create a combined index with values from 1 to 10, which was then inverted to create a cost surface. These values were applied only to potential black bear habitat. All other ce lls were assigned values using the same

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93 Table 3-13. Cost Surface 5 categories and rankings Land use intensity Rank Forest 1 Other natural cover 10 Lower intensity land use (pasture, cropland, disturbed but undeveloped) 25 Moderate intensity la nd use (mining, large water bodies, etc.) 50 Major roads 100 High intensity land use (urban, co mmercial, industr ial) No data

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94 Table 3-14. Cost Surface 6 categories and rankings Distance from major roads Rank Forest patches with log 11 or 12 1 Forest patches with log 10 2 Forest patches with log 9 3 Forest patches with log 8 4 Forest patches with log 7 5 Forest patches with log 6 6 Forest patches with log 5 7 Forest patches with log 4 8 Forest patches with log 3, 2, or 1 9 Other natural cover 10 Lower intensity land use (pasture, cropland, disturbed but undeveloped) 25 Moderate intensity la nd use (mining, large water bodies, etc.) 50 Major roads 100 High intensity land use (urban, co mmercial, industr ial) No data

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95 Table 3-15. Cost Surface 7 categories and rankings Distance from major roads Rank Potential black bear habitat bl ock greater than or equal to 200,000 ha 1 Potential black bear habita t less than 200,000 ha and greater than or equal to 100,000 ha 2 Potential black bear habita t less than 100,000 ha and greater than or equal to 40,000 ha 3 Potential black bear habitat less than 40,000 ha and greater than or equal to 20,000 ha 4 Potential black bear habitat less than 20,000 ha and greater than or equal to 4,000 ha 5 Potential black bear habita t less than 4,000 ha and greater than or equal to 2,000 ha 6 Potential black bear habita t less than 2,000 ha and greater than or equal to 400 ha 7 All other potential bear habitat 8 Other natural cover 10 Lower intensity land use (pasture, cropland, disturbed but undeveloped) 25 Moderate intensity la nd use (mining, large water bodies, etc.) 50 Major roads 100 High intensity land use (urban, co mmercial, industr ial) No data

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96 categories in Cost Surface 5, except other na tural cover was assigned a value of 12 to accommodate the 1 to 10 rank of bear habitat (Table 3-16). Cost Surface 9: combination of habitat patch size and distance from intensive development Cost Surface 9 was created to test the effect of not including the distance from the major roads index used in Cost Surface 8. Cost Surface 9 was made using the same methods as Cost Surface 8 except only habita t patch size and distance from intensive development indices were combined to rank potential black bear habitat (Table 3-17). Exponential Function Cost Surfaces One method to emphasize the significance of cell values versus distance in the LCP function is to expand the range between suitability values drastically in a cost surface. This set of cost surfaces was crea ted by using several me thods to expand some of the preceding cost surfaces to investigate how changing the range of values between high and low suitability affected LCP results. Cost Surface 10: expanded version of Cost Surface 3 I transformed Cost Surface 3 (with only values of 1-10 before the addition of large water bodies and major roads) using the exponential function in ArcView Spatial Analyst. The resulting surface had ten va lues ranging from 3 to 22,026 (Table 3-18). Cost Surface 11: expanded version of Cost Surface 4 I transformed Cost Surface 4 (with only values of 1-10 before the addition of large water bodies and major roads) using an exponential function in ArcView. The resulting surface had ten values ranging from 3 to 22,026.

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97 Table 3-16. Cost Surface 8 categories and rankings Distance from major roads Rank Bear habitat ranked based on patch size and distance from intensive development and major roads 1 Bear habitat ranked based on patch size and distance from intensive development and major roads 2 Bear habitat ranked based on patch size and distance from intensive development and major roads 3 Bear habitat ranked based on patch size and distance from intensive development and major roads 4 Bear habitat ranked based on patch size and distance from intensive development and major roads 5 Bear habitat ranked based on patch size and distance from intensive development and major roads 6 Bear habitat ranked based on patch size and distance from intensive development and major roads 7 Bear habitat ranked based on patch size and distance from intensive development and major roads 8 Bear habitat ranked based on patch size and distance from intensive development and major roads 9 Bear habitat ranked based on patch size and distance from intensive development and major roads 10 Other natural cover 12 Lower intensity land use (pasture, cropland, disturbed but undeveloped) 25 Moderate intensity la nd use (mining, large water bodies, golf courses, etc.) 50 Major roads 100 High intensity land use (urban, co mmercial, industr ial) No data

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98 Table 3-17. Cost Surface 9 categories and rankings Distance from major roads Rank Bear habitat ranked based on patch size and distance from intensive development 1 Bear habitat ranked based on patch size and distance from intensive development 2 Bear habitat ranked based on patch size and distance from intensive development 3 Bear habitat ranked based on patch size and distance from intensive development 4 Bear habitat ranked based on pa tch size and distance from intensive development 5 Bear habitat ranked based on patch size and distance from intensive development 6 Bear habitat ranked based on patch size and distance from intensive development 7 Bear habitat ranked based on patch size and distance from intensive development 8 Bear habitat ranked based on patch size and distance from intensive development 9 Bear habitat ranked based on patch size and distance from intensive development 10 Other natural cover 12 Lower intensity land use (pasture, cropland, disturbed but undeveloped) 25 Moderate intensity la nd use (mining, large water bodies, golf courses, etc.) 50 Major roads 100 High intensity land use (urban, co mmercial, industr ial) No data

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99 Table 3-18. Comparison of original valu es from Cost Surface 3 and the transformed values using an exponential func tion to create Cost Surface 10 Original value Transformed value 1 3 2 7 3 20 4 55 5 148 6 403 7 1,097 8 2,981 9 8,103 10 22,026

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100 Cost Surface 12: water bodies and major roads added to expanded Cost Surface 10 This cost surface is the same as Expa nded Cost Surface 10 with water bodies and major roads added by assigning major road s the highest cost (22,026) and water bodies the next highest cost (8,103). Cost Surface 13: water bodies and major roads added to expanded Cost Surface 11 This cost surface is the same as Co st Surface 11, with water bodies and major roads added by assigning major roads the high est cost (22,026) and water bodies the next highest cost (8,103). Cost Surface 14: Cost Surface 8 expanded by squaring This cost surface was created by squari ng the values of Cost Surface 8, which resulted in a range of values from 1 to 10,000 (Table 3-19). Cost Surface 15: Cost Surface 9 expanded by squaring This cost surface was created by squari ng the values of Cost Surface 9, which resulted in a range of values from 1 to 10,000. Using Multiple Logistic Regression Modeling to Develop Cost Surfaces The previous methods used to create cost surfaces primarily involved a combination of multiple indices, each representing a measure of habitat suitability. There are many issues associated with creating cost su rfaces including ranking thresholds for individual indices, and weighting the relativ e significances of habitat and landscape variables that may determine habitat or corridor quality. An alternative approach for creating a cost surface is to develop a predictive model where known occurrences of the species are compared to various landscape variables that may determine bear habitat quality.

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101 Table 3-19. Comparison of original valu es from Cost Surface 8 and the transformed values to create Cost Surface 14 Original value Transformed value 1 1 2 4 3 9 4 16 5 25 6 36 7 49 8 64 9 81 10 100 12 144 25 625 50 2,500 100 10,000

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102 Multiple logistic regression models can be used to predict where a species might occur or where habitat of sufficient quality may exist to restore populations (Maehr and Cox 1995; Mladenoff et al. 1995; Mladenoff and Sickley 1995; van Manen 1997 ; Mladenoff et al. 1999; Carroll et al. 1999). This is rele vant to the Florida black bear because it may be recolonizing its former range. Logistic regression attempts to determine the probability that something will occur. The probability of occurrence is a function of the explanatory or independent variables. The dependent variable is represen ted by a binary value defining presence (1) or absence (0) of the occurrence. The lo gistic regression formula is as follows: P = Exp(Y) / ( 1 + Exp(Y)) This equation is derived from th e basic linear regression formula: Y= Bo+B1X1+ B2X2+…BnXn+e This results in the expanded logistic regression formula: P = (1/(1 + exp(-Bo B1X1-X2B2…XnBn)))*100 Where: P is the probability of presence, Y is a dummy dependent variable, =1 for presence, =0 for absence, Bo is the coefficient on the constant term, Bn is/are the coefficient(s) on the independent variable(s), X is/are the independent variable(s), and e is the error term. The independent variables, Xn, represent the various surfaces representing measures of habitat suitability. The resulting model indicates the probability, from 0-1.0, of bears occurring in a particular area and is used to rank bear habitat statewide. Multiple logistic regression was used to create two alternative cost surfaces. I assumed that more high quality bear

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103 habitat increased the likelihood of an area se rving as a high quality landscape linkage. This approach is practical because it provide s a more objective, quantitative approach for building cost surfaces than the preceding cost surfaces. Over sixty independent variable grids were created as inputs. These included all indices used to create Cost Surface 1, other related data sets that represent variations that were similar to the Cost Surface 1 indices but might have a more si gnificant relationship with bear occurrences, and new categories such as forest density. In stepwise multiple logistic regression, independent (or predicto r) variables are added and removed from the model in successive steps based on their contribut ion to a model that fits the input data. Due to the large number of occurrences a nd independent variables including many variables that were potentially very similar, the thresholds used for determining significance for both inclusions (0.01) and removal of predictors (0.02) were set conservatively to increase the discriminatory power of the model. A correlation matrix was then created for the remaining variables. Highly correlated variables were located and compared, and the variables with less ex planatory value were removed. The major categories of variables included (for a complete listing of all variables used in the model see Appendix A): Habitat variables including: 1) habitat type 2) preferred habita ts, 3) habitat patch size, 4) habitat density measured at va rious scales, and 5) distance from habitat Protected habitat including block size of protected habitat and distance from protected blocks of habitat Habitat diversity, measured as the number of major habitat cla sses within a 256 ha area Roadless areas including many different vari ations (Appendix A) of road data sets ranging from all roads, paved roads only, roads maintained by the Florida Department of Transportation, highways with 2500 or grea ter average daily traffic, highways with

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104 5000 or greater average daily traffic, highways in the Intrastate Highway System, and Class 1 and Class 2 roads from 1:24000 USGS roads Road densities including the road classes in 1:24000 roads ranging from all roads (Class 1-5), Class 1-4, Class 1-3, and Class 1-2 roads Distance from major roads including various road data sets such as roads maintained by the Florida Department of Transporta tion, highways with 2500 or greater average daily traffic, highways with 5000 or greater average daily traffic, and highways in the Intrastate Highway System Land use intensity including land use type re classified into categories using land use intensity classifications, densit y of intensive land uses at several different scales, and distance from intensive land uses Forest data including patch size, forest de nsity measured at several different scales, and distance from forest patches. Black bear occurrence data came from telemetry studies in the Ocala National Forest and Wekiva River basin, the Osceo la-Okefenokee population, southwest Florida, and Eglin Air Force Base (Figure 3-3). Only occurrences collected since 1992 were used, and 80% (12,327 telemetry locations) of su ch points were randomly selected for inclusion in the model so that the remaining occurrences could be used for validation. Because the telemetry data include onl y known locations, random points were used in lieu of absence data. Given concer n about the appropriate selection of random points at the scale of a st atewide model covering approximately 15.2 million ha (Maehr and Cox 1994), two sets of random locations were chosen: one set was selected outside of known occupied bear range within the state (total of 11,281 points), and the other set was selected only within occupied bear range (t otal of 4,075 points) (Figure 3-4). In both cases, random points were located only in terres trial areas (uplands and wetlands) and not within water bodies. Then two alternative vers ions of the model were created using the

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105 Figure 3-3. Telemetry loca tions from major Florida black bear populations used in the multiple logistic regression analysis

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106 Figure 3-4. Recent bear range map from the Florida Fish and Wildlife Conservation Commission. This data was used as th e basis for selecting random locations either outside occupied range or only within occupied range.

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107 two sets. The first version used the random locations outside of known occupied bear range and a stepwise multiple logistic regression modeling process using the SPSS statistics software package. For comparis on, the second version was created using the selected significant output predictor variables from the first model and used these variables and random locations only inside o ccupied bear range in a multiple logistic regression model in Arc-Info GRID. Creation of Analysis Masks to Modify Cost Surfaces The effects of using different masks in the LCP modeling were also analyzed. A mask is a grid map of all areas to be excluded from an analysis or set of analyses. In the creation of cost surfaces, some cover types or land uses are often excluded as unsuitable. Cost surfaces can include a variety of cover types, landscape features, or land use types with a range of suitabilities, or costs, ranging from very high to very low. Areas that are completely unsuitable can be excluded by designating them as no data, which masks them out of the analysis so that the LCP func tion cannot include them within path results. Though black bears may occasionally traver se in or through residential areas (Maehr et al. 1988; Maehr 1997a), most inte nsive land uses including residential, commercial, and industrial (not including most mining) were considered unsuitable when assessing landscape linkages. However, to exa mine the effect of different thresholds of land use intensity when creating no data masks to apply to cost surfaces, two variations of masks were created: one where low density residential land uses (defined as less than 2 units per 0.4 ha) were not masked and anothe r where it was masked. In both versions, moderate density reside ntial (defined as 2-5 units per 0.4 ha) and all more intensive land uses were masked.

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108 To test the effects of bottlenecks (areas where suitable lands narrow and are surrounded by unsuitable lands) on LCP results within potential landscape linkages, two analysis scales were used to delete narrow connections that were surrounded by intensive land uses. The scales used were 3 x 3 ce lls and a 5 x 5 cells or 7.29 ha and 20.25 ha neighborhoods respectively (Figure 3-5). In the 3 x 3 analysis, any neighborhood with at least 2 out of 9 cells with intensive land uses were converted to no data, and in the 5 x 5 analysis, any area with at least 3 or more cells with intensive land uses were converted to no data. To create both a less conservative ma sk and more conservative mask: one mask with low density residential excluded a nd a 3 x 3 neighborhood; and the second mask with low density residential included and a 5 x 5 neighborhood analysis. Therefore, for each cost surface, 3 variations were created and tested: Original cost surface with no mask Low density residential not included in th e mask that was modified using a 3 x 3 neighborhood analysis Low density residential included in the mask that was modified using a 5 x 5 neighborhood analysis. Sources and Destinations for LCP Analysis Opportunities for maintaining or restoring connectivity were analyzed using all cost surface variations to assess landscape li nkages between the 5 primary populations of the Florida black bear. Each population is named after the nearest large conservation land: Big Cypress (National Preserve), Oc ala (National Forest), Osceola (National Forest), Apalachicola (National Forest), and Eglin (Air Force Base). These conservation areas were used as the sources and destin ations for the LCP modeling (Figure 3-6). After examining the LCP results for all cost surfaces for connections between major populations, 3 cost surfaces were select ed to assess connectivity to and from areas

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109 supporting smaller populations or with the pot ential to support populations in the future (Figure 3-6). Areas selected to represent and assess these additi onal landscape linkages included the following: Weekiwachee Preserve, which is a critical part of the small Chassahowitzka black bear population Twelve Mile Swamp Conservation Area, which is part of the northeast extreme of the St. Johns black bear population found in Volusia, Flagler, St. Johns, and Duval counties Lower Suwannee River National Wildlife Refuge, which is in the middle of the Big Bend south of the expanding Apalachicola population Goethe State Forest, which is on the south end of the Big Bend Green Swamp Conservation Area, which is a large protected landscape that could support a breeding population in the future and might play a significant role as part of the bear population in the Chassahowitzka region Myakka River State Preserve, which anchors a large protected landscape to the northwest of the Big Cypress population a nd west of the smaller Highlands County population Corbett Wildlife Management Area, which is the anchor of a large protected landscape in southeast Florida. Identifying Florida Black Bear Habita t and Landscape Linkage Opportunities The habitat model results from the first multiple logistic regression and the least cost path results for 3 of the Cost Surfaces for all connections between major populations, smaller populations, and other de stinations (Figure 3-6) were combined to identify the best opportunities for protecting a statewide me tapopulation of the Florida black bear. Bear habitat was identified as all areas with probability values of 0.5 to 1.0 (Mladenoff and Sickley 1998; Mladenoff et al. 1999). The LCPs for Cost Surfaces 8, 13, and 16 were all buffered by a total of 5 km, a nd all contiguous natural, seminatural, and agricultural land uses within the buffer were identified as part of potential landscape linkages.

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110 Figure 3-5. Comparison between a 3 X 3 and a 5 X 5 neighborhood for analyzing potential bottlenecks. The 5 X 5 neig hborhood with a threshold of requiring no more than 2 cells being No Data will result in more narrow bottlenecks (less than 270 m wide using 90 m cells) being deleted from the analysis.

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111 Figure 3-6. Sources and destinations for a ssessing best potential la ndscape linkages. All cost surface types were used to assess connectivity opportunities between primary populations, and 3 cost su rfaces were selected to assess opportunities to or from small popula tions and other destinations.

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112 Results and Discussion Stepwise Multiple Logistic Regression Habitat Model In the first run of the model, distance from large blocks (20,000 ha and larger) of protected bear habitat was included as one of the final variables. However, after creating the predictive surface using the beta value outputs of the model, large bear habitat conservation areas were considered to have an undesirably strong influence on the model. This was based on two considerations. First, almost all black bear studies conducted in Florida have been primarily centered on la rge blocks of public conservation lands. Though such conservation lands are likely th e cores for various populations, black bear occur regularly on private lands, and severa l populations are expanding in range and, apparently, density on private lands (Thom as Eason, FWC, personal communication). Whether the significance in the initial model is a product of the superiority of bear habitat on conservation lands or whethe r it is an artifact of apparent sampling bias is an open question. Furthermore, the results of this regression model were intended as an alternative method for creating a cost surfac e to identify potential landscape linkages. Therefore, an additional run of the multiple logistic regression model was completed without including conservation lands. Seven predictor variables were included in the final model: Primary and secondary black bear habitat (name of data layer: bhab_37p12arc): This is a local and landscape scale variable th at identified primary habitat as blocks 15.2 ha and larger and secondary ha bitat as all smaller blocks of preferred cover types and less preferred cover types with in 1 km of primary blocks. Block size of primary and secondary habitat (bhab_37p12_rg): This predictor identified contiguous blocks of primary and secondar y habitat bounded by major roads (in this case, major roads used were all roads with average daily traffic of 2500 or greater and other road segments with bear road kills). The value used in the model was the patch size modified using a logarithmic transformation due to the large variation in patch sizes.

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113 Major roadless patches (rdless_dotm): Many different types of roadless areas based on different road data sets and classes of road s were used in this model. However, the only road data set identified in the final model was major roads maintained by the Florida Department of Transportation. Th is data set includes interstate highways, turnpikes, parkways, state highways, and some county roads. Roadless area patch size was modified using a logarithmic transformation. Forest density (forest_dens_m): This wa s a landscape scale variable where the amount of forest was calculated in a 35 x 35 neighborhood using 90 m cells (approximately 992 ha). The final model selected this neighborhood size over two smaller scales: 11 x 11 and 3 x 3. The values used in the model were the number of cells within the neighborhood th at contained forest cover. Land use intensity (luse_intsum): This was a landscape scale variable using a neighborhood analysis in a 11 x 11 neighborhood using 90 m cells, which is approximately a 98 ha area. Land uses were lumped into 4 categories: natural, which was given a value of 0; low intensity and se mi-natural, which was given a value of 1; moderate intensity including most agriculture and some mining, which was given a value of 2, and high intensity including resi dential, commercial, and industrial, which was given a value of 3. These values were then summed for each focal cell of the neighborhood so that the larger the returned value, the more intensive the land use in the surrounding area. Bear habitat density (bhab_37p12sum): This va riable was created by giving primary and secondary habitat the same value (1) and all ot her cells a 0, and then a neighborhood analysis was conducted at the scale of 11 x 11 90 m cell area. Distance from intensive land uses (cat3_int): This variable was created by calculating the distance of all cells from the nearest intensive land uses (all residential, commercial, and industrial). Three versi ons of the analysis were done where all patches of intensive land use were used as inputs for the distance calculations, then only patches 4 ha or larger, and then only patches 40 ha and greater. However, the model selected the version using all patches regardless of size as most significant. The distance values input into the mode l were modified using a logarithmic transformation due to the la rge variation in distances from intensive land uses. The equation used to create the predictive surface was: Pred_v1 = 1 div (1 + (exp( (-7.360 + (0.545 bhab_37p12arc) + (-0.271 bhab_37p12_rg.log) + (0.577 rdless_dotm.log) + (0.004 forest_dens_m) + (-0.014 luse_intsum) + (0.005 bhab_37p12sum ) + (0.681 cat3_int.log))))) The model predicted bear occurrence in large forested blocks and where most bears are currently distributed, thus it offe rs a good representation of potential bear

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114 habitat (Figure 3-7). The only important excep tion may be in south-central Florida where some smaller forest blocks surrounded by open habitats and agricultural lands also received high probabilities. Twenty percent ( 3473 locations) of the black bear telemetry locations were not included in the model so they could be used for model validation. These locations were much more likely to occur in areas with higher probability values than the 2821 random locations that were us ed for validation (Table 3-20). Alternative Model Multiple Logistic Regression Results Because the best method for selecting ra ndom locations as inputs into the multiple logistic regression modeling process was uncer tain, an alternative was created. In the alternative, the same final 7 variables were used but random locations were selected only within known occupied black bear range. Th e new analysis resulted in some changes to the variable coefficients used to create an alternative probability surface: Pred_v2 = 1 div (1 + (exp( (-3.676 + (0.485 bhab_37p12arc) + (-0.285 bhab_37p12_rg.log) + (0.375 rdless_dotm.log) + (0.002 forest_dens_m) + (-0.010 luse_intsum) + (0.004 bhab_37p12sum) + (0.523 cat3_int.log))))) The resulting surface is very similar to the original version (Figure 3-8). The primary difference was that some rural and op en natural landscapes received have higher probabilities than in the original model. The best example is in the Everglades in south Florida. This increase in the value in such areas may have significant impacts on the results of LCP modeling because it increases the probability that the computer will incorporate open landscapes within a LCP. The same twenty percent of the black bear telemetry locations (3,473 locations) not included in the original model were used for validation of the alternative model. Most of these locations are within areas with probability values of 0.75 and higher (Table 3-21). Random locations within occupied bear range (2,313 locations) were also kept out

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115 Figure 3-7. Results of the primary version of the stepwise multiple logistic regression model. Probability of occurrence repres ents the likelihood that a black bear would occur at that location. Theref ore a value of 0 represents 0% probability of occurrence whereas a value of 1 represents 100% probability of occurrence. Habitat quality can be considered to increase as values get closer to 1.

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116 Table 3-20. Comparison of occurrences and ra ndom locations used for multiple logistic regression habitat model validation Probability level Percent of bear occurrences Percent of random locations 0.9-1.0 56% 6% 0.75-1.0 85% 14% 0.50-1.0 93% 25%

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117 Figure 3-8. Results of the alternative version of the multiple logistic regression model. The main difference between the models is that values of lands with very low probabilities of occurrence in the original model tend to have elevated values in this version. This can be es pecially seen in south-central and south Florida.

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118 of the model for validation. These random locations occurred much more frequently within areas with high occurrence probabilities than the random occurrences used in the original model (Table 3-21; Table 3-20). The number of bear occurrences within the top 10% dropped from 56% in the original mode l to 42% in this alternative version. However, the number of bear occurrences with in the top 25% and 50% increased slightly (85% versus 89% and 93% versus 98% respec tively). The number of random locations within the top 10, 25, and 50 percent of the model results increased dramatically: 6% versus 19%, 14% versus 53%, and 25% versus 73 %, respectively. Overall, these results suggest a decrease in the discriminatory power of the model though it is logical that more random occurrences would occur in areas with higher probability values when they were limited to known bear range. Comparison of LCP Results Using Different Intensive Land Use Masks The types of residential development included in a mask and the scale of the analysis to delete bottlenecks affected the results for least cost paths between some of the bear populations. A hypothesis for comparin g cost surfaces is that differences in resulting LCPs will be enhanced in fragmented landscapes versus those that are less fragmented. Fragmented landscapes will contain more areas with low to no suitability. Therefore, cell suitability and the differences between cell suitabilities among cost surfaces should have more influence on LCP resu lts. This property appeared to affect the results of the LCP analyses when using masks with low density residential included versus masks without low densit y residential. LCPs varied based on the use of different masks for some cost surfaces and especially for the paths between the Big Cypress and Ocala populations.

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119 Table 3-21. Comparison of occurrences and ra ndom locations used for validation of the alternative multiple logistic regression habitat model Probability level Percent of bear occurrences Percent of random locations 0.9-1.0 42% 19% 0.75-1.0 89% 53% 0.50-1.0 98% 73%

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120 Differences in using no mask, the mask w ithout low density residential and a 3 x 3 cell neighborhood analysis to de lete bottlenecks (the liberal mask), and the mask with low density residential and a 5 x 5 neighbor hood analysis (the conservative mask) are most evident for Cost Surface 1. In some of the cost surfaces, high intensity land uses were already deleted as no da ta before mask application. However, in Cost Surface 1, all cells within the study area received a value from 1 to 100, and therefore, intensive development received very low suitability scores but could be incorporated in a landscape linkage. The LCP for the 3 variations of Cost Surface 1 between the Big Cypress to Ocala bear populations followed different routes (Figure 3-9). The no mask LCP followed the two other paths until reaching the area just north of Lake Kissimmee, where it diverged from the other two paths by c ontinuing up the Reedy Creek basin, crossing through the western Orlando metr opolitan area, then the Wekiva River basin to reach the Ocala National Forest. Though this path fo llowed suitable areas throughout much of its length, its traversal of we stern Orlando reduces its feasibility as a potential landscape linkage. Because both cost surfaces were identical, except for the difference in the masks, divergences can only be explained by the no mask and liberal mask paths traversing residential areas or narrow co rridors that could not be followed using the conservative mask. In comparing the results of the liberal and conservative LCP results for the rest of the cost surfaces, only 6 of the 17 cost surfaces had no differences in the LCP results including Cost Surfaces 9, 10, 11, 12, 13, and 17. Four of these 6 cost surfaces (10, 11, 12, 13) represented versions of Cost Surface 3 and Cost Surface 4, where the original values from 1-10 were transformed using th e exponential function in ArcView Spatial Analyst, which increased the range of cost surface values from 3 to 22026. When the

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121 Figure 3-9. Comparison of LCP resu lts for the three mask alternatives. The conservative mask LCP is on top of both other paths.

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122 liberal and conservative masks were applied to the original Cost Surface 3 and Cost Surface 4, LCPs diverged in several locations Differences in the performance utilizing both masks in Cost Surfaces 3 and 4 versus Cost Surfaces 10-13 suggests that increasing the range between high and low suitabilities resulted in greater avoidance of marginal areas that were not very suitabl e landscape linkages for black bear. These comparisons suggest that decisions about what to include in a cost surface as highly unsuitable but traversable versus not suitable, and therefore not traversable, is a very important consideration. The intenti on of LCP analysis is to identify potential optimal paths for supporting f unctional landscape linkages or corridors, and more conservative cost surfaces are more likely to produce results that reflect feasible linkage options. In fact, even the conservative mask used in this analysis may not be discriminating enough to eliminate all potential bottlenecks that may be unsuitable for supporting connectivity. Based on these results only the conservative mask was used to identify landscape linkage options between bear populations. Least Cost Path Results for Landscape Linkages between Major Populations The following descriptions focus on the major patterns found in the LCP results. See Appendix C for much more details on comparisons between cost surfaces. Big Cypress National Preserve to Ocala National Forest The Ocala National Forest and Big Cypre ss National Preserve were used as the source and destination for the LCP modeling (F igure 3-6). The landscape between these populations is the most interesting for tes ting cost surfaces because it represents the longest distance between major populations (approximately 300 km) and is the most fragmented landscape regarding bear habitat. Although successful bear dispersal may still be feasible, forest frag mentation and the long distan ce between these two populations

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123 may strongly affect the balance between minimizing path length and cell suitability when calculating LCPs. There was general correspondence at the regional scale among paths for all 17 cost surfaces, however, significant differences existed at several locations in potential landscape linkages between Big Cypress Na tional Preserve (BCNP) and the Ocala National Forest (OCNF) (Figure 3-10). The most important common characteristic of all paths was selection of a nor theasterly route from BCNP to OCNF. There was some divergence just north of BCNP, where 4 of the LCPs first headed in a northwesterly direction. However, all LCPs converged in the Fisheating Creek basin, followed two primary options north along the Lakes Wales Ridge, then traveled through the Kissimmee River basin before branching around Lake Ki ssimmee both to the north and south of the lake. Almost all of the LCPs then conve rged through the Big Bend/Holopaw Florida Forever Project just north of the Three La kes Wildlife Management area, followed the upper Econlockhatchee River southeast of Or lando, crossed the St. Johns River through the Tosohatchee State Reserve and Seminol e Ranch Conservation Area, followed the Volusia Conservation Corridor/Tiger Bay cons ervation complex north, and headed west through the Lake George State Forest/Lak e Woodruff National Wildlife Refuge area to reach OCNF. For more details on the differences between least cost path results for the Big Cypress to Ocala National Forest landscape linkage, see Appendix D. Ocala National Forest to Osceola National Forest Large swaths of black bear habitat currently connect the Ocala and Osceola National Forests. The straight-line distance between them is less than 100 km, which is the shortest distance between the conservati on land hubs of each of the five major black bear populations. All LCPs for the 17 cost surfaces followed the same general path

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124 Figure 3-10. LCP results for the landscape linkage options between Big Cypress National Preserve (BCNP) and the Oc ala National Forest. The pink lines represent all of the LCP results for all 17 cost surfaces. Line thickness for these paths is a function of scale. The actual width of each cost path is only 1 cell width (90 ms) and the width of linkages necessary for facilitating connectivity is discussed later.

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125 (Figure 3-11). From the northeast corner of the Ocala National Forest, the route crossed through the Caravelle Ranch Wildlife Management Area, the Cross Florida Greenway, the Etoniah Creek Florida Forever Project the southern half of the Northeast Timberlands Florida Forever Project, then through the eastern and northern portions of the Camp Blanding Military Site. The most significant bottleneck occurs along US 301, where development spreading north from Starke and south from Jacksonville impinges on the landscape connections that cross this highway. The area around US 301 is also the site of active and inactive surface mines along the Trail Ridge. Currently most of these sites are open and support heavy machinery where active, and, therefore, may not be conducive to bear movement. The protection of existing habitat on each side of US 301 and restoration of mining s ites are critical issues for securing this linkage. West of US 301 the route crossed eith er through the northern New River basin and associated swamps within the norther n boundary, or just north of the Raiford Wildlife Management Area, then headed northwest through the Turkey Creek Swamp and South Prong Swamp areas to reach the southeast corner of the Osceola National Forest. Though this linkage does not techni cally have to cross Interstate 10, which crosses through the southern portion of the Os ceola National Forest, I-10 appears to be a barrier to black bear movement with little ac tivity south of the interstate (Jeremy Dixon, University of Florida, personal communicati on). Facilitation of c onnectivity between the Osceola and Ocala black bear populations may also require future retrofitting of I-10 to alleviate any barrier effects. However, in total, the landscape linkage between the Ocala National Forest and Osceola National Forest/Okefenokee National Wildlife Refuge appears to provide the best opportunity to support genetic and dem ographic links between major populations. Based on roa dkill data and recent survey information (Jeremy Dixon,

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126 University of Florida, personal communication) black bears inhabit lands from the Ocala National Forest north through at least the Camp Blanding Military Site. Though I-10 may be a barrier to bear movement, ther e are also some bears between US 301 and Interstate 10 (Jeremy Dixon, University of Florida, personal communication). Osceola National Forest to Ap alachicola National Forest This linkage is the second longest at approximately 160 km. The landscape between these national forests is largely fo rested, though a bottleneck of agricultural lands occurs along the Suwannee River. The LCPs were clumped into two major variations (Figure 3-12). West of the Osceo la National Forest some paths headed west and followed the Suwannee River very closel y, while others diverged northwest of Osceola National Forest to cross through an area of pinelands and swamps west of the Pinhook Swamp and the Suwannee River. T hough only part of this landscape was included in the Florida Ecological Network, it su pports occupied habita t that is confirmed by 9 bear roadkills (including two females) since 1994 in the area. Based on its use by bears compared to the Suwannee River opti on, it may provide a more optimal connection than a linkage limited to the Suwannee river corridor. West of the Suwannee River, all LC Ps incorporated a critical landscape connection to reach San Pedro Bay. From San Pedro Bay, two routes are followed to reach the Apalachicola National Forest. Although both options are included within the Florida Ecological Greenways Network and incorporate areas used by bears based on roadkill data, the northern rout e appears tenuous where it becomes more fragmented just south of the Tallahassee urban area. Existin g and future development may preclude the feasibility of this option.

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127 Figure 3-11. The landscape linkage betw een the Ocala National Forest and Osceola National Forest. The 17 LCPs have a very high level of congruence, which follow a continuous route of existing and proposed conservation lands from Ocala NF to Camp Blanding and then head northwest through the upper New River basin to reach the Osceola National Forest.

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128 Figure 3-12. LCP results for Osceola Nati onal Forest to Apalachicola National Forest landscape linkage. Only two major vari ations in potential linkage options among the LCP results. Just west of the Osceola National Forest, the LCPs either immediately followed the Suwannee River or headed northwest and traversed a large pi neland and swamp landscape west of Pinhook Swamp and the Suwannee River. All LCPs converged to follow the middle portion of the Suwann ee River through the Suwannee highlands and then diverged west through San Pedro Bay. At this point, most of the paths headed due west to connect to the northeast corner of the Apalachicola National Forest through a narrow bottleneck just south of Tallahassee. However, the LCPs from Cost Surfaces 10, 11, and 12 diverged south and follow the St. Marks National Wildlife Refuge to reach the southeast corner of the Apalachicola National Forest.

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129 Apalachicola National Forest to Eglin Air Force Base The landscape linkage between the Apalachicola National Forest and Eglin Air Force Base is the second shortest (approx imately 100 km) of the 4 major population connections. The LCPs for the 17 cost surfaces followed two primary routes (Figure 313). The variation may be explained by the broad coverage of forest within the region and a lack of strategically located conser vation lands (Figure 3-14). Although this landscape is currently in a rural forest ed landscape that may support black bear movement between these populati ons, development trends threaten its future. The St. Joe Company, the largest landowner in the region, currently plans massive development in the area. Projects that could significantly affect linkage options include the construction of a new airport north of Pana ma City and a new interstate highway connecting Interstate 10 to Panama City and other areas along the coast. Though not currently severe, increased development on highway US 231 betw een Interstate 10 and Panama City could also threaten this linkage. Assessment of Potential Landscape Linkages between Major Populations and Other Bear Populations or Habitat Based on analysis of the least cost path results for each cost surface between the 5 major populations, three of the seventeen cost surfaces were selected to assess linkages that might facilitate connectivity between some of the major populations and other areas that currently support smaller populations or that may be suitable candidates for recolonization (See Figure 3-6). Such destin ations were selected only if the existing major landscape linkages did not encompass them, therefore, areas such as Fisheating Creek and Tosohatchee Reserve were not includ ed as new destinations (See Figure 3-10).

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130 Figure 3-13. The LCP results for the landscape linkage between the Apalachicola National Forest and Eglin Air Force Ba se. There are two major variations for the potential landscape linkage. Most of the paths crossed the Econfina Creek Conservation Area and the Choctawhatchee River Conservation Area before reaching the northeast portion of Eglin Air Force Base. Cost Surfaces 5, 7, 9, 1215 took a more southerly route and connected to the southeastern corner of Eglin Air Force Base though they also crossed the Econfina Creek a nd Choctawhatchee River Conservation Areas.

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131 Figure 3-14. Forest cover compared to LCP results the Apalachicola National Forest and Eglin Air Force Base landscape linkage. The high degree of variation among the general pattern followed by the LCPs may be explained by the high degree of intact forest cover within the region and no major bottlenecks.

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132 The Cost Surfaces used were: Cost Surface 8, which was a simplified surface based on the bear habitat patch size, distance from in tensive development, and distance from major roads; Cost Surface 13, which was Cost Su rface 4 transformed using an exponential function with major roads and water bodies included; and Cost Surface 16, which was based on the first multiple logistic regression model. These 3 cost surfaces represented the variety of approaches taken for developing cost surfaces and delineated feasible landscape linkages for the major populations. The results of these least cost path analyses indicate that there are feasible opportunities to maintain or restore connections between the five major black bear populations and the remaining smaller populations or additi onal habitat where bears may be restored or recolonize (Figures 3-15; 3-16; 3-17; 3-18; 3-19). See Appendix E for more details on the potential importance of th ese connections and the differences between the LCPs for these landscape linkages. Statewide Black Bear Habi tat and Landscape Linkages To delineate a statewide system of black bear habitat and landscape linkages, the results for the first multiple logistic regression model and buffered landscape linkages were combined. Instead of using the results of all 17 cost surfaces, the LCPs for Cost Surfaces 8, 13, and 16 were selected to be st represent linkage opportunities between major populations, smaller popula tions, and other large blocks of potential habitat. However, 3 exceptions were made. First, the LCP for Cost Surface 1 was added to demonstrate the Suwannee River corridor op tion between Osceola National Forest and Apalachicola National Forest. This was done because the results for Cost Surfaces 8, 13, and 16, though generally feasible, did not re present the upper Suwannee River corridor, which is likely an additional feasible option for connecting the Osceola and Apalachicola

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133 Figure 3-15. LCP results for landscape li nkages between Apalachicola National Forest, Lower Suwannee National Wildlife Refu ge (LSRNWR) and Goethe State Forest (GSF). The LCPs for Cost Surfaces 8 and 13 followed more coastal routes to reach the Lower Suwannee River National Wildlife Refuge and Goethe State Forest. The paths for Cost Surface 16 diverged inland to follow the interior swamps before heading back to the coast to reach LSRNWR and GSF.

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134 Figure 3-16. The LCP results for the Oc ala National Forest to Twelve Mile Swamp landscape linkage. The LCPs for the 3 Cost Surfaces followed the two major options from Ocala National Fore st before converging in St. Johns County. The paths for Cost Surface 8 and Cost Surface 16 headed from the northeast corner of Ocala National Forest and through Dunn’s Creek State Park to reach the pinelands a nd swamps of northern Flagler and southern St. Johns County. The path for Cost Surface 13 left the Ocala National Forest south of Lake Geor ge and then crossed through Lake George State Forest and the Haw Creek Conservation Area before meeting the other paths. Within St. Johns County all of the pa ths cross several bottlenecks along road crossings to reach Twelve Mile Swamp.

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135 Figure 3-17. The LCP results between O cala National Forest and the Weekiwachee and Green Swamp conservation areas. The paths for all 3 cost surfaces followed similar routes to Lower Suwannee River National Wildlife Refuge and Goethe State Forest. The paths to Weekiwachee Conservation Area and Green Swamp Conservation Ar ea were much more variable. The two major alternatives include d both a coastal route and a route following the Cross Florida Greenway, Withlacoochee River, and adjacent conservation lands to reach Weekiw achee Conservation Area. The paths to Green Swamp Conservation Area included the Cross Florida Greenway-Withlacoochee River route and a path for Cost Surface 13 that crossed from Payne’s Prairie State Pr eserve south through rural lands in western Marion County to reach the W ithlacoochee River and then Green Swamp.

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136 Figure 3-18. The LCP results for landscape linkages between Weekiwachee Conservation Area and the Green Swamp Conservation Area, Goethe State Forest, and Lower Suwannee Na tional Wildlife Refuge. The LCPs between Weekiwachee Conservation Area and both Lower Suwannee National Wildlife Refuge and Goethe State Forest were very similar. Most of the paths followed the comple x of coastal conservation lands to both destinations. The LCPs also followed essentially the same path through the Chassahowitzka Wildlife Management Area and various tracts of the Withlacoochee State Forest to reach Green Swamp Conservation Area.

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137 Figure 3-19. The LCP results between Bi g Cypress National Preserve and the Green Swamp Conservation Area, Myakka River State Park, and Corbett Wildlife Management Area. The paths to Myakka River State Park followed the two major options acro ss the Caloosahatchee River before heading northwest through the Babcock Ranch Florida Forever Project and across the Peace River. The pa ths to the Green Swamp Conservation Area followed that major alternatives between Big Cypress-Ocala up to the Kissimmee River basin. The paths then followed various options up the Reedy Creek basin and across the Lake Wales Ridge to reach the Green Swamp. The paths to Corbett Wildlife Management Area either followed the Everglades conservation lands or crossed the Everglades Agricultural Area.

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138 National Forests. Two LCPs were not include d because they likely represent options of low suitability due to large swaths of agricultural land use or potential bottlenecks: the LCP for Cost Surface 13 between Ocala National Forest and the Green Swamp Conservation Area that traversed western Marion County was not included; and the LCP for Cost Surface 16 between Big Cypress National Preserve and Corbett Wildlife Management Area that crossed the Everglades Agricultural Area. Overall these linkages represent the major route options for a ll 17 Cost Surfaces between the 5 major populations, smaller populations, and additional habitat areas. The multiple logistic regression model and the landscape linkages were combined by including all lands with probability values of 0.5 and higher from the habitat model (Mladenoff and Sickley 1995) and all connected natural, low intensity, or agricultural land within 2500 m of each LCP. The 2500 m expansion of the LCPs resulted in a 5 km buffer for each path. This buffer does not delimit an absolute width needed to facilitate black bear movement nor is it meant to represent the actual boundaries of landscape linkages that might be designed and protect ed in the conservation planning process. However, a 5 km landscape linkage is relevant to a wide-ranging species such as black bear and is an appropriate estimate of the minimum widths that may be necessary for regional scale connectivity (Harris and Sch eck 1991; Harrison 1992; Noss 1993; Noss et al. 1996). Finally, bear habitat and the la ndscape linkages were combined so that landscape linkages only show where they do not overlap with habitat meeting the criteria of 0.5-1.0 probability (Figure 3-20). Approximately 5 million ha of potential habitat had probability values of 0.5 or higher in the first multiple logistic regr ession model. An additional 680,000 ha were within the various landscape linkage options outside of potential bear habitat (Figure 3-

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139 20). Of the 680,000 ha, approxima tely 200,000 ha (29%) were forested (including pine plantations) and 145,000 ha were in other natural communities (21%). Another 116,000 ha (17%) were in rangeland, shrubland, a nd other types of seminatural lands, and 220,000 ha (32%) were agricultural lands includi ng pasture, citrus, and croplands, with approximately 150,000 ha in unimpr oved and improved pasture. The distribution of habitat is obviously bias ed to the northern half of Florida due to the greater predominance of forest (M aehr et al. 2001a; Maehr et al. 2001b). Throughout northern Florida the identified la ndscape linkages are predominantly covered by potential habitat. Although there may be distinct populations centered in the Ocala National Forest, Osceola National Forest -Okefenokee National Wildlife Refuge, Apalachicola National Forest, and Eglin Air Fo rce Base, the wide distribution of habitat suggests that there are multiple opportunitie s for connectivity between these populations (Figure 3-21). The large area of potential habita t in north Florida also leads to questions about why some of these areas are not currentl y occupied. With the cessation of the last legal black bear hunting in north Florida in 1994 and the likelihood that harvest in the recent past may have been high, large public conservation lands may have served as relatively stable population cores that are now beginning to respond through population expansion (Cox et al. 1994). Roadkill and other reports collected by the Florida Fish and Wildlife Conservation Commission suggest that this may already be occurring north and east of the Ocala National Forest, east and west of Apalachicola National Forest, and west of Osceola National Forest (Figure 3-21). The only apparent anomaly in the multiple logistic regression model comparing known bear populations with potential habita t is the Highlands County population. Based on the multiple logistic regression model, very little potential habitat occurs in the

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140 Figure 3-20. Black bear habitat and landscape linkages statewide. Because of the extent of potential habita t in north Florida, lands cape linkages between the large populations are largely compri sed of large blocks of potential habitat.

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141 Figure 3-21. Potential black bear hab itat and landscape linkages with population cores and roadkills

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142 area although the landscape linkages between Big Cypress National Preserve and Ocala National Forest traverse the area (Figure 3-22). Based on roadk ill data, this population appears to be persisting though blocks of ha bitat along the southern end of the Lake Wales Ridge appear to be very fragmented by citrus groves, other agricultural lands, and scattered residential areas. The status of this population and how bears within it use the landscape to meet their life history needs would be a worthy research subject relevant to black bear conservation in Florida and to wi de-ranging species in general. In addition, because there have not been any studies of this population, tele metry data were not available to include in the multiple logistic regression model. Though the results of the model are in keeping with the literature on black bear and resulted in the expected importance of patch size, areas without ma jor roads, and other intuitive habitat and landscape variables, it is possible that the Highlands population might indicate differences in fragmentation thresholds, pa tch size, landscape conf iguration, matrix quality, etc. that may be instructive for future modeling and habitat conservation efforts. Habitat, Linkages, Conservation Lands and the Florida Ecological Network Though potential bear habitat and lands cape linkages comprise a significant portion of Florida’s land area (approximately 41 percent), a high percentage of these lands are also within existing and proposed conservation lands. A pproximately 53% of the potential black bear habitat and 43% of the potential landscape linkages are within existing and proposed conservation lands (Table 3-22; Figure 3-23). Approximately 88% of potential black bear habitat and 66% of the landscape linkages are within the Florida Ecological Network (Table 3-23; Figure 3-24). The largest areas of habitat that are not within the Ecological Network are south and west of the Osceola National Forest and north and west of the Apalachicola National Forest.

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143 Figure 3-22. Bear habitat and landscape linka ges in south Florida. Persistence of the Highlands black bear population west and northwest of Lake Okeechobee is not well represented as large blocks of potential habitat in the multiple logistic regression model though th e best potential landscape linkages between Big Cypress National Pres erve and Ocala National Forest traverse the area.

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144 Table 3-22. Existing and proposed conservati on land statistics for potential black bear habitat and landscape linkages Class types Land status Acres % of total area Potential habitat Existing conservation lands 5,356,102 43 Proposed conservation lands 1,270,170 10 Other private lands 5,967,562 47 Total 12,593,834 100 Potential landscape linkages Existing conservation lands 481,924 28 Proposed conservation lands 257,620 15 Other private lands 960,944 57 Total 1,700,488 100

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145 Figure 3-23. Existing and proposed cons ervation lands are shown on top of potential black bear habitat and landscape linkages. The biggest gaps in large blocks of habitat not within existing or proposed conservation lands occur along the Big Bend east of Apalachicola National Forest and between Apalachicola National Forest and Eglin Ai r Force Base in the Panhandle.

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146 Table 3-23. Comparison sta tistics between potential black bear habitat and landscape linkages and the Florida Ecological Network Class types Florida Ecological Network Acres % of Total Area Potential habitat Within Ecological Network 4,407,948 88 Potential habitat Outside Ecological Network 629,565 12 Total 5,037,513 100 Potential landscape linkages Within Ecological Network 449,062 66 Potential landscape linkages Outside Ecological Network 231,138 34 Total 680,200 100 Outside Habitat and Linkages Land in Ecological Network 2,856,845 68 Outside Habitat and Linkages Water In Ecological Network 1,332,805 32 Total 4,189,650 100

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147 Figure 3-24. Florida Ecological Network drawn on top of potential black bear habitat and landscape linkages. Areas of poten tial bear habitat s outh and west of Osceola National Forest and north and west of Apalachicola National Forest may be good candidates for add ition to the Ecological Network in future iterations. The potential la ndscape linkages are more coarsely represented, and more analysis north of Big Cypress National Preserve and southwest of Ocala National Forest is needed to determine the need for additions to the Ecological Network in these areas.

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148 These areas are logical additions to the Florid a Ecological Network when it is revised in the near future. For landscape linkages, the largest discrepancies with the Florida Ecological Network occur primarily in s outh-central and southwest Florida, and southwest of the Ocala National Forest near the Withlacoochee River basin. Though some parts of landscape linka ges that do not overlap with the Ecological Network may also be candidates for addition, the width and the multiple options used to represent the linkage opportunities may exaggera te the discrepancies. The Florida Ecological Network includes many areas that are not within potential black bear habitat or landscape linkages for bears primarily in south Florida (Figure 325). This is because of the low percentage of forest cover in much of this area and biodiversity protection goals beyond bears that were incorporated within the Florida Ecological Network. In some areas such as along the southeastern coast, formerly vast areas of pine flatwoods, scrub, and tropica l hammock have been replaced by urban development and agriculture. This is also the case along the southwest coast where urban lands, agriculture, and phosphate mines have destroyed much of the pine flatwoods and other forests that once dominated. Howeve r, the upper St. Johns River system, the Kissimmee River valley, and the Everglades were historically dominated by marshes, wet prairies, and dry prairies where hammocks and flatwoods occurred as islands within an expansive, more open matrix. These landscapes are all still very important for conservation efforts in the southern half of the Florida peninsula and were therefore included within the Florida Ecological Network. Though bears likely occurred in these areas, population densities were also likely much lower than in landscape dominated by forest and scrub.

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149 Figure 3-25. Black bear habitat and la ndscape linkages drawn on top of the Florida Ecological Network. South Florida st ands out as the primary area where the Florida Ecological is not within potential black bear habitat or modeled potential landscape linkage s. The dominance of herbaceous wetlands and uplands in the Evergl ades and Kissimmee River and St. Johns River basins, is pr edominantly responsible.

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150 Habitat Connectivity and Potential Bear Population Size To determine the extent of large blocks of available habitat, all areas meeting the 0.5 probability threshold within the first multip le logistic regressi on model results were analyzed. First, very narrow gaps (le ss than 200 m) between habitat blocks were identified using a neighborhood analysis in Ar c-Info and added to the potential habitat model. This was done to close narrow gaps a ssociated with highways that in many cases do not represent completely disc rete habitat blocks. Then a ll connected blocks of habitat that were greater than 40,000 ha were identifie d. Finally, all blocks of potential habitat between 4,000-39,999 ha that were co mpletely or partly within 60 km of the larger blocks were also identified. Sixty km was used as a threshold based on more commonly observed dispersal distances for black bear s (Cox et al. 1994; Maehr 1997a). Most potential habitat blocks (approximately 80%) meeting these criteria occur from central Florida north through the panhandle (Figure 3-26). The only exception is in southwest Florida. This analysis resulted in one ve ry large block of (habitat approximately 2.9 million ha) that met these minimal criteria for connectivity including lands from the Ocala National Forest to Eglin Air Force Ba se (Figure 3-27). The narrowest connection within this large block occurs along the upper portion of the Suwannee River. The primary blocks of pote ntial habitat (40,000 ha and larger) and the secondary blocks (between 10,000-39,999 ha) contain 3,962,282 ha and 460,160 ha respectively. Though not all of these areas are currently occupied, they could support from 2211-4422 bears using a density estimate of 0.05-0.10 bears per km2 (Cox et al. 1994). However, recent work in population cores including the Osceola National Forest-Okefenokee National Wildlife Refuge and the Ocala National Forest suggest that densities can be much higher (Thomas Eason, Florida Fish and Wildlife Conservation Commission,

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151 personal communication), thus the total numbe r of bears that could be supported in approximately 4.5 million ha might be much higher. However, a primary assumption of this population estimate is that if current bl ocks of habitat are ma intained, large areas currently without bear populations, incl uding the Big Bend coast, lands between Apalachicola National Forest and Eglin Air Fo rce Base, lands north of Eglin Air Force Base, and lands in extreme northeastern Flor ida (including Duval and Nassau County), will harbor bear populations in the futu re if population expansion continues. Potential Black Bear Habitat, Landscape Linkages, and Deve lopment Pressure The large area of potential black be ar habitat and exis ting opportunities to maintain or reestablish conn ections between populations app ear favorable for conserving a viable statewide black bear metapopulation in Florida. However, continued conversion of lands to intensive uses and urban and s uburban sprawl will resu lt in reduced habitat availability and connectivity. The location of potential future development is just as important as amount because development in key locations could easily divide large blocks of bear habitat into isolated fragments. To predict the potential impact of future development on black bear habitat and landscape linkages, future suburban and ur ban growth from a development prediction was compared to potential habitat and la ndscape linkages (Figure 3-28). The development model was based on geographic featur es that tend to attract growth (such as existing large developed areas, access to majo r roads, large water bodies, etc.), existing development trends based on De partment of Revenue tax reco rds, and projected growth in each county through 2030 (Teisinger 2002).

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152 Figure 3-26. Distribution of large black bear habitat blocks statewide

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153 Figure 3-27. Largest blocks of black bear habitat in Florida. One very large block occurs all the way from the Ocala National Forest, along the upper Suwannee River and then west to Eglin Air Force Base. The next largest block is in the Big Cypress region in southwest Florida.

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154 Figure 3-28. Impact of future developmen t on bear habitat and landscape linkages. If urban and suburban development occurs to the extent and in the spatial arrangement predicted, many of th e landscape linkages between bear populations statewide would either be completely severed or seriously threatened.

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155 Based on this comparison, the most important threat to Florida black bear habitat is fragmentation and isolation of larger ha bitat blocks and the isolation of smaller populations from larger populations (Figur e 3-28). These impacts could include: Isolation of the Big Cypress population from all populations to the north including the Highlands population by development spreadin g east from along the southwest coast, along the Lake Wales Ridge, and around Orlando Isolation of the Highlands population fro m all other populations and, therefore, potential extirpation Habitat loss and fragmentation of the St Johns population from northern Brevard County to southeastern Duval County. What is now one continuous block of habitat could be isolated into 5 smaller, isolated blocks. Reduction of the integrity of landscape linkages between the Ocala population and the St. Johns population. Though the Ocala population may have linkages to some of the habitat east of the St. Johns River, much of the habitat currently available there would be fragmented as described above. Also, development could completely sever the landscape linkage north of Lake George a nd threaten the integrity of the landscape linkage south of Lake George. The Green Swamp, which may have an important role in securing the Chassahowitzka population, w ould become isolated from all existing populations. The Chassahowitzka population would likely become permanently isolated from all other populations and the Green Swamp. Any potential for a direct connection betw een the Ocala population and the southern part of the Big Bend would probably be lost. Though it is probably the best existing connection between major populations, the Ocala and Osceola-Okefenokee populations c ould become separated by development spreading southwest from Jacksonville. The integrity of the potential landscape linkage between the Osceola-Okefenokee and Apalachicola populations could be threat ened by development along the upper Suwannee River. Development around Keaton and Dekle Be ach south of Perry could sever the existing habitat linkage along the coast betw een the northern and southern portions of the Big Bend.

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156 Development south of Tallahassee could si gnificantly reduce the integrity of the landscape linkage through the St. Marks National Wildlife Refuge that currently connects the Apalachicola National Forest to additional occupied habitat in the Aucilla River basin. The development would also sever any potential linkages between the northeastern portion of the Apalachicola National Forest and the Aucilla River basin. Development spreading north from Panama City could threaten the landscape linkage between the Apalachicola and Eglin bear populations. Development southeast of Eglin Air Force Ba se in the Freeport area could destroy the southern option of the connection betwee n the Apalachicola and Eglin populations. Development spreading east from Pensacola along Interstate 10 could threaten the connection between Eglin Air Force Base and the Blackwater River State Forest. This comparison between bear habitat a nd landscape linkages and predicted future development serves as a warning about potentia l impacts to bear habitat that could have an irreversible effect on the amount of available habitat, connectivity between populations, and the viability of bear populati ons across the state during the next 3 decades. However, this analysis must also be considered preliminary because the development prediction model is considered to be a prototype that will be refined in the future based on the availability of funding (Teisinger 2002). Potential development in some areas may be overstated whereas as ot her areas may be in more danger than depicted. A good example of the latter occu rs in the Florida panhandle. The St. Joe Company owns almost all of the private land along the coast between Apalachicola National Forest and Eglin Air Force Base. This company has plans to bring massive development to the region and is already building new subdivisions in the area. The company plans the construction of a ne w airport and adjacent development on approximately 30,000 ha north of Panama City, the construc tion of a new interstate highway from southern Alabama to Panama City, and several highway bypasses around

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157 coastal development. New hubs of growth and new transportation facilities can greatly affect the results of growth prediction models, and development impacts may be much more significant in the panhandle than currentl y depicted. Nevertheless, such models are useful tools in reserve design and habitat c onservation planning and efforts to predict and monitor development activities that threaten to destroy and fragment black bear habitat in critical areas should be strengthened. Conclusions Recommendations for Conducting LCP Analyses to Identify Potential Landscape Linkages LCP analysis using ESRI’s Arc-Info GR ID or ArcView is a useful tool for analyzing opportunities to protect or restore connectivity between wildlife populations. It is feasible to use landcover data, known migration routes, ro adkill information, and other data to assess potential landscape linkages. However, LCP analysis allows the testing of simple sets of geographic criteria that may be relevant for facilitating connectivity or more complicated models assessing habita t quality and connectivity potential. LCP models may also result in chosen routes that may not be intuitively obvious but may become preferred alternatives upon further examination in comparison with landscape linkages selected using other methods. Disadvantages of LCP analysis include the limitations presented by the use of one cell wide paths. An algorithm that provi ded the opportunity to explore a variety of minimum widths for corridors and landscape li nkages would be more powerful and more relevant identifying functional landscape linkage s. In addition, methods for creating cost surface values needed to run the LCP algorithm are not well established. More

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158 information is needed to develop ranking me thods that are statisti cally acceptable and represent the relative suitability of areas for facilitating animal movement. The following recommendations are provi ded to guide the application of LCP analysis for identifying landscape linkages: Though there was good correspondence among the results for many of the LCP alternatives in this analysis, variations in cost surface and landscape structure resulted in some differences in path results. Theref ore, several cost surfaces should be used when assessing landscape linkages. Using only one cost surface may result in missing linkage opportunities that may be pref erred alternatives or that may be more biologically feasible than an intuitively obvi ous alternative. The differences between including and not including major roads or other potentially important landscape features should be investigated in cost surface alternatives. LCP results should always be treated as working hypotheses to be confirmed through expert examination. Such examination may result in the selec tion of other linkage options entirely or modifications of routes selected by LCP analysis. Species movement capabilities and landscape st ructure should be considered carefully when constructing input cost surfaces. Un less landscape structure suggests otherwise (such as in highly fragmented landscapes ), a conservative approach to making decisions about what should be included as traversable should be adopted. Land uses or land cover types that are unlikely to a llow movement should typically be converted to no data in cost surfaces so that LCPs avoid them. A method for overcoming the limitation of one cell wide LCPs involves the use of neighborhood analyses that can help identify areas not meeting standards for minimum connectedness. In ESRI grid analysis, focal sum functions can be used to assess connectedness and bottlenecks at local and landscape scales. In this analysis all final cost surfaces were all modified to delete areas that had less than 23 cells or potentially suitable land uses or cover types in a 25 cell neighborhood using 90 m cells. In some cases a more conservative threshold or larger neighborhood size would have resulted in different results for severa l LCPs. Ideally, such analyses should be conducted at a local scale (such as usin g a 9 to 25 cell neighborhoods) to delete bottlenecks not meeting minimum width require ments. Broad connected areas with good habitat quality can also be identifie d at the landscape scale and given high suitabilities in cost surfaces (Hoctor et al. 2002). When roads are included within cost surfaces, the identification of areas most likely to provide suitable crossing points such as bridges crossings major rivers or other existing structures that may facilitate move ment should be considered for inclusion.

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159 When more complicated models assessing habitat quality and suitability for movement are not feasible, simple models using only a few geographic variables most relevant to identifying landscape li nkages can be used to provide potentially useful assessments. Because distance is an important part of the LCP algorithm, increasing the differentiation between high and low suitab ility areas should be investigated. Based on the results of this analysis, a range of at least 4 orders of magnitude (1-1000) should be considered. However, more res earch on suitable value ranges in cost surfaces and the best methods for expanding or stretching value ranges is needed. The applicability of quantitative habitat su itability models should not be overlooked. Multiple logistic regression and other me thods to develop ha bitat models with statistically valid suitability values may overcome the problem of developing and justifying values used in cost surfaces. However, the assumption that habitat suitability and suitability fo r facilitating movement, though intuitively appealing, needs more consideration. Further, met hods for expanding probability values ranging from 1-100 into cost surfaces with a more us eful range of values as suggested above needs more investigation. Finally, neutral landscape models (With 1997) may be a useful method for further investigation of the interaction between cost surface and landscape structure. In this analysis, representations of real landscapes were used to test the interaction between different cost surfaces and lands cape structure. Neutral mode ls would involve the use of randomly or systematically generated landscape st ructures to test how variations in cost surface structure affect LCP results. Such m odels may provide a more systematic way to develop criteria to guide the creation of op timal cost surfaces for identifying landscape linkage opportunities. Landscape Ecology and a Florid a Black Bear Metapopulation A regional landscape approach to conser vation is based on the thesis that an integrated system of reserves would have significantly enhanced function compared to current protected areas: Connectivity is in many respects the opposite of fragmentation. A reserve system with high connectivity is one where i ndividual reserves are functionally united into a whole that is greater than the sum of its parts (Noss 1992, p. 17).

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160 A landscape-based approach is essential for effective conservation and management of the Florida black bear, because they have large home ranges and need diverse plant communities in relatively close proximity to m eet seasonal food and cover requirements. Black bears also have low reproductive pot ential, are sensitive to hunting and poaching pressure, and come into c onflict with humans due to ap iary depredations, garbage raiding, occasional livestock depredations, et c. Black bear populations are impacted by major roads and high road densities which can cause roadkills, fragment bear habitat, and allow access to hunters and poachers. The Flor ida black bear is also affected by fire regimes in flatwoods and other fire-adapted habitat types, and natural fire regimes are best generated in large, intact landscapes a nd over long temporal s cales (Harris et al. 1996a; Gordon et al. 1997). Large, connected, an d well-buffered reserves are easier to manage with prescribed fire than small reserves surrounded by urban land. Bears are capable of using managed landscapes such as pine plantations, and effective integration of core areas and buffer zones is a useful c onservation strategy for bears and other wideranging species (Harris 1984; Noss et al. 1996). Before the advent of cities, roads, hous ing developments, and large agricultural areas that characterize human-dominated la ndscapes, bears roamed freely across a landscape that included vast forests and suboptimal habitats such as extensive marshes and prairies in south Florida. Even in su ch marginal habitats, stepping stones and corridors of suitable habitat occurred. Within sandhills, scrub occurred in patches and linear strands. In and of themselves, these patches were probably insufficient to support viable populations, but they likely experien ced repeated colonization or provided seasonal habitats within a larger, interc onnected landscape. River systems provide

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161 another example of landscape connectivity (Harris 1984; Harris et al. 1996b). The Withlacoochee River begins in the Green Swamp and runs between two ridge systems that once supported vast sandhills. The river incorporates several large expanses of swamp before emptying into the Gulf of Me xico and connecting with a vast forest of flatwoods, swamp, and hammock along the coast. Though bears likely crossed sandhills, rivers constituted natural dispersal corridors through the landscapes of north-central Florida. Such river systems in Florida probably served to promote access to seasonal food supplies and genetic interchange throughout much of the state. The Florida black bear used to be found in one large, interacting population, but is now relegated to 5 larger and several smaller populations that, at best, may interact as a metapopulation (Levins 1970; Maehr et al. 2001a) Some populations may be completely isolated (such as the Big Cypress and po ssibly the Chassahowitzka populations), but several populations are likely linked through at least some dispersal. The Ocala and Okefenokee/Osceola populations may have e nough interaction to be considered one population (Wooding et al. 1994; Jeremy Di xon, University of Florida, personal communication). However, recent conserva tion recommendations for the Florida black bear focused on protecting habitat only around the five largest populations to provide additional security (Cox et al. 1994). In several cases, the recommended Strate gic Habitat Conservation Areas for the Florida black bear include landscape linkage s (Cox et al. 1994). The recommendation for the Okefenokee/Osceola population incl udes Pinhook Swamp, which ensures the protection of a landscape linkage betwee n the Osceola National Forest and the Okefenokee National Wildlife Refuge. Th e recommendation for the Eglin population

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162 includes protecting habitat li nkages between Air Force property, the Blackwater River State Forest, and Northwest Water Management District lands along the Choctawhatchee River. The Ocala recommendation include s habitat linkages from the Ocala National Forest to the Wekiva River conservation lands complex, wh ich contains a high density bear population (Roof and Wooding 1996), and acr oss the St. Johns River to bear habitat on private timberlands and the Tiger Bay cons ervation lands complex found in Flagler and Volusia counties. The recommended Strategic Habitat Conservation Areas are essential to effectively conserve the Florida black bear. However, there are other opportunities that would enhance these conservation recommenda tions. Cox et al. (1994, p. 60) suggested that the smaller populations such as Chassa howitzka and Highlands County are too small, potentially too isolated, and too threatened by encroaching development to warrant conservation attention: The chances of an area supporting a stable population without recurring immigration is another criterion that should be used to evaluate minimum habitat conservation priorities. The level of immigration required to sustain some of the smaller populations describe d may be achieved through the establishment of habitat corridors, but required immigration rates may also be higher than habitat corridors alone can provide. The small popul ations described fo r Chassahowitzka National Wildlife Refuge, Durbin and Tw elve Mile swamps, Green Swamp, and other areas would also require major ne w land conservation efforts in order to provide a sufficient habitat base to su stain these populati ons for acceptable lengths of time. This strategy will most likely ensure th e loss of the smaller populations/subpopulations, unless land-saving actions are taken quickly to protect or restore components of the Florida black bear metapopulation. Howe ver, there are not unlimited funds, time, nor political will to protect everything (Simberlo ff et al. 1992; Cox et al. 1994), and options must be weighed carefully including detailed assessments of opportunities for

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163 connectivity and for conserving biological diversity (Noss et al. 1996; Beier and Noss 1998; Dobson et al. 1999). Recent trends in land conservation in Florida black bear habitat suggest that efforts to conserve the smalle r populations may be feasible. The state recently closed on a 24,000 ha acquisition and easement project in the Fisheating Creek basin with the Lykes Brothers Corporation. An additional 32,000 ha conservation easement in the same area is planned. This project protects habita t that is essential to the Highlands bear population because it secures an important pa rt of existing habitat while protecting connectivity with the larger population sout h of the Caloosahatchee River. Through efforts of The Nature Conservancy, over 40,000 ha of land has recently been added to the Florida Forever Program between Big Cypress National Preserve and the Caloosahatachee River that is essential for the conservation of the Florida panther but will also facilitate demographic connections between the Big Cypress and Highlands populations. A conservation coalition including The Nature Conservancy is working with large landowners in southern Duval and St. Johns counties to pr otect a conservation network that may help maintain a bear population in the Durbin and Twelve Mile Swamp area despite ongoing development in the region. Th e Nature Conservancy has also established a conservation partnership with Eglin Air For ce Base, Georgia-Pacific, Blackwater River State Forest, and the Conecuh National Fore st in southern Alabama to integrate conservation and land use activities to conserve biological dive rsity in that region. These efforts include securing habitat connections such as the resuscitated Yellow River Ravines Florida Forever Project that may support the expansion of the Eglin bear

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164 population and provide connectivity to a sma ll population of Florida black bear in southern Alabama (Dusi and King 1990). Recent demographic trends provide op timism for future bear metapopulation management in Florida. Roadkill distribu tion suggests that the Apalachicola population is expanding to the east and south through coastal and riverine conservation lands and private timber lands in the Big Bend. Existin g conditions and recent experiments in the Lower Suwannee River National Wildlife Refu ge and surrounding lands indicated that the area could support a bear population (W ooding 1995, 1996). An adult male bear was recently captured on the Goethe State Forest in the southern Big Bend and exhibited a stable home range (Dave Maehr, Universi ty of Kentucky, personal communication). Wooding et al. (1992) documented the moveme nts of an adult female to Alabama, and more recently a subadult bear from th e Eglin population moved to Alabama (M. Sunquist, University of Florida, personal co mmunication), suggesting a dispersal linkage between northwestern Florida and southern Alabama. A relocated adult male bear recently traveled approximately 130 km from Putnam County to Brooksville (the Greater Chassahowitzka Ecosystem population) through a fragmented landscape (Smith 2001). Thus, the idea of a Florida black bear me tapopulation is more than an armchair hypothesis. The most common argument by thos e unconvinced of the importance of landscape connectivity is that there is little evidence that corridors work (Simberloff et al. 1992). Corridor and connectivity experiments ar e especially difficult to conduct at scales relevant to wide-ranging species. Though evidence is accumulating, there is still a dearth of information on corridor function (Beier and Noss 1998). However, observations of

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165 large carnivore movement across naturally and culturally fragmented landscapes, provide ample evidence of corridor use (Maehr 1990, Harris and Sheck 1991; Beier 1995; Beier 1996; Noss et al. 1996; Duke et al. 2001). Ke llyhouse (1977) and Weaver et al. (1990) found that black bears used riparian strips to move within fragmented landscapes. In agricultural landscapes, bears often restricted movements to linear wooded areas such as ravines, shelterbelts, and ri parian zones (Klenner 1974; Weaver et al. 1990). Where suitable cover was limited in a naturally fragmented landscape, bears used vegetated canyon corridors to make seasonal forays (Mollohan and Lecount 1989; Onorato and Hellgren 2001). Beecham ( 1983, p. 411) concluded that: migration corridors [are] . critical in maintaining black bear numbers. These corridors tend to funnel dispersing subadult bears through the area, masking the influence of hunting on population size. If the migration corridors are not maintained, a significan t decline in bear numbers can be expected unless hunting pressure is reduced. A strategy that emphasizes broad landscap e linkages and maintaining landscapes with low-intensity land uses will generally be more successful in providing connectivity between bear populations than a system of na rrow corridors. This view is supported by Noss et al. (1996, p. 958-959), who reviewed a nd discussed the application of landscape conservation techniques for large carnivores: Collectively these data suggest that in most cases connectivity will be best provided by broad, heterogeneous linkages, not narrow, strictly defined corridors. . With these in mind, biologists have recommend ed the retention or restoration of wide habitat linkages betwee n population centers for large carnivores. . reserves play vital roles in these networks, but so does the su rrounding semi-natural ma trix. The regional landscape must be considered and managed as a whole.

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166 Connectivity beyond Bears Some suggest that instead of protec ting linkages and pursuing a connectivity approach, intensive management such as transl ocation should be used to simulate natural gene flow (Simberloff et al. 1992). Howe ver, this view misses the point that conservation of biological diversity transce nds individual species, as suggested by Soul and Terborgh (1999, p. 200): Humans and nature can coexist, but peaceful coexistence cannot come about under present conditions. The revi val and survival of nature across North America will require the establishment of a network of large nature reserves. Large areas managed for biodi versity are needed to ward off a host of ecological pathologies. Through conservation-oriented management of extensive core and multiple-use areas, the vital abiotic and biotic processes that sustain bi odiversity can be perpetuated. The protection of ecological and evoluti onary processes such as herbivory, migration, dispersal, gene flow, and predation are also important components of effective biodiversity conservation. A landscape approach is an essential part of meeting these conservation objectives. It should be the goal of wildlife managers to conserve systems that sustain natural processes including evolu tion, a notion that is at least as old as The Wildlife Society (Bennitt et al. 1937, Maehr 2001). Corridors and landscape linkages serve many other functions beyond providing a functional metapopulation for the Florida black bear. Bear movement is only a part of a landscape-based approach to conserve biodiversity through the maintenance or rest oration of natural la ndscape patterns and processes. The black bear plays a role in ecosystem dynamics. Black bears may improve the germination of seeds that pass through their digestive tracts (Rog ers and Applegate 1983; Maehr 1984a). Bears may also be particularly important seed dispersers of heavier fruits

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167 that cannot be carried by birds (Rogers a nd Applegate 1983). Therefore, though it is extremely important to design a conservation strategy for the black bear that will protect viable populations, it may also be advisable to maintain sm aller populations and facilitate movement into smaller habitat patches where their ecological services can be provided. Reserves that do not have bears are mi ssing an important ecological component. Riparian corridors could be an important part of a linkage system that targets bears. They tend to have diverse flora and fauna, are highly productive, and can serve as important buffer zones to protect hydrological processes and water quality (Schaefer and Brown 1992). If wide enough, these areas can also serve as important habitat for forest interior bird species and cavity nesters (Har ris 1988). Riparian st rips also serve as important habitat and as corridors for other wi de-ranging species including otters (Harris 1988). The protection or restoration of landscape connectivity for Florida black bear will also have important benefits for the Florida pa nther. Panthers have even larger habitat requirements than do bears, and it is extremely unlikely that any one core in Florida will be capable of supporting a viable populati on (Cox et al. 1994; Maehr et al. 2001b). However, a strategically connected reserve system might facilitate population expansion critical for increasing viability (Harris and Gallagher 1989, Harris et al. 1996b; Maehr et al. 2001b; Maehr et al. 2002a; Maehr et al. 2002b). As a flagship and umbrella species the bl ack bear can be an important catalyst for protecting a statewide, integrated system of reserves that will benefit many native species that are sensitive to habitat fragmentation (C ox et al. 1994). Though managers must realize that umbrella species will never cover the habitat needs for all species (Caro and

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168 O'Doherty 1999), "It is highly probable that if we can maintain a region's capability for supporting bears, we will also have achieved the greater goal of maintaining the earth's biodiversity (Schoen 1990, p.152)." Landscape Conservation Opportunities The potential for creating an interconnected system of reserves for black bear conservation is very good. Ha bitat availability in the north ern half of Florida suggests that there are still ample opportunities to prot ect and restore connectivity between major populations, smaller populations and areas where populations could recolonize. In addition, there are a number of active Flor ida Forever and other land conservation projects that can enhance connectivity of Fl orida black bear populations. Probably the most significant for maintaining existing c onnectivity between large populations is the landscape linkage between the Osceola-Okefe nokee conservation complex and the Ocala National Forest. The Etoniah Creek Florida Forever Project and the southern portion of the Northeast Florida Timberlands Florida Fo rever Project are essential pieces of this linkage. To complete the linkage to the Osceola National Forest, a span of 10 km between Camp Blanding and the Raiford Wildlife Management Area (WMA) to the west would need protection. Finally, the Raifor d WMA is connected to the Osceola National Forest by a private WMA (Lake Butler). To ensure protection of this area, a stronger form of protection such as an easement or ot her incentive needs to be considered. This proposed corridor is a large landscape linkage containing a mosaic of flatwoods, pine plantations, forested wetlands, riparian ha mmocks, scrub, and sa ndhill of over 80,000 ha that already supports a bear population thro ughout much of the area between Osceola-Okefenokee and Ocala National Forest.

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169 There is also an opportunity to protect linkages from Ocala National Forest to southern Duval County and to northern Brevard County. This region represents an expanse of over 400,000 ha of occupied and potential bear habitat (Cox et al. 1994), though less than 10% of this area is in pub lic ownership. Therefore, if the linkages between the Ocala National Forest and the St Johns bear population are to be protected, the best strategy would be conservation easem ents or agreements with industrial forest companies. Such action will need to occur quickly due to development pressure from Orlando, Jacksonville, Daytona/Ormond Beach an d St. Augustine. Based on currently available habitat, it would be feasible to protect 4 larger core areas (approximately 40,000-80,000 ha each) from north to south that could be connected by corridors from 38 km in width and 8-16 km long ranging fr om southeastern Duval County to northern Brevard County. Protection of this landscap e may also enhance the survival probability of a small bear population in the Tosohatch ee State Reserve in eastern Orange County (Cox et al. 1994). Connectivity between the Ocala population and the large habitat area east of the St. Johns River is dependent on th e maintenance of two linkages across the St. Johns River, which were both included in the Strategic Habitat Conservation Area recommendation for the Ocala population (Cox et al. 1994). The panhandle and the Big Bend region pr ovide opportunities to enhance the Apalachicola population with linkages to othe r populations. The Big Bend supports at least 600,000 ha of potential bear habitat based on this analys is and the estimates of Cox et al. (1994). It also contai ns a number of coastal state a nd federal conservation lands. Inland of these conservation projects is a vast landscape of pine plantations, forested wetlands, and shrub swamps associated with the headwaters of the Aucilla River, San

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170 Pedro Bay, Mallory Swamp, the Suwannee Rive r, and Goethe State Forest. Although much of the area is intensively managed, it has very few paved roads and very low human population densities. As is suggested by the apparent growth of the Apalachicola bear population, this entire region could suppor t a large bear population distributed from the Apalachicola National Forest to Goethe State Forest. Though it is likely that females will slowly colonize to the south, the Florida Fish and Wildlife Conservation Commission should consider more reintroducti ons of females as was done in the Lower Suwannee National Wildlife Refuge (Wooding 1996). The Goethe State Forest may be the strategic link for restoring connectivity to the small Chassahowitzka population (Maehr et al 1999). The long-term viability of the Chassahowitzka population may depend on such connectivity to a large, stable population. Though much of the land betw een occupied range in the Greater Chassahowitzka Ecosystem and Goethe State Forest is protected, there are gaps and bottlenecks that need protection (i.e., near Homosassa and Crystal Rivers, the Crystal River power plant, the mouth of the CrossFlorida Barge Canal, and the Withlacoochee River). However, development in this region is rapid and habitat a nd corridor protection efforts will have to happen in the near future. The Florida Fish and Wildlife Conservation Commission should also consider restoring a bear population in the Green Swamp. My analysis suggests that there are over 60,000 ha of high quality bear habitat within the Green Swamp Conservation Area. Re-establishment of a population in the Green Swamp, coupled with the protection of key corridors, could create a functional metapopulation in the Chassa howitzka region. A Green Swamp population may also

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171 serve as a key node linking the Southwest Fl orida bear population with conspecifics to the north. Protecting a landscape linkage between th e Apalachicola and Osceola National Forests is the best opportunity for connectin g bear populations in the panhandle to those in central Florida. The Osceola-Okefenok ee population and the Apalachicola populations could be connected from the Econfina Ri ver basin and San Pedro Bay to Osceola National Forest via the Suwannee River and po ssibly the matrix of mixed agricultural and forestry lands north of the Suwannee. Two broad, fairly intact landscapes c ould provide connectivity between the Apalachicola, Eglin, and sout hwest Alabama populations. The maintenance of existing private forest lands and the protection of ripari an habitat along major rivers and creeks in the region may be sufficient to facilitate these linkages. However, increased development pressure in this region through plans of the St. Joes Development Corporation may threaten the viability of these landscape connections in the near future. The most isolated core population of Fl orida black bear is found in southwest Florida, and efforts to restore connectivity w ith other bear populations may be difficult. However, the re-establishment of small b ear populations and connectivity in southcentral Florida may be feasible in concert w ith other statewide and regional conservation efforts. The highest priority for this popula tion is the protection of the landscape linkage between the Big Cypress core population and the Highlands County subpopulation. Completion of the Fisheating Creek basin conservation project and protection and restoration of habitat between Big Cypre ss National Preserve and the Caloosahatachee River are essential. Furthe r northwest, efforts to protec t lands and reforest phosphate

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172 mines in the Myakka and Peace River River ba sins could provide a dditional habitat and a linkage to the Green Swamp. To the north and northeast land acquisition in the Kissimmee and upper St. Johns River basins may provide the best opportunities for connectivity. An examination of land us e/land cover data for the region between Highlands County and Tosahatchee State Rese rve shows a mosaic of rangelands, pine flatwoods, and forested wetlands that could s upport a low density bear population or the possibility of dispersal by sub-adults. Securing the existing Florida Forever and WMD land acquisition projects such as Bombing Range Ridge, Big Bend/Holopaw, and the Econ Mosaic as well as working on additional conservation easements and agreements with large ranches could rees tablish connectivity between s outh and central Florida for both the black bear and the panther. Research and Policy Priorities for Prot ecting a Statewide Florida Black Bear Metapopulation The Florida Fish and Wildlife Conserva tion Commission and the University of Florida are currently investigating bear st atus and the genetic composition of bear populations in several key areas including eas t of the Ocala National Forest and between the Ocala and Osceola National Forest (T homas Eason, Florida Fish and Wildlife Conservation Commission, personal communicat ion; Jeremy Dixon, University of Florida, personal communication). Such resear ch should be expanded to other areas such as between Apalachicola National Forest a nd Eglin Air Force Base, west of Osceola National Forest, and between Big Cypre ss National Preserve and the Highlands population. Multiple logistic regression or other quantitative approaches for evaluating Florida black bear habitat should continue to be investigated and refined. In addition, a

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173 quantitative habitat mode l could be incorporated into a spatially explicit population viability model to assess population viabilit y and the implications of connectivity between populations (Noss et al. 2002). More information on the design criteria fo r protecting landscape linkages is also needed. Though general guidelines for li nkage widths and composition have already been discussed, the relationship between linka ge width and length, internal composition, context, etc. need to be further explored to the degree that opportunities and limitations presented by landscape level experimentation allow (Beier and Noss 1998). One option that should be considered is to target suba dult bears and possibly relocated bears for radio and satellite telemetry research. Such animals are most likely to disperse long distances and detailed information of movement across landscapes would be helpful for strengthening criteria for protecting landscape linkages between populations. Highways are critical challenges for protecting a statewide black bear metapopulation. Major highways cross most of the landscape linkages between populations as well as most of the conserva tion areas that currently support bears. Retrofitting existing highways that cross bear habitat and landscape linkages to facilitate bear movement is essential. Plans to wide n many of the east-west state roads across the Florida peninsula and proposed highways need increased scrutiny regarding their potential impact on the Florida black bear. Plan s should be altered to avoid impacts first, and elevated bridge spans and other structures should be built to facilitate movement on road projects where impacts cannot be avoided. Research to determine how bears interact with various highway types and traffic levels and on designs and placement of crossing structures that w ill facilitate movement

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174 under or over highways needs to be conti nued and expanded. The Florida Fish and Wildlife Conservation Commission is current ly conducting a study within the Ocala National Forest to document black bear move ments in relation to State Road 40 that bisects the national forest. The University of Florida has already identified priority locations for retrofitting existing roads statewide to mitigate wildlife impacts and is investigating the use of existing structures such as culverts by wildlife including bears (Smith 1999; Dan Smith, University of Florida, personal communication). This research should be compared to the results of the LCP results to deter mine whether additional priority areas for crossing structures should be established and whether bears are already using existing structures within potential landscape linkages. Though more research would be useful, this research indicates that there are still ample opportunities to restore and protect a nd statewide population of the Florida black bear. This would appear remarkable for a state with such a large and growing human population, but Florida’s large conservation areas and existing pattern of land use can still support a statewide metapopulation. The hab itat and landscape linkage analyses also confirm that the Florida Ecological Network represents black bear conservation priorities well. Efforts to protect critical landscap e linkages within the Ecological Network (Hoctor et al. 2002) will also secure th e most important linkages between bear populations. Effective conservation of the Fl orida black bear will require protection and management at the landscape scale. Florid a has a strong foundation for ensuring the protection of a viable black bear metapopula tion, and conservation efforts for bears may serve as an important flagship for protec ting and restoring functional landscapes across the state.

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CHAPTER 4 ECOREGIONAL PLANNING FOR BIODIVERSITY CONSERVATION IN THE FLORIDA PENINSULA Introduction The Nature Conservancys mission is the conservation of biological diversity worldwide. Since 1951, The Nature Conservancy has primarily worked to accomplish this mission by identifying areas with rare plant and animal species and conserving them by working with private landowners and using management agreements, conservation easements, and fee simple acquisitions. As the science of biodiversity conservation has evolved, The Nature Conservancy has modified and expanded its strategies and methods. The increasing importance of systematic reserve design and landscape ecology has strongly influenced conservation biology over the last three decades (Sullivan and Shaffer 1975; Harris 1984; Noss and Harris 1986; Forman 1995; Harris et al. 1996b; Noss 1996; Meffe and Carroll 1997; Margules and Pressey 2000; Poiani et al. 2000). In response, The Nature Conservancy has developed a planning methodology called ecoregional planning in an attempt to systematically identify all of the areas needed to effectively conserve biodiversity throughout the United States and other selected locations across the globe (Groves et al. 2002; Groves et al. 2002). Ecoregions are intended to be large geographical areas with common ecological characteristics including geology, climate, and biota, and are logical units of analysis for identifying the areas needed to conserve biodiversity (Omernik 1995; Bailey 1996). Over the last 5 years, The Nature Conservancy has been in the process of developing 175

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176 ecoregional plans for every ecoregion within the United States based on a slightly modified version of Baileys (1996) ecoregi onal classification system for the United States. Although the methodology has varied across ecoregions based on available data, analytical capabilities, and evolving guidelines, ecoregional planning includes the identification of all areas needed to conserve viable populations of all species on conservation interest, all natural communities, and functional or restorable landscapes in each ecoregion. Florida is split among 4 different terrestrial ecoregions (Figure 4-1). Two of these ecroregions, the East Gulf Coastal Plain a nd the South Atlantic Coastal Plain, contain multiple states. Their plans were conducted in team efforts involving multiple state offices and regional staff of The Nature Conservancy. The Peninsular Florida and Tropical Florida ecoregions are both completely within Florida, and the Florida Chapter of The Nature Conservancy was in charge of conducting and completing the ecoregional plans. The Peninsular and Tropical Florida eco regions provide a great opportunity to take advantage of detailed bi odiversity and ecological asse ssments in a state known for its conservation efforts. Florida has a very ri ch natural heritage that is threatened by continued habitat loss and fragmentation from residential, commercial, industrial, and agricultural development. Florida is fourth highest in native species among all states in the United States and ranks third in the num ber of species listed as threatened or endangered by the U.S. Fish and Wildlife Service. Florida supports at least 3,500 native plant species (235 of which are endemic), 126 fish species (7 endemic), 57 species of amphibians (6 species/subspecies endemic), 127 reptiles (37 species/subspecies

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177 Figure 4-1. Boundaries of the four ecoregions in Florida

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178 endemic), 283 bird species (7 endemic subspecies), 75 mammal species (58 species/subspecies endemic) and countless invertebrates (with at least 410 known to be endemic). At least 117 species or subspeci es nearly 17% of all native fauna are thought to be in danger of extinction (F lorida Biodiversity Task Force 1993). In response, Florida has developed a trad ition of land protection that has included various efforts to strengthen the knowledge base used to deter mine land conservation priorities. Larry Harris and Reed Noss identified reserve design conservation strategies and priority areas in a series of papers in the 1980s (Harris 1985; Noss and Harris 1986; Noss 1987b; Harris and Gallagher 1989; Harri s and Scheck 1991; Harris and Atkins 1991). In 1990, The Nature Conservancy organi zed a mapping charrette of experts to identify the highest priority areas for conservation to guide the Florida Preservation 2000 land acquisition program. Since then several da ta collecting efforts and spatial analyses have significantly enhanced conservation planning efforts. Florida Natural Areas Inventory (FNAI) has collected and maintained a large element occurrence database of species and natural communities that is critical to state and ecoregional planning. In the early 1990s FNAI also used high-resolution aerial photographs to identify potentially significant natural areas statewide. The Florida Fish and Wildlife Conservation Commission has compiled more than a decade of strategic work to identify priority habitats for protecting viable populations of species and important natural communities (Cox et al. 1994; Cox and Kautz 2000; Kautz and Cox 2001). Their combination of habitat models with analysis of population viability to identif y additional lands that need protection created a sound foundation for conser vation efforts in Florida and also served

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179 as one of the primary inspirations for th e development of The Nature Conservancys ecoregional planning initiative (Groves et al. 2000). The state of Florida created a greenways program to develop a recreational trails network but also to identify and protect an ecological network that would functionally connect the major existing conservation lands and other areas of ecological significance across the state. The University of Florida has been working with the Florida Department of Environmental Protection since 1995 to identify and protect the network now termed the Florida Ecological Network. The Florida Ecological Network identifies critical areas needed to protect landscape connectivity for wide-ranging species such as the Florida panther ( Puma concolor coryi ) and black bear ( Ursus americanus floridanus ) and the long-term viability of biodiversity, which is another critical contribution to ecoregional planning. Finally, as part of Floridas new land acquisition program, Florida Forever, the Florida Natural Areas Inventory is responsib le for assessing the importance of existing and proposed land acquisition projects for mee ting the programs biodiversity and other conservation goals. Additional and updated species data layers have been created as part of their Florida Forever Needs Assessment (Florida Natural Areas Inventory 2000). The conservation planning process for the Peninsular and Tropical Florida ecoregions takes advantage of this wealth of available biodiversity information with the goal of effective biodiversity conservati on despite ongoing development and habitat fragmentation. The process incorporates analysis at multiple spatial s cales and levels of biological organization while emphasizing pl anning and implementation at the regional

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180 and landscape scale to identify and protect the por tfolio of sites necessa ry to conserve all components of biodiversity. Description of the Florida Peninsula Ecoregion Covering approximately 3 a nd-a-half degrees of latitude, the Florida Peninsula Ecoregion includes areas having a temperat e flora and fauna characteristic of the Carolinian Biotic Province in its northern reaches to species and communities with definite tropical affinities of the Caribbean Biotic Province at its southern limit (Myers and Ewel 1990; Figure 4-2). Encompassed by the Gulf of Mexico on its west and the Atlantic Ocean (and the Gulf Stream) on its east, the ecoregion supports hundreds of kilometers of coastline. The Florida Peninsula Ecoregion experiences very few freezes during the winter and warm temperatures in summer. The entire peninsula is characterized by relatively high rainfall averaging 165.1 cm per year. The natural communities and species are shaped by seve ral dominant forces: pronounced wet and dry seasons, once frequent fires that swept unimpeded for kilometers across the landscape (and other large-scale disturbance factors such as hurricanes), a high water table, mucky or peaty soils that have developed in numerous depressional features in a karst, limestone-based substrate, a relatively flat terrain where even slight changes in topography can dramatically influence th e kind of community that develops and generally infertile, moderately to excessively well-drained sandy soils on several prominent ridge systems that run parallel to the coastlines (Myers and Ewel 1990). Major river systems include the St. Johns River, Kissimmee Ri ver, Peace River, Withlacoochee River, and Ocklawaha River. The Green Swamp, an extremely large wetland basin west of Orlando, is the s ource of the Peace, Ocklawaha, and

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181 Figure 4-2. Boundaries of the Florida Peninsula and Tropical Florida Ecoregions

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182 Withlacoochee Rivers. The Peninsula Florida Ecoregion is also the heart of Floridas lake region, with approximately two-thirds of Floridas lakes occurring within the ecoregions boundaries. Upland areas in the northern portion of the ecoregion support a large, although now fragmented, area of upland hardwood forest that extends southward to just north of the Tampa Bay area on the central Gulf Coast. Several high ridges comprised of deep, Pleistocene-deposited sands parallel the coasts: the Brooksville Ridge on the upper west coast and the Trail Ridge and Crescent City ridges on the east coast. All of these sandy ridge systems support the remnants of the longleaf pine ( Pinus palustris)-dominated sandhill communities and landscapes. These ridges are vitally important to the recharge of the Floridan Aquifer, a massive subterranean system of porous limestone from which the majority of Floridians derive their drinking water. Abrupt discharges from the Floridan Aquifer are also responsible for th e 12 first magnitude springs (springs with a flow > 66 million gallons per day) that occur within the ecoregion and house numerous endemic invertebrates. One of the most distinctive topographic a nd physiographic features of the entire ecoregion is the Lake Wales Ridge, a high ri dge system that runs through the central portion of the ecoregion. Encompassing the high est point in the ecoregion at an elevation of 73.2 m, the Lake Wales Ridge represents some of the most ancient land in the Florida peninsula that was derived from the forces of marine wind and wave action as ancient beach dunes and marine terraces during extremely high sea levels. Portions of the ridge are thought to have remained continuously above sea level during the cyclic rise of marine waters during if not substantially longer than the interglacial periods of the

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183 Pleistocene (Myers and Ewel 1990). The isol ation of the ridge tops has led to the evolution of an endemic plant and animal biota that is also supported by a unique community the Florida scrub. It is estimate d that 85% of the Lake Wales Ridge scrubs have been destroyed. Coastal ridges also supported scrub communities containing rare species (though less endemics than the Lake Wales Ridge) but have experienced habitat loss over 90%. The Ocala Big Scrub north of the Lake Wales Ridge is largely conserved, though intensively managed, with in the Ocala National Forest (Myers and Ewel 1990). Uplands in areas of lower topography than the Pleistocene-deposited ridge systems largely support pine flatwood domin ated landscapes characterized by a pine canopy (either longleaf pine or slash pine depending upon the soils and hydrology), a thick, low shrub stratum and a highly dive rse ground cover vegetation. It has been estimated (Davis 1967) that flatwoods once covered 50% of the upland Florida peninsular landscape. Dry prairie communities dominated areas north and west of Lake Okeechobee within the Kissimmee River Valley and served as the primary habitat for several endemic avifauna, although much of it has been converted to improve d pasture and citrus groves. Description of the Tropic al Florida Ecoregion Tropical Florida is a landscape under siege. It is also a landscape of great contrasts between highly fragmented upland te rrestrial ecosystems and vast expanses of herbaceous wetlands. The Tropical Florida Ecoregion is surrounded by the Gulf of Mexico to its west, the Atlantic Ocean (and Gulf Stream) to its east and the Florida Straits that divide Florida from the Bahamas and the Caribbean island of Cuba to its south (Figure 4-2). The Florida Keys, an archipelago of limestone islands clothed in lush

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184 vegetation heavily influenced by the adjacent tropics, arc south-southwestward from the southeastern edge of the peninsula. Florid a Bay is a vast estuarine ecosystem connecting Everglades National Park to the Florida Keys that has been heavily impacted by water mismanagement in its Evegrlades headwaters. Biscayne Bay, a once incredibly productive estuary that is now largely enveloped by the burgeoning metropolis of Miami and Miami Beach, lies along the southeastern coast of the ecoregion, while dense forests of mangroves dominate the Ten Thousands Is lands along a still nearly inaccessible portion of the southwestern coastline. The Tropical Florida Ecoregion has mild temperatures with very rare winter freezes and warm, humid summer weather. The entire ecoregion is characterized by relatively high rainfall averaging 152.4 cm per year, although it is somewhat lesser in the Florida Keys. The species and communities are shaped by several dominant forces: pronounced wet and dry seasons; once frequent fires that swept unimpeded for kilometers across the landscape and hurricanes; a high wate r table and often deep muck soils over a limestone-based substrate; a flat terrain where even slight changes in topography can dramatically influence the kind of community that develops; the recent geology of the region; and the proximity to the tropics a nd Gulf Stream (Myers and Ewel 1990). Lake Okeechobee forms the northernmost boundary of the ecoregion and is by far the largest freshwater lake in Florida. Receiving substantial inflows from the Kissimmee River in the south-central reaches of the Florida Peninsula Ecoregion directly to its north, Lake Okeechobee is where the Greater Everglades Ecosystem begins in earnest. Prior to settlement, when waters within Lake Okee chobee reached flood stage they would spill over the southern rim of the lake and flow southward helping to form the great River of

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185 Grass that is the Everglades. Elevati ons at the southern rim of the lake are approximately 6.1 m above sea level, while eleva tions at the southern end of what is now Everglades National Park, where the fresh waters of the Everglades flow into Florida Bay, are at zero feet above sea level. Duri ng the flow from the lake to Florida Bay a distance of more than 160 km the land drops just over 5 cm for every 1.6 km allowing for the development of a slow-moving, shallow, yet broad, river that is the Everglades (Davis and Ogden 1994). The dominant ecological community of the Everglades is essentially a floodplain marsh, or more prope rly a tropical swale, whose predominant emergent vegetation is sawgrass (actually a sedge Cladium jamaicense ). Unfortunately much of the Everglades system has been ditched, diked and drained. Much of its waters now flow mostly through canals and its levels and flows are highly engineered by myriad control structures that artificially regulate the timing and quantity of waters reaching the southern exte nt of the Everglades including Everglades National Park and the productive estuary of Florida Bay. A 1500 km 2 area along the southern shore of Lake Okeechobee the Everglades Agricultural Area (EAA) has been completely cleared and converted to agri cultural land, particularly for sugarcane that grows well in the mucky and peaty soils that once supported the pristine Everglades. High levels of nutrients, particularly phos phorous from agriculture, have also greatly impacted the quality of the vital waters that flow southward from the EAA through the Everglades. For years the waters have also been diverted from the Everglades through the elaborate canal system and dumped into Biscayne Bay, the Atlantic Ocean and the southern extent of the Indian River Lagoon estu arine system. Federal, state, and regional government, non-governmental organizations, and private landowners are now struggling

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186 to develop and implement a multi-billion dollar effort to restore the Everglades and hopefully other facets of the south Florida landscape. The Everglades basin is partially formed by lands of slightly higher elevation along the coasts. Perhaps the most significant of these features from an ecological and conservation perspective is the Atlantic Co astal Ridge, a Pleistocene-aged geologic formation. Consisting of thin, sandy soils overlying a limestone bedrock along the northeastern coast of the ecoregion, the Atlan tic Ridge was once vegetated by the Florida Scrub ecological community/system dominated by sand pine ( Pinus clausa ) and various species of scrub oaks. Along the southeastern coast of the ecoregion, however, the sandy Scrubs and pinelands give way to the Mia mi Rock Ridge composed of a soft, mostly exposed, oolitic limestone precipitated from marine systems during Pleistocene interglacial periods when the tip of the Florida peninsula was completely, and very recently, submerged (Gleason 1974). The Miami Rock Ridge was once vegetate d by a unique and endemic ecological system, pine rockland (although similar to some communities in the Bahamas), which covered roughly 40,000 ha in the Miami area. Driven by the appetite of the American public for winter vegetables, much of this area was converted by rock-plowing to virtually hydroponic farmland in the 1950s a nd early 1960s. As Miami continued to grow southward, these agricultural areas were rapidly converted to housing and commercial developments. It is estimated that greater than 98% of the Pine Rockland community, including untold populations of its highly endemic flora, have been destroyed. Today, the pine rocklands exist as tiny fragments of 2-16 ha parcels, but still

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187 support populations of their incr edible endemic flora that may remain viable through appropriate management activ ities (Myers and Ewel 1990). Also occurring on the Miami Rock Ridge and extending throughout the Everglades and into the Florida Keys are a series of tropical hardwood-dominated forests referred to locally as hammocks. This tropical hardwood hammock natural community, supporting a mixed canopy of up to 65 Caribbean-derived hardwood tree species, once covered thousands of ha along the southeaste rn coast of the ecoregion in what is now Miami and Ft. Lauderdale. Although no precise estimates are available, it is thought that greater than 99% of this community type on the mainland has been lost. While a few, high quality fragments exist on the southeastern coast, it is Everglades National Park, the northern end of Key Largo and several othe r of the Florida Keys that still support substantial, though imperiled, tracts of th e hammock community. Additionally, the Florida Keys support several endemic verteb rates including the diminutive, federally endangered, key deer ( Odocoileus virginianus clavium ), large mangrove forests, and the only coral reef system in the continental United States (Gleason 1974; Myers and Ewel 1990). The northwestern portion of the ecoregion supports the Big Cypress swamp ecosystem, much of which is now protected as a National Preserve. Big Cypress swamp supports bald cypress ( Taxodium distichum ) dominated tropical strand swamp, scattered pine flatwoods on higher ground, and pond appl e/pop ash swamps embedded in deeper water depressions within the ba ld cypress strands. These wetter areas within the tropical strand swamp mosaic support par ticularly diverse assemblages of epiphytes, including numerous species of orchids, bromeliads a nd ferns. The Big Cypress region also

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188 supports most of the individuals in the only remaining breeding population of the Florida panther. Methods Ecoregional planning requires the selection of focal species and natural communities, setting goals to functionally conserve focal species and natural communities, and then selection of the best areas for meeting the established goals. In this study, site selection was accomplished in three steps. First, sites were selected to meet goals for all natural communities and sp ecies without enough viable occurrences to meet their goals. Then, viable occurrences for all other species were compared to the initial portfolio, and additional sites were selected where they were needed to meet goals for these species. Habitat identified as needed to meet species viability goals in other inventories and habitat analys es was also added. Finally, areas needed to provide connectivity were incorporated to create the final portfolios (Figure 4-3). These steps are detailed below. Selecting Species and Natural Communities The first step of the ecoregional planning process is the selection of focal species (frequently referred to as targets in ecore gional planning) and natural communities. During the spring and summer of 1999 technical teams representing all relevant species experts were assembled to select focal speci es in five different categories: plants, invertebrates, fish, herpetof auna, birds, and mammals for both the Florida Peninsula and Tropical Florida ecoregions. The guidelines fo r selecting species of conservation interest to serve as focal species included (using th e natural heritage rankings where G stands for global rank and T is the subspecies rank):

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189 All globally-imperiled (G1-G2/T1-T2) species or subspecies Other species and subspecies (G3-G5 or T3 -T5) that met any of following criteria: Declining significantly through all or a substantial part of their range Endemic to the ecoregion Disjunct from distant ecoregions Area sensitive (requiring landscape scale sites to be viable) and/or are of other ecological/conservation value (e.g. aggregations of special concern, keystone species) Workshop participants recommended species for inclusion in the ecoregional planning process based on these criteria. Thou gh there was an effort to make sure not to include too many species, which might overwhe lm available resources, both high species richness and the high degree of habitat loss a nd fragmentation dictated that many species met the criteria for inclusion in both ecoregi ons. In the Florida Peninsula Ecoregion, 367 species were selected including: 143 plants, 63 invertebrates, 19 fish, 27 herpetofauna, 41 birds, and 18 mammals. Three hundred and four teen (314) species were selected in the Tropical Florida Ecoregion including: 185 plants, 15 invertebrates, 6 fish, 16 herpetofauna, 35 birds, and 14 mammals (See Appendix E and Appendix F for the complete list of species included in each ecoregion). A workshop was also conducted for natural communities for both ecoregions. Unlike species, ecoregional planning requires the inclusion of all natural communities as conservation targets. The workshop was held to pick the natural community classification system to be used. This wa s necessary because various potential sources exist with different natural community or co ver type classifications including: Florida Natural Areas Inventory natural community classification; the Florida Land Use/Land Cover Classification System used by Florida s five Water Management Districts in their land use maps; the Florida Fish and W ildlife Conservation Commissions land cover classification used in their statewide land cover map; The Florida GAP Analysis Projects

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190 Figure 4-3. Process for identifying the site portfolios for the Florida Peninsula and Tropical Florida Ecoregions

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191 land cover classification for their statew ide land cover map; and the new National Vegetation Classification system (NVC) de veloped by The Nature Conservancy. Although the NVC system is the one recommend ed for use in ecoregional planning, the experts in the natural communities workshop decided that there were a number of problems using this classification system, especially at the Plant Association level. Therefore, a hybrid classification system was developed that combined the more realistic and workable classes contained within the Ecological Groups level from the NVC and the FNAI natural communities classification. Ecor egional Groups were developed as logical groupings of Plant Associations in order to facilitate the use of the NVC in ecoregional planning, but were in a draft form at the time these plans were conducted and not yet refined for complete adoption. Ecological Groups were used when feasible and then FNAI natural communities were relied on to fill gaps. In addition, several community types (such as Red Oak Woods) not within eith er classification system were included to specifically address unique community types that were legitimate conservation targets representing the full range of biodiversit y within each ecoregion. The adopted classification resulted in 56 natural communities as targets for the Florida Peninsula Ecoregion, whereas the Tropical Florida Ec oregion had 43 natural community targets (See Table 4-1 and Table 4-2 for list of natural communities for each ecoregion). Setting Conservation Goals for Species and Natural Communities The selection of goals is by far the most enigmatic step of the ecoregional planning process. Significant advances ha ve been made within conservation biology regarding population viability theory and viab ility modeling and asse ssment techniques. However, for the vast majority of species there is either too little or no information on

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192 Table 4-1. Natural community classifica tion and goals for the Florida Peninsula Ecoregion Natural community Patch type Extent Goal Subecoregion goal Algal bed small/large patch limited 10 1 per suitable subregion Aquatic cave small patch limited 13 1 per subregion Basin and depression marsh small/large patch widespread 6 At least 1 per subregion (mainly non-coastal subregions) Basin swamp small/large patch widespread 5 At least 1 per subregion Baygall small patch widespread 5 At least 1 per subregion Beach dune large patch widespread 5 At least 2 per suitable subregion Blackwater stream small/large patch widespread 5 1 per suitable subregion Bottomland forest large patch widespread 5 At least 1 per subregion Coastal grassland small patch limited 13 At least 2 per coastal subregion Coastal interdunal swale small patch limited 13 At least 2 per coastal subregion Coastal strand large patch limited 9 At least 2 per coastal subregion while capturing gradient Composite substrate small/large patch limited 10 1 per suitable subregion Consolidated substrate small/large patch limited 10 1 per suitable subregion Coral reef small/large patch restricted/ endemic 20 only in one subregion Dome swamp small/large patch limited 10 At least 1 per subregion Dry prairie matrix restricted/ endemic 10 At least 2 per suitable subregion Flatwoods/prairie lake small/large patch limited 10 1 per suitable subregion Floodplain forest and swamp large patch widespread 5 At least 1 per subregion Floodplain marsh small/large patch widespread 6 At least 1 per subregion (mainly non-coastal subregions) Florida scrub small/large patch restricted/ endemic 25 At least 3 per subregion (only 3 subregions in tropical) Freshwater tidal swamp small patch widespread 5 At least 1 per coastal ecoregion Hydric hammock large patch limited 9 At least 1 per subregion Hypersaline coastal salt flat small patch limited 13 At least 1 per subregion (coastal subregions only) Loblolly pine hammock large patch limited 9 At least 1 per suitable subregion Mangrove large patch limited 9 At least 2 per subregion (in all coastal subregions)

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193 Table 4-1. Continued Natural community Patch type Extent Goal Subecoregion goal Maritime hammock large patch limited 9 Need to include enough sites to capture climatic gradient Marsh lake small/large patch widespread 5 1 per suitable subregion Mesic flatwoods matrix limited 5 At least 2 per suitable subregion Mesic/prairie hammock small/large patch limited 10 At least 1 per suitable subregion Mollusk reef small patch limited 13 1 per suitable subregion Octocoral bed small/large patch restricted/ endemic 20 1 per suitable subregion Peninsular swale small/large patch limited 10 At least 1 per subregion Red oak woods small/large patch restricted/ endemic 18 Probably only in one subregion River floodplain lake small patch widespread 5 1 per suitable subregion Sandhill matrix limited 5 At least 2 per suitable subregion Sandhill upland lake small/large patch restricted/ endemic 20 3 per suitable subregion Scrubby flatwoods small/large patch restricted/ endemic 25 At least 2 per suitable subregion Seepage stream small patch widespread 5 1 per suitable subregion Shell mound small patch limited 13 2 per coastal subregion Sinkhole small patch limited 13 1 per suitable subregion Sinkhole lake small patch restricted/ endemic 20 3 per suitable subregion Slash pine-cutthroat seepage large patch restricted/ endemic 20 At least 2 per suitable subregion Flatwoods/ seepage slope Sponge bed small/large patch restricted/ endemic 20 1 per suitable subregion Spring-run streams small patch limited 13 1 per suitable subregion Streamhead Atlantic small patch limited 13 Only occurs in 1 or possibly White-cedar forest 2 subregions Swamp lake small/large patch widespread 5 1 per suitable subregion Temperate seagrass beds small/large patch limited 10 1 per suitable subregion Terrestrial cave small patch limited 13 1 per suitable subregion Tidal marsh large patch widespread 5 At least 1 per subregion (in potentially 3 subregions) Unconsolidated substrate small/large patch widespread 5 1 per suitable subregion Upland hardwood forest large patch widespread 5 At least 2 per suitable subregion (2 possible)

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194 Table 4-1. Continued Natural community Patch type Extent Goal Subecoregion goal Upland mixed forest large patch widespread 5 At least 1 per suitable subregion Wet flatwoods large patch limited 9 At least 1 per subregion Wet prairie small patch limited 13 At least 1 per subregion Worm reef small/large patch restricted/ endemic 20 1 per suitable subregion Xeric hammock small patch Limited 13 At least 1 per suitable subregion

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195 Table 4-2. Natural community classifica tion and goals for the Tropical Florida Ecoregion Natural community Patch type Extent Goal Subecoregional goal Algal bed small/large patch limited 10 1 per suitable subregion Aquatic cave small patch limited 13 1 per subregion Beach dune large patch widespread 5 At least 1 per suitable subregion Blackwater stream small/large patch widespread 5 1 per suitable subregion Coastal berm small patch restricted/ endemic 25 At least 10 per subregion (in 2 subregions) Coastal grassland small patch limited 13 At least 2 per coastal subregion Coastal rock barren small patch restricted/ endemic 25 Predominantly only in 1 subregion Coastal rockland lake small patch restricted/ endemic 25 Predominantly only in 1 subregion Coastal strand large patch limited 9 At least 2 per coastal subregion Composite substrate small/large patch limited 10 1 per suitable subregion Consolidated substrate small/large patch limited 10 1 per suitable subregion Coral reef small/large patch restricted/ endemic 20 only in one subregion Flatwoods/ prairie lake small/large patch limited 10 1 per suitable subregion Floodplain marsh small/large patch widespread 6 Likely only in 1 subregion Florida scrub small/large patch restricted/ endemic 25 At least 3 per subregion (only 3 subregions in tropical) Hatrack cypress small/large limited 10 At least 2 per subregion if possible (only 3 subregions likely) Hypersaline coastal small patch limited 13 At least 1 per subregion Salt flat (coastal subregions only) Mangrove large patch limited 9 At least 2 per subregion (in all coastal subregions) Marl prairie large patch restricted/ endemic 18 At least 2 per suitable subregion if possible Marsh lake small/large patch widespread 5 1 per suitable subregion Mesic flatwoods small/large patch limited 10 At least 2 per suitable subregion Mesic/prairie hammock small/large patch limited 10 At least 1 per suitable subregion (only 1 possible) Mollusk reef small patch limited 13 1 per suitable subregion Octocoral bed small/large patch restricted/ endemic 20 1 per suitable subregion Pine rockland large patch restricted/ endemic 18 At least 5 per subregion (only in 2 subregions)

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196 Table 4-2. Continued Natural community Patch type Extent Goal Subecoregional goal River floodplain lake small patch widespread 5 1 per suitable subregion Scrubby flatwoods small/large patch restricted/ endemic 25 At least 2 per suitable subregion (probably only 3 subregions) Seepage stream small patch widespread 5 1 per suitable subregion Shell mound small patch limited 13 2 per coastal subregion Sinkhole small patch limited 13 1 per subregion Sinkhole lake small patch restricted/ endemic 20 3 per suitable subregion Sponge bed small/large patch restricted/ endemic 20 1 per suitable subregion Spring-run streams small patch limited 13 1 per suitable subregion Subtropical seagrass beds small/large patch limited 10 1 per suitable subregion Swamp lake small/large patch widespread 5 1 per suitable subregion Terrestrial cave small patch limited 13 1 per suitable subregion Tidal marsh small patch widespread 6 At least 1 per subregion (in potentially 4 subregions) Tropical bayswamp small restricted/ endemic 25 At least 5 per subregion if possible (only 3 subregions likely) Tropical hardwood small/large patch restricted/ endemic 20 At least 3 per subregion Hammocks (all 5 subregions possible) Tropical hydric flatwoods large patch limited 9 Only in two subregion (at least 2 per subregion) Tropical strand swamp forest large patch restricted/ endemic 18 At 5 per suitable subregion (only 2 subregions) Tropical swale matrix restricted/ endemic 10 within subregion anthropogenic barriers Unconsolidated substrate small/large patch widespread 5 1 per suitable subregion Worm reef small/large patch restricted/ endemic 20 1 per suitable subregion

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197 population sizes, population densities, and ke y demographic parameters needed to accomplish either coarse or refined viability assessments. Setting conservation goals was discussed at each of the species workshops though little progress was made beyond the general acknowledgement that the best occu rrences/populations should be protected and that multiple populations are needed. Furthe rmore, it was also acknowledged that there may be some significant geographic variation for some species and that efforts to capture sub-ecoregional geographic variation shoul d also be considered when selecting populations to include within the portfolio of s ites. Therefore, the default goals set in the ecoregional planning guidelines to include a minimum (if available) of 10 populations for each species were used (Groves et al. 2000). This guideline was based on the standard set in the Florida Fish and Wildlife Conservation Commissions (FWC) population viability analyses and habitat analyses de scribed above. As a result of multiple population viability assessments, they recommended that ten populations of a given species need to be conserved to provide a >90% probability of persistence for 100 years (Cox et al. 1994; Groves et al. 2000). Th e FWC also concluded that a general recommendation for population size was at l east 200 individuals (Cox et al. 1994; Kautz and Cox 2001). Although goal setting for natural communitie s is potentially as problematic as for species, the ecoregional planning guidelin es provide a more detailed and logical framework for setting goals for each natural community type (Groves et al. 2000). There are 3 primary considerations used to set natural community goals: Rangewide distribution Landscape status

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198 Ecoregional distribution Rangewide distribution and landscape status ar e the two factors used to set the primary goal for each natural community. Rangew ide distribution considers both the overall extent of a natural community type as well as its status within the ecoregion versus its entire range. The categories that may potentially apply include: restricted/endemic (occurs primarily in one ecoregion) limited (occurs in the ecoregion and a few other adjacent ecoregions) widespread (widely distributed in several to many ecoregions) disjunct (occurs in ecoregion disjunct from the core of its distribution) peripheral (more commonly found in other ecoregions) Only restricted/endemic, limited, and widespread categories were used in each ecoregion. Landscape status refers to the typical exte nt of the natural community with most landscapes within the ecoregion. The matr ix and patches are two of the primary components in Forman's (1995) landscape structure classification sy stem. The landscape status category used to define goals for natural communities is based on this landscape structure classification and includes three types: matrix communities large patch small patch Matrix communities are the largest natural community types that cover large areas and typically surround other natural community types. In much of the eastern United States, deciduous hardwood forest is the matrix within which many other patchier natural communities occur. In the Peninsula Florida Ecorgeion, pine flatwoods, sandhill, and dry

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199 prairie were designated as matrix communi ties. In contrast, only tropical swale was selected as a matrix community in the Tropical Florida Ecoregion. Large patch communities may occur in a variety of sizes depending on the landscape and in some cases may actually encompass natural communities that are more frequently the matrix, such as where scrub surrounds patches of lo ngleaf pine sandhill in the Ocala National Forest. Small patch communities occur as small resource patches that require specific, small scale conditions and may occur either in numerous patche s or very rarely depending on the natural community and the landscape. Rangewide distribution and landscape stat us were combined to determine the ecoregional goal for each natural community. Based on ecoregional guidelines, less occurrences are required as a natural community is more common and the larger its typical landscape extent. Therefore widespread matrix communities require the smallest number of occurrences whereas a restrict ed/endemic, small pa tch community would require many more occurrences to meet its conservation goal. One adaptation of these guidelines to the Peninsula and Tropical Flor ida ecoregions was the designation of some natural communities as small/large patch when typical landscape status was considered to be too variable to be more specific. Accordingly, small/large patch communities were given intermediate goals. Though matrix communities re quired less occurrences than patch communities, a size threshold was also used to distinguish small remnants from larger sites where these communities may still function as a functional matrix to s upport dependent species and provide sufficient context for patch communities. The area goal for matrix communities was at least 2,000 ha. Though this goal could have been larger, habitat fragmentation has

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200 reduced once common matrix communities such as sandhill, dry prairie, and even pine flatwoods into isolated and frequently small fragments. A threshold of 2,000 ha was considered to be a reasonable compromise that would still legitimately separate smaller sites from those more likely to provide fe asible conservation oppor tunities for matrix communities and intact landscapes. The secondary goal for natural communities was a subecoregional standard for conservation success. Each ecoregion is sepa rated into additional geographic units based on further subdivision of Baileys ecoregional classification (Figure 4-4). To attempt to capture all of the potential geographic variation in each natural community, a mimimum goal of at least one viable occurrence in each ecoregion (where the community was at least known to occur) is required. Howeve r, small patch commun ities with a limited or endemic extent were required to have 3 occurrences per subecoregion and communities with intermediate status for range and landsca pe status were typically required to have two occurrences. Table 4-1 and Table 4-2 contain the range extent, landscape status, overall goal, and subregional goal for each natural community within the two ecoregions. Assessing Viability Ecoregional planning is prima rily driven by element occurrence data when it is available. Occurrence data are the locations of species of conserva tion interest collected and maintained by the natural heritage programs in each state. Florida Natural Areas Inventory (FNAI) maintains a large element occurrence database for Florida. Occurrences are either directly observed and recorded by FNAI staff or observed by other recognized professionals who submit adequa te documentation. The Florida element occurrence database is large, with over 27,000 records included, and this planning effort

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201 Figure 4-4. Subecoregions for the Florida Peninsula and Tropical Florida Ecoregions

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202 used over 11,500 total occurrences (prior to vi ability assessment) in the Peninsula Florida ecoregion and over 4,700 in the Tropical Florida ecoregion. Assessment of the viability of occurrences was a critical step in the planning process and resulted in the deletion of a number of occurrences from consideration. The age or date of the observation was the first criterion used in the viability assessment. No element occurrences collected prior to 1980 were considered to be viable since the status of such occurrences could not be relied upon as accurate descriptions of current conditions. Pre-1980 element occurrences included 21% of all species and 15% of all natural communities/systems within the two ecoregions. Beyond age, the first of two methods used to further assess the viability of element occurrences was Element Occurrence Ranks. These ranks measure the quality of the element occurrence based on size, condition, and landscape context. The system uses ranks from A through E, with A representing a rank of excellent. Based on ecoregional planning guidelines, all occurrences with ranks of A, B, and C were considered potentially viable and therefore suitable for inclusion. Element Occurrence Ranks represent a ground-truthed basis for indicating the quality and potential viability of a species or natural community occurrence even though there may be problems with consistent a pplication of the ranking criteria among observations. However, only a small percentage of the occurrences within the ecoregions had Element Occurrence Ranks (18% of species and 53% of communities). A secondary, surrogate method for a ssessing viability was developed to incorporate the large number of element o ccurrences without Element Occurrence Ranks. A spatial landscape condition i ndex was developed for this purpose using various GIS

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203 data layers including land use, roads, a nd water quality data (fo r aquatic species and communities). ESRIs Arc-Info GRID was used with 90 m pixels to create individual characterizations of landscape condition that were then combined into three different cumulative indices. The 3 di fferent indices were created depending on the type of species or ecological system i nvolved: terrestrial, a quatic, and an average. The terrestrial viability index was applied to all truly terrestrial species and ecological communities. The aquatic viability index was applied to species that were specifically aquatic or most dependent on an aquatic li fe stage (such as all fish species and all aquatic invertebrates). The average index, a simple combined average of the terrestrial and aquatic indices, was created for species that are dependent on th e integrity of both a quatic and terrestrial system components (such as wading birds a nd shorebirds). Sea turtles were handled differently: nesting sites were assessed using the terrestrial index and the developmental/foraging sites were assessed using the aquatic i ndex. Each of the indices are described in more de tail below (Table 4-3): Terrestrial vi ability index The terrestrial viability index was based on information on roads, land use/land cover, and exotic plant communities. The primary assumption for this index is that areas with the highest percentage of intact habitat, lowest road densities, and greatest distance from major roads and intensive development, lowest human population densities, and far from exotic plant infestations (see Table 4-3) are much more likely to support functional or viable ecological systems. Land use/land c over data (ca. 1995) from four of Floridas five Water Management Dist rict (developed using both Landsat imagery and aerial photographs) were used to assess the intensity of land use throughout the ecoregion using

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204 Table 4-3. Data and criteria used in desi gning the terrestrial, aquatic and averaged viability indices Terrestrial viability rank Distance from Cat 3 landuse Density of Cat 3 landuse Density of Cat 2 landuse Density of Cat 1 landuse 1 = better gt 5000 m lt 2% lt 10% lt 25% 2 le 5000 m ge 2% ge 10% ge 25% 3 le 1000 m ge 10% ge 40% ge 50% 4 le 500 m ge 20% ge 60% ge 75% 5 = worst le 100 m ge 30% ge 80% All road density Distance from major roads Distance from exotic plant communities 1 = better le 0.33 km/km 2 gt 5000 m gt 5000 m 2 le 0.66 km/km 2 le 5000 m le 5000 m 3 le 1.32 km/km 2 le 1000 m le 1000 m 4 le 1.98 km/km 2 le 300 m le 500 m 5 = worst gt 1.98 km/km 2 le 100 m le 100 m Aquatic Distance from Dam NPDES All road viability rank Cat 3 landuse buffers buffers density 1 = best gt 5000 m le 0.33 km/km 2 2 le 5000 m le 0.66 km/km 2 3 le 1000 m Not within 2km Not within 2km le 1.32 km/km 2 4 le 500 m le 1.98 km/km 2 5 = worst le 100 m Within 2km Within 2km gt 1.98 km/km 2 Combination of two indices: weight = 0.8 weight = 0.2 Landuse intensity watershed quality watershed quality within basins average status 10yr trend 1 = best *** See below Good Much better 2 *** Better 3 *** Fair Stable 4 *** Worse 5 = worst *** Poor Much worse ***To create this ranking, WMD land use categories were reclassified to a 0 to 3 scale, where 0=native, 1=low impact to water quality, 2=moderate impact on water quality, 3=high impact on water quality. Then, the rank was calculated to equal: (%cat0 in basin x 1 + %cat1 in basin x 3 + %cat2 in basin 4 + %cat3 in basin 5) / 100.

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205 neighborhood analyses in ESRIs Arc-Info GRID module. The window/neighborhood size used for all of the land use intensity indices was 2.5 km 2 (27 X 27 cells using 90 meter cells). The land use classification was divided into 4 general categories: Category 0 land use (natural communities); Category 1 land use (low intensity land uses such as pine plantations and ranchla nds); Category 2 land use (m oderate intensity land uses including improved pasture, cr oplands, citrus groves, etc.); and Category 3 land use (higher intensity land use including residentia l, commercial, and industrial). Then three separate indices were create d assessing the density of Category 1, 2, and 3 land use respectively. The density of all roads was calculated using 1:100,000 TIGER roads and the linedensity function in GRID with a 1 km s earch radius. The distance from major roads was created from the Florida Department of Transportations major roads data using all roads with average daily traffic counts exceedin g 2,500 trips per day, which is half of the threshold considered critical for roads experien cing higher levels of road kills (Terry Gilbert, Florida Fish and Wildlife Cons ervation Commission, pers onal communication) and other impacts such as road noise and high er pollution levels. Distance from Category 3 land use (high intensity) was created usin g the Water Management District land use data described above. The distance from exotic plant communities index was created using the exotic plants class from the Florida Fish and Wildlife Conservation Commissions statewide land cover map (30 m Landsat-based). To create the cumulative index, all individual indices were averaged to gether with none weighted. The final result was an index with rankings ranging from 1 (hig hest integrity) to 5 (lowest integrity).

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206 Aquatic viability index The aquatic viability index was created using two of the same indices (road density and distance from intensive land us e). However, 4 additional indices were created to specifically assess potential impacts to water quality and potential disruption of important aquatic ecological proc esses. First, 2 km buffers were created around all dams and all identified pollution disc harge sites within the ecoregion. All areas within the 2 km buffer were given a low ranking and all areas outside these buffers were given a moderate (or neutral) ranking. Fourteen dig it HUCs were used to assess the intensity of land uses within watersheds, where watersheds harboring higher percentages of intensive land uses received the lowest ranks. Two parts of a watershedbased assessment of existing water quality and water quality trends from the Florida Department of Environmental Protection were combined to create a single water quality index, with existing water quality status receiving a weight of 0.8 and water quality trend receiving a weight of 0.2. All of these indices were th en combined to create a cumulative aquatic viability index with rankings ranging from 1 (highest integrity) to 5 (lowest integrity). Average viability index The average viability was a simple combination of the both the terrestrial and aquatic viability indices. Both indices were combined and then divided by two to create a new averaged index with rankings ranging from 1 (highest integrity) to 5 (lowest integrity). Assessing element occurrences For all occurrences without Element Occurrence Ranks (and observed since 1980), two complementary criteria were require d for the occurrence to be considered

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207 viable. First, the element occurrence ha d to have a GIS analysis-based ecological integrity/viability rank below the established threshold for the index applicable to that occurrence. The threshold was set at 2.5 for all 3 cumulative indices on the scale described above from 1 to 5, where one has the highest potential integrity and 5 has the lowest. The threshold of 2.5 was delineated in two ways: The landscape condition of areas that received either ranks of 1 or 2 (on average) for each individual index (Table 4-3) was likely to be high or moderate. Known areas within the ecoregions were sa mpled informally to get an indication of how areas considered to have high ecological integrity were ranked. The threshold of 2.5 is likely conservative be cause it is much more likely that viable occurrences would be excluded versus non-viable occurrences being treated as viable. Second, Element Occurrences had to also overlap with areas known to likely have high to moderate ecological integrity/viability. These areas included existing conservation lands, officially proposed conservation lands that have been evaluated for ecological significance, and Areas of Conservation Interest (ACI) and Potential Natural Areas (PNA) from the Florida Naturals Areas Inventory. ACIs and PNAs were identified throughout Florida using aerial photography a nd ground-truthing to identify most of the significant natural areas remaining on private lands. This filter was also likely conservative. Not all natural areas were identified by FNAI, and there are likely some areas outside of existing and proposed conser vation lands, ACIs, and PNAs that harbor element occurrences that are viable. This GIS-based viability assessment can serve as a defendable means to assess landscape context and to some extent, ecosy stem condition (though it may not necessarily indicate conditions such as fi re suppression), although it is less suited for serving as an

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208 indicator of population size. For many specie s there may be a greater likelihood for there to be larger, and hence more viable, populations in sites that are larger and more intact, yet the GIS-based viability asse ssment cannot serve as a direct measure equivalent to the population size criteria incorporated into an Element Occurrence Rank. Nevertheless, the GIS-based assessment provides a defendable, surrogate method to allow the potential incorporation of thousands of element occurrences that did not have Element Occurrence Ranks. Portfolio Site Selection There were 8 primary steps in the site se lection process to develop the portfolio boundaries: Planning units were selected for potential in clusion in the ecoregional portfolios. The planning units selected as candidate areas included all existing and proposed conservation areas, FNAI Areas of Conserva tion Interest (ACIs), and FNAI Potential Natural Areas (PNAs). All sites to meet the goals for all natural communities were selected using element occurrence records, land cover data, vi ability rankings, and expert knowledge. Species targets were separated into two cat egories: 1) species which did not have enough viable occurrences to meet their goals, therefore requiring all viable occurrences (called AVO species) to be includ ed in the portfolio; and 2) species that had enough viable occurrences to potentially meet their viability goals (Discretionary Species). All data available for AVO Species were examined to determine whether additional sites could be selected to meet their goals. The sites selected to meet the goals for all natural communities and AVO Species were combined into an interim portfolio, a nd all viable occurrences of discretionary species within the interim portfolio were identified. All available data were examined to determine whether any additional sites were needed to meet the goals for discretionary species, and any needed sites were added to the final portfolio.

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209 Strategic Habitat Conservation Areas for species and natural communities, other habitat models, recent data for rookery s ites and shorebird aggr egation areas data from the Florida Fish and Wildlife Cons ervation Commission, a nd other additional data (such as Florida Aquatic Preserves) were examined to determine whether there were other important sites that should be added to the portfolio. Landscape connectivity needs were assessed and appropriate lands cape linkages were added to create the final portfolio boundary. The following section provides more detail on th e steps used to select the two ecoregional portfolios. Selection of planning units Planning units were needed to delineate the potential geographic extent of the ecoregional portfolios. There were two op tions for delineating portfolio site boundaries since element occurrences were the primary basis for selecting the portfolio. The first option would be to buffer element occurrences However, since buffers may not define functional conservation units and since other ancillary data was also used to select portfolio sites, a planning unit approach wa s used. Planning units are the potential components of the ecoregional plan that are selected whenever they contain a viable occurrence of a target species or natural community. To maximize the likelihood that planning units represented potentially f unctional conservation areas, existing and proposed conservation lands and FNAI ACIs a nd PNAs were used as the planning units in both ecoregions. Element occurrences that were included in the portfolio but did not overlap with any of these areas (which could happen for occurrences that received an acceptable Element Occurrence Rank) were then buffered by 1 km to serve as a visual indication of the site location but not as a specific portfolio site boundary.

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210 Selection of sites for natural communities FNAI element occurrence data for natural communities, Florida Fish and Wildlife Conservation Commission and Florida Gap An alysis Landsat-based land cover data, SPOT satellite imagery, land use/land cover data from 4 of the 5 states Water Management Districts, FNAI ACIs and PNAs and expert knowledge were all employed to select the portfolio sites for natural communities. Many of these sites are landscapes encompassing a mosaic of several to many interrelated natural communities linked by such ecological processes as frequent fire, underlying edaphic factors, and hydrophysiographic gradients. Florida Natural Areas Inventory (Heritage) element occurrences were the primary means for identifying high quality natural communities. More natural community occurrences had Element Occurrence Ranks than did species occurrences, and the occurrences with high EO ranks (and the most recent observation dates) were used in preference to other potentially viable occu rrences whenever possible. However, the availability of high quality land use/land cover data, imagery, the GIS-based viability assessment, and expert knowledge of specific sites with high quality occurrences allowed many other viable occurrences to also be selected. Selection of sites for target species The incorporation of viable populations for all target species was the next step of the portfolio design process. After using both Element Occurrence Ranks and the GIS viability index to assess the potential viability of species occurrences, target species were split into two groups:

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211 Those that did not have enough viable occu rrences to meet their conservation goals, called All Viable Occurrences (AVO) Specie s meaning that all viable occurrences needed to be included within the portfolio Species that apparently had enough viab le occurrences necessary to meet their conservation goals, which were called Discretionary Species since the best occurrences could be selected when the number of occurrences exceeded the conservation goal for a particular species. AVO species analysis For all AVO species, a two-step process was used to determine whether there were any additional element occurrences that could be added as part of portfolio sites. First, FNAI element occurrence data was reexamined to see if there were additional occurrences that were close to our viability thresholds or any additional information (such as EO data descriptions) that would allow additional occurrences to be considered viable. Then, for some species additional element occurrence data was also assessed for potential viability, and viable occurrences were added to the portfolio when possible. Add itional element occurrence data came from a variety of sources including wildlife observa tion data from the Florida Fish and Wildlife Conservation Commission, Florida Museum of Natural History occurrence records for fish and mussels, Red-cockaded Woodpecker da ta from several sources, and more recent rare plant occurrences. An interim Portfolio was then created by combining all the sites that were needed to meet the goals for ecological communities and AVO species. Discretionary species analysis Efficiency was the first goal for selecting discretionary species occurrences. Therefor e, viable occurrences within the Interim Portfolio were preferred and selected before viable occurrences for Discretionary Species that were not. For some species many more viable occurrences than needed to meet the conservation goal were already within th e Interim Portfolio. For example, 168 occurrences of gopher tortoise ( Gopherus polyphemus a near-endemic species

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212 important for xeric upland vertebrate and invertebrate biodiversity) were within the interim Portfolio. In some cases, however, the conservati on goals for some Discretionary Species were not met within the Interim Portfolio. In those cases, all other viable element occurrences not within the Interim Portfolio were assessed to determine what additional sites/occurrences were best for meeting the conservation goal. Element Occurrences that had the highest viability ranks, the most recent observations, or otherwise known to be the most significant were preferred. Additional occurrences were selected to meet geographic distributional goals for some Discretionary Species. The two best examples were the Florida Scrub-Jay ( Aphelocoma coerulescens) and Florida scrub lizard ( Sceloporus woodi ), both which occur on isolated inland and coastal scrub ridg es across the Florida peninsula. Portfolio selection included the selection of viable occurrences for each of these species from each geographically isolated ridge system. Finally, in a few additional cases, some exceptional, high quality occurrences that repr esented the best occurrences from a size, condition, and functional landscape context (Poiani et al. 2001) were added to enhance the conservation efficacy of the entire portfolio. Identification of Additional Sites In order to more thoroughly address the inclusion of areas needed to ensure the viability of target species, Florida Fish and Wildlife Conservation Commissions (FWC) Strategic Habitat Conservation Areas (SHCA) were also assessed for inclusion within the ecoregional portfolios. SHCAs represent priority conservation areas needed to protect viable populations of focal species. The FWCs habitat models and SHCAs also represented the only potential

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213 habitat or occurrence data we had for some target species including Mangrove Cuckoo ( Coccyzus minor ) and Black-Whiskered Vireo ( Vireo altiloquus). For ecological communities (including Sandhill and Scrub), SHCAs are priori ty sites for conserving unprotected occurrences. All of the SHCAs are spatial areas (versus points) based on habitat models for species using Landsat-bas ed land cover data a nd the appropriate land cover class representing the remaining, unprot ected patches needed to protect viable populations or priority natural community lo cations. Although element occurrence point data were used as the primary basis for portf olio site selection, SH CAs were used to add additional sites for specific target species and ecological communities or to add area to existing portfolio sites to better represent the spatial needs of various targets (Table 4-4). In addition, other recently created habitat models were utilized where appropriate to help meet the viability goals for several species (Cox and Kautz, 2000) (Table 4-4). Finally, USFWS critical habitat designated for several federally listed species was also incorporated into the portfolio (Table 4-4). Almost all SHCAs, habitat models, and critical habitat were handled in the same fashion as element occurrence data for de termining site boundaries. Generally, only areas overlapping with existing and proposed conservation lands, or FNAI Areas of Conservation Interest or Potential Natural Ar eas were added to the portfolio. However, afterwards, models were assessed for their degree of overlap with the portfolio and additional habitat for selected species was then added to the portfolio in some cases. The habitat model for the Crested Caracara ( Caracara cheriway ) is a specific example where the portfolio site selection process was altered to meet the unique needs of a species. The Caracara is native to Florid as dry prairies in south-central Florida,

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214 Table 4-4. Additional data used to id entify portfolio sites (See Appendix E and Appendix F for scie ntific names) Florida Fish and Wildlife Conservation Commission Strategic (FWC) Habitat Conservation Areas Habitat models (source in parantheses) U. S. Fish and Wildlife Service critical habitat Anastasia Beach Mouse Crested Caracara (University of Florida) (UF ) American Crocodile Mottled Duck Florida Grasshopper Sparrow (FNAI) Silver Rice Rat Atlantic Saltmarsh Snake American Crocodile (FWC) Snail Kite Bald Eagle Scotts Seaside Sparrow (FWC) Cape Sable Seaside Sparrow Southeastern Bat Saltmarsh Vole (FWC) Piping Plover Mangrove Fox Squirrel Swallow-tailed Kite (Ken Meyer, UF) Limpkin Short-tailed Hawk (Ken Meyer, UF) Florida Black Bear Black-whiskered Vireo White-crowned Pigeon Red-cockaded Woodpecke r Scotts Seaside Sparrow American Kestrel Southeastern Beach Mouse Mangrove Cuckoo Short-tailed Hawk Florida Panther Florida Scrub-Jay Sandhill Crane Snail Kite Rare Plants Sandhill Pine Rockland Tropical Hammock

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215 however, it has shown to be capable of utilizing ranchlands or pasturelands as well as remaining areas of natural dry prairie. Sin ce agriculturally-disturbed habitats tend to be avoided for almost all other species and were not incorporated within most other portfolio sites, a habitat model using core nesting territories with suitable land use/land cover within 3 km of nests was deve loped to identify a broad portfolio site that should meet the viability goal for this species. In addition, th e Caracara model and portfolio site served as a surrogate for a set of other target species such as the Florida Burrowing Owl ( Athene cunicularia floridana), Florida Sandhill Crane ( Grus canadensis pratensis), and Southeastern American Kestrel ( Falco sparverius paulus ) that also utilize agricultural landscapes in the Kissimmee Valley. Several other data sets were also used to add additional sites to the portfolio. The Florida Fish and Wildlife Conservation Commissi ons recent statewide survey of wading bird rookery sites, which was received afte r the portfolio boundaries had been largely established, was used to identify the most sign ificant rookery sites for target wading bird species that were not already represented in the portfolio. Sites identified as supporting large aggregations of wintering shorebirds in another FWC dataset we re also added to the portfolio. Selected Florida A quatic Preserves were added to the portfolio both to serve as sites for seagrass communities as well as a surrogate for other estuarine and marine biological diversity. Finally, several rivers (St. Johns, Sante Fe, Withlacoochee) that had been identified as significant for freshwater aquatic biodiversity and for maintaining ecological connectivity were buffered and adde d to the portfolio where they were not already represented by larger portfolio sites.

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216 Representing Critical Areas for Connectivity The last set of sites added to the portfolio were those required for landscape c onnectivity. These sites are particularly important for the Florida panther and Florida black bear. These areas were identified by assessing the SHCAs for both the Florida black bear and Florida panther and determining which additional areas needed to be added to provide critical landscape connections as well as larger blocks of habitat (Cox et al. 1994; Beier and Noss 1998; Maehr et al. 2002b). The Florida Ecological Greenways and intact habitat areas (such as FNAI ACIs and PNAs) were also used to identify strategically located sites necessary to forge the interconnected landscapes required to cons erve biodiversity in both ecoregions. Results and Discussion The two portfolios selected to meet go als for hundreds of target species and natural communities cover a large portion of both the Florida Peninsula and Tropical Florida Ecoregions. In both ecoregion por tfolios, sites range from some small ones selected for individual focal species or natural communities to large ones including hundreds of species and natural community occu rrences. Overall, the emphasis in the site selection process was on landscape-scal e sites, while small sites had to be incorporated when they were necessary for meeting species and natural community goals. In the Florida Peninsula Ecoregion, only 16% of the total portfolio sites are for a single target. In the Tropical Florida Ecoregion, onl y 9% of the total portfolio sites are for a single target. Florida Peninsula Ecoregion Portfolio The Florida Peninsula Ecoregion portfo lio contained 186 sites that cover 3.4 million ha, which is 36% of the entire ecoregion including coastal water (Figure 4-5).

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217 Figure 4-5. The Florida Peninsula Ecoregion site portfolio. Many of the sites within the portfolio are larger landscapes and linkages among sites are fairly well represented, especially from southwest Florida through the Kissimmee Valley, through the St. Johns River basin and to the Ocala National Forest.

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218 With open water areas removed, the portfo lio contained 43% of the ecoregions land area. Portfolio sites are sometimes adjacent to each other when they represent different ownerships of different ecological resources. In some cases portfolio sites represent multiple parcels that are in the same general locality and represent a common ecological feature such as a river basin, ridge, natura l community type, etc. Fifty-four of the portfolio sites contained at least one par cel that is 20,000 ha or larger, which were considered large enough to be a landscape site (Poiani et al. 2000). Eighty-five sites have at least one parcel that is 10,000 ha or larg er. The largest portf olio site was 195,000 ha (the Green Swamp) and the smallest was 3 ha. The mean portfolio site size was 18,400 ha. Tropical Florida Ec oregion Portfolio The Tropical Florida Ecoregion portfolio contained 65 sites that cover 2 million ha, which is 42% of the entire ecoregion incl uding coastal water (Figure 4-6). With open water areas removed, the portf olio contained 72% of the ecoregions land area. Most portfolio sites were adjacent to other portfolio sites that we re kept separated mainly to represent the different public conservation ow nerships within the ecoregion. In some cases portfolio sites represent multiple parcels that are in the same general locality and represent a common ecological feature such as a hydrologic basin, ridge, natural community type, etc. The South Dade Pine Rockland Macrosite is the most extreme example of a multi-parcel portfolio site. Eighteen of the portfolio sites contained at least one parcel that was 20,000 ha or larger, and 23 sites had at least one parcel that is 10,000 ha or larger. The largest portfolio site was 630,000 ha (Everglade s National Park) and the smallest was 24 ha. The mean portfolio site size was 31,000 ha.

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219 Figure 4-6. The Tropical Florida Ecoregion site portfolio

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220 Goal Achievement Goals for natural community and species representation in the portfolio served two purposes. First, though goals based on the number of viable occurrences is a coarse method for ensuring viability, the likelihood that a species will be viable or that a natural community is well represented increases as the site portfolio comes closer to meeting or exceeds the minimum goal. Another important assumption, which will be discussed in more detail below, is that all the land (and waters) in the portfolio will be protected and managed properly. The goals for each specie s and natural community also serve to drive the site selection process and therefore are the primary justification for the inclusion of specific areas within the portfolio and the total area within the portfolio. Whether a goal was obtainable or not for a par ticular species or natural community, the goals served to justify the inclusion of all areas needed to come as close to meeting the goal based on the available number of viable occurrences. Plant species are a good example of the limita tions of the default goals (10 viable occurrences) due to the inherent rarity of many species, the lack of comprehensive occurrence data for some species, and the difficulty establishing realistic representation/viability goals. In the Florida Peninsula Ecoregion only 38 (27%) out of 142 plant species had enough viable occurrences to meet their goals within the site portfolio (See Appendix G for a detailed list of plant species and goal status for the Florida Peninsula Ecoregion). However, even before assessing the potential viability of occurrences, only 56 (39%) of the plant species had enough total occurrences to potentially meet the goal. In other words, 86 plant species did not have enough total occurrences within the ecoregion to meet the standard default goal of including at least 10

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221 viable occurrences within the portfolio. This is due to either natural rarity of species that were never common, induced rarity caused by habitat loss and fragmentation, and a lack of systematic surveys across all lands to fi nd additional occurrences. And when species did have enough total occurren ces to potentially meet their go al, a plethora of old records (last documented prior to 1980) and no, or poor, information about the status or quality of occurrences resulted in the loss of many occurre nces as non-viable. Even with the use of the landscape-based viability index to augment the lack of Element Occurrence Rank data, only 1,538 (52%) of 2,972 plant species occu rrences could be considered viable. The issues were the same for plant speci es in the Tropical Florida Ecoregion. Only 40 (22%) of 185 species had enough viable occurrences to meet their goals within the site portfolio (See Appendix H for a detailed list of plant species and goal status for the Tropical Florida Ecoregion). Only 54 ( 29%) of the plant species had enough total occurrences to potentially meet the goal. And only 1,089 (61%) of 1,777 plant species occurrences could be considered viable. For animal species, both vertebrates and i nvertebrates, there was also a lack of adequate occurrence data for many target species. For Example, in the Peninsula Florida Ecoregion, 14 (13%) of 104 have no occurrences within the Florida Natural Areas Inventory database (usually because they are not species tracked by FNAI), and only 46 (44%) had enough total occurrences to meet their goals. In the Tropical Florida Ecoregion, only 32 (45%) out of 71 vertebrate species had enough occurrences to potentially meet their goals. Even worse, after assessing the potential viability of all occurrences, only 1,847 (38%) of the 4,868 verteb rate occurrences could be considered viable in the Florida Peninsula Ecoregion, though 829 (61%) of the 1,353 vertebrate

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222 occurrences could be considered viable in th e Tropical Florida Ecoregion. In response to the lack of occurrence data needed to meet the goals for many vertebrate species, additional occurrence records from the Florida Fish and Wildlife Conservation Commission and the Florida Museum of Natural History were used for some taxa though this typically did not add enough data to meet viability goals. In addition, habitat analyses were used from the Florida Fish and Wildlife Conservation Commission (Cox et al. 1994; Cox and Kautz 2000) a nd several other sources to identify additional sites for some species. However, the results were still few species meeting the goal of 10 viable occurrences in both ecoregions. In the Florida Peninsula Ecoregion, only 43 (41%) of 104 vertebrate species met their goals, and onl y 28 (39%) of 71 species met their goals in the Tropical Florida Ecoregion. However, since the Florida Fish a nd Wildlife Conservation Commission (FWC) has completed viability assessments for many of the vertebrate species included in these ecoregional plans, another standard for assessing the potential viability of vertebrate species within the portfolio was also used. This was a subjective process where the viability assessments done by the FWC (Cox et al. 1994; Cox and Kautz 2000) and other ecological information on each species were used to determine whether it was likely that the species would be viable within the por tfolio if all sites were protected and appropriately managed. Base d on this assessment, 74 (71%) of 104 vertebrate species likely met their viability goals in the Florida Peninsula Ecoregion, and 48 (68%) of 71 species likely met their goals in the Tropical Florida Ecoregion (Table 4-5 and Table 4-6) (See Appendix I and Appendix J for a detailed lis t of vertebrate species and goal status for each ecoregion).

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223 Table 4-5. Goal achievement by taxonomic gr oup for vertebrate species in the Florida Peninsula Ecoregion Taxonomic group Total # of species # of species meeting goal of 10 occurrences # of species likely meeting viability goal within portfolio Fish 19 0(0%) 10(53%) Herps 27 10(37%) 17(63%) Birds 40 29(73%) 37(93%) Mammals 18 4(22%) 10(56%) Total 104 43(41%) 74(71%)

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224 Table 4-6. Goal achievement by taxonomic gr oup for vertebrate species in the Tropical Florida Ecoregion Taxonomic group Total # of species # of species meeting goal of 10 occurrences # of species likely meeting viability goal within portfolio Fish 6 0(0%) 4(67%) Herps 16 3(19%) 7(44%) Birds 35 21(60%) 30(86%) Mammals 14 4(29%) 7(50%) Total 71 28(39%) 48(68%)

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225 Invertebrate animals were especially challenging. Most invertebrates selected as focal species in these ecoregions are either cave or spring dwelling and are frequently documented from only one locality. Obviously, a goal of 10 occurrences is not attainable for extremely rare invertebrates that occur at only one location. In the Florida Peninsula Ecoregion, only 7 (13%) of 56 invertebrate species had enough total occurrences to potentially meet their goal, but only 1 ( Cicindela highlandensis a terrestrial beetle) had enough viable occurrences to meet its goal (See Appendix I for a detailed list of invertebrate species and goal status for th e Florida Peninsula Ecoregion). For many species the available occurrence data is either outdated or lacking the information needed to adequately assess viability. However, if protecting all known occurrences or enough total occurrences (regardless of viability assessments) was the standard, as many as 26 (46%) of the species could be considered adeq uately represented within the portfolio. In the Tropical Florida Ecoregion, 6 (4 6%) of the 13 focal invertebrate species either had no documented occurrences or were known from only one location, and no species met their goals. Using the same likelihood standards for meeting viability goals discussed above, as many as 7 (54%) species could be considered potentially viable within the site portfolio (See Appendix J for a detailed list of invertebrate species and goal status for the Tropical Florida Ecoregion). For natural communities, both an overall goal for the entire ecoregion and a subecoregional goal were set to ensure ade quate representation overa ll and to make sure that geographic variation in natural communities was captured. In the Florida Peninsula Ecoregion, 1,604 (67%) out of 2,408 natural comm unity occurrences could be considered

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226 viable, and 34 (61%) of the 56 natural communities met their overall goal for representation. Based on gene ral information about the distribution and status of these natural communities and sites included in the portfolio, it is likely that as many as 41 (73%) of the natural communities met their goals within the Florida Peninsula Ecoregion site portfolio. Thirty-two (57%) of the natural communities met their subregional goals, which means that they are still well distributed within their historic range within the ecoregion (See Table 4-1 for subecoregional goals). Sandhill, mesic flatwoods, and dry prairie were designated as matrix communities and therefore were required to ha ve sites that were at least 2000 ha to meet their goals. Both sandhill (at least 8 sites with 2000 ha or more) and mesic flatwoods (at least 19 sites) had enough large sites to meet thei r overall goals but dry prairie did not (only 8 sites were large enough whereas 10 were needed). In addition, although all 3 communities met their subregional goals in terms of total number of sites per subecoregion, dry prairie did not have an ad equately large site in 1 subecoregion, and sandhill did not have an adequately large site in 2 subecoregions. In the Tropical Florida Ecoregion, 513 (76%) out of 671 natural community occurrences could be considered viable, but only 15(34%) of the 44 natural communities met their overall goal for representation (See Appendix K for a detailed list of natural communities and goal status for the Florida Peninsula Ecoregion). The primary reason for the poor performance was that many co mmunities were poorly represented in the available occurrence data. Twenty-seven (61%) of the communities did not have enough total documented occurrences to meet their goals. Therefore the occurrence data has many occurrences for a few communities and very few for most communities. However,

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227 based on general information about the distribution and status of these natural communities and sites included in the portfolio, it is likely that as many as 25 (57%) of the natural communities met their goals within the Tropical Florida Ecoregion site portfolio. Fourteen (32%) of the natural communities met their subregional goals (See Table 4-2 for subecoregional goals). The only designated matrix community in the Tropical Florida Ecoregion was tropical swale, although pine rockland may ha ve been a matrix community before the development of eastern Dade County. At l east 12 sites have enough remaining Tropical Swale (2,000 or more ha) to meet the repr esentation goal for this community (See Appendix L for a detailed list of natural communities and goal status for the Tropical Florida Ecoregion). Finally, it is acknowledged that marine and estuarine natural communities (or ecosystems) are poorly represented in both por tfolios. Though coastal waters (and lands) are included in the portfolios in both ecoregions, the marine and estuarine community classification used in this analysis is not comprehensive and the available occurrence information in this analysis for these natural communities is extremely poor. Though in some ways estuarine and marine species may be better represented in the portfolios, the included species and occurrence information is not a thorough inventory of coastal species. Fortunately, more comprehensive ecoregional planning for the marine and estuarine ecosystems in the Gulf of Mexico has been initiated, and a similar analysis is planned along the Florida east coast.

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228 Conservation Land and Open Water Statistics Existing and proposed conservation la nds and open water were a significant portion of the area within both ecoregional portfolios (Figure 4-7). In the Peninsula Florida Ecoregion, 51% of the portfolio was w ithin either existing conservation lands or open water, and an additional 21% was within proposed cons ervation lands (Table 4-7). The ecoregion site portfolio also contains most of the existing (95%) and proposed (86%) conservation lands within the ecoregion, which s uggests that virtually all of the existing and currently planned conservation land i nvestments are needed to conserve the ecoregions biodiversity. In addition some of the proposed and existing conservation lands not within the portfolio are recent additions added to th e conservation lands inventory since the portfolio was selected, and some of these areas may have been included if they had been available during the selection process. In the Tropical Florida Ecoregion, 89% of the portfolio was within either existing conservation lands or open water, and an additiona l 4% was within proposed conservation lands (Figure 4-8; Table 4-8). The ecoregion site portfolio also contains most of the existing (98%) and proposed (77% ) conservation lands within the ecoregion. However, most of the existing and proposed conservation lands not included within the portfolio are critical as part of the strategy for restoring ecosystem function to the tropical swale landscape of the central and southern Everglades and Florida Bay, which is an issue that will be discussed in more detail below. Comparison with the Fl orida Ecological Network The primary goal of the Florida Ecological Network was to identify large areas of ecological significance and the best landscap e linkages to connect these areas into a

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229 Figure 4-7. Conservation lands, open water, and private lands both within and outside the Florida Peninsula Ecoregion

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230 Table 4-7. Conservation lands and open water statistics for the Florida Peninsula site portfolio Category Hectares % of portfolio % of ecoregion Existing conservation lands outside portfolio 71,101 N/A 1% Open water outside portfolio* 2,140,630 N/A 22% Proposed conservation lands outside portfolio 110,647 N/A 1% Other private lands outside portfolio 3,829,785 N/A 40% Existing conservation lands within portfolio 1,441,101 42% 15% Open water within portfolio* 292,582 9% 3% Proposed conservation lands within portfolio 702,514 21% 7% Other private lands within portfolio 982,213 29% 10% Total area in portfolio 3,418,410 100% 36% Total area in ecoregion 9,570,573 100% *Open water does not include open water within ex isting conservation lands.

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231 Figure 4-8. Conservation lands, open water, and private lands both within and outside the Tropical Florida Ecoregion site portfolio

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232 Table 4-8. Conservation lands and open water statistics for the Tropical Florida site portfolio Category Hectares % of portfolio % of ecoregion Existing conservation lands outside portfolio 39,064 N/A 1% Open water outside portfolio* 2,201,634 N/A 46% Proposed conservation lands outside portfolio 21,977 N/A 0% Other private lands outside portfolio 490,378 N/A 10% Existing conservation lands within portfolio 1,694,934 84% 35% Open water within portfolio* 103,007 5% 2% Proposed conservation lands within portfolio 74,911 4% 2% Other private lands within portfolio 151,815 7% 3% Total area in portfolio 2,024,667 100% 42% Total area in ecoregion 4,777,720 100% *Open water does not include open water within ex isting conservation lands.

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233 functional statewide conser vation network. Based on a cursory analysis of species occurrences in Chapter 2, it appears that th e Florida Ecological Network does a good job of protecting available occurrences of most sp ecies of conservation interest statewide. The amount of overlap between the Florid a Ecological Network and the ecoregional portfolios is also an indication that the Ecol ogical Network captures much of the area needed to conserve biodiversity in the Florid a Peninsula and Tropical Florida Ecoregions. In the Florida Peninsula Ecoregion, the Florida Ecological Network covers 3.95 million ha, and therefore cont ains approximately 500,000 ha more than the Florida Peninsula Ecoregion site portfolio. Seventy-two percent of the Ecological Network overlaps with the site portfoli o, and 84% of the site portfolio overlaps with the Ecological Network (Figure 4-9). On land, the primary differences are in the Kissimmee River Valley and in the northwest portion of the ecoregion. In the Kissimmee River Valley, the site portfolio better represents dry prairie and other open grasslands necessary for a host of species including Crested Caracara, Florida Grasshopper Sparrow ( Ammodramus savannarum floridanus ), Florida Burrowing Owl, Florida Sandhill Crane, and Southeastern American Kestrel. Such areas were largely avoided by the Ecological Network primarily because they represented a mosaic of natural grasslands and wet prairies dispersed within a matrix of impr oved pasture and other agricultural land uses. In other areas including the northwest portion of the Ecoregion, the Ecological Network does a much more thorough job of representing large landscapes that may be dominated by semi-natural areas such as pine plantations but are needed to consolidate conservation areas and provide functional c onnections. Although connectiv ity was considered in the development of the ecoregional portfolio, th e focus was the Florida panther and Florida

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234 Figure 4-9. Overlap between the Florida Ecological Network and the Peninsula Florida and Tropical Florida ecoregional portfolios. Overall, the Florida Ecological Network more thoroughly represents large landscapes and landscape linkages in the western and northern portions of the Florida Peninsula Ecoregion, and the ecoregional portfolios more thoroughly include important tropical hammocks and pine rocklands in south Florida and dry prairie habitats in south-central Florida.

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235 black bear. Only primary connections amon g large bear populations or key expansion areas for the panther in southwest Florida were thoroughly incorporated. There are also significant differences within the Florida Pe ninsula Ecoregion in aquatic ecosystems. The Florida Ecological Network more thoroughly incorporates certain estuaries such as the Indian River Lagoon and Tampa Bay wher eas the ecoregional portfolio incorporates the recently expanded boundaries of Big Bend Aquatic Preserves on the west coast and the Guana River Estuarine Research Reserve along the northeast coast. Finally, the Ecological Network better represents several riparian systems including the Peace River, parts of the St. Johns River, and the Sante Fe River. There is an even greater amount of overlap between the Florida Ecological Network and the Tropical Florida Ecoregion site portfolio (Figure 4-9). In this case, the ecoregional portfolio is approximately 100,000 acres larger than the Ecological Network. The primary reason is that tropical hammocks in the Florida Keys and pine rocklands in Dade County in the ecoregional portfolio were largely unrepresented in the Ecological Network since they are fragmented by bot h human caused habitat loss and geography. However, large protected areas dominat e both the Ecological Network and the ecoregional portfolio within the Tropical Florida Ecoregion, which results in a 95% overlap of the Ecological Network with the ecoregional portfolio and a 90% overlap of the ecoregional portfolio with the Ecological Network. Comparison with Black Bear Habitat and Landscape Linkages Since the Florida Black Bear requires larg e areas to support viable populations, in theory it could frequently serve as an umbre lla species, which means that most other species might be adequately protected in the areas needed to effectively protect black

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236 bear. Based on the black bear habitat and landscape linkage modeling conducted in Chapter 3, a base layer of potential high qua lity bear habitat and landscape linkages was identified that contained enough habitat and connectivity to likely protect a viable statewide bear metapopulation. Comparing this data layer to the ecoregional portfolios suggests that there are significant gaps within the most significant bear habitat and linkages that would not adequately cover certain areas also needed to conserve biodiversity within these ecoregions. First to compare the ecoregional por tfolios with bear habitat, only land areas are compared since bear habitat would not directly protect aqua tic habitats (though it could protect watersheds). In the Florida Peninsula Ecoregion, only 48% of the land area within the ecoregional portfolio overlapped with the bear habitat and landscape linkages data layer, whereas 74% of bear habitat overlapped with the ecoregional portfolio (Figure 4-10). Only 44% of the land within the Tropi cal Florida Ecoregion overlapped with bear habitat, whereas almost all identified bear habitat (95%) overlapped with the ecoregional portfolio (Figure 4-10). The primary reason fo r the lack of correspondence is the extent of more open herbaceous and shrub dominated wetlands and upland in south-central and south Florida. Landscapes dominated by such communities include the marshes of the upper St. Johns River; the marshes, wet prairies, and dry prairies of the Kissimmee River Valley; and the sloughs and wet prairies of the Everglades. These areas are critical for biodiversity conservation in these ecoregions though they do not support enough forest cover to meet the definition of primary bear habitat.

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237 Figure 4-10. Overlap between the Peninsula Florida and Tropical Florida ecoregional portfolios and Florida black bear habitat or landscape linkages. The open marshes, wet prairies, dry prairies, and sloughs of the upper St. Johns River, Kissimmee River Valley, and the Everglades are critical for conserving biodiversity in these ecoregions though they do not support the forest cover needed for prime bear habitat.

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238 Conclusions The science and application of identifyi ng and designing reserve networks has become increasingly important as biodivers ity continues to erode through habitat fragmentation and numerous other threats. Th e disciplines of conservation biology and landscape ecology now have preeminent roles in improving efforts to identify and design integrated systems of reserves to functionally protect biodiversity. In the last decade, The Nature Conservancy has embraced the grow th of biodiversity science and landscape ecology to guide their efforts to conserve native species, all natural communities, and intact and restored landscapes. Ecoregional planning provides lots of promise for more comprehensive biodiversity assessment in the future. Recent science has made it clear that thorough development of representation analysis, viability assessments, and landscape approaches are critical for identifying the area and configuration of reserves needed to conserve biodiversity across regions (Noss and Coope rrider 1994; Harris et al. 1996b; Schwartz 1999; Jennings 2000; Margules and Pressey 2000; Poiani et al. 2000; Groves et al. 2002). Ecoregional planning attempts to collect all the relevant data needed to protect viable populations of focal species, functionally represent all natura l communities, and incorporate landscapes that can be maintained or restored to protect ecological integrity. In the Florida Peninsula and Tropical Florid a Ecorgions, the guidelines for ecoregional planning worked fairly well but important data gaps and problem s with criteria for defining success were evident. One of the first important issues is th e selection of ecoregion boundaries. Though ecoregion boundaries may be based on legitimate cr iteria to differentiate ecological units

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239 based on coarse climatic, geolog ic, and other factors, the s cale at which these boundaries are selected and criteria used may not always reflect the most important patterns in the geographic distribution of biodiversity. Th e suitability of the existing boundary between the Florida Peninsula Ecoregion and Tropical Florida Ecoregion is a good example. There are two primary ecoregion classifications, at least for the United States: Bailey's classification (1996), which has been adopted for use by the USDA Forest Service and for The Nature Conservancy's ecoregional planning; and Omernik's classification (1995), which is used by the U.S. Environmental Protection Agency. Both ecoregion classifications have similar boundaries between the ecoregions covering most of the Florida peninsula and then an ecoregion fo r south Florida (See Figure 3-2 for the boundaries from the Bailey classification). However, neither system well represents the influence of climate on the distribution of tropical associated species in the southern half of the Florida peninsula. Freeze influence ameliorated by the waters of the Gulf of Mexico and the Gulf Stream in the Atlantic dictates that tropical associated plant species frequently occur along the coasts from the Fl orida Keys up to approximately the latitude of Orlando. However, these species are largel y absent from the interior of south-central Florida where freezes are much more fre quent (Myers and Ewel 1990; Harris and Cropper 1992). Since so many focal species we re rare plants (though not all tropicallyaffiliated), a boundary between the Florida Peninsula and Tropical Florida ecoregions that better represented the climatic influence of cold winter weather may have resulted in better representation and success for tropical and coastal species. Modification of the ecoregion boundaries was discussed at the begi nning of the analysis but due to time limitations and other consider ations, the ecoregion boundaries were maintained.

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240 However revision of the boundaries between ecoregions should be more thoroughly considered in future iterations. Setting goals and assessing viability are critical parts of the ecoregional planning process and are also potentially the most pr oblematic element of the reserve design process. Goals are meant to indicate when a species or natural community is adequately protected or represented. For species, ad equate protection should mean that, if the portfolio of sites is protect ed and properly managed, the species would remain viable within the ecoregion. The goal used for all species targets was the inclusion of 10 viable occurrences within each ecoregional portfolio. A species with 10 separate, viable populations within an ecoregion should have an excellent chance of persisting (Cox et al. 1994; Kautz and Cox 2001). However, the a pplication of the goal criteria and the definition of viability used in ecoregional planning result in some important issues based on both the limitations of occurrence data, thoroughness of occurrence data, and the significant differences in the ecology of focal species. Population viability assessme nt continues to evolve, but a frequently used standard is 90% or 95% pr obability of a population surviving for 100 years (Meffe and Carroll 1997). In Florida, the Florida Fish and Wildlife Conservation Commission used such a standard and also reasoned that a speci es that had at least 10 populations that met this standard would have an excellent overall probability of long-term persistence (Cox et al. 1994; Kautz and Cox 2001). This was the standard that was the basis for the default viability goals for ecoregional planning. However, there are significant differences in assessing population sizes needed to meet a standard of 90-95% survival probability of 100 years based on the demographic and ecologica l characteristics of a particular species

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241 and reliance on occurrence data and coarse viab ility standards for such occurrences. The two methods for assessing viability of species occurrences in this analysis did not include population viability assessments. Element Occurrence Ranks (EOR) that are sometimes included with natural heritage occurrences ar e supposed to incorporate population size within the ranking and population EORs and landscape-based viability assessment techniques had to be used as a surrogate for mo st occurrences. In addition, the ecology of some species dictates that occurrence data can represent individual occurrences for some species. This includes raptors such as the Southern Bald Eagle where many occurrences represent single nest locations. Cryptic or di fficult to survey species such as fossorial reptiles and other vertebrate species also often have occurrence data that represent one or a few observed individuals. These issues do not invalidate the approach taken in ecoregional planning, nor are the problems with the data available in Florida exceptional. For the vast majority of species across all ecocregions there is not enough population status and demographic data available to attempt population viability asse ssments (Groves et al. 2002). Future ecoregional plans will be improved as occu rrence data is update d to expand population information and as techniques to assess viability that do not require extremely detailed demographic data advance (Morris et al. 1999). For natural communities, adequate protection or representation should mean the community can be maintained as a functional ecological system that provides habitat for both focal species and other species that may have been missed (such as many invertebrates) in the selection process. The subecoregion goals for natural communities are meant to capture any geographic variati on in ecological processes and component

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242 species. These goals are a reasonable way to ensure adequate natural community representation using natural he ritage occurrences and supplementary data (Groves et al. 2002). However, the analysis was somewhat constrained by a lack of complete information about the condition of many na tural community occurrences. As with species, a landscape-based viability index was used as a surrogate for occurrences without Element Occurrence Rank data (which incorporates information on condition), but issues such as fire suppression and exotic plants may not be ade quately addressed in a land use and land cover base d landscape index. Natural community representation, like population viability assessment, has also received increasing attention in conservation bi ology and reserve design. Standards used to determine adequate representation are fr equently based on prot ecting either some percentage of existing area of a natural community or a percentage of presettlement or potential natural vegetation (Margules and Pre ssey 2000). This approach is dependent on land cover data (such as classified Landsat imagery) that adequately identifies existing natural communities and is strengthened by realistic representations of potential natural vegetation. Though such data exist for Flor ida, the community classifications for both existing and potential natural vegetation are coarse and miss most natural communities. In future iterations a hybrid approach that includes area representation as a criterion for communities that can be distinguished using imagery and occurrence-based goals for all other communities should be considered. Large wide-ranging species are another im portant issue for ecoregional planning. The area needed to conserve viable population of species such as the Florida panther and Florida black will frequently exceed the am ount of available land within individual

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243 ecoregions (Noss et al. 1996; Maehr et al 2002b). Although the Florida Peninsula and Tropical Florida ecoregional portfolios include most of the available habitat for these species, protection of viable populations w ill require coordination across the boundaries of at least 4 ecoregions. Although there are important data gaps to be addressed in future iterations, ecoregional planning is an ambitious atte mpt to comprehensively assess biodiversity conservation needs. The Florida Penins ula and Tropical Florida ecoregional plans combine fine filter, coarse filter, and landscape approaches to identify the areas that must to be protected to effectively conserve biodi versity across the Florida peninsula (Franklin 1993). The fine filter approach included assessm ent of not only priority focal vertebrate species, but also hundreds of plants and key i nvertebrates including many cave and spring endemics. All natural communities were included in the assessments using a hybrid classification based on both the Florida Natural Areas Inventory and The Nature Conservancys National Vegeta tion Classification. Landscape considerations were addressed by using Florida Fish and Wild life Conservation Commission Strategic Habitat Conservation Areas for the Florida Panther and Florida Black Bear, the Florida Ecological Greenways Network, and area goals for large, matrix natural communities to identify large landscape sites and linkages. The results of the analysis indicate that most of the existing conservation lands have a critical role in conserving the ecoregions' biodiversity, and that there are still large areas that need to be protected in a rapidl y developing region. There are several next steps that are still in progress to enhance conservation action by The Nature Conservancy. First, unprotected lands within the portfolio s will be prioritized so that conservation

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244 attention can be focused on the sites that contain the most important biodiversity elements and are most threatened by deve lopment. Second, the proper management of existing conservation lands is essential to make sure that biodiversity thrives on all such lands. Restoration is also required on existing and proposed conservation lands to restore intact natural communities and functional ecological processes. This is most evident throughout what can be called the Everglades watershed from the Kissimmee River basin and Lake Okeechobee through almost the entire s outhern tip of the state. There is a dire need for landscape restoration in South Fl orida that was beyond the scope of this research, but is absolutely essential for piecing together some semblance of the once vast subtropical marsh, swamp, pi neland, and hammock landscape mosaic that once existed (Harris et al. 2001). Furthermore, the prot ection of some ecoregi on portfolio sites will require active participation in land use planning in surrounding areas. The best examples are the myriad spring sites within the Peninsula Florida portfolio that are threatened by groundwater extraction and pollution over vast ar eas within their watersheds. Since fire is an integral ecological process throughout these regions, efforts must also be expanded to minimize human-created conflicts that impede the ability of managers to use prescribed fire to maintain ecological integrity. Ecoregional planning in the Florida Pe ninsula and Tropical Florida ecoregions represents another big step in our ever-e xpanding knowledge about Florida biodiversity conservation needs and assessm ent techniques. These effo rts were both complementary with previous assessments and supported by thei r data. More formal efforts to integrate these efforts in one comprehensive assessment for the entire state of Florida should be the next step towards ensuring the future of Florida's unique natural heritage.

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CHAPTER 5 CONCLUSIONS, POLICY ISSUES, AND RECOMMENDATIONS Reserve Design Analysis: Landscape Approaches and Methods Numerous empirical studies (Saunders et al. 1991; Harris and Silva-Lopez 1992; Friesen et al. 1995; Bolger et al. 1997; Hartley and Hunter 1998; Trine 1998; Heske et al. 1999; Debinski and Holt 2000; Findlay and Bourdages 2000; Odell and Knight 2001), have established that habitat fragmentation results in the erosion of biodiversity and ecological integrity. Landscapes harboring functional ecological processes, which are both depended on, and produced, by biodiversity (Harris et al. 1996a), are essential for protecting ecological integrity and important ecological services for all species including humans (Constanza et al. 1997; Daily 1997). The need to protect large areas to maintain ecological integrity, juxtaposed with the fact that most reserves are small and most landscapes are highly altered, has lead to landscape-based reserve design (Noss 1983; Harris 1984; Noss and Harris 1986; Noss 1987b; Noss and Cooperrider 1994; Harris et al. 199b6; Noss et al. 1996; Barrett and Barrett 1997; Soul and Terborgh 1999). The three regional landscape assessments and reserve design applications analyzed here incorporate landscape-based approaches. The intent of the Florida Ecological Network analysis was to identify the largest areas of natural and semi-natural land that could be incorporated into a functionally connected, statewide reserve network. The analysis indicates there are still large landscapes comprised of pinelands, swamps, hammocks, prairies, and rangelands that could be integrated into a reserve system with 245

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246 ecological conservation value greater than th e sum of its parts (Noss 1991; Harris et al. 1996a). Such a reserve network would ensure the future of the Florida black bear as a viable statewide metapopulation, provide good opportunities for expanding Florida panther range and significantly enhance its viability (Maehr et al. 2001a; Maehr et al. 2001b), and protect most of the biodiversity across the state. The Florida black bear habitat and lands cape linkage analysis confirmed a high degree of overlap between priority areas fo r this species and the Florida Ecological Network. The multiple logistic regression analysis indicated that the most important variables for determining bear habitat quality included landscape attributes such as patch size, forest density, large roadless areas (def ined using major highways), and density and proximity of intensive land uses. The least cost path (LCP) analysis for identifying landscape linkages for the Florida black bear was also based on landscape indices that identified pathways through the largest swaths of intact habitat. In turn, the cost surfaces used in the LCP analysis were influenced by landscape characteristics, where more fragmented landscapes resulted in greater differences in LCP results for various cost surfaces. The Florida black bear landscap e linkage analysis also confirmed the congruence between the Florida Ecological Network and the best opportunities for maintaining and restoring connectivity among the five large and several smaller bear populations across the state. However, the analysis also indicates that burgeoning development threatens many landscape linkages, especially in central Florida. Ecoregional planning for the two ecoregions encompassed by the Florida peninsula combined species (fine filter), natural community (coarse filter), and landscape approaches to identify the areas needed to conserve biodiversity (Groves et al. 2000;

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247 Groves et al. 2002). Though this process was largely driven by species and natural community occurrence data, landscape-based indices were used to help determine the potential viability of species and natural community occurrences. Landscape-scale habitat priorities for the Florida black bear and Florida panther (Cox et al. 1994; Kautz and Cox 2001) and the Florida Ecological Greenways Network were used to identify additional landscapes needed to conserve biodiversity in the two ecoregions. The ecoregional planning results matched well with the Florida Ecological Network, although some additional areas are included in the eco regional portfolios. The most important examples include the tropical hammocks and other upland habitat of the Florida Keys; pine rocklands (and hammocks) in Miami-Dade County; Flor ida scrub patches along the Lake Wales Ridge; and some coastal scrub, maritime hammock, and coastal strand along both coasts. Such areas have either been heavily impacted by human-induced habitat fragmentation or are naturally isolated (t hough even in these cases they are now threatened by human activity). These areas did not meet the intact landscape criteria used in the Florida Ecological Network; however, they are significant last chance refuges for biodiversity elements that are not well-represented in larger landscapes, especially for many rare plant species (Myers 1990). Primary components of reserve design in clude representation, habitat assessments for focal species, inclusion of special elem ents, and consideration of ecological and evolutionary processes (Noss and Coppe rrider 1994; Harris et al. 1996a; Noss 1996; Margules and Pressey 2000). All of these asp ects of reserve design are well covered by the three analyses collectively. Representation is addressed in the Florida Ecological Network through the inclusion of high priority natural communities, but ecoregional

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248 planning goes much further in ensuring representation of all natural communities and focal species. The Florida Ecological Network includes The Florida Fish and Wildlife Conservation Commissions (FWC) St rategic Habitat Conservation Area recommendations based on habita t and population analyses for wide-ranging and other focal species, and the black bear analysis provides a detailed asse ssment of all potential high quality habitat and landscape linkage oppor tunities statewide for the best potential umbrella species in Florida. The ecoregio nal planning analysis incorporates habitat assessments for many additional focal species. Special elements were incorporated through the inclusion of roadless areas and high quality natural communities, and ecoregional planning incorporated special feat ures such as caves, sinks, springs, aquatic preserves, and the occurrences of the highest quality natural communities. The Florida Ecological Network identifie d large, interconnected landscapes most likely to support functional ecological and evolutionary processes. The habitat and landscape linkages needed to conserve a viab le metapopulation of black bear may include enough area to ensure the maintenance and rest oration of functional la ndscapes. Finally, ecoregional planning identified landscapes likely to support intact natural community mosaics. Therefore, though the three regional landscape assessments and reserve design applications focus on particular elements of a reserve design process, together they represent all the key reserve design steps. The three approaches are clearly complementary, yet they are also not necessarily comprehensive. All of these approaches ha ve shortcomings that have less to do with procedural issues than just the outright co mplexity of reserve design. Conservation

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249 biology has been described as a triage, crisis science (Soul 1985; Meffe and Carroll 1997). Reserve designers will ne ver have all of the informa tion they would like, and yet there is a need to make decisions now as habitat loss and fragmentation accelerate. There are simply too many species and too much ecological complexity for us to have all the answers. Therefore we are forced to make decisions based on the best available information. And the definition of best available information is most frequently determined by available money and time. Nevertheless, it is important to point out where improvements can be made to enhance future re serve design iterations before it is finally too late. The methodology used to delineate the Florida Ecological Network had the advantage of being a relatively simple landscape-based approach focused on the identification of areas that are most likely to maintain important ecosystem attributes. However, the strength of the process and re sults may be very dependent on the quality of the available data. Habitat and viability asse ssments by the FWC (Cox et al. 1994; Kautz and Cox 2001) and identification of significant natural features by the Florida Natural Areas Inventory (1997) were important building blocks. Whether the results would have been similar with only basic land cover data and simple assessments of important landscape features such as roadless areas is debatable. The FWC Strategic Habitat Conservation Areas for species such as the Florida black bear helped select critical areas of semi-natural land uses (suc h as pine plantations) that likely would not have been identified using more basic information. Ther efore, the viability and habitat assessments and the identification of key natural areas likely significantly enhanced the representation of key areas for biodiversity within the Florida Ecological Network.

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250 The analysis of landscape linkages for the Florida black bear is primarily limited by the uncertainties in the development of cost surfaces and the ecological utility of the LCP function in ESRIs ArcInfo GRID and Spatial Analyst, though LCP analysis is a viable tool for assessing connectivity (Mee gan and Maehr 2002). LCP analysis has some advantages and flexibility as a methodology fo r identifying the best way to traverse landscapes to minimize cost. However, there are some limitations to its applicability for assessing landscape linkages or corridors to facilitate species movement. The limitation of using one-cell wide paths across long distan ces (over 100 km in the case of several of the landscape linkages) increases the probability that sub-optimal paths may be selected. Though cost surfaces can be modified to addre ss this issue, an algorithm that allows the designation of minimum allowable corridor wi dths would enhance corridor analysis. The LCP function selects paths based on the total accumulated cost across a landscape. However, most dispersing non-vol ant organisms experience landscapes in a much more limited fashion and are forced to make decisions based on how far they can see, or otherwise sense, what lays ahead (Beier 1995; Lima and Zollner 1996; Meegan and Maehr 2002). Though the LCP function may likely pick the best option from a topdown design perspective, a cell-spread func tion that assesses options cell-by-cell may provide opportunities to identify both best ov erall linkages and dead-ends or bottlenecks that present dispersal hazards. Finally, the LCP function is limited by the uncertainties of selecting and ranking input indices, though quantitative habitat m odels may provide a promising alternative to more subjective cost surfaces. Ecoregional planning is affected by its ambitious scope and the inadequacies of available data. The selection of hundreds of focal species incl uding many rare plants and

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251 invertebrates may greatly enhance the thoroughness of the reserve design process but it significantly increases the complexity of analyzing species and natural community viability and representation. Occurrence info rmation is not adequate for many species due to the incomplete surveys, outdated occurrence records, and the dearth of viability or quality rankings. Natural heritage occurrence data are critical for reserve design but suffer from a lack of information from many private lands and the difficulty and expense of maintaining and e nhancing existing records. In addition, there is not enough information on population sizes and key demogr aphic parameters to accomplish detailed viability assessments for most species. T hough ecoregional planning for the Florida Peninsula and Tropical Florida ecoregions is an important step in Florida biodiversity conservation planning, there is a need to increase the quality of species occurrence, population, and demographic info rmation and to develop less data-intensive methods to do viability and risk assessments for focal species. Another important issue is the assessment of ecological integrity or landscape viability. Phrases such as ecological integr ity and functional ecological processes have been used in the discussion of all of these analyses. Ecological integrity can be defined as the presence of all native ecological elements and the occurrence of all processes at appropriate rate s (Angermeier and Karr 1993; Harr is et al. 1996a; Pimentel et al. 2000). The key is the restoration and protection of landscapes with natural ecological, evolutionary, and biogeographi c processes (Angermeier and Karr 1993; Turner et al. 1995; Harris et al. 1996a). Though ecological integrity has become a driving force behind reserve design and regional conservation planning, a precise definition of its attributes and identification of areas with high ecological integrity or

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252 restoration potential remains difficult (Pime ntel et al. 2000). The landscape-based methods incorporated within these analyses may be adequate surroga tes for more detailed analyses of ecological integrity. The intricate spatial and ecological relati onships between uplands and wetlands in the southeastern coastal plain is a critical landscape property of the region (Harris and Kangas 1978; Harris 1988; Harris et al. 1996a). Fire and flooding are key ecological processes required for the maintenance of many of the regionss natural communities and focal species (Harris et al. 1996a). As indi cated in chapter 2, the Florida Ecological Network appears to well represent the availabl e juxtapositions between large uplands and wetlands across the state. The Florida Ecological Network also identifies available buffers around many of the states major ri vers and other important water bodies. Ecoregional planning identifie d landscapes with enough area to support viable natural communities that are fire dependent including sandhill, flatwoods, and dry prairie. However, as long as precise delineation of ecological integrity and functional ecological properties remains elusive, efforts to thoroughly identify landscapes with these characteristics will continue to be constrained. Incorporating landscapes with functional (or restorable) ecological processes is a key step in reserve design that needs to be addressed in more de tail in the future (Harris et al. 1996a; Magules and Pressey 2000; Poiani et al. 2000). Reserve design efforts must be itera tive because new data, new methods, new hardware, new software, and land use changes increase our capacity to improve assessments while requiring update s as land is lost to development (or restoration occurs) and new priorities are adopted. With these and other existing analyses and data, Florida

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253 has a sound reserve design foundation to guide land acquisition decisions and land use planning to maximize the protection of biodiversity as development continues in this high growth state. A next step may be to fo rmally integrate these and other recently completed or ongoing biodiversity assessments Related work includes the federal Gap Analysis for Florida, the Florida Natural Areas Inventorys new species habitat data created to help set priorities for the Florida Forever land acquisition program, the multispecies recovery planning for the U.S. Fish and Wildlife Service for all federally listed species in south Florida, and updates to the Florida Fish and Wildlife Conservation Commissions species viability and habitat assessments. Integration of efforts could include strengthening land cover based representation analysis for natural communities and detailed viability assessments for more species. More research is needed on ecological processes and landscapes that pr ovide opportunities to protect the minimum dynamic areas (Pickett and Thompson 1978) best capable of maintaining functional biotic and environmental inter actions (Harris et al. 1996a). As part of future improvements in reserv e design, the Florida Ecological Network will be periodically updated to reflect la nd use changes and to incorporate new information on areas of ecological significance The next step of the Florida black bear analysis is to expand quantitative habitat a ssessment methods and link such models to spatially explicit population m odels (Dunning et al. 1995; Carroll et al. 2001). Such information would enhance the identification of habitat protection priorities for this species. Ecoregional planning for the Flor ida peninsula provided a detailed assessment with enhancements that could not be incor porated in the earlier ecoregional assessments done in northern Florida. The ecoregional approach taken in the peninsula could be

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254 enhanced with improved data a nd applied to the entire state to provide more consistent and detailed information for identifying statewide priorities. Land Conservation Policy Issues and Recommendations Land Protection Florida has aggressively pursued the protection of ecologically significant land through fee simple and less-than-fee ac quisition. Since 1990, the states two land acquisition programs, Preservation 2000 and Flor ida Forever, have raised approximately $300 million per year. Additional money for la nd acquisition comes from Floridas five Water Management Districts, and federal and county programs. Approximately 3.7 million ha and 26 percent of the land area is currently within conservation lands including federal, state, regional, local, and private preserves. However, based on the Florida Ecological Network, high quality black bear hab itat, and the ecoregional site portfolios, there are approximately 5 million ha of private land important for biodiversity conservation. Therefore, the primary policy issue is the continuation and enhancement of the various land acquisition programs needed to protect Floridas biodiversity and natural heritage. Florida voters recently passed (i n 1998) a constitutional amendment allowing continued funding of aggressi ve conservation land acquisiti on (Florida Department of State 2002). Though arguably honored by the Florida legislature through the passage of the Florida Forever program, 60% of the 300 million dollar a year allotment can be spent on urban parks, water supply projects, and developing recreational uses (Florida Department of Environmenta l Protection 2002), which greatly reduces the available resources for protecting biodiversity.

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255 The Florida legislature needs to honor the commitment of Floridians to protect the states natural resources. A first step coul d be the reapportionment of the existing Florida Forever allotments to focus primarily on protec ting lands important for biodiversity. The next step is to conduct more specific analyses of the cost and timeframe necessary to protect the remaining lands needed to effectiv ely conserve Floridas biodiversity. Such an assessment would provide the opportunity to plan funding levels and money sources that ensure enough funds will be available in a timely manner to protect most identified lands. Good conservation planning also require s prioritization a nd predictions of potential conflicts with conser vation goals. Reserve designs are the essential foundation for this process, but the fate of private (a nd, in some cases, even public) lands identified for inclusions in reserves will determine success or failure of conservation efforts. With large areas of private land identified in reserve design assessments, prioritization is essential to identify the lands that should be targeted for conservation action first. Such efforts have been recently completed to identify the critical landscape linkages within the Florida Ecological Network (Hoctor et al. 2002), and prioritizati on of the Peninsula Florida and Tropical Florida ecoregional portfolios by The Nature Conservancy is ongoing. Prioritization must also take into account the probability of development. Florida currently loses approximately 60,000 ha of rural land each year (Kautz 1993; Reynolds 1999; Florida Division of Forestry 200 1), and efforts to identify the lands most threatened by development are necessary for proactive planning. Based on location and economic activity, some areas are more likely to be developed, such as those closer to existing ur ban areas. Such information was taken into

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256 account to develop a growth potential prediction model for Florida (Teisinger 2002). Growth prediction models are important tools for prioritizin g lands for protection. Lands with very high significance for biodiversit y conservation and very high development pressure should usually be the highest protecti on priorities. Prioritization of the Florida Ecological Network combined both ecological prioritization and predicted development pressure to identify the most critical lands cape linkages (Hoctor et al. 2002). The model by Teisinger (2002) is considered to be a prototype that can be enhanced with new analytical methods and data. Tracking of new development trends such as the proposed massive development in the Florida panhandle by the St. Joe Company is also necessary. Funding of such enhancements to furthe r develop the model for use in Florida conservation planning should also be a high priority. Land Management Though Florida has made significant pr ogress in protecting key conservation lands over the last several decades, appropriate management of such lands remains a critical issue. A zoning approach to c onservation land management is an important aspect of landscape-based reserve desi gn (Harris 1984; Noss and Harris 1986; Schonewald-Cox 1988; Scott et al. 1993; No ss and Cooperrider 1994; Harris et al. 1996b; Soul and Terborgh 1999). The zoning appro ach recognizes the importance of protecting some lands as strict ecological reserves wh ere biodiversity conservation is paramount. However, other conservation lands that accommodate a variety of uses compatible with conservation objectives also have an important role. Ideally, strictly protected reserves, or core areas, should be surrounded by buffer zones that protect the cores from intensive land uses, provide additional ha bitat for wide-ranging species and species tolerant of

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257 various human uses, or mainta in connectivity between core areas (Harris 1984; Noss and Harris 1986; Noss et al. 1996). The protection level of existing conservati on lands has been included as part of the federal GAP Analysis being conducted in each state (Scott et al. 1993; Jennings 2000), since most conservation land is not dedi cated to strict ecol ogical protection or predominantly managed for native biodiversity. Scott et al. (1993) defined core areas as any area that is maintained in its natural state and within which natural disturbance events are either allowed to proceed w ithout interference or are mimicked through management. Many conservation areas, in cluding national and state forests, many national wildlife refuges, and state wildlife management areas are managed primarily for multiple uses that can conflict with biodive rsity conservation. GAP Analysis protocol ranks conservation areas based on the compatibility of their overall management with the definition of core areas (Scott et al. 1993). The Florida Natural Areas Inventory ha s ranked existing conservation lands in Florida based on the GAP classification. Protec tion Status 1 lands (national parks, state parks and preserves, The Nature Conservancy preserves, etc.), which are most likely to meet the standards of core areas, make up less than 17% of existing conservation lands (and 4% of all land) in Florida. However, most of this land is within Everglades National Park. Only 6% of existing conservation lands (1.4% of all la nd) are in Protection Status 1 when Everglades National Park is excluded. Noss (1992b) recommended that all lands cape types, natural communities, and environmental gradients should be represente d within core reserves. Core reserves provide protection to species and ecological processes that are most sensitive to human

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258 activities including land uses typically f ound on multiple use conservation areas (Noss and Cooperrider 1994). Core reserves also serve as baselines or research controls for the ecological compatibility of land management activities on multiple use conservation lands (Noss and Cooperrider 1994; Soul and Te rborgh 1999). GAP Analysis has yet to be completed for Florida, and therefore no comprehensive attempt has been made to evaluate the representation of species, natural communities, or other biodiversity components within Protection Status 1 cons ervation lands. However, based on Florida Fish and Wildlife Conservation Commission la ndcover data, approxima tely 6% of the scrub remaining in Florida and 0.7% of sandhill are within Protection Status 1 conservation lands. Therefore, representation of key natural communities within core reserves is likely inadequate. Instead of working to narrow the gap in core reserves on Florida conservation lands, state policy emphasizes multiple use of state-owned lands. In 1999, legislation (Florida Statute 253.034) was passed to make multiple uses of state conservation lands the priority for land managers. The statute directs state land management agencies to develop land management plans for all parcels larger than 400 ha, and such plans are required to "contain an analysis of the multiple-use potential of the parcel, which analysis shall include the potential of the parcel to generate revenues . ." Although strictly protected areas can be further protected thro ugh the establishment of buffer zones where it can be demonstrated that areas "require sp ecial protection or have special management needs," such buffer zones can be no more than 50% of the total area of the conservation parcel. "Single use" conservation lands such as state parks may be exempt from these multiple use requirements, otherwise these provisions affect millions of acres of state

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259 forests, wildlife management areas, and Water Management District lands. The statute also allows for additional uses of public c onservation lands when they are "consistent with the public interest" including "water resource development projects, water supply development projects, stormwater management projects, linear facilities, and sustainable agriculture and forestry." The bias of state law towards multiple us e of public conservation land is coupled with increasing pressure on these lands by a rapidly growing human population. An increasing population represents two problems. Population growth results in the loss of natural and rural lands while it also increases the demand for access and multiple use of remaining lands. Conservation land managers are faced with impacts both from increasing habitat fragmentation and external threats outside their lands (SchonewaldCox 1988; Freemuth 1991), while impacts from huma n use of conservation lands is also increasing (Cole 1993; Noss and Cooperride r 1994). Demand for more intensive activities on public conservation lands is also increasing, including demands for more access for all terrain vehicles, airboats, and development of in tensive recreational facilities including ballparks, recreational vehicle parks, etc. Disposal of state lands is another threat to biodiversity conservation. Florida Statute 253.034 gives the state (represented by the state cabinet and the Governor) the authority to dispose of state conservation lands for a variety of purposes including "public schools, public libraries, fire or law enforcem ent substations, and governmental, judicial, or recreational centers." Requests for the disposal of public conservation land can "be made by any public or private entity or pers on." Demand for public land disposal is high, with just the Southwest Florida Water Management District receiving requests for over

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260 1,200 ha in the last three years (Mary Barnwell, Southwest Florida Water Management District, personal communication). In one recent case, over 100 acres of scrub in Jonathan Dickinson State Park were disposed to develop a stormwater retention project to alleviate flooding in an adjacent subdivision (Hartnett and Ash 2002). Several steps should be taken to ensu re that biodiversity conservation is appropriately considered in management decisions on st ate-owned lands. One such alteration would be the requirement for comp rehensive land manageme nt planning for all public conservation lands collectively. Thou gh land management plans are required for all state-owned conservation lands, there is no requirement for coordination of land management plans at a statewide level. A comprehensive assessment of how biodiversity is represented within public conservation lands could be used to guide efforts to determine priorities for designating core reserves on state lands. This statewide analysis could then be used as the overarching guide for developing responsible land management plans for individual parcels th at contribute to overall biodiversity conservation needs. Core area additions need to be assessed at the statewide scale so that all biodiversity components are well represented within strictly protected areas and to ensure that large sites are incorporated in core reserves to adequately represent landscape-level processes (Noss 1992). Another solution to the problem of increa sed pressure for recreational uses would be to offer incentives to the private sector fo r offering services that conservation lands are now expected to provide (Mary Barnwell, S outhwest Florida Water Management District, personal communication). Such uses could be located adjacent to conservation lands so

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261 that they would both reduce the intensity of land uses on conservation lands while also providing buffers from even more intensive land uses. The disposal of state conservation lands for development should be curtailed. Current procedures require a conclusion from the Acquisition a nd Restoration Council (ARC) on whether "resource values" would be harmed through a requested disposal. The ARC includes both agency representatives and appointed members from the public. Though appointed members are supposed to ha ve some natural reso urce background, this requirement is not stringent enough to guar antee that biodiversity conservation objectives are weighed objectively. Instead, a panel of scientists, with required degrees in conservation biology, wildlife ecology, or la ndscape ecology should be appointed to review such proposals. Proposals that do not receive the recommendation of such a panel should not proceed. Growth Management Given the pace of human population growth and intensive development in Florida, efforts beyond land acquisition and management of existing conservation lands are required to protect biodiversity adequately. Growth management designed to limit the footprint and secondary impac ts of development is also essential. In 1985, Florida enacted legislation on growth management th at requires all local governments to create comprehensive plans to guide development a nd adequate infrastructure (such as road capacity) before development is allowed. These legal requirements have largely failed (Nicolas and Steiner 2000). Co llectively, all of the future land use plans adopted by local governments (including counties and cities) would allow anywhere from 50 to 90 million

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262 people, which is approximately 3 to 6 times larger than the current population (Nicolas and Steiner 2000). Effective growth management woul d direct development away from environmentally sensitive areas whenever po ssible (Soul 1991). Current comprehensive plans appear to accommodate growth and not pr otection of critical natural resources. The protection of areas important for biodiversity, fiber production, and agriculture should be key components of comprehensive plans. In addition, good comprehensive plans would limit sprawling development, which would give land acquisition efforts more time to protect lands critical for biodiversity conservation. Finally good planning is also needed to contribute to the core area-buffer m odel of reserve design, where intensive development is separated from bi odiversity reserves by rural lands including silviculture, agriculture, and other uses more compatible with conservation objectives (Harris 1984; Noss and Harris 1986; Soul 1991). Transportation Planning Highway and other linear transportation projects (such as proposed high-speed train routes) are a very important threat to biodiversity conservation (Trombulak and Frissell 2000). Florida has an existing network of highways that already fragments and otherwise impacts conservation lands and othe r areas of ecological significance across the state. The need to retrofit existing highways to facilitate the movement of focal species and to reduce roadkills has already been discussed. However, the Florida Department of Transportation ha s adopted a Florida Intrastate Highway System plan that will increase ecological impacts (Florida De partment of Transportation 2001). A major component of the plan is to widen most eastwest state highways from two lanes to four

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263 or six lanes. In 2002, the Florida Legislature passed legislation reducing the requirements needed to justify the construction of new toll roads and broadened the powers of the Florida Turnpike Authority. Overall, many new highways that would severely impact biodiversity c onservation are in different st ages of planning. Projects being considered include the following: A highway along the Gulf Coast from Tampa to the Georgia border that would cut through large areas of ecological significance A new interstate highway from Alabama to Panama City that would impact landscape linkages between the Apalachicola Nationa l Forest and Eglin Air Force Base A beltway around coastal US 98 in the panhandle from Apalachicola to Panama City An extension of the Florida Turnpike from its current northern terminus northwest to the Big Bend A beltway around northern Orlando through the environmentally-sensitive Wekiva River basin A toll road from Daytona Beach to Orlando that would sever the most important landscape linkage connecting north and south Florida Another beltway encircling Jacksonville that could impact conservation lands surrounding the city The proposal to build a toll road from Jacksonville to Tampa. Now that good information about lands important for biodiversity exists, the intrastate highway plan and the various pr oposed toll roads should be revisited in a comprehensive planning process. Alterations in the plan that would avoid biodiversity impacts while meeting transportation needs s hould be possible now that more complete information exists. Furthermore, a statewide assessment of road a nd other transportation projects would enhance efforts to minimize and mitigate impacts that may be unavoidable. Currently, such efforts are limited to individual projects where politics,

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264 road design constraints, and limited budgets are frequently used to avoid spending enough money and time to adequately minimize and mitigate ecological impacts. System-wide planning might also ensure th at an appropriate budget is developed to minimize and mitigate impacts. The Florida Department of Transportation planned budget for infrastructure improvements between 2001-2020 is $108 billion (Florida Department of Transportation 2001). Just 5% of that budget could be used to build bridge spans, widen bridges, build wildlife underpasses and overpasse s, and protect large areas of habitat to minimize and mitigate impacts to ensure that biodiversity is protected while transportation capacity is increased. Ecological Linkages across State Borders This analysis has focused exclusively on biodiversity conservation in Florida, even though the ecological processes responsible for shaping and maintaining biodiversity do not stop at the state boundary. Li nkages with key ecological features in Georgia include the Pinhook Swamp--Oke fenokee Swamp landscape, and major tributaries of the Suwannee and the Ochloc konee Rivers. The Apalachicola River's headwaters cover much of western Georgia and eastern Alabama. Rivers that originate in Alabama and run through the Florida panha ndle to the Gulf of Mexico include the Choctawhatchee, Yellow, Es cambia, and Perdido, and th e Conecuh National Forest-Blackwater River State Forest complex along the Florida-Alabama border encompasses a broad interstate pineland landscape. The future of the Florida panther will be dependent on the re-establishment of at least one add itional population that could incorporate lands in northern Florida, Georgia, and Alabama (Maehr et al. 2002a). Florida black bear populations range into both Georgia and Alab ama. Furthermore, climate change will

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265 require consideration of landscape linkages acro ss these states to allow biota to respond (Peters and Darling 1985; Hunter et al. 1988; Graham 1988; Hunter 1991; Harris and Cropper 1992; Peters and Lovejoy 1992). The Southeastern Ecological Framework, which identified significant landscapes th roughout the southeastern United States, provides a starting point for assessing the importance of the ecological connections between Florida and lands to the north (Hoctor et al. 2002). South Florida's tropical ecological affinitie s should also not be ignored (Harris et al. 2001). Sweepstakes dispersal of tropical bi ota across the Gulfstream has had a strong influence on the ecology of the Tropical Florid a ecoregion, which is part of the Antillean Biotic Province (Harris and Cropper 1992; Ha rris et al. 2001). Restoration of the tropically influenced forests of south Flor ida should receive more attention so that functional tropical affinities can continue to evolve, and so the future of the Florida panther and other characteristic fauna will be more secure (Harris et al. 2001). Protecting Biodiversity and Ecosystem Services Perhaps the most important research, planning, and policy issue is linking biodiversity, ecological integrity, and ecosyst em services into an integrated whole that clarifies the importance of maintaining ecological infrastructure. Ecosystem or ecological services can be defined as the processes through which natural ecosystems sustain and fulfill human needs (Daily 1997) including functions such as water quality maintenance and enhancement, drinking water, storm water management, flood control, particulate matter removal and carbon sequestration, as we ll as food and shelter for native species (Noss 1996; Costanza 1997; Daily 1997; Daily 2000). The term green infrastructure has been recently proposed as an appropriate umbre lla for biodiversity

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266 conservation and ecological services, and can be defined as the natural support system that maintains native species and natural ecological services, sustains air and water resources and contributes to the health and quality of life for human communities (Benedict 2000). A merging of the rewilding concept of The Wildlands Project's reserve design strategy (Soul and Noss 1998), which emphasizes the restoration and protection of large areas devoted primarily to biodiversity conservation (Soul and Terborgh 1999), and more anthropocentric approaches that focus on ecological services (Daily 1997; Benedict 2000; Benedict and McMahon 2001) may be critical for developing the education, public opinion, and political will neces sary to overcome the current obstacles to responsible conservation planning. Further research in Florida should include the development of a statewide conservation plan that integrates existing regional landscape assessments and reserve design with additional analyses to identify all areas needed to sustain the state's biodiversity a nd ecosystem services. The protection and restora tion of landscapes with functional ecological and evolutionary processes is the mandate for conservation in the 21st century. Thinking big is nothing new since visionaries such as Wright (Wright et al. 1933; Wright and Thompson 1934), Shelford (1933; 1936), and Leopold (1949) understood the necessary scope of conservation efforts well before the popularization of island biogeography theory, the growth of conservation biology and landscape ecology, and the development of reserve design theory. However, all re search on biodiversity conservation indicates the same thing: large, functionally integrated reserve networks are required to effectively conserve biodiversity. Reserve design regional conservation planning, and land management must be conducted at sufficiently large scales to promote compatibility

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267 between land uses and protect natural resource s. Based on landscape ecology principles, Forman (1995, p. 452) articulated the ethics of isolation:" Simply stated, in land use decisions and acti ons, it is unethical to evaluate an area in isolation from its surrounding or from its development over time. Ethics impel us to consider an area in its broadest spatial and tempor al perspectives. Only a comprehensive approach applied at a regional landscape scale will ensure the protection of biodiversity, ecosystem services, and other ecological and aesthetic values that natural systems provide. To accomplish this, the challenge remains to enhance regional landscape assessments to make reserv e design efforts more efficient and more comprehensive. Furthermore, the challe nge to make biodiversity and landscape conservation more tangible for the human populat ion that now dominates this planet also remains. While Leopold's land ethic (1949) and Forman's ethics of isolation (1995) provide a moral foundation for the impera tives of landscape-based conservation, the overwhelming economic value of functional ecosystems and bi osphere is an essential consideration (Costanza et al. 1997). Concepts such as green infrastructure (Benedict 2000) may be an important tool for fostering a movement to ensure the future integrity of the biosphere and the "ecological theater and the evolutionary play" (Hutchinson 1965; Harris et al. 1996a) responsible for creating a nd maintaining the biological diversity we are blessed to still have.

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APPENDIX A DATA FOR FLORIDA BLACK BEAR LANDSCAPE REGRESSION ANALYSIS This appendix contains all variables used as input variables in the multiple logistic regression model. After each numbered entry the there is a brief description of the variable, then the name of the grid, and then the data fields in the grid used in the regression analysis. For instance, under A1 all cells within the study were separated into either non-habitat, secondary, or primary habitat. The name of the data set was bhab_37p12arc, and the field used was value, which means that the nominal values representing non-habitat, secondary, or primary. For other variables the fields used in the analysis include log or count. Log represents when original values were log transformed and count is the count of cells within a particular class, such as a particular patch. Habitat Data bear habitat (non-habitat, secondary, and primary); bhab_37p12arc; value bear habitat (preference classes: none, low medium, high); bhab_prefrcls; value bear habitat patch size; bhab_37p12_rg; log, count22 bear habitat patch size ranked (values 1-9); bhab_37p12_sf; value distance from bear habitat; bhab_37p12adi; log, value bear habitat density (11x11 focalsum of bhab_37p12arc; values 0-242); bhab_37p12sum; value bear habitat patch size and distance combined; (9X9 focalmax of bhab_37p12_rg.count22); bhab_rgbuf; log, value Protected Bear Habitat protected bear habitat (10,000 acres or larger); bhabclan10k; value protected bear habitat (50,000 acres or larger); bhabclan50kb; value protected bear habitat patch size; bhabclan_reg; log, count2 268

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269 distance from protected bear habitat ranked (50,000 acres or larger); values 1, 3, 7, 10); bhabclan_disr; value distance from protected bear habitat (any patch size); bhabclan_dis; log, value distance from protected bear habitat (50,000 acres or larger); bhabclan50k_d; log, value distance from protected bear habitat (10,000 acres or larger); bhabclan10kdi; log, value within conservation lands (regardless of bear habitat); clane_all1; value Habitat Diversity bear habitat diversity (within 1 km neighborhood; 5 classes); habdiv1kmnd; value Roadless Areas roadless areas (all roads) ranked based on size and percent habitat (classes 1-10); rdless_all; rank roadless areas (all roads) (broken into lumped into 3 size classes); rdless_all_sr; value roadless areas excluding class 5 roads (lumped into 3 size classes); rdless_n5_scr; value roadless areas excluding class 4 and 5 roads (lumped into 3 size classes); rdless_n45_sr; value roadless areas excluding class 3, 4, and 5 roads (lumped into 3 size classes); rdless_345_sr; value roadless areas (using DOT major roads) (lumped into 3 size classes); rdless_dot_sr roadless areas (using roads with adt of 2500 or greater and all roads with black bear roadkills) (lumped into 3 size classes); rdless_25b_sr; value roadless areas (using roads with adt of 5000 or greater and all roads with black bear roadkills) (lumped into 3 size classes); rdless_50b_sr; value roadless areas (using the Florida Intrastate Highway System roads) (lumped into 3 size classes); rdless_fln_sr; value roadless areas (all roads); rdless_allrg; log, count2 roadless area excluding class 5 roads; rdless_n5; log, count2 roadless areas excluding class 4 and 5 roads; rdless_n45; log, count2 roadless areas excluding class 3, 4, and 5 roads; rdless_n345; log, count2 roadless areas using DOT major roads; rdless_dotm; log, count2 roadless areas using roads with adt of 2500 or greater and all roads with black bear roadkills; rdless_2500bk; log, count2 roadless areas using roads with adt of 5000 or greater and all roads with black bear roadkills; rdless_5000bk; log, count2 roadless areas using the Florida Intrastate Highway System roads; rdless_flnhpn; rdless_flnhpn; log, count2

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270 Distance from Major Roads distance from roads with adt of 2500 or greater and all roads with black bear roadkills (ranked into 10 classes); road2500dr; value distance from DOT major roads; roadallmaj1; log, value distance from roads with adt of 2500 or greater and all roads with black bear roadkills; road2500disi; log, value distance from roads with adt of 5000 or greater and all roads with black bear roadkills; road5000disi; log, value distance from Florida Intrastate Highway System roads; roadflndisi; log, value Road Density road density using all roads (ranked into 10 classes); rddens_allr1; value road density using all roads; rddens_all; value (floating point) road density excluding class 5 roads; rddens_n5; value (floating point) road density excluding class 4 and 5 roads; rddens_n45; value (floating point) road density excluding class 3, 4, and 5 roads; rddens_n345; value (floating point) weighted road density using all roads; rddens_wall; value (floating point) Land Use Intensity land use intensity split into 4 categories; fl_cat123a; value land use neighborhood intensity (focal sum using fl_cat123a); luse_intsum; value land use intensity split into 6 categories; luse_intv2a; value land use neighborhood intensity (focal sum using luse_intv2a); luse_intv2sum; value land use types split into four categories; lusecata; value land use types neighborhood dominance; lusecat_dom; value distance from category 3 land use 100 acres or larger ranked (10 classes); cat3_100acr; value distance from category 3 land use using all patch sizes; cat3_int; log, value distance from category 3 land use 10 acres or larger; cat3_10acint; log, value distance from category 3 land use 100 acres or larger; cat3_100acint; log, value Forest forest (combination of GFC hab and WMD land use); forest_all; value forest patches 100 acres or larger; forest_100ac; value forest density (11x11 focal sum); forest_dens; value, percent forest density (35x35 focal sum); forest_dens_m; value, percent forest density (3x3 focal sum); forest_dens_d; value; percent forest patch size; forest_reg; log, count2 distance from forest; forest_disti; log, value distance from forest patches 100 acres or larger; forest_100di; log, value

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271 Patch size and distance from forest combined (9X9 focalmax of forest_reg.count2); forest_rgbuf; log, value

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APPENDIX B COMPARISON OF MAJOR COST SURFACE VARIATIONS Although some of the differences between the various cost surface types were discussed in the sections above, comparisons between specific sets of cost surfaces more clearly elucidates the differences in results obtained when using different approaches to create cost surfaces. The following results indicate the differences between selected pairs of cost surfaces using examples from the results for each of the four major connections described above. Cost Surface 1 and Cost Surface 2: The Influence of Adding Major Roads and Large Water Bodies The only difference between Cost Surface 1 and Cost Surface 2 is that large water bodies (including major rivers) and major roads were added to Cost Surface 1 with values of 150 and 200. The rationale for specifically including large water bodies and major roads with very low suitability was to avoid paths that crossed such potential movement filters. The two cost surfaces resulted in similar LCPs (Figure B-1). The largest divergence between the two paths was an approximately 3 km separation in the Econlockhatchee basin east of Orlando. Other differences occurred along the middle St. Johns River (Figure B-2). Minor differences occurred between the Ocala National Forest-Osceola National Forest and the Apalachicola National Forest-Eglin Air Force Base linkages. In all cases the differences were related to the avoidance of water bodies. The roads used in Cost Surface 1 were limited to major interstate and intrastate highways 272

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273 Figure B-1. Comparison between Cost Surface 1 and Cost Surface 2. Almost no differences between Cost Surface 1 (with Intrastate Highways and large water bodies explicitly included) and Cost Surface 2 (same as Cost Surface 1 without adding the highways and water bodies) are evident at a statewide scale. Only minor differences occurred in three of the four linkages with the most significant differences occurring near Orlando around large water bodies.

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274 Figure B-2. Comparison of Cost Surface 1 and Cost Surface 2 in central Florida. The minor differences between the LCPs for Cost Surface 1 and Cost Surface 2 can be seen within the Upper Econ Mosaic and the middle St. Johns River.

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275 that are more likely to have vehicle traffic that might hinder bear movement (Brody and Pelton 1989). Most of these highways are major north-south and east-west routes that must be crossed by bears using linkages betw een major populations. If more roads had been assigned a high cost, it is likely that there may have been larger differences in the results though the rationale for including sma ller, less traveled roads would need to be elucidated. Furthermore, road-based SUAs (roadless areas, distance from major roads, and road density) were included as a compone nt in both cost surfaces, and these indices may make adding large highways redundant. Cost Surface 1 and Cost Surfa ce 3: Testing the Influence of Changing the Range of Cost Surface Values Cost Surface 1 and 3 had the same set of input indices and also included large water bodies and major roads. The difference was that the eleven input indices were added together differently. In Cost Surface 1 the eleven indices were added together and then 10 was subtracted to create a value ra nge of 1-100 before water bodies and major roads were added. In Cost Surface 3, all el even indices were multiplied by the same weighting or transformation factor that resulted in a combined index or MUA with a value range of 1-10. Then large water bodies and major roads were given values of 15 and 20 respectively. These differences resulted in some divergence between LCPs for the two cost surfaces for each of the major connections (Figure B-3). The most apparent differences occurred between Osceola and Apalachicola Na tional Forests. Cost Surface 1 followed the Suwannee River longer before diverging west through San Pedro Bay and then also swung further south through the Aucilla Wildlife Management Area. The LCP function always attempts to minimize distance to reduce the number of cells included within the

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276 Figure B-3. Comparison between Cost Surface 1 and Cost Surface 3. Minor differences existed between the paths for Cost Surface 1 and Cost Surface 3, with the most evident divergences occurring between Osceola National Forest and Apalachicola National Forest. For each of the 4 major linkages, the LCP for Cost Surface 1 was longer than that for Cost Surface 3, which is consistent with the hypothesis that cost surfaces with a larger range in values will be more likely to maximize the avoidance of low suitability cells versus minimizing the total path length.

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277 path, and a cost surface with uniform valu es would result in a straight-line path. Therefore the greater length of the path fo r Cost Surface 1 (215 kilometers versus 198 kilometers for Cost Surface 3) is in accordance with the hypothesis that as the value range of a cost surface increases, the balance between minimizing path length and avoiding high cost cells shifts to favor pa ths that maximize the inclusion of highly suitable areas. The LCPs were consistently longer for Cost Surface 1 than Cost Surface 3 for the three other major linkages as we ll, though the differences were minor. Cost Surface 3 versus Cost Surface 4: Testing the Influence of Differential Weighting of Input Indices (SUAs) Cost Surface 3 and 4 were constructed using the same 11 indices and both had a range of values from 1-10 plus large water bodies and major roads included with values of 15 and 20 respectively. However, in Cost Surface 4 the 11 indices were weighted differentially versus the equal weighting used in Cost Surface 3. Indices given more weight in Cost Surface 4 included land cover id entified as primary bear habitat, potential habitat patch size, and distance from large urban land uses. The differences in the results were fairly significant (Figure B-4). In particular, the difference between the two paths for the Big Cypress-Ocala National Forest linkage was most illustrative. In the Kissimmee River basin the two LCPs selected the two different major alternatives follo wed by all of the LCPs discussed in the previous section. The LCP for Cost Surface 4 followed what is most likely the best alternative for crossing through potential bottlenecks including the Florida Turnpike. Weighting of input variables should be c onsidered when creating cost surfaces. However, the basis, or lack of a basis, for weighting variables can be an important obstacle. In this example, evidence from the literature on black bear, examination of

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278 Figure B-4. Comparison between Cost Surface 3 and Cost Surface 4. The differential weighting of input variables in Cost Surface 4 versus the equal weighting used in Cost Surface 3 resulted in some significant differences in LCPs. The most significant difference in paths occurred in the Kissimmee River basin, where the path for Cost Surface 4 tended to follow the likely more suitable alternative for crossing the basin especially along the Florida Turnpike.

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279 some basic graphical relationships between be ar occurrence data and the eleven input variables, and expert opinion we re all used to create the weighting system employed in creating Cost Surface 4. However, the weights used can only be considered a qualitative assessment of the relative significance of the various indices, and no quantitative relationship regarding the importance of each variable for determining bear habitat quality or suitability for facilitating connectivity has been established. Cost Surface 5 versus Cost Surface 6: Te sting the Performan ce of Simplified Surfaces and the Influence of Habitat Patch Size These two cost surfaces were simplified to be based primarily of forest cover as well as other landcover and land use types. The only difference between the two surfaces is that Cost Surface 5 gives all forest cover the same value whereas forest cover is ranked based on patch size (with bigger patches receiving higher suitabilities) in Cost Surface 6. There was a high degree of variation in the LCP results for these two cost surface variations (Figure B-5). For both the Big Cy press-Ocala National Fo rest linkage and the Apalachicola National Forest-Eglin Air For ce Bases linkage, the two paths took two of the major route alternatives followed by the other cost surface paths. Overall, these results were similar to the other the cost surfaces used, though the difference between these forest-based surfaces and most other cost surfaces north of Big Cypress Preserve was discussed in the previ ous section. This suggests that simplified surfaces well below the complexity of Cost Surfaces 1-4 may be a viable alternative for using LCP analysis to assess corridors and la ndscape linkages. However, the significant differences between Cost Surface 5 and Cost Surface 6 also indicate that landscape variables such as patch size can affect LCP re sults. Clearly forest patch size or habitat

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280 Figure B-5. Comparison between Cost Surface 5 and Cost Surface 6. Cost surfaces based on forest cover and other landcover and landuse variable produced similar results to the other cost surfaces used in this study. However, Cost Surface 6, which included forest patch size as a component, resulted in LCPs that were significantly different from paths for Cost Surface 5, where all forest cover received the same value.

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281 patch size is relevant to black bear habitat quality and the function of corridors and landscape linkages, so such variables should be incorporated when feasible. Cost Surfaces 7, 8, and 9: Testing th e Performance of Simplified Surfaces Cost Surfaces 7-9 all used a different subset of the original indices used to create Cost Surfaces 1-4. Cost Surfaces 7-9 also represented simplifications using less input variables. Cost Surface 7 included the bear habitat patch size index and then other landcover and landuse types. Cost Surface 8 combined the bear habitat patch size, distance from intensive development, and the distance from major roads indices, and Cost Surface 9 included just the habitat patch size and distance from intensive development indices. All three cost surfaces resulted in LCPs that followed all the same major alternatives for all four potential landscape linkages (Figure B-6). The LCPs for Cost Surfaces 8 and 9 avoided some areas closer to intensive development than the path for Cost Surface 7. The LCPs for Cost Surface 8 tended to vary more from those for Cost Surface 7 and Cost Surface 9 apparently to avoid areas near major roads. Overall, these alternatives appear to provide feasible alternatives to more complicated cost surfaces. They incorporate key factors that should be considered when identifying potential landscape linkages: larger intact blocks of ha bitat, avoidance of intensive land uses, and avoidance of major roads and appear to provide results equal or better than more complex cost surfaces. Cost Surfaces 3 and 4 versus Cost Surfa ces 10 and 11: Testing the Influence of Drastically Changing the Ra nge of Cost Surface Values Cost Surfaces 10 and 11 were the same as Coast Surfaces 3 and 4 except the range of values were expanded using an exponentia l function that converted values from 1-20

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282 Figure B-6. Comparison of Cost Surfaces 7, 8, and 9. Cost Surface 7, Cost Surface 8, and Cost Surface 9 incorporated the bear habitat patch size index, bear habitat patch size-distance from intensive development-distance from major roads, and bear habitat patch size-distance from intensive development respectively. The LCPs followed the same major alternatives for all four potential landscape linkages and appear to provide a feasible alternative to more complex cost surfaces.

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283 to 3-22,026. This is a similar comparison to that between Cost Surface 1 and 3 though the change in range was much more substantial in this case. As expected, the LCPs for Cost Surfaces 10 and 11 are consistently longer than the paths for Cost Surfaces 3 and 4 for all of the four major linkages (Figure B-7). The greater influence of avoiding very low suitability areas in the Cost Surfaces 10 and 11 can also be seen by the much more circuitous paths. The difference in value range also led to some major differences in selected route alternatives for the Big Cypress-Ocala National Forest and Osceola National Forest-Apalachicola National Forest linkages. Finally, though there were some differences in the LCP results for Cost Surfaces 3 and 4, Cost Surfaces 10 and 11 resulted in the same selected paths. This suggests that the influence of giving areas of low suitability extremely high costs in Cost Surfaces 10 and 11 outweighed potential influence of the differen ce in weighting schemes used to create Cost Surfaces 3 and 4. Cost Surfaces 10 and 11 versus Cost Surfa ces 12 and 13: Testing the Effect of Adding Major Roads and Large Water Bodies to Expanded Cost Surfaces Cost Surfaces 12 and 13 differ from Cost Surfaces 10 and 11 by the addition of major roads and large water bodies to the highest and next highest cost levels respectively. The resulting LCPs were significantly different for 3 of the 4 major linkages (Figure B-8). However, as with Cost Surfaces 10 and 11, Cost Surfaces 12 and 13 are the same despite the fact that they represent the unweighted and weighted combinations of the 11 input indi ces used in Cost Surfaces 1-4. These differences contrast sharply with those between Cost Surface 1 and 2 described above, which also di ffered only in the inclusion of major roads and large water bodies. These differences can likel y be attributed to the much greater cost given to major

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284 Figure B-7. Comparison of Cost Surface 10 and Cost Surface 11. Cost Surfaces 10 and 11 were created by transforming Cost Surfaces 3 and 4 using an exponential function resulting in a range of values from 3 to 22,026. As expected the resulting LCPs were longer than those for Cost Surfaces 3 and 4 but also followed different route alternatives for two of the four major linkages.

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285 Figure B-8. Comparison of Coast Surfaces 10, 11, 12, and 13. Adding major roads and large water bodies to Cost Surfaces 12 and 13 resulted in significant changes in routes followed versus the paths for Cost Surfaces 10 and 11. Major roads and large water bodies were assigned very high costs (22,026 and 8103 respectively) and the changes in features assigned very high costs, which likely accounts for the significant difference in results versus the minor differences found when comparing Cost Surface 1 and 2.

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286 roads and water bodies in Cost 12 and 13 versus the much lower cost assigned in Cost Surface 1. Cost Surfaces 8 and 9 versus Cost Surfa ces 14 and 15: Testing the Influence of Drastically Changing the Ra nge of Cost Surface Values Cost Surfaces 14 and 15 were versions of Cost Surfaces 8 and 9 transformed by squaring the original cost surface values, which resulted in a range of values from 1 to 10,000. This more moderate transformation of cost values did not result in changes as significant as the differences between Cost Surfaces 3 and 4 versus Cost Surfaces 10 and 11. However, expanding the range of values still resulted in some significant changes in routes followed (Figure B-9). Cost Surface 16 and Cost Surface 17: Co mparing Cost Surfaces Created Using Multiple Logist ic Regression Cost Surface 16 and Cost Surface 17 were created using two slightly different versions of a multiple logis tic regression analysis usin g known bear occurrences and various landscape and habitat variables. The difference between the two models was that different sets of random locations were created to serve as surrogates for absence data. In the logistic regression model used to cr eate Cost Surface 16 random locations were generated statewide whereas in Cost Surface 17 random points were restricted to areas considered to be generally occupied by bear s (Figure 3-3). The primary difference in the results of the logistic regression models was that the matrix surrounding higher quality potential bear habitat tended to have higher probability values in Cost Surface 17 versus Cost Surface 16 (See Figure 3-7 and Figure 3-8).

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287 Figure B-9. Comparison of Cost Surfaces 8, 9, 14, and 15. The values of Cost Surfaces 8 and 9 were squared to create Cost Surfaces 14 and 15 respectively. Though this increase in the range of cost values did result in changes in LCP routing, the differences were not as great as those between Cost Surfaces 10 and 11 and Cost Surfaces 12 and 13 where cost values were transformed with an exponential function.

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288 The resulting LCPs were also different, especially for the Osceola National Forest-Apalachicola National Forest landscape lin kage (Figure B-10). In three cases the two cost surfaces resulted in significantly different path alternatives. Overall the results for Cost Surfaces 16 and 17 compared well to and are similar to the LCPs selected by the preceding 15 cost surfaces. The only major divergence occurred in southwest Florida, where the paths of 16 and 17 mirrored those for the forest-based Cost Surfaces 5 and 6 (See Figure C-1 and Figure C-2). Since Cost Surfaces 16 and 17 have the advantage of being based on a statistical re lationship between bears and ha bitat variables, more work should be done to refine a quantitative black bear habitat model. These efforts should include methods for generating random point data for comparison to known bear occurrences or collecting true presence-abs ence data generated through hair trap censusing or other applicable techniques.

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289 Figure B-10. Comparison of Cost Surface 16 and Cost Surface 17. The LCPs for the two cost surfaces based on multiple logistic regression models (Cost Surface 16 and Cost Surface 17) had some significant differences especially for the Osceola National Forest-Apalachicola National Forest landscape linkage. The primary difference in the surfaces was that matrix areas between higher quality areas of potential bear habitat tended to have higher values in Cost Surface 17 than in Cost Surface 16.

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APPENDIX C DETAILED COMPARISON OF LEAST COST PATH RESULTS FOR THE BIG CYPRESS NATIONAL PRESERVE TO OCALA NATIONAL FOREST LANDSCAPE LINKAGE Though there was a general consensus on the best overall route for providing a landscape linkage between BCNP and OCNF, there were some path variations. First, in terms of the longest distance in divergence, the two major alternatives just north of BCNP represented the biggest variation. In the landscape north of BCNP, the LCPs followed two variations: the primary one, which 13 of the 17 cost surfaces followed, ran due north of BCNP through the Okaloacoochee Slough State Forest and the Caloosahatchee Ecoscape Florida Forever Project and then through private ranchlands to reach the Fisheating Creek basin (Figure C-1). This path corresponds well with the landscape linkage identified within the Florida Ecological Network as the best connection between BCNP and the Fisheasting Creek basins. It also followed the dispersal path of the 3 radio-collared Florida panthers that crossed the Caloosahatchee River from 1998-2000 (Maehr et al. 2002b). Protecting the Caloosahatchee Ecoscape Florida Forever Project is the best option for maintaining connectivity for the Florida panther between occupied habitat south of the Caloosahatchee River and potential habitat north of the river (Maehr et al. 2002b) and would likely do the same for the black bear. The alternative route was followed by the LCPs for four cost surfaces: 5, 6, 16, and 17 (Figure C-1). This route left BCNP through the Florida Panther Wildlife Refuge, headed northwest through the currently undeveloped portions of northern Golden Gate Estates, 290

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291 Figure C-1. LCP results for for the Big Cypress National Preserve to Ocala National Forest landscape linkage in southwest Florida. There were two major options between Big Cypress National Preserve and the Fisheating Creek basin selected during the LCP analysis for all 17 cost surfaces. The primary route followed a corridor due north from BCNP through a rural landscape with agricultural land uses and large blocks of natural land cover that incorporates existing conservation lands and several important project areas. This route also has been identified as the primary route for connecting Florida panther habitat south of the Caloosahatchee River to potential habitat north of the river. The second route (used by only 4 of the 17 cost surfaces) traversed a more disturbed landscape first to the northwest of BCNP towards Ft. Myers and then northeast to the Fisheating Creek basin. Though this path incorporates significant conservation lands in the CREW complex and some large forested block it also traveled through several bottlenecks in urbanizing areas both south of CREW and then east of Ft. Myers.

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292 crossed through the western portion of th e Corkscrew Regional Ecosystem Watershed (CREW) conservation complex, c ontinued north by paralleling th e east side of Interstate 75 and then east of Ft. Myers through a bottleneck in an urbanizing landscape. After crossing the Caloosahatchee River, the r oute continued northeast through the Babcock Ranch Florida Forever Project to reach the Fisheating Creek basin. The commonality between the four cost surfaces that followed this route was forest cover. Cost Surfaces 5 and 6 were based on either forest cover or bl ock size of forest cover. Cost Surfaces 16 and 17 were the two versions of the multiple logistic regression model that included patches of forest cover as an important fact or influencing potential bear habitat quality. Though this route is likely infeasible because of its proximity to Ft. Myers, it incorporated more forest than the primary r oute described above, which traversed a rural landscape that is a mosaic of ranches, cropl ands, forest, prairies, and marshes (Figure C2). The next divergence between the results of the various cost surfaces occurs along the Lake Wales Ridge (LWR) (Figure C-3). The LWR is a sand ridge on a narrow north and south axis that runs from south of Ar chbold Biological Station to northwest of Orlando. Once covered in sc rub and sandhill, the LWR is now dominated by citrus groves and scattered low dens ity residential development. Some remnant patches of scrub and sandhill have been recently purchased through the Florida Forever Program (and its predecessor, Preservation 2000) or are high priorities for protection. The LWR also is traversed along its axis from north to south by US 27, which could represent a significant barrier to movement and source of roadkill mortality. There were two routes taken by the LCPs of the 17 cost surfaces. The LCPs for Cost Surfaces 5, 6, 16, and 17

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293 Figure C-2. Forest cover and LCP results in southwest Florida. Though the alternative path identified using 4 of the 17 cost surfaces is likely infeasible due to its close proximity to a rapidly urbanizing area, it does incorporate more forest cover than the primary path that traverses rural areas primarily in Hendry and Glades Counties.

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294 Figure C-3. LCP results for the Big Cypress National Preserve to Ocala National Forest landscape linkage in south-central Florida. The LCPs for the 17 cost surfaces followed two primary paths across the Lake Wales Ridge (LWR), which are both included in the Florida Ecological Network. The southern path crossed US 27 at or near Josephine Creek and then followed a tributary north towards Avon Park Bombing Range. The second path crossed the LWR further north after traversing through Highlands Hammock State Park and the Charlie Creek watershed before crossing US 27 using the Livingston Creek drainage.

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295 followed one route and the rest of the cost surfaces used another. Both linkages are included within the Florida Ecological Netw ork but are narrow where they cross US 27 and are threatened by continued residentia l development and hab itat fragmentation. The route followed by most LCPs across the Lake Wales Ridge is the Josephine Creek corridor north of Archbold Biologic al Station and southeast of Highlands Hammock State Park. The corridor crosses the Jack Creek project area of the Lake Wales Ridge National Wildlif e Refuge (LWRNWR) north of Archbold Biological Station. The potential linkage narrows wher e Josephine Creek crosses US 27, and this crossing area is a significant potential bottleneck. The corridor continues northeast and crosses US 98 while following Yellow Bluff Creek, which is a tributary of Josephine Creek and then incorporates the Flamingo Villas project area of the LWRNWR. The route then continues north through a mosa ic of ranchlands, fo rest, and herbaceous wetlands to reach Avon Park Bombing Range. Highlands County, the site of the above linkage, supports a small Florida black bear population that may be part of the southwest Florida bear population or essentially isolated. Though a male bear crossed the Caloosahatchee River fro m the south (Maehr et al. 1988), the degree of population interc hange is unknown. Despite the fragmented nature of Highlands County forest, bears still frequent the area based on the high number of roadkills from Florida Fish and Wildlife Conservation Commission data collected from 1978-2001 (Figure C-3). Although the Josephine Creek/Yellow Bluff Creek corridor is narrow and threatened by development, roadkill data suggest that bears use this area to move through the landscape. Three roadkills (from 1984, 1997, and 1999) occurred along the selected pathway on US 27 just north of the Josephine Creek corridor

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296 and five roadkills have been documente d from 1993-1997 at the US 98 crossing of Yellow Bluff Creek including cubs and an adult female. The second alternative followed the wester n edge of the LWR, crossed through both Highlands Hammock State Park and the Charlie Creek Watershed before crossing US 27 using the upper Livingston Creek drainage that runs to the Lake Wales Ridge State Forest and Avon Park Bombing Range. Though this crossing of US 27 is also narrow and threatened by development, it represents a slightly larger and more intact crossing of US 27 and the LWR than Josephine Creek. In addition, though most bear activity appears to be relegated to the southern half of Highlands County, two male bears (one in 1986 and another in 1996) were killed at this crossing of US 27 just north of the Highlands/Polk County boundary. There are three routes taken by LCPs th rough the Kissimmee River basin east of the Lake Wales Ridge (Figure C4). All of the LCPs began in this region either at Avon Park Bombing Range or in the adjacent Lake Wales Ridge State Forest to the northwest, and 16 out of 17 of the paths traversed the Big Bend Swamp/Holopaw Ranch Florida Forever Project area (BBHR) to reach the Econlockhatchee Upper Mosaic Florida Forever Project area (EM). The southern route, followed by 8 of the 17 cost surfaces, crossed the Kissimmee River just south of La ke Kissimmee. All of these paths except one (Cost Surface 5) headed north through the Three Lakes Wildlife Management Area to reach the BBHR and EM. Cost Surface 5 followed a more easterly route across the Osceola Pine Savannas Florida Forever Proj ect and ranchlands to reach the St. Johns River corridor and then followed the river north.

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297 Figure C-4. LCP results for for the Big Cypress National Preserve to Ocala National Forest landscape linkage through the Kissimmee River basin. Three primary routes were taken by the LCPs to cross the Kissimmee River basin to reach the Econlockhatchee--St. Johns River basin. The southern route that crossed the Kissimmee River just south of Lake Kissimmee then traversed the Three Lakes Wildlife Management Area and the Big Bend Swamp/Holopaw Ranch Florida Forever Project likely represents the most intact route especially in regards to the most feasible crossing of the Florida Turnpike transportation corridor. The middle route followed the west side of Lake Kissimmee north through the bombing Range Ridge Florida Forever Project and Lake Kissimmee State Park, turned northeast through the Kissimmee Chain of Lakes Conservation Area and then followed a canal edge forested corridor to cross the Florida Turnpike to reach the Big Bend/Holopaw project area. The northern route followed Tiger Creek Preserve, Catfish Creek Preserve, and the Disney Wilderness Preserve to before heading due east to cross the Florida Turnpike 2-3 kilometers north of the middle route.

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298 The middle route through the Kissimmee Ri ver basin headed north from Avon Park Bombing Range and along the western shore of Lake Kissimmee through the Bombing Range Ridge Florida Forever Project, La ke Kissimmee State Park, and the Kissimmee Chain of Lakes Conservation Area before turn ing northeast to cross the Florida Turnpike and reach the BBHR Florida Forever project by following a forested canal edge (the channelized Canoe Creek) unde r the Florida Turnpike. The northern route followed Tiger Creek Preserve, Catfish Creek Preserve, and the Disney Wilderness Preserve before headin g due east to cross the Florida Turnpike 2-3 km north of the middle route. This route was the most circuitous and appears to be potentially the most fragmented. However, it corresponds very well with the telemetry records for Panther 62 and his movements between the Lake Wales Ridge State Forest, Catfish Creek Preserve, and the Disney W ilderness Preserve (Maehr et al. 2002b). Panthers may be even more sensitive to habitat fragmentation that bears when moving across landscapes (Maehr 1997b), so paths that can facilitate panther movement may also work for bears. The Florida Turnpike crossings of the mi ddle and northern routes appear to be more tenuous than the southern route based on both existing landcover and their proximity to southern Orlando. The southern route follows a primary landscape linkage within the Florida Ecological Network and appears to be the most feasible connection through this landscape. However, the Canoe Creek corridor under the Florida Turnpike was also included in the Florida Ecologic al Network, and both the middle and northern routes followed a similar route to where Panther 62 appeared to cross the turnpike to reach the BBHR Florida Forever Project and other habitats east of the highway.

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299 Most of the LCPs followed a similar route from the Upper Econlockhatchee Mosaic to the Ocala National Forest (Figure C-5). The primary route selected by 13 of the paths followed the landscape from the Econl ockhatchee River or slightly east of the river through the Deseret Ranch, crossed the St. Johns River south of Lake Harney, and then followed the Volusia Conservation Corridor-Tiger Bay State Forest-Lake George State Forest-Lake Woodruff National Wildlife Refuge conservation complex to reach the Ocala National Forest. This corridor also in cluded a large private parcel of land east and southeast of the Volusia Conservation Corridor Florida Forever Project owned primarily by the Miami Corporation. Although it followed the other paths for most of th
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Title: Regional landscape analysis and reserve design to conserve Florida's biodiversity
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Material Information

Title: Regional landscape analysis and reserve design to conserve Florida's biodiversity
Physical Description: Mixed Material
Creator: Hoctor, Thomas Scott ( Author, Primary )
Publication Date: 2003
Copyright Date: 2003

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Source Institution: University of Florida
Holding Location: University of Florida
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System ID: UFE0000702:00001


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REGIONAL LANDSCAPE ANALYSIS AND RESERVE DESIGN TO CONSERVE
FLORIDA'S BIODIVERSITY















By

THOMAS SCOTT HOCTOR


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2003































Copyright 2003

by

Thomas Scott Hoctor















ACKNOWLEDGMENTS

Many different people have helped shape my thinking and provided support

through the long process of completing this work. First, I want to express my sincere

gratitude to my parents, Michael and Lorraine Hoctor, for all of their support, love, and

understanding throughout the years. They have been very patient throughout my long

graduate career but always had the confidence that I would finally finish.

I would not have been a graduate student at the University of Florida and I would

never have developed the conceptual foundation of my work and expertise without the

guidance of Dr. Larry Harris. Larry created the foundation of ecological conservation in

Florida upon which this dissertation is built. There would not be a Florida Ecological

Network without Larry's blood, sweat, tears, and inspiration; and I and innumerable

others are indebted to him for his vision for saving Florida's natural heritage. Larry is a

conservation scholar without peer, and I have very much enjoyed all of the challenges

and intellectual support that our collaboration has fostered.

Peggy Carr and Paul Zwick have provided me with immeasurable support in

funds, space, time, guidance, collaboration, and friendship. One of my luckiest moments

was when I met Peggy and Paul early in my graduate career, working together on the

Cross Florida Greenway Management Plan. Their support and encouragement have been

instrumental to my success. Peggy Carr reviewed all chapters in draft and her comments

greatly strengthened the clarity of the central message of this work.









I also want to thank the many students and co-workers who helped me along the

way. Jason Teisinger provided essential help developing the bear habitat models; and

was a valued fishing partner. Karen Whitney helped develop the methods for creating

bear connectivity cost surfaces and contributed to my thoughts on the importance of

reserve networks. Crystal Goodison, Patty Hernandez, Jessica Green, Christy McCain,

and Wendy Robinson Rieth all helped collect and analyze the data for the ecoregional

planning analysis. Rich Doty and Juna Papajorgji were instrumental in developing the

computer code for the Florida Ecological Network analysis. Dan Smith contributed

important information on highway projects and wildlife movement mitigation structures.

Maynard Hiss provided almost endless commentary, help, and prodding that expanded

my thinking and increased my motivation to finish. The various birding trips with Kurt

Leuschner were a welcome respite from job and dissertation obligations. All have been

good friends and compatriots along the way.

Many others also contributed. Mark Benedict provided conceptual help and much

needed organizational skills during the development of the Florida Ecological Network

project. Richard Hilsenbeck, Ray Moranz, Wendy Castor, and others at the Florida

Chapter of the Nature Conservancy were integral to accomplishing the ecoregional

planning analysis. I am also indebted to the many scientists who contributed to the

identification of focal species and natural communities.

Dave Maehr deserves special praise for his intellectual support and friendship.

Dave helped pull me through this process more than once. He contributed instrumental

comments on various sections of my dissertation, decreasing its length and increasing its

impact.









I also want to thank my committee (Larry Harris, Peggy Carr, Tom Crisman, Joe

Schaefer, and Mike Binford) for their support, patience, and perseverance. All helped me

at critical times during my graduate program. Their encouragement toward the end of

this process was essential.

The Florida Ecological Network was funded by the Florida Department of

Environmental Protection and the Florida Department of Transportation. Their support

was essential and is much appreciated. I also want to thank the staff of the FDEP's Office

of Greenways and Trails for their hard work and perseverance through the

implementation process for the Florida Ecological Network. The ecoregional planning

analysis was funded by The Nature Conservancy; I hope that future collaborations will

prove as interesting and fruitful. Randy Kautz from the Florida Fish and Wildlife

Conservation Commission provided data and other help that greatly improved the

thoroughness of this work. Florida Natural Areas Inventory also provided several

datasets that improved the specificity of the Florida Ecological Network and were

essential for completing the Florida Peninsula and Tropical Florida ecoregional plans.

I also want to thank my two brothers, Jim and Dan. I enjoyed all of the mutual

travails Dan and I shared as resident advisors in the old athletic dorm, Yon Hall. Those

memories will not fade anytime soon. The occasional fishing trips with Jim provided

much-needed relief throughout this process. Finally, I want to thank Kristin Leuschner

for her simultaneous support and cajolery. Her friendship, wittiness, sagacity, and keen

sense of irony have been very important to me throughout this long, hard journey.















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ........................................................................................... iii

A B S T R A C T .................................................................. ............................... . x

CHAPTER

1 IN TR O D U C TIO N ........................ .... ........................ ........ ..... ................

Study A rea .................................... ... .......... ..................10
General Geographic Information System Methods ............................................13

2 THE FLORIDA ECOLOGICAL NETWORK.....................................................17

Intro du action ...................................... .............................. ................ 17
M eth o d s................................. ....................................................... ............... 2 0
R review Process ...................................................... .... ...... .... .. .............20
Analysis Used to Identify the Florida Ecological Network.............................20
R results ............. ... .......... .... ........... ......... ...... ............. ... ........ 34
Comparisons to Other Ecological Inventories..............................................36
Landscape Com prisons ............................................................................. 41
R presentation .....................................................................43
D discussion ................................................................. ..... .........47

3 LANDSCAPE CONNECTIVITY FOR THE FLORIDA BLACK BEAR..........54

Introdu action ...................................... .............................. ................. 54
Florida B lack B ear E cology .............................................................................. ...59
M methods ................................. .................... ...............................65
Multiple Criteria-Based Cost Surfaces .................................... ............... 69
Sim plified Cost Surfaces ............................................................................. 91
Exponential Function Cost Surfaces................................................................ 96
Using Multiple Logistic Regression Modeling to Develop Cost Surfaces.......100
Creation of Analysis Masks to Modify Cost Surfaces..................................... 107
Sources and Destinations for LCP Analysis..................................................108
Identifying Florida Black Bear Habitat and Landscape Linkage
O pportunities....... ............................................................ .... .... .... 109
Results and D discussion ........................................ ...............................112









Stepwise Multiple Logistic Regression Habitat Model ..................................112
Alternative Model Multiple Logistic Regression Results.................................114
Comparison of LCP Results Using Different Intensive Land Use Masks........ 118
Least Cost Path Results for Landscape Linkages between Major
Populations................. ......... ........ ............... .. .....................122
Assessment of Potential Landscape Linkages between Major Populations
and Other Bear Populations or H abitat...................................................129
Statewide Black Bear Habitat and Landscape Linkages ...............................132
Habitat, Linkages, Conservation Lands, and the Florida Ecological
N etw ork ..................................... ........................... ....... ..... 142
Habitat Connectivity and Potential Bear Population Size ..............................150
Potential Black Bear Habitat, Landscape Linkages, and Development
Pressure .................................... .......................... ... ........ .151
C on clu sion s ................... ................................ ........................................... 157
Recommendations for Conducting LCP Analyses to Identify Potential
L landscape L inkages........................................................... ................ .. 157
Landscape Ecology and a Florida Black Bear Metapopulation.....................159
Connectivity Beyond B ears ......................................................... ............... 166
Landscape Conservation Opportunities................................. ...... ............ ...168
Research Priorities for Protecting a Statewide Florida Black Bear
M etapopulation ................................... ........ ... .. .. ........ .... 172

4 ECOREGIONAL PLANNING FOR BIODIVERSITY CONSERVATION
IN THE FLORIDA PENINSULA.......................................... ...........................175

Intro du action ............................ ................... .......... ..... ......... ...... 17 5
Description of the Florida Peninsula Ecoregion..................... ................. 180
Description of the Tropical Florida Ecoregion......... ................................. 183
M methods ............................................................. .. ...... ................ ............... 188
Selecting Species and Natural Communities ......... ....................................188
Setting Conservation Goals for Species and Natural Communities ............191
A ssessing V ability ......................... ...................... ............ ................200
Portfolio Site Selection ......................................................... ............. 208
Results and Discussion ...................... ............................... 216
Florida Peninsula Ecoregion Portfolio................................... ............... 216
Tropical Florida Ecoregion Portfolio..................................... ............... 218
G oal A chievem ent ............................... ................ ................ ............ ... 220
Conservation Land and Open Water Statistics ...........................................228
Comparison with the Florida Ecological Network .......................................228
Comparison with Black Bear Habitat and Landscape Linkages ................. 236
C conclusions ................................ ........................... ... ... ........ 238

5 CONCLUSIONS, POLICY ISSUES, AND RECOMMENDATIONS .............245

Reserve Design Analysis: Landscape Approaches and Methods ........................245
Land Conservation Policy Issues and Recommendations .............. ...............254









L and P protection ........ .............................................................. .. .... .. .. 254
L and M anagem ent ................................................ ............................... 256
Growth M management .......................... .................... .............. 261
Transportation Planning....................................................... .. ............... 262
Ecological Linkages across State Borders ................................. ............... 264
Protecting Biodiversity and Ecosystem Services.....................................265

APPENDIX

A DATA FOR FLORIDA BLACK BEAR LANDSCAPE REGRESSION
ANALYSIS .................................... ............................... .......... 268

B COMPARISON OF MAJOR COST SURFACE VARIATIONS .....................272
Cost Surface 1 and Cost Surface 2: The Influence of Adding Major Roads
and Large W ater B odies............................... ....... ............... ... 272
Cost Surface 1 and Cost Surface 3: Testing the Influence of Changing the
Range of Cost Surface V alue............................................................. 275
Cost Surface 3 versus Cost Surface 4: Testing the Influence of Differential
Weighting of Input Indices (SUAs) ................... .................277
Cost Surface 5 versus Cost Surface 6: Testing the Performance of Simplified
Surfaces and the Influence of Habitat Patch Size....................................279
Cost Surfaces 7, 8, and 9: Testing the Performance of Simplified Surfaces .......281
Cost Surfaces 3 and 4 versus Cost Surfaces 10 and 11: Testing the Influence
of Drastically Changing the Range of Cost Surface Values....................281
Cost Surfaces 10 and 11 versus Cost Surfaces 12 and 13: Testing the Effect
of Adding Major Roads and Large Water Bodies to Expanded
C o st S u rfa ce s ....................... ...... ... ...... .............. ....................... 2 8 3
Cost Surfaces 8 and 9 versus Cost Surfaces 14 and 15: Testing the Influence
of Drastically Changing the Range of Cost Surface Values....................286
Cost Surface 16 and Cost Surface 17: Comparing Cost Surfaces Created
U sing M multiple Logistic Regression ................................ ............... 286

C DETAILED COMPARISON OF LEAST COST PATH RESULTS FOR THE
BIG CYPRESS NATIONAL PRESERVE TO OCALA NATIONAL
FOREST LAND SCAPE LINKAGE ........................................ .....................290

D ASSESSMENT OF POTENTIAL LANDSCAPE LINKAGES BETWEEN
MAJOR POPULATIONS AND OTHER BEAR POPULATIONS
O R H A B IT A T .......................................................................... .......... .. .. 3 0 1

Apalachicola National Forest to the Lower Suwannee National Wildlife
Refuge and Goethe State Forest................................................. 301
Ocala National Forest to Twelve Mile Swamp ...........................................303
Ocala National Forest to Gulf Coast Destinations............................. ...............3. 06
Weekiwachee Conservation Area to Green Swamp, Goethe State Forest, and
Lower Suwannee River National Wildlife Refuge...............................311









Big Cypress National Preserve to Myakka River State Park, Green Swamp
Conservation Area, and Corbett Wildlife Management Area................ 13

E FOCAL SPECIES FOR THE FLORIDA PENINSULA ECOREGION............318

F FOCAL SPECIES FOR THE TROPICAL FLORIDA ECOREGION..............325

G GOAL STATUS FOR FOCAL PLANT SPECIES IN THE FLORIDA
PENINSULA ECOREGION ............................ ...............331

H GOAL STATUS FOR FOCAL PLANT SPECIES IN THE TROPICAL
FLORIDA ECOREGION ........... ...... ......... ................... 335

I GOAL STATUS FOR FOCAL ANIMAL SPECIES IN THE FLORIDA
PENINSULA ECOREGION ............................ ...............340

J GOAL STATUS FOR FOCAL ANIMAL SPECIES IN THE TROPICAL
FLORIDA ECOREGION ............. .. ............. ................... 345

K GOAL STATUS FOR NATURAL COMMUNITIES IN THE FLORIDA
PENINSULA ECOREGION ............................ ...............348

L GOAL STATUS FOR NATURAL COMMUNITIES IN THE TROPICAL
FLORIDA ECOREGION ........... ...... ......... ................... 350

LITER A TU RE CITED ........................................... .................. ............... 352

BIOGRAPHICAL SKETCH ........... ...... ......... .................... 375















LIST OF TABLES


Table page

2-1 Criteria for selecting Priority Ecological Areas for the Florida Ecological
N etw o rk ............................... ......... ........ .................. ................ 2 4

2-2 Landscape unit classification used in landscape linkage identification for
the Florida Ecological Network........... ... ...... ......... .. ................... 28

2-3 Riverine suitability surface values for the Florida Ecological Network ............30

2-4 Hub-to-hub suitability surface values for the Florida Ecological Network.........31

2-5 Area of land in various land ownership categories within Florida's
E cological N etw ork ....................... .. .................... ............ ... .......... ..38

2-6 Comparison of the Florida Ecological Network, other ecological resource
inventories, and existing and proposed conservation lands..............................39

2-7 Comparison of roadless areas found in existing conservation lands and the
those included in the Ecological N network .............................................. .44

2-8 Comparison of the total land area of existing ecological community types
(habitats) in the state of Florida with area of habitat types found in existing
conservation lands and the amount included in the Ecological Network ...........46

3-1 Seventeen cost surfaces used to assess landscape linkages for the Florida
b lack b ear ...................................... .............................. ................ 7 0

3-2 SUA ranking land cover types based on preference as habitat..........................72

3-3 Ranking of potential habitat based on patch size ............................ ..............74

3-4 H habitat diversity rankings......................................................... ............... 75

3-5 Ranking of distance from protected bear habitat 20,000 ha or larger .................77

3-6 Roadless area ranks based on size of the roadless areas and the percentage
of bear habitat within roadless areas..... ................... ...............79









3-7 Ranking of road densities .............. ... ......... ......... ....................... 80

3-8 Ranking of distances from major roads.... ....................................82

3-9 Land use intensity rankings ........................................ ........................... 84

3-10 Ranking of distances from major roads........................... ...............85

3-11 C conservation land rankings ........................................... .......................... 86

3-12 Weighting factors used to create Cost Surface............................... ...............90

3-13 Cost Surface 5 categories and rankings............... .......................................... 93

3-14 Cost Surface 6 categories and rankings............... .......................................... 94

3-15 Cost Surface 7 categories and rankings............... .......................................... 95

3-16 Cost Surface 8 categories and rankings............... .......................................... 97

3-17 Cost Surface 9 categories and rankings............... .......................................... 98

3-18 Comparison of original values from Cost Surface 3 and the transformed
values using an exponential function to create Cost Surface 10.......................99

3-19 Comparison of original values from Cost Surface 8 and the transformed
values to create Cost Surface 14 .............................................. ............... 101

3-20 Comparison of occurrences and random locations used for multiple logistic
regression habitat model validation ............. .......................... ....... ........... 116

3-21 Comparison of occurrences and random locations used for validation of
the alternative multiple logistic regression habitat model ..............................119

3-22 Existing and proposed conservation land statistics for potential black bear
habitat and landscape linkages.................................. ..................................... 144

3-23 Comparison statistics between potential black bear habitat and landscape
linkages and the Florida Ecological Network............................146

4-1 Natural community classification and goals for the Florida Peninsula
Ecoregion .................................... ............................... .......... 192

4-2 Natural community classification and goals for the Tropical Florida
Ecoregion .................................... ............................... .......... 195









4-3 Data and criteria used in designing the terrestrial, aquatic and averaged
v iab ility in d ice s ................................................... .......................... 2 0 4

4-4 Additional data used to identify portfolio sites .............................................214

4-5 Goal achievement by taxonomic group for vertebrate species in the Florida
Peninsula Ecoregion ............... .................... ................. .. .... .. ........ .... 223

4-6 Goal achievement by taxonomic group for vertebrate species in the
Tropical Florida E coregion ..................................... .......................... .......... 224

4-7 Conservation lands and open water statistics for the Florida Peninsula
site p portfolio ............................................................................ ............... 2 3 0

4-8 Conservation lands and open water statistics for the Tropical Florida site
portfolio..................................................... ........................... ...... .. 232

E-l Focal species for the Florida Peninsula Ecoregion ................ ..............318

F-l Focal species for the Tropical Florida Ecoregion ..........................................325

G-l Goal status for focal plant species in the Florida Peninsula Ecoregion............331

H-1 Goal status for focal plant species in the Tropical Florida Ecoregion...............335

I-1 Goal status for focal animal species in the Florida Peninsula Ecoregion ..........340

J-1 Goal status for focal animal species in the Tropical Florida Ecoregion ............345

K-1 Goal status for natural communities in the Florida Peninsula Ecoregion .........348

L-1 Goal status for natural communities in the Tropical Florida Ecoregion ...........350















LIST OF FIGURES


Figure page

2-1 Results of 1991 mapping workshop (charrette) coordinated by The Nature
C conservancy ............................................................... ... ......... 18

2-2 Major steps in the Florida Ecological Network modeling process....................21

2-3 Riverine cost surface example.......... .. ...................... ............... 33

2-4 Florida Ecological Network model results ................... ......................... 35

2-5 Comparison of the Ecological Network other statewide ecological resource
in v e n to rie s .................................................. ................ 4 0

3-1 Process used to identify the land area with the potential to support a
statewide black bear metapopulation.............................. ............ ............. 66

3-2 C o st Su rface 1..............................................................88

3-3 Telemetry locations from major Florida black bear populations used in the
multiple logistic regression analysis .............................. ......... ... ........... 105

3-4 Recent bear range map from the Florida Fish and Wildlife Conservation
Com m mission ................................ .............. ............. .... ............ 106

3-5 Comparison between a 3 X 3 and a 5 X 5 neighborhood for analyzing
potential bottlenecks .................. .......................... .... .... .. .. ...... .. .. .. 110

3-6 Sources and destinations for assessing best potential landscape linkages......... 111

3-7 Results of the primary version of the stepwise multiple logistic regression
m odel ............................................................... .... ..... ......... 115

3-8 Results of the alternative version of the multiple logistic regression model.....117

3-9 Comparison of LCP results for the three mask alternatives ........................... 121









3-10 LCP results for the landscape linkage options between Big Cypress
National Preserve (BCNP) and the Ocala National Forest..............................124

3-11 The landscape linkage between the Ocala National Forest and Osceola
N national F orest............................................................................... .... 127

3-12 LCP results for Osceola National Forest to Apalachicola National Forest
landscape linkage ....... ... ........ ................ ................. ................128

3-13 The LCP results for the landscape linkage between the Apalachicola
National Forest and Eglin Air Force Base ..................................................... 130

3-14 Forest cover compared to LCP results the Apalachicola National Forest
and Eglin Air Force Base landscape linkage ......................... ................. 131

3-15 LCP results for landscape linkages between Apalachicola National Forest,
Lower Suwannee National Wildlife Refuge (LSRNWR) and Goethe
State F o rest (G S F ) ................................................................... ................ .. 13 3

3-16 The LCP results for the Ocala National Forest to Twelve Mile Swamp
landscape linkage .............................................. .. ........ .. .......... ... 134

3-17 The LCP results between Ocala National Forest and the Weekiwachee and
Green Sw am p conservation areas ................................. ......... ................. 135

3-18 The LCP results for landscape linkages between Weekiwachee
Conservation Area and the Green Swamp Conservation Area, Goethe
State Forest, and Lower Suwannee National Wildlife Refuge .......................136

3-19 The LCP results between Big Cypress National Preserve and the Green
Swamp Conservation Area, Myakka River State Park, and Corbett
W wildlife M anagem ent A rea..................................... ............................ ........ 137

3-20 Black bear habitat and landscape linkages statewide ............ ................140

3-21 Potential black bear habitat and landscape linkages with population cores
an d ro ad k ills ................................................ ................ 14 1

3-22 Bear habitat and landscape linkages in south Florida.............. ... ...............143

3-23 Existing and proposed conservation lands are shown on top of potential
black bear habitat and landscape linkages ................................... ............... 145

3-24 Florida Ecological Network drawn on top of potential black bear habitat
and landscape linkages ......................................................... .............. 147









3-25 Black bear habitat and landscape linkages drawn on top of the Florida
E cological N etw ork ............................................... .............. ............. 149

3-26 Distribution of large black bear habitat blocks statewide...............................152

3-27 Largest blocks of black bear habitat in Florida .........................................153

3-28 Impact of future development on bear habitat and landscape linkages.............154

4-1 Boundaries of the four ecoregions in Florida............................... .................177

4-2 Boundaries of the Florida Peninsula and Tropical Florida Ecoregions ...........181

4-3 Process for identifying the site portfolios for the Florida Peninsula and
Tropical Florida Ecoregions ........................................ ......................... 190

4-4 Subecoregions for the Florida Peninsula and Tropical Florida Ecoregions......201

4-5 The Florida Peninsula Ecoregion site portfolio........................... ................ 217

4-6 The Tropical Florida Ecoregion site portfolio ...........................................219

4-7 Conservation lands, open water, and private lands both within and
outside the Florida Peninsula Ecoregion............................... ............... 229

4-8 Conservation lands, open water, and private lands both within and
outside the Tropical Florida Ecoregion site portfolio .........................231

4-9 Overlap between the Florida Ecological Network and the Peninsula
Florida and Tropical Florida ecoregional portfolios .............. ... ...............234

4-10 Overlap between the Peninsula Florida and Tropical Florida ecoregional
portfolios and Florida black bear habitat or landscape linkages.......................237

B-l Comparison between Cost Surface 1 and Cost Surface 2..............................273

B-2 Comparison of Cost Surface 1 and Cost Surface 2 in central Florida .............274

B-3 Comparison between Cost Surface 1 and Cost Surface 3...............................276

B-4 Comparison between Cost Surface 3 and Cost Surface 4...............................278

B-5 Comparison between Cost Surface 5 and Cost Surface 6...............................280

B-6 Comparison of Cost Surfaces 7, 8, and 9................................... ............... 282









B-7 Comparison of Cost Surface 10 and Cost Surface 11 .....................................284

B-8 Comparison of Coast Surfaces 10, 11, 12, and 13.......................................... 285

B-9 Comparison of Cost Surfaces 8, 9, 14, and 15............... ................................. 287

B-10 Comparison of Cost Surface 16 and Cost Surface 17...................................289

C-1 LCP results for for the Big Cypress National Preserve to Ocala National
Forest landscape linkage in southwest Florida ...........................................291

C-2 Forest cover and LCP results in southwest Florida .......................................293

C-3 LCP results for the Big Cypress National Preserve to Ocala National
Forest landscape linkage in south-central Florida ........................................ 294

C-4 LCP results for for the Big Cypress National Preserve to Ocala National
Forest landscape linkage through the Kissimmee River basin .......................297

C-5 LCP results for for the Big Cypress National Preserve to Ocala National
Forest landscape linkage east of Orlando ............................... ............... .300

D-1 Landscape linkage opportunities in the Big Bend ....................................... 302

D-2 LCP results for the Ocala National Forest to Twelve Mile Swamp
landscape linkage ....................................................... .......... ....... 305

D-3 LCP results between the Ocala National Forest and Gulf Coast
destination s ......................................................................308

D-4 LCP results from Weekiwachee Preserve to other Gulf Coast destinations......312

D-5 LCP results for the Big Cypress National Preserve and for destinations in
central and south Florida............. ................. ............ ... 315
















Abstract of Dissertation Presented to the Graduate School
Of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

REGIONAL LANDSCAPE ANALYSIS AND RESERVE DESIGN TO CONSERVE
FLORIDA'S BIODIVERSITY

By

Thomas Scott Hoctor

May 2003

Chair: Lawrence D. Harris
Major Department: Wildlife Ecology and Conservation

The design and management of reserve networks are driving forces in

conservation biology and landscape ecology. Reserve design principles and methods are

continually being developed and applied worldwide. Designing functionally integrated

reserve networks is now considered essential to conserve biodiversity, ecological

functions, and evolutionary processes effectively.

The state of Florida has been a leader in adopting systematic, landscape-based

reserve design, and thus provides an excellent opportunity to explore regional landscape

assessments and reserve design strategies for effective protection of biodiversity. In this

study, I develop and compare three such approaches:

* Identify a connected statewide network of intact landscapes and landscape linkages
called the Florida Ecological Network.

* Identify important habitat blocks and connectivity options for the Florida black bear,
Ursus americanusfloridanus, which may serve as an umbrella species for many other
biodiversity components.


xvii










* Develop ecoregional plans for the Florida peninsula that integrate fine filter, coarse
filter, and landscape approaches for designing reserve networks.

The Florida Ecological Network incorporates 9.3 million ha of large, connected

landscapes, over half of which lie within existing conservation lands and public domain

waterways. Over 5 million ha were identified as potentially high quality black bear

habitat, with an additional 680,000 ha identified as landscape linkages to facilitate

connectivity. The Florida Peninsula Ecoregion site portfolio contains 3.4 million

hectares (51% within public domain lands and water) and the Tropical Florida Ecoregion

site portfolio contains 2 million hectares (89% in public domain lands and waters).

Collectively, 85% of the bear habitat and landscape linkages were within the Florida

Ecological Network, which also overlaps with 84% and 90% of the Florida Peninsula and

Tropical Florida Ecoregions, respectively.

The results suggest the following:

* Even given Florida's rapid urbanization, opportunities remain to protect a statewide
reserve network that could protect most biodiversity effectively.

* Each approach I developed identifies some unique areas for protection not found in
the other two analyses.

* Collectively, the assessments address the primary steps of reserve design including
representation analysis, focal species analysis, incorporation of special resource
elements, and considerations for maintaining or restoring ecological and evolutionary
processes.


xviii














CHAPTER 1
INTRODUCTION


If a chance process of reserve selection continues, it may produce a network ...
in which all but a few species adapted to urban life become extinct. The
challenge remains to integrate the existing distribution of national parks and
wilderness areas with a plan that will ensure the functional integrity of the
world's ecosystems while land use for human purposes increases. (Sullivan and
Shaffer 1975, p. 13)

Since the science of conserving biological diversity gained significant momentum

with the discussions prompted by popularization of island biogeography theory (Preston

1962; MacArthur and Wilson 1963; MacArthur and Wilson 1967; Wilson and Willis

1975), the design and management of reserve networks have been primary driving forces

behind conservation biology, and cornerstones of landscape ecology. The importance of

analysis and planning at the regional landscape scale for effective conservation has been

a central theme in reserve design over the last two decades (Harris 1984; Noss and Harris

1986; Thomas et al. 1990; Wilcove and Murphy 1991; Noss and Cooperrider 1994;

Forman 1995; Harris et al. 1996b; Soule and Terborgh 1999; Margules and Pressey 2000;

Poiani et al. 2000). Principles guiding reserve design are in continual development, and

application of these principles is occurring in various regions to identify areas needed to

conserve biodiversity. The state of Florida is a leader in conducting detailed species

assessments and the identification of large, intact landscapes needed to protect

connectivity and ecological processes. Reserve design efforts continue to evolve, and











Florida provides an excellent opportunity to explore regional landscape assessments and

reserve design strategies for effectively protecting biodiversity.

Awareness of the significance of habitat patch size and isolation on the viability

of species and ecological dynamics began as early as the nineteenth century. A French

scientist, de Candolle (1855), recognized the importance of patch and sample effects on

species richness, and Wallace (1880) wrote about the influence of islands and other

geographical factors on speciation (Browne 1983).

Development of a national parks system in the United States resulted in

observations and research about national parks as viable, natural landscapes. Well before

popularization of island biogeography theory, wildlife biologists were noticing that

national parks were not of sufficient size to maintain many animal species, especially

ones that are wide-ranging (Wright et al. 1933; Wright and Thompson 1934). Additional

studies over the next several decades (Shelford 1936, Cahalane 1947, Leopold et al.

1963) demonstrated the inadequacy of what was thought to be extremely large reserves

such as Yellowstone National Park. Early suggestions for improving this situation

included creation of buffer zones around reserves to provide more space to meet seasonal

habitat requirements or to support viable populations (Wright and Thompson 1934;

Shelford 1936).

However, despite these early recommendations to adopt landscape-scale

conservation strategies, most protected areas have become more insularized and impacted

by land use changes beyond their boundaries (Leopold et al. 1963; Freemuth 1991).

Studies during the last few decades confirm the loss of many species from protected

lands, both in Africa and North America, with such losses presumed to be caused by











insufficient size of protected areas, their increasing isolation, and negative edge and

boundary effects due to the intensification of land uses outside park boundaries (Miller

and Harris 1977; Soule et al. 1979; Newmark 1985, 1987, 1995; Schonewald-Cox 1988;

Freemuth 1991).

Articulation of island biogeography theory has also had a significant role in the

evolving science of designing reserve networks (Preston 1962; McArthur and Wilson

1967; Wilson and Willis 1975; Browne 1983; Harris 1984; Shafer 1990; Noss and

Cooperrider 1994; Soule and Terborgh 1999). When island biogeography was

popularized by McArthur and Wilson in the 1960s, its influence over the nascent

discipline of conservation biology was particularly strong. Island biogeography theory

helped spur much discussion about the relevance of insularity to habitat fragments in

continental landscapes through the 1970s and early 1980s (Wilson and Willis 1975;

Harris 1984; Shafer 1990).

During the 1970s, reserve design rules based on the principles of island

biogeography were proposed (Sullivan and Shaffer 1975; Terborgh 1975; Diamond 1975;

Wilson and Willis 1975; Diamond 1976; Diamond and May 1976; Terborgh 1976;

Wilcox 1980). Such rules included the importance of reserve size, avoidance of habitat

fragmentation effects, and the need for functional connectivity among reserves. Debates

regarding the rationale and applicability of island biogeography to conservation raged in

the scientific literature throughout the late 1970s and into the mid 1980s (Shafer 1990),

but they included what are now considered to be fallacious arguments such as SLOSS

(Single Large Or Several Small reserves) (Soule and Simberloff 1986; Noss and

Cooperrider 1994).











Conservation biologists and ecologists now generally agree that it will be

necessary to have many large and strategically located reserves to conserve biodiversity

effectively (Wilcox and Murphy 1985; Soule and Simberloff 1986; Noss and Cooperrider

1994; Harris et al. 1996b; Soule and Terborgh 1999). The solidity and importance of

reserve design guidelines increased with the development of conservation biology and

additional research on habitat fragmentation effects on population viability and genetic

integrity (Soule 1986; Meffe and Carroll 1997). Furthermore, both the emerging

disciplines of conservation biology and landscape ecology tended to substantiate many of

the reserve design principles proposed initially through application of island

biogeography and provided new principles as well (Harris 1984; Forman and Godron

1986; Noss and Cooperrider 1994; Forman 1995).

Effective protection of biodiversity and ecological integrity is dependent on

research and planning efforts at a variety of scales (Poiani et al. 2000). This includes

research on species, natural communities, and landscapes. Effective conservation

requires analysis and planning at large scales in order to understand functional relations

between landscapes and to integrate efforts. One of the primary lessons of landscape

ecology is that spatial context matters (Harris 1984; Harris et al. 1996a), and natural

resource conservation and land use planning must consider the effects of actions within

their largest spatial and temporal perspectives (Forman 1987). Within both landscape

ecology and conservation biology, habitat loss and fragmentation are the primary threats

to biodiversity and functional ecological processes and services (Wilcox and Murphy

1985; Harris and Silva-Lopez 1992). Strategies are needed that help to protect and

restore natural levels of spatial and temporal heterogeneity that are necessary for











maintaining intact ecosystems and biodiversity while minimizing the effects of

fragmentation (Harris et al. 1996a).

The need for regional landscape approaches to conservation has resulted in

increasing attention to the design of reserve networks that incorporate landscapes

apportioned into reserves, multiple-use buffer zones, and landscape linkages (Harris

1984; Noss and Harris 1986; Noss and Cooperrider 1994; Harris et al. 1996b; Soule and

Terborgh 1999; Margules and Pressey 2000). Buffers provide protection to core

reserves, provide additional habitat, and can potentially link reserves (Harris 1984; Noss

and Harris 1986; Noss and Cooperrider 1994). Reserve networks that are functionally

connected by buffers, landscape linkages, and corridors are more likely to maintain

viable populations, functional ecological processes, and flexibility to respond to

environmental changes (Harris 1984; Noss and Harris 1986; Williams 1986; Harris and

Scheck 1991; Noss and Cooperrider 1994; Forman 1995; Harris et al. 1996b; Noss et al.

1996). The overarching goals for such systems include those described by Noss (1996,

p. 95-96):

1) Represent, in a system of protected areas, all native ecosystem types and seral
stages; 2) Maintain viable populations of all native species in natural patterns of
abundance and distribution; 3) Maintain ecological and evolutionary processes,
such as disturbance regimes, hydrological processes, nutrient cycles, and biotic
interactions; 4) Design and manage the system to be responsive to short-term and
long-term environmental change and to maintain the evolutionary potential of
lineages.

Along with these 4 goals, there are 4 primary components of a comprehensive reserve

design process: identification of special elements such as roadless areas and high quality

natural community sites; representation analysis to identify biodiversity elements

(especially natural communities) that are not well protected; focal species habitat











assessments; and consideration of functional ecological and evolutionary processes (Noss

and Cooperrider 1994; Harris et al. 1996a; Noss 1996; Margules and Pressey 2000;

Sanderson and Harris 2002).

By the late 1980s and early 1990s, reserve design principles, or guidelines, for

conserving biodiversity were generally accepted in conservation biology and were being

applied to cases such as the Spotted Owl (Strix occidentalis) (Wilcove and Murphy

1991). The most commonly accepted "rules of thumb" for reserve design include the

following (Harris 1984; Thomas et al. 1990; Soule 1991; Noss and Cooperrider 1994;

Noss et al. 1997):

* Large reserves (or blocks or habitat) are preferable to smaller reserves. Such reserves
will tend to have larger blocks of habitat and larger populations, more potential for
supporting various ecological communities and therefore more diversity, are more
likely to be both resistant and resilient to disturbances and potentially support natural,
functional disturbance regimes and other ecological processes, and will be better
insulated from incompatible land uses outside the reserve (Harris 1984; Soule and
Simberloff 1986; Thomas et al. 1990; Soule 1991; Noss and Cooperrider 1994; Noss
et al. 1997).

* Functionally interconnected reserves are generally preferable over isolated reserves.
Depending on the situation and species, connectivity can be provided by establishing
corridors or landscape linkages or through compatibly managed multiple-use
landscapes surrounding and connecting reserves. Reserves that are close together
may also provide functional connectivity for species that are either able to fly or
traverse the matrix surrounding the reserves (Harris 1984; Noss and Harris 1986;
Harris and Scheck 1991; Soule 1991; Noss 1993; Noss and Cooperrider 1994; Noss
et al. 1996; Noss et al. 1997; Beier and Noss 1998; Soule and Terborgh 1999).

* Reserves in contiguous or consolidated blocks are preferable over fragmented blocks.
Examples of fragmentation within reserves include roads, inholdings with
incompatible land uses, or clear cuts (Harris and Silva-Lopez 1992; Noss and
Cooperrider 1994; Noss et al. 1997).

* Reserves that are roadless and less accessible to human disturbance are preferable to
areas with high road density and access (Noss and Cooperrider 1994; Noss et al.
1996). This principle is born out of the established relation between areas of high
road density and avoidance of such areas by a number of wide-ranging species











sensitive to humans in general or vulnerable to hunting, poaching, and roadkills
including grizzly bear (Ursus arctos) (Mattson et al. 1987; McLellan and Shackleton
1988), wolf(Canis lupus) (Thiel 1985; Mech et al. 1988; Mladenoff 1995), elk
(Cervus elaphus) (Lyon 1983), cougar (Puma concolor) (Van Dyke et al. 1986), and
black bear (Ursus americanus) (Brody 1984; Brody and Pelton 1989).

* Reserves that include native carnivores especially, and wide ranging species
generally, are preferred to reserves without these guilds (Terborgh 1988; Bolger et al.
1991; Soule 1991; Noss et al. 1996; Soule and Terborgh 1999). There are sound
ecological reasons for maintaining and restoring such species. Carnivores are often
keystone species that effect the structure of entire communities ranging from genetics
to species abundance. Keystone functions of carnivores include: controlling tree
seed predators in tropical forests (Terborgh 1988), controlling herbivore and
neotropical migrant bird abundance in the Greater Yellowstone Ecosystem (Berger et
al. 2001a; Berger et al. 2001b), or meso-mammals in southern California chaparral
fragments that benefits native ground/shrub dwelling and nesting bird species (Bolger
et al. 1991; Soule 1991); and wolves providing carrion for other species in
Yellowstone including grizzly bears, eagles, and other species (MacNulty et al.
2001). Carnivores can also be important for maintaining functional evolutionary
relations between predator and prey (Maehr et al. 2001b).

* Reserves that are well distributed across the native range of a species provide a better
opportunity to maintain genetic variation and adaptive responses to local conditions
and temporal environmental changes (Thomas et al. 1990; Wilcove and Murphy
1991; Harris 1992; Noss and Cooperrider 1994; Noss et al. 1997).

Although exceptions are always possible and options must be weighed carefully when

addressing specific situations (Noss et al. 1997), these guidelines have played an

important role in the development of conservation science and planning.

Regional landscape analysis and reserve design are now part of a new natural

resource management strategy that can be termed "regional conservation planning." The

goal of such efforts is to conduct research and planning at sufficiently large spatial scales

to account for the interactions of competing land uses and protect and restore landscapes

that will effectively conserve biological diversity while providing important ecological

services and other natural resources needed to sustain healthy human communities.

Efforts to involve local people in conservation efforts are also a critical part of regional











conservation planning (Jacobson 1995; Meffe and Carroll 1997; Benedict 2000). By

identifying a large scale, regional conservation framework, it is possible to provide a

foundation on which protection of the important ecological properties and processes can

be optimized for multiple benefits at local to regional scales (Noss 1996; Hoctor et al.

2002).

Various efforts to design reserve or ecological networks began in the United

States in the 1990s. The state of Maryland has developed a green infrastructure

assessment to identify areas of highest conservation significance and opportunities to

maintain and restore ecological connectivity (Maryland Greenways Commission 2000;

Weber and Wolf 2000; Weber 2001). The Wildlands Project (Soule and Terborgh 1999)

is engaged in various regional reserve design projects with special focus on wide-ranging

species. Defenders of Wildlife recently completed an analysis of areas most significant

for conserving Oregon's biodiversity and developed policy strategies and incentives to

effect protection (Heagerty et al. 1998). The Nature Conservancy, which until the late

1980s (Noss 1987a) embraced site-specific strategies for conserving biological diversity,

has begun an ambitious biodiversity planning effort called ecoregional planning (Groves

et al. 2000; Groves et al. 2002). All of these projects are based on the fact that regional

landscape assessment is essential to protect biodiversity and ecological integrity.

However, such efforts had already gained momentum in Florida in the 1980s in

response to rapid human population growth and habitat fragmentation (Harris 1984;

Harris 1985; Noss and Harris 1986; Noss 1987b; Harris and Gallagher 1989; Harris and

Scheck 1991; Harris and Atkins 1991). Since then, Florida has completed several

statewide assessments to identify strategic habitats and landscapes that can be integrated











into an integrated reserve network that effectively protects biodiversity and ecological

processes (Millsap et al. 1990; Cox et al. 1994; Florida Greenways Commission report

1994; Cox and Kautz 2000).

Although reserve design has become an important part of conservation practice,

methods for conducting analyses to identify areas of ecological significance and design

reserve networks at regional scales are still in their early stages of development.

Strategies and methods are constrained by funding, time, data availability, data quality,

and software limitations. Because Florida remains at the forefront of applying regional

landscape assessments for identifying and conserving biodiversity, it provides an

excellent opportunity to explore developments and issues in designing reserve networks.

This dissertation develops three comparative and potentially complementary

approaches to regional landscape analysis and reserve design to conserve Florida's

biodiversity effectively. They include identification of a connected statewide network of

intact landscapes and landscape linkages called the Florida Ecological Network;

identification of connectivity options and important habitat blocks for the Florida black

bear (Ursus americanusfloridanus), which may serve as an umbrella species for many

other biodiversity components; and development of ecoregional plans for the Florida

peninsula that integrate fine filter, coarse filter, and landscape approaches for designing

reserve networks. Collectively the three approaches address the four goals and primary

components of reserve design (Noss and Copperrider 1994; Noss 1996; Noss et al. 1999;

Margules and Pressey 2000). The three approaches are discussed in detail to compare

their relative advantages and develop recommendations for additional steps in the











biodiversity reserve design process in Florida and beyond. Policy considerations for

protecting regional ecological networks are also discussed.

Study Area

Florida is an ecologically diverse region ranging in climate and biota from the

temperate to tropical. It is relatively flat with a maximum elevation in the north of

approximately 100 m, and much of the state below elevations of 30 m. There are

approximately 14 million ha in the state with approximately two-thirds of that area

occurring as a long peninsula.

Northern Florida is within the southern temperate zone and harbors broad alluvial

riparian habitats, and upland flats and modest "ridges" once dominated by longleaf pine

(Pinuspalustris) communities. The central peninsula consisted (until recent

development) of broad flatlands dominated by longleaf and slash pine (Pinus elliottii),

dry and wet prairies, and sandy ridges with scrub and sandhill communities harboring

numerous rare and endemic species (Myers 1990). The southern tip of the peninsula,

though heavily modified by development, still contains tropically-influenced hammocks,

swamps, rocklands, and marshes of the Big Cypress Swamp, Everglades, and the Florida

Keys.

Rivers originating in the southern Appalachians and Piedmont are an important

ecological component in north Florida that harbor increasingly rare mollusk and fish

species. Lakes are very common in the Florida peninsula, and Lake Okeechobee in south

Florida is one of the largest lakes in North America. Numerous springs are also

characteristic of the vast limestone regions of north and central Florida. Springs and

limestone caves and sinks also support many rare aquatic invertebrates (Deyrup and











Franz 1994). Estuarine ecosystems include productive saltmarsh communities

dominating the northern half of the state and mangrove and seagrass dominating the

southern half of the peninsula.

The extensive Gulf of Mexico and Atlantic coastlines of Florida significantly

influence a climate that is generally warm and humid. Summer thunderstorms are

frequent, and lightning-caused fires have been an extremely important ecological process

shaping many upland and wetland communities across the state for millennia (Myers and

Ewel 1990). Rains vary from highly seasonal patterns in south Florida with heavy rains

occurring mainly in the summer to more even rainfall year round in northern Florida due

to more frequent precipitation in winter from continental frontal systems (Chen and

Gerber 1990). Freezes occur every year in north Florida but are extremely rare in south

Florida. Freeze events have a strong influence on the range of tropical species up the

Florida peninsula, with such species typically found further north along the coasts, which

are better buffered from freeze events than interior areas because of the warm waters of

the Atlantic and Gulf of Mexico (Harris and Cropper 1992).

Florida's biota is a mixture of southern temperate, neotropical, and even

southwestern species. Sea level rise and fall have been a dominating biogeographic force

controlling the evolution of Florida's biota. The Florida Scrub-Jay (Aphelocoma

coerulescens), eastern diamondback rattlesnake (Crotalus adamanteus), and gopher

tortoise (Gopheruspolyphemus) are all closely related to species found in southwestern

U. S. biomes, which were directly connected to Florida during the much lower sea levels

of Pleistocene glacial periods (Webb 1990). Tropical species have colonized by flying

across the Gulf of Mexico or by riding Gulf Stream currents and include numerous











plants, wading bird species, Snail Kite (Rostrhamus sociabilisplumbeus), and Short-

tailed Hawk (Buteo brachyurus) (Rodgers et al. 1996). In fact, Florida is a premier

birding destination due to the various tropical species that can only be seen or are best

seen in Florida within the United States (Kale and Maehr 1990). Temperate species

include the Red-cockaded Woodpecker (Picoides borealis), and various amphibians, fish,

and mollusk species (Gilbert 1992; Moler 1992; Deyrup and Franz 1994; Rodgers et al.

1996).

Characteristic vertebrate species that has been either extirpated or have gone

extinct since the arrival of Europeans in Florida include the red wolf (Canis rufus), monk

seal (Monachus tropicalis), bison (Bos bison), Ivory-billed Woodpecker (Campephilus

principalss, Carolina Parakeet (Conuropsis carolinensis), Passenger Pigeon (Ectopistes

migratorius), and Bachman's Warbler (Vermivora bachmanii). Extant megafauna

include the Florida panther (Puma concolor coryi), Florida black bear, West Indian

manatee (Trichechus manatus), American alligator (Alligator mississippiensis), and

American crocodile (Crocodylus acutus).

Urgency is the key word for Florida conservation planning. The state is rapidly

developing with a human population of over 16 million and approximately 250,000

additional residents each year (U. S. Bureau of the Census 1996). As a state Florida has

the fourth largest human population in the United States, but its population density is

approximately double that of the largest state, California. Vast urban areas including

southeast Florida, Orlando, Tampa, and Jacksonville continue to incorporate more area at

a rapid rate supported by a dense network of highways with extensive planned

expansions. The rate of rural land loss is approximately 60,000 ha per year, which











represents approximately 1% of the unprotected rural land remaining (Reynolds 1999).

In addition, habitat fragmentation due to expanding urban areas and rapid growth along

major highways threatens to disrupt ecological connectivity and landscape function even

more rapidly in the very near future.

Based on the rate of habitat fragmentation and ever-increasing land costs, the

future of Florida's biodiversity will likely be determined by the conservation planning

conducted and policies enacted over the next ten to twenty years. However, with more

than 20% of the state in public conservation land and large wetland, timberland, and

rangeland tracts still remaining in private ownership, conservation efforts still have the

potential to effectively protect much of Florida's natural heritage. Land acquisition and

conservation easement programs at the federal, state, and local levels will be an essential

component to protect the lands identified in reserve design assessments, and effective

means to manage public and private lands in ways that are compatible with biodiversity

conservation will be an additional challenge.

General Geographic Information System Methods

A Geographic Information System (GIS) consists of integrated hardware and

software that captures, stores, retrieves, analyzes, and displays spatially explicit data.

Geographic data are generally stored in layers, each representing a particular theme, such

as land use, roads or hydrology. Data layers are overlain spatially for analysis of

overlapping features, such as finding residential areas within 100-year floodplains.

Geographic information systems are increasingly being used to assist in analysis and

synthesis of information in environmental planning and design.











GIS applications include conservation as well as other forms of land use planning.

The Florida Fish and Wildlife Conservation Commission (FWC) used GIS to identify

Strategic Habitat Conservation Areas for selected species and communities of

conservation interest (Cox et al. 1994). The federal Gap Analysis Program (GAP)

methodology is dependent on GIS to analyze vegetative communities and identify

potential habitat for all selected species (Scott et al. 1993). Although GIS is now

considered to be extremely useful or even essential for conservation or land use planning,

there have been impediments to its wider application: thematic data accuracy, data

handling and management issues, positional accuracy, lack of data and unwieldy

software. These are gradually being eliminated, ensuring increased future application of

GIS to reserve design and regional conservation planning.

There are two main types of geographic information systems data, vector and

raster. The primary difference between the two types is the way in which geographic

information (features and attributes) is stored. In vector GIS, features are always

represented with either points, lines, or polygons, and associated attributes (information

about the features) are stored with each feature.

Raster-based GIS is a way of storing geographic information in a matrix that is

divided into a grid of equally sized cells. Grid cells are most typically square. Each cell

represents an area on the Earth's surface, for example a cell could represent 1 m2, or 10

m2, or any other convenient multiple. In raster GIS, attribute information is stored with

each cell. Each cell is assigned a value that corresponds to what it contains on the

ground. Cell size is defined by the user and corresponds to the length of one side of one

grid cell.











The cell size determines the grid's resolution, or the finest level of detail that can

be depicted by the data layer. For example, if a cell size of 10 m is chosen, then the

finest level of detail for that map will be 10 m in width and height, and 100 m2 in area.

Features smaller than the cell size can be shown, but they will be represented larger than

their actual size. For example, a road that is approximately 5 m wide (actual width) can

be represented on a 10 m grid, but its width will appear as 10 m. Smaller cell sizes

correspond to higher resolutions.

When working with raster-based GIS, choosing an appropriate cell size is an

important issue that involves consideration of the features being represented/modeled, the

geographic extent of the area of interest, and any existing input data that are already in

raster format. Cell size is important because it determines the level of accuracy in the

features represented (resolution) and dictates (along with study area extent) the computer

processing time needed to run analyses. Of course, the computer hardware being used

also dictates the processing time, but cell size is critical. Furthermore, when choosing a

cell size for a raster GIS analysis, it is important to consider any existing raster data sets

to be used. The cell size chosen would ideally be compatible with, if not equal to the cell

size of existing raster data sets.

Depending on the geographic area and subject of interest, data can be abundant or

scarce. Data can be from various sources, including state and federal agencies, research

institutions, and Data Clearing House websites that compile and organize data for

distribution. In any GIS-based project or analysis, the first step is to frame the question,

develop goals, and create a list of necessary data. Florida is blessed with a large quantity

of detailed GIS information, much of which is stored at the University of Florida's











GeoPlan Center, a primary GIS data repository for the state. The second step involves

taking an inventory of existing data. Thereafter, data gaps can be evaluated and decisions

can be made as to whether there is time or resources to create primary data that may be

necessary, or whether there is a surrogate data source available. Data availability is often

the limiting factor in GIS-based research projects, and sometimes less than ideal data

must be used in order to complete an analysis. However, the availability of GIS data is

increasing, as it has quickly become a popular tool for various planning and management

applications.

Environmental Systems Research Institute's Arc-Info 7.2 and ArcView 3.2

software packages were used to do all of the analysis and modeling for this dissertation.

Although some vector analysis was conducted, the majority of the work used raster

analytical tools in ESRI's Grid module in the Arc-Info software package. Grid utilizes a

map-algebra spatial language that is particularly useful both for conditional combinations

of multiple GIS data layers and conducting quantitative spatial modeling.














CHAPTER 2
THE FLORIDA ECOLOGICAL NETWORK

Introduction

The protection of an integrated reserve system has been proposed in Florida since

the 1980s (Harris 1984; Harris 1985; Noss and Harris 1986; Noss 1987b; Harris and

Gallagher 1989; Harris and Scheck 1991; Harris and Atkins 1991). These proposals

provided critical momentum for the importance of landscape-level planning. They

helped establish that effective biodiversity conservation requires spatial considerations at

large scales to ensure the restoration and maintenance of functional ecological and

evolutionary processes (Harris et al. 1996a; Sanderson and Harris 2002). Included in this

process was a Florida reserve design proposal by Noss (1987b; Noss and Cooperrider

1994) and the results of a mapping workshop coordinated by The Nature Conservancy

that involved a variety of experts to identify conservation priorities and areas of

conservation interest (Figure 2-1).

Building on these proposals, the Conservation Fund and 1000 Friends of Florida

began the Florida Greenways Program in 1991 with the goal of public endorsement and

adoption of a greenways initiative. Next, the Florida Greenways Commission was

appointed by the Governor to explore the utility of creating a statewide greenways

program. It recommended (Florida Greenways Commission 1994) the development and

protection of a statewide greenways system that would include an ecological network

functionally connecting existing conservation lands and other large areas of ecological














N
AA






SOpen water
S Existing conservation lands
TNC charette results
0 90 180 270 360 Miles

Figure 2-1. Results of 1991 mapping workshop (charrette) coordinated by The Nature
Conservancy. The charrette identified conservation priority areas and areas
of conservation interest with some emphasis on ecological connectivity.
Natural resource and biodiversity conservation experts from state, federal,
regional agencies, universities, and NGOs participated to identify the
priorities for the Preservation 2000 state land acquisition program that began
in 1990.









significance. These recommendations were adopted by the state legislature, and the

Florida Department of Environmental Protection was chosen as the lead state agency to

develop an implementation plan.

Identification of the best opportunities for protecting a Florida ecological greenways

network was the first step in the implementation process. I conducted a statewide GIS-

based analysis to identify large areas of ecological significance and landscape linkages to

serve as the ecological component of the Florida greenways program. Florida has a good

foundation of GIS data on species habitats, land uses, hydrology, roads, etc. that are all

relevant for developing landscape-based reserve design analyses to delineate a statewide

ecological network. This chapter covers the methodology developed to conduct the GIS

assessment, the significance of the identified ecological network for conserving Florida's

biodiversity, and some policy considerations for protecting the ecological network. The

goal of this reserve design analysis was to use a regional landscape-based approach to

design a statewide reserve network that accomplishes the following:

* Conserves critical elements of Florida's native ecosystems and landscapes

* Restores and maintains essential connectivity among diverse native ecological
systems and processes

* Facilitates the ability of these ecosystems and landscapes to function as dynamic
systems

* Maintains the evolutionary potential of the biota of these ecosystems and landscapes
to adapt to future environmental changes (Florida Greenways Commission 1994)

Such a network would result in the protection of an integrated reserve system

protecting ecological processes and biodiversity that would not necessarily be achieved

by individual reserves (Harris 1984; Noss 1992). Identification of the reserve network









was accomplished by incorporating assays of ecological significance, such as locations of

rare and listed species, intact ecological communities, habitat areas needed to maintain

viable populations of sensitive species, and land use data, into a reserve design process

that integrates them. The result is the first iteration of an interconnected Florida reserve

system called the Ecological Network (based on the definition by Forman 1995).

Methods

Review Process

Numerous assumptions and decisions about specific parameters and the step

sequence had to be made because of the complexity of the modeling process and the

breadth of goals and objectives. To ensure appropriateness of the assumptions and

modeling decisions and to seek input on the use and application of available statewide

data, technical input was obtained from 1995 through 1997 from the Florida Greenways

Commission, the Florida Greenways Coordinating Council, scientists, university

personnel, conservation groups, planners and others in federal, state, and regional

environmental agencies, and the general public in more than 20 meetings. Those

attending these sessions reviewed the progress of the modeling process and provided

input on the relevant data and thresholds for identifying areas of ecological significance

and landscape linkages.

Analysis Used to Identify the Florida Ecological Network

The GIS decision support model used consisted of four steps (Figure 2-2). The

cell, or pixel, size for the analysis was 180 x 180 m (approximately 3 ha). Use of 180 x

180 m cell size resulted from the necessity to reduce data storage requirements and model

simulation speed. Three ha cells provided enough resolution to identify large connected






21


Step 2
Step 1 Identification Step 4
Identification of of hubs Create
areas of Ecological
I Step 3 Network
ecological significance e 3Network
Identification
of linkages

Figure 2-2. Major steps in the Florida Ecological Network modeling process









landscapes while allowing reasonable computing times on the hardware available when

this analysis was conducted.

Step 1, identification of areas of ecological significance, derived from queries and

re-classification of various GIS data layers including Strategic Habitat Conservation

Areas; priority natural communities; existing conservation lands; roadless areas; and

information on significant aquatic ecosystems. Each of the layers was evaluated to

identify areas with ecological significance, and then all areas with the highest ecological

significance were combined into a single layer called Priority Ecological Areas (PEAs).

The data and thresholds used to identify PEAs are contained in Table 2-1. An area was

included if it met one of the criteria, and no special significance was ascribed to areas

meeting multiple criteria. These areas represented the primary building blocks of the

linked reserve network.

Step 2, selection of hubs, involved the identification of potential core areas for

protection of biological diversity and ecological processes. This process began with the

PEAs layer (Step 1), then identified the areas with the highest ecological integrity

potential through the application of a five part process:

* Intensive land uses ranging from improved pastures and croplands to residential,
commercial, and industrial lands were excluded from consideration. This helped to
rectify potential inconsistencies or errors in data used to determine areas of ecological
priority. Land use data created by each of Florida's 5 water management districts
(WMD) based on both satellite imagery and aerial photography ranging from 1988-
1994 were used for this purpose. Data on the most intensive land uses (urban) were
also updated by using SPOT imagery from 1995-1996 to ensure exclusion of areas
that were no longer suitable.

* Areas of high road density (> 3km/km2) that greatly exceed general road density
standards for protecting sensitive species were excluded from consideration (Noss
1992).









* Areas with the greatest potential for negative edge effects, which were modeled
coarsely as areas within 180 m of urban land uses, were excluded from consideration.
This distance was the minimum edge effect that could be modeled given our cell size
and it was selected as a minimal estimate for the most intensive potential negative
edge effects (Meffe et al. 1997).

* Priority Ecological Areas that remained after this exclusion process that were > 2,000
contiguous ha were selected as Hubs. Reviewers recommended this size threshold
during model development. Such areas are potentially large enough to support many
species and ecological processes while still capturing most areas of ecological
significance (Forman 1995).

* Resulting hubs were consolidated by smoothing edges and filling in internal gaps by
adding lower priority native habitat and potentially compatible land uses such as pine
plantations and rangelands, which were identified by using a combination of the FWC
land cover and WMD land use data.

Step 3, identification of linkages, was the most complicated portion of the GIS

modeling. First, the National Wetlands Inventory classification system (Cowardin et al.

1979) was used as the starting point for deriving three native landscape units or type

(Table 2-2):

* Upland dominated

* Riverine and large wetland basins

* Coastal.

These landscape units served as a logical, broad basis for identifying various potential

landscape linkage types. The landscape units were used to partition hubs into the three

general landscape classes and to develop linkage types.

Next, five linkage types for hubs partitioned into the three landscape types were

identified, including coastal to coastal, riverine to riverine, upland to upland, riverine to

coastal, and cross-basin hub to hub. Linkages between hubs of like types were modeled

before linkages between hubs of different types. The last linkage type, cross-basin (or









Table 2-1. Criteria for selecting Priority Ecological Areas for the Florida Ecological
Network


Data layer

FWCa Strategic
Habitat
Conservation Area
(SHCA)













FWCa Hotspots



FWCa Wetland
Hotspots







FNAlb Areas of
Conservation
Interest (ACIs)



FNAIb Potential
Natural Areas
(PNAs)


Priority area
criterion
All SHCAs
















Areas containing
potential habitat for
7 or more focal
species
Areas containing
potential habitat for
7 or more wetland-
dependent species
or 4 or more
species requiring
both wetland and
upland habitat
All ACIs






All PNAs except
those receiving the
lowest rank due to
significant
disturbance


Explanation

Includes lands outside existing protected
areas needed to maintain or restore
minimally viable populations of 30 focal
vertebrate species, rare natural
community types, important wetlands
for wading birds, and globally rare plant
species (Cox et al. 1994; Kautz and Cox
2001). Many focal species used in this
analysis are umbrella species, whose
conservation requirements meet the
needs of other species. The natural
communities identified represent a
coarse filter approach to protect suites
of species.

Areas containing potential habitat for 7
or more of the focal species analyzed in
the identification of SHCAs. FWC staff
recommended the threshold of 7.
Areas represent wetlands in Florida
with habitat to support additional
wetland-dependent and partially
wetland- dependent vertebrate species.
FWC staff recommended the thresholds.



ACIs were identified outside existing
public lands using aerial photos, natural
heritage data, and expert knowledge.
ACIs are high-quality, relatively pristine
sites that contain occurrences of rare
species.
Includes most of the remaining sites
available to conserve native ecosystems
in Florida, though some disturbance ma
be present and status of tracked species
may not be completely known.









Table 2-1. Continued
Data layer

Rare and priority
natural community
types based on
FWC habitat data
and rankings by
Florida Natural
Areas Inventory
(FNAI)







Existing public
conservation lands
and private
preserves (e.g.,
Audubon,
The Nature
Conservancy)
Proposed public
conservation lands
and easements


Priority area
criterion
All community
types ranked S2 or
higher that could be
identified using the
22 class FWC
landcover map that
included coastal
strand, dry prairie,
sand pine and oak
scrub, sandhill,
tropical hardwood
hammocks,
freshwater marsh,
and wet prairie
All such lands







All such lands


Lands identified as All such lands
part of the Coastal
Barrier Resources
Act


Explanation

FNAI "S" ranks are state ranks based
on The Nature Conservancy's global
rankings (G1 G5, 1 being most
imperiled). The FWC landcover data
are classified LANDSAT TM imagery
from 1985-1989, but due to the coarse
scale of the classification, some S1
communities were not identified in thi
data set. However, these communities
were represented in the SHCA, ACI
and PNA analyses.



Approximately 20% of the state are
now contained in conservation lands.
Though management practices vary
widely, all sites are potentially
significant building blocks for a
statewide reserve system.

Approximately 6% of the state have
been identified for purchase through
Florida's aggressive conservation land
acquisition program. These parcels
were selected based on the presence
of high quality natural communities,
habitat for rare species, opportunities
to protect connectivity, or other
conditions supportive of conservation
objectives.
These areas are typically coastal barrier
islands identified by the federal
government as undeveloped. Such
sites are significant for conserving
coastal ecosystems.









Table 2-1. Continued
Data layer

Roadless areas









Roadless areas
without major
roads









State Aquatic
Preserves,
National Estuarine
Research Reserves
Outstanding
Florida Waters,
Shellfish
Harvesting Waters
Wild and Scenic
Rivers


Priority area
criterion
Areas 2,000 ha or
larger containing nc
roads of any kind







Areas 40,000 ha or
larger containing nc
major roadways
such as interstate,
federal, or state
highways, and large
capacity county
roads



All such designated
aquatic ecosystems


Explanation

Roadless areas are important to species
sensitive to humans, are typically
buffered from disturbance and provide
connectivity for species isolated by
roads. A 2,000 ha area was used based
on federal roadless standards, average
home range size for the Florida black
bear (Ursus americanus floridanus),
and recommendations by reviewers.
Large areas containing no high-volume
roads may be critical for maintaining
many sensitive species especially
wide-ranging animals such as the
Florida black bear and the Florida
panther (Puma concolor coryi). The
threshold is consistent with the FWC's
objective to prevent major road
construction in areas greater than
40,000 ha currently without major
roads.
The greatest dearth in information
about Florida's natural communities
and species is in aquatic ecosystems. In
the absence of such data, these
designated aquatic areas, all indicating
a level of quality that could support
functional aquatic ecosystems, were
used as a surrogate for a more
comprehensive identification of
significant aquatic features.










Table 2-1. Continued
Data layer Priority area Explanation
criterion
Overlap Criteria Moderately ranked Moderately ranked habitat areas and
FWC focal species, roadless areas that overlap with areas
FWC wetland significant for maintaining aquatic
species hotspots, ecosystems and processes are also
and lower ranked significant conservation features.
FNAI PNAs,
smaller roadless
areas (1000 ha or
greater and 20,000
ha or greater
respectively) that
overlap with 100
year floodplains or
areas of significant
aquifer recharge
a The Florida Fish and Wildlife Conservation Commission was previously named the
Florida Game and Fresh Water Fish Commission.
b Florida Natural Areas Inventory









Table 2-2. Landscape unit classification used in landscape linkage identification for the
Florida Ecological Network
Landscape Unit Ecosystems


open coastal waters;
coastal strand;
coastal salt marsh;
mangrove


Riverine and
large wetland
basins


inshore marine habitats;
all other native habitats within
contiguous 100-year coastal
flood zone


Open waters of major Florida rivers (FREAC 1990), plus the
following when contiguous to major rivers or > 400 ha:
bottomland hardwood forest
mixed hardwood swamp
cypress swamp
shrub swamp
freshwater marsh and wet prairie
freshwater aquatic habitats
bay swamp
open lake waters


Upland
dominated


dry prairie; flatwoods;
xeric scrub; sandill;
mixed hardwood-pine
forest


hardwood forest; tree
plantations; wetland/isolated
aquatic habitats when less than
400 ha


Coastal









general hub to hub), was a broad category that permitted exploration of linkage feasibility

between, for example, an upland ridge system and a neighboring river corridor or through

agricultural landscapes where some restoration may be needed to restore connectivity.

An algorithmic function called least cost path was used to identify landscape

linkages. Suitability surfaces (cost surfaces in Arc-Info parlance) were created to

represent the relative suitability of each cell for potential inclusion in a linkage. Five

different suitability surfaces were created with one for each linkage type. The value

assigned to each cell was inversely proportional to its relative suitability for that linkage

type, (e.g., a cell with the value of 1 is most suitable, 2 next, etc.) (Figure 2-3, Table 2-3,

Table 2-4). The function also allows for identification of unsuitable cells where a

potential linkage cannot be located. The relative suitability of each cell was determined

by querying original data layers and data layers derived in Steps 1 and 2. Suitability

surfaces ranged from simple for the same type linkages such as riverine to riverine (Table

2-3) to complex for the general hub linkages that required a much broader range of

suitability values to discriminate between highly suitable and much less suitable areas

(Table 2-4).

The least cost path function was then run to find the optimal path for selected hub

pairs for each linkage type. Accepted paths were widened to include all contiguous cells

of native habitat or lower intensity land uses, up to 25% of the linkage length. Such

landscape linkages are more likely provide functional movement corridors, maintain

habitat gradients from aquatic to upland ecosystems, and buffer aquatic ecosystems in

riverine and coastal landscapes (Harris and Scheck 1991; Noss 1993; Forman 1995).









Table 2-3. Riverine suitability surface values for the Florida Ecological Network
Category Value
Criteria for highly suitable areas

Open water associated with major Florida rivers classified as Priority la
Ecological Area (PEA)

Freshwater wetland ecosystems classified as PEAs 1

Open water associated with major Florida rivers classified as SEAb 2

Freshwater wetland ecosystems classified as SEAb 2
Criteria for moderately suitable areas

Open water associated with major Florida rivers not classified as 3
PEA or SEAb

Freshwater wetland ecosystems not classified as PEAs or SEAsb 3
Open water and areas with high road density or negative edge effect 4
Areas with high road density or negative edge effect that meet the 4
riverine open water or freshwater wetland criteria for this linkage
type
Criteria for unsuitable areas

Intensive agriculture and urban lands No value

All other cells No value
a The lower the value the higher the suitability.
b SEA or Significant Ecological Area, was an area meeting criteria for moderate
significance such as moderately ranked FWC hotspots and FNAI Potential Natural Areas.









Table 2-4. Hub-to-hub suitability surface values for the Florida Ecological Network
Category Value

Priority Ecological Areas (PEAs) that meet all but the 2,000 hectare size la
criteria for hubs and are contiguous to significant coastal and/or inland
aquatic features

Other PEAs that meet the 2,000 hectare size filter 2

SEAsb that are contiguous to significant coastal and/or inland aquatic 2
features

Native habitat contiguous to significant coastal and/or inland 3
aquatic features

All remaining SEAsb 3

All other native habitat 4

Low intensity land use/land cover contiguous to significant coastal 4
and/or inland aquatic features

All other low intensity land use/land cover 5

Native habitat lands with areas of negative edge effects or areas of high road 600
density

Lands with low intensity use and areas of negative edge effects or areas of 700
high road density

Improved pasture contiguous to significant coastal and/or inland aquatic 7,000
features

Cropland contiguous to significant coastal and/or inland aquatic features 8,000

All other lands in moderate intensity use, contiguous to significant coastal 9,000
and/or inland aquatic features

Improved pasture 70,000

Cropland 80,000

All other lands with moderate intensity use 90,000






32



Table 2-4. Continued
Category Value

Open water 100,000

Urban lands No value

All other cells No value
a The lower the value the higher the suitability.
b SEA or Significant Ecological Area, was an area meeting criteria for moderate
significance such as moderately ranked FWC hotspots and FNAI Potential Natural Areas.




















H-ighest suitability
SHigh suitability
=Moderate suitability
=Low suitability
Not suitable













0


100 150 KIlomaters


Figure 2-3. Riverine cost surface example. This example from south central Florida and
the Kissimmee River basin (headwaters of the Everglades) of a suitability
surface used for identifying potential riverine and large wetland basin
landscape linkages and corridors where only wetlands and fresh water
ecosystems are considered suitable and are valued based on their resource
significance.










Step 4, creation of the Ecological Network, was achieved by combining the

identified hubs and linkages.

Results

Florida still supports large areas of intact native ecological systems and

potentially compatible land uses that can serve as a connected statewide reserve system.

The Ecological Network links the larger public conservation lands, while also

incorporating other important landscape features of each region (Figure 2-4). In the

Florida Panhandle, the numerous rivers that flow north to south (such as the

Apalachicola) form a network from the Blackwater River State Forest and Eglin Air

Force Base to the Apalachicola National Forest. North-central Florida is dominated by

the Suwannee River corridor, which links the lowlands of the Big Bend on the Gulf Coast

to the Osceola National Forest--Pinhook Swamp--Okefenokee National Wildlife Refuge

complex, and a large landscape linkage parallel to the western shore of the St. Johns

River that connects the Ocala and Osceola National Forests. In central Florida, river and

swamp basins including the Kissimmee, Peace, St. Johns, Myakka, and Withlacoochee

Rivers join the sandhills and scrub of the Lake Wales Ridge and Brooksville Ridge and

provide the primary elements of a network that includes the Ocala National Forest, Green

Swamp, Three Lakes Wildlife Management Area, and Avon Park Bombing Range.

Southern Florida is dominated by the Everglades National Park--Big Cypress National

Preserve complex. This complex is linked to landscapes in central Florida via

Okaloacoochee Slough and Fisheating Creek west of Lake Okeechobee, and via the

Corbett Wildlife

















EglinAir
Force Base


rW'


,WMA


Everglades-
Nan oal
Park


Figure 2-4. Florida Ecological Network model results. The results include existing and
proposed conservation lands within the ecological network. Existing
conservation includes all public lands with some conservation management
and private preserves. Proposed conservation lands include all projects
within official federal, state, regional and local land acquisition/protection
programs. Although the ecological network includes water within all of the
major rivers and most intact estuarine systems, these features have not been
differentiated from other areas of open water in this figure.


B EXISTING CONSERVATION
LANDS WITHIN THE
ECOLOGICAL NETWORK
H PROPOSED CONSERVATION
LANDS WITHIN THE
ECOLOGICAL NETWORK
ECOLOGICAL NETWORK
OUTSIDE OF EXISTING
AND PROPOSED
CONSERVATION LANDS

OPEN WATER

ALABAMA, GEORGIA

80 0 80 160 KM
r









Management Area and ranchlands containing flatwoods, prairies, and sloughs northeast

of Lake Okeechobee.

Of the approximately 9.3 million ha (57.5% of the state) incorporated into the

Ecological Network, 4.8 million ha (52.2% of the network) are within existing public

conservation lands of various federal, state, regional, and local designations, private

preserves (such as those owned by The Nature Conservancy), or open water (considered

public domain by Florida statute). Thus, less than half of the identified Ecological

Network occurs on private land that may need protection (Table 2-5). Of the private land

included in the Ecological Network, more than 50% occurs within an existing

conservation project, wetlands, or in 100-year floodplains. Although these areas may be

more easily protected than the 2 million ha of uplands occurring in private ownership,

approximately 4.5 million ha of private land is still identified in the model results.

Comparisons to Other Ecological Inventories

For Florida, good analyses and data indicate priority areas for conserving

biological diversity. Two key analyses used in the ecological model are the Strategic

Habitat Conservation Areas identified by the Florida Fish and Wildlife Conservation

Commission (FWC) (Cox et al. 1994; Kautz and Cox 2001) and Florida Natural Areas

Inventory's (FNAI) Areas of Conservation Interest and Potential Natural Areas (FNAI

2001) (Table 2-1). Although many other data were used in this study, the FWC and

FNAI data were integral to identifying a connected statewide reserve system. Because of

the details and sequence of the modeling process, not all areas contained within the FWC

or FNAI data were included in the Ecological Network. For example:









* The lowest ranking FNAI Potential Natural Areas were not automatically included
because of the level of disturbance found on lower priority sites.

* Areas of intensive land use identified from data sources more current than the FNAI
and FWC data were excluded from consideration.

* Any area included in FNAI and/or FWC results that did not occur within a hub
totaling at least 2000 ha was not included in the Ecological Network unless it was
incorporated within landscape linkages selected to connect hubs.

Comparison between the FWC and FNAI data and the Ecological Network is a

useful measures of the significance of the model results for conservation of focal species

and natural communities. Over 80% of the Strategic Habitat Conservation Areas and

over 68% of the Areas of Conservation Interest and Potential Natural Areas are contained

in the Network (Table 2-6). Most of the Strategic Habitat Conservation Areas that did

not overlap with the Ecological Network are either isolated wetlands and scrub or areas

recommended to conserve the Crested Caracara in south-central Florida that often

overlapped with improved pastures that were excluded from consideration in the hub

identification process. Moreover, 80% of the Network is at least one of the following:

* Existing or proposed conservation lands

* Inland or coastal waters

* Strategic Habitat Conservation Areas

* Areas of Conservation Interest and Potential Natural Areas.

This suggests that the remaining 20% of the Network contains other suitable areas that

integrate these primary ecological features spatially into a statewide ecological network

(Figure 2-5).









Table 2-5. Area of land in various land ownership categories within Florida's Ecological
Network
Percentage of Percentage
Land Use Hectares state area of model
results
Public ownership 3,239,476 20.0 34.8
Open water (outside existing 1,613,418 10.0 17.4
conservation areas)
Proposed public conservation lands 985,936 6.1 10.6
Private ownership in wetlandsa 701,650 4.3 7.5
Private ownership in 100 yr. 656,691 4.1 7.1
Floodplainab
Private ownership in uplandsa 2,101,559 13.0 22.6
Totals 9,298,742 57.5 100.0
a Ha of private ownership in wetlands, 100 yr. flood plain and uplands is calculated as if
all proposed public acquisitions are/will be completed.
b Floodplain data were not available for Bradford, Columbia, Dixie, Gilchrist, Hamilton,
Jefferson, Lafayette, Madison, Okeechobee, Taylor, and Union Counties, so the statistics
shown above underestimate total floodplain.










Table 2-6. Comparison of the Florida Ecological Network, other ecological resource
inventories, and existing and proposed conservation lands
Area of Percent of
Area of
Comparison category Percent category
Comparison . category in Percel
within of model within the r
categones model results model study area of state
model results model
results (ha) results (ha)
State N/A N/A N/A 16,175,928 100.0


nt
te


Ecological
Network model
results

FWCa Strategic
Habitat
Conservation
Areas (SHCAs)

FNAIb Areas
of Conservation
Interest and
Potential
Natural Areas
(ACIs)


9,298,742 100.0




1,586,567 17.1





1,521,085 16.4


Existing or 7,539,052 81.1 81.4 9,259,270 57.2
proposed
conservation
lands; open
water; SHCAs;
or ACIs
a Florida Game and Fresh Water Fish Commission (renamed Florida Fish and Wildlife
Conservation Commission in 1999)
b Florida Natural Areas Inventory


N/A




80.6





68.7


9,298,742




1,968,587





2,214,813


57.5




12.2





13.7



























Open water
Conservation lands
Existing
Proposed
FWC SHCAs
f i FNAI ACIs and PNAs
] Florida Ecological Network
0 50 100 150 Miles

Figure 2-5. Comparison of the Ecological Network other statewide ecological resource
inventories. Though the overlap of the Florida Ecological Network with the
Florida Fish and Wildlife Conservation Commission's Strategic Habitat
Conservation Areas and the Florida Natural Area Inventory's Areas of
Conservation Interest and Potential Natural Areas is high, the Florida
Ecological Network identifies additional lands that would help integrate all
lands into an integrated network.









Landscape Comparisons

Since the Florida Ecological Network is almost three times as large as the total

area within existing conservation lands (9.3 million ha versus 3.2 million ha), a logical

conclusion or hypothesis is that the Ecological Network would better protect large

landscapes. These large landscapes should have a better opportunity to protect functional

ecological processes (such as the interplay of flooding and fire in intact landscapes of the

southeastern United States) and viable populations of wide-ranging species and most

other species of conservation interest (Harris et al. 1996a). Several landscape-level

comparisons between existing conservation lands and the Ecological Network help to

bring specificity to this conclusion.

Wetland-upland adjacencies

In Florida, wetland-upland adjacency or juxtaposition is a critical landscape

feature that mediates important ecological processes and is essential for providing habitat

for many species of conservation interest (Harris 1988; Echternacht and Harris 1993;

Harris et al. 1996a). In this comparison, areas containing natural and semi-natural upland

patches (all natural upland communities and pine plantation) of 400 ha or larger adjacent

to all wetlands 40 ha or larger were identified. Of these areas containing adjacencies of

large uplands and wetlands, existing conservation lands contained 32% of the area,

whereas the Florida Ecological Network contained 88% of the area. Although this

analysis does not include information regarding the intactness of these wetland-upland

complexes, degree of interspersion, or other potential measures of significance, it does

suggest that the Ecological Network greatly enhances the representation of landscapes

containing functional blocks of large wetlands and uplands.









Small or ephemeral wetland complexes

Another critical component of landscapes in Florida is the presence of small,

often ephemeral, wetlands. Such wetlands provide seasonally important foraging habitat

for many species, including various wading birds such as the federally-listed Wood Stork

(Mycteria americana); and essential breeding habitat for various, increasingly rare,

amphibian and reptile species (Moler 1992; Cox et al. 1994; Burke and Gibbons 1995;

Dodd and Cade 1998; Gibbs 1998; Haig et al. 1998; Semlitsch 2000; Snodgrass et al.

2000; Joly et al. 2001; Joyal et al. 2001). To identify landscapes containing significant

complexes of isolated wetlands, I conducted a neighborhood or shifting window analysis

to identify all areas containing natural and semi-natural uplands that were also comprised

of 5% or more isolated wetlands (defined as all wetlands 2 ha or smaller) within a 2 km2

window. Such areas are more likely to support functional metapopulations of ephemeral

pond breeding species and important foraging habitat for many other species (Cox et al.

1994; Dodd and Cade 1998; Semlitsch 2000; Snodgrass et al. 2000; Joyal et al. 2001).

Existing conservation lands contain only 18% of such areas, whereas the Ecological

Network contains 61%.

Wetland biodiversity in general, and ephemeral pond breeding amphibians in

particular, are very sensitive to impacts associated with roads and increasing road

densities (Gibbs 1998; Findlay and Bourdages 2000). Therefore, I also identified

landscapes containing 5% or more isolated wetlands (as identified above) that were

within 400 ha or larger roadless blocks (defined as areas containing no paved roads).

Existing conservation lands encompass 23% of such areas, whereas the Ecological

Network contains 78%. Although more specific analysis is needed regarding landscape









integrity (such as differentiating areas with well-managed upland forests from low

integrity forests), this comparison suggests that the Ecological Network provides much

greater opportunity for protecting functional complexes of small wetlands.

Roadless areas

The importance of roadless areas for conserving landscapes with high integrity

cannot be overstated. Roads have a myriad of impacts including fragmentation, isolation,

mortality, disturbance effects, and pollution that can severely impact biodiversity (Noss

and Cooperrider 1994; Reed et al. 1996; Reijnen et al. 1997; Findlay and Bourdages

2000; Jones et al. 2000; Trombulak and Frissell 2000; Develice and Martin 2001;

Strittholt and Dellasala 2001; Heilman et al. 2002). Another important comparison

between existing conservation lands and the Florida Ecological Network is the number of

roadless areas with each. I identified roadless areas using different subsets of Florida's

roads system and different roadless area sizes. In all cases, the Florida Ecological

Network contains substantially more roadless areas and total roadless area than contained

in existing conservation lands (Table 2-7).

Representation

Representation analysis involves comparing features of ecological significance

(usually natural communities or species) with existing protected areas to determine which

features require greater protection (Scott et al. 1993; Noss 1996). I conducted a coarse

analysis of habitat representation by comparing total existing ha of major natural

communities (Cox et al. 1994) with the amount found in existing conservation areas and

the Ecological Network. Although some important elements are not included in the

Ecological Network, it is clear that the identified Ecological Network enhances the









Table 2-7. Comparison of roadless areas found in existing conservation lands and the
those included in the Ecological Network. Comparisons include the total
number of roadless patches and total roadless areas for two road class types
(major roads versus all roads) and various roadless patch sizes.
Existing Florida Florida
Roadless area conservation Ecological Existing Ecological
type lands Network conservation Network
number of number of lands total area
patches patches total area (ha) (ha)


Intrastate
Highway System
(contains all major
paved roads)
40,000 ha or larger
20,000 ha or larger
4,000 ha or larger

All Roads
(including unpaved)
40,000 ha or larger
20,000 ha or larger
4,000 ha or larger


52
100
274


104 190


2,597,989
2,919,142
3,777,137


1,230,823
1,417,061
2,099,166


5,479,562
6,832,500
8,551,438


1,887,800
2,175,800
3,394,887









protection of each community type (Table 2-8). The increases for sand pine scrub, xeric

oak scrub, and longleaf pine sandhill are of particular significance. These community

types are endangered globally; and provide habitat for many endangered, threatened, and

endemic species, as well as a host of species that are candidates for listing (Myers 1990;

Noss et al. 1995; Platt 1998).

Conserving most of the intact natural and semi-natural landscapes in Florida may

prove to be an effective coarse filter strategy (Noss 1996) for protecting most of Florida's

biological diversity, but this strategy must be complemented by more focused analyses

for specific rare natural communities and species that may not be well represented by

focal species analyses (Caro and O'Doherty 1999) or coarse habitat classifications (Noss

1996). I compared the Ecological Network to element occurrence information for natural

communities and rare species from the Florida Natural Areas Inventory (FNAI 1997).

Of 69 natural communities contained in the FNAI data, all 69 had at least one occurrence

in the Ecological Network, and only 4 had less than 50% of their occurrences within the

Ecological Network. Analysis of rare species occurrences showed there are 32 species

(mostly plants) not known to be found on existing conservation lands or within the

Ecological Network. These taxa represent only 6% of the species and subspecies

analyzed. Therefore, most rare natural communities and species are represented in

existing conservation areas and the Ecological Network, but more work needs to be done

to assess whether this representation is sufficient and to identify other areas needed to

viably protect those that are not adequately protected.











Table 2-8. Comparison of the total land area of existing ecological community types
(habitats) in the state of Florida with area of habitat types found in existing
conservation lands and the amount included in the Ecological Network.


Ecological
community
type


Coastal strand
Dry prairie
Pinelands
Sand pine scrub
Sandhill
Xeric oak scrub
Mixed
hardwood-pine
forests
Hardwood forest
Tropical
hardwood forest
Saltmarsh
Freshwater
marsh/wet prairie
Cypress
Mixed hardwood
swamp
Bay swamp
Shrub swamp
Mangrove
swamp
Bottomland
hardwoods


Total Area in
area (ha) existing
conservation
lands (ha)


3,145
133,334
413,066
105,501
146,250
22,272
46,532


Total habitat
in existing
conservation
lands (ha)

73.4
25.6
25.0
80.1
37.5
42.3
12.0


818,030 185,651 22.7
5,872 3,313 56.4


121,584
778,923


621,504 253,454
1,076,484 276,915


16,763
152,976
198,100


40,033 23,532 58.8


Area in
Ecological
Network
(ha)

3,475
422,050
1,076,578
117,500
248,888
38,967
197,300


Habitat
in
Ecological
Network
(ha)
81.2
81.2
65.2
89.2
63.8
74.0
50.9


530,194 64.8
4,210 71.7

182,616 93.3
1,023,724 88.8

546,964 88.0
864,698 80.3


47,102
222,950
221,703


39,926 99.7


Increase Percent
in increase
protected in
area (ha) protected
area
330 7.7
288,716 55.5
663,512 40.2
11,999 9.1
102,638 26.3
16,695 31.7
150,767 38.9


344,544 42.1
897 15.3

61,032 31.2
244,801 21.2

293,509 47.2
587,783 54.6


30,339
69,974
23,603


16,394 41.0


4,281
519,895
1,651,235
131,708
390,056
52,628
387,889


195,710
1,153,285


57,968
252,327
229,012









Discussion

The Florida Ecological Network, identified as part of the Florida Statewide

Greenways planning process, is another significant step toward protecting an integrated

state reserve system for biodiversity conservation. Harris (1985), Noss (1987b), and The

Nature Conservancy recommended connected reserve systems through intuitive

representations of networks and mapping charrettes. The Strategic Habitat Conservation

Area analysis by the Florida Fish and Wildlife Conservation Commission and the natural

areas identification by the Florida Natural Areas Inventory provided systematic assays to

identify priority areas for conservation (Mann 1995). The progress represented by the

design and execution of the Ecological Network delineation process was the combination

of a systematic landscape analysis of ecological significance; and the identification of

critical landscape linkages; in a way that can be replicated, enhanced with new data, or

applied at different scales.

The Ecological Network connects and integrates existing conservation areas and

unprotected areas of high ecological significance. The network can be used in concert

with other information on conservation priorities to develop a more integrated landscape

protection strategy. Such an integrated reserve network will more thoroughly protect

important ecological functions, community and landscape juxtapositions, and biotic

connectivity than the present collection of isolated conservation areas (Noss and Harris

1986; Harris et al. 1996a; Harris et al. 1996b). The Ecological Network also includes

most of the intact natural communities and most known occurrences of species tracked by

FNAI. These factors suggest that the Ecological Network will be integral to efforts to

conserve Florida's biological diversity.









Although the Ecological Network model represents an important step in Florida's

conservation strategy, many issues and questions still need to be addressed. Among these

is the need for a more thorough analysis of the relation between the model results and

specific conservation needs for sensitive species and all communities. In the process of

identifying potentially viable reserve networks, Noss (1996) recommended three primary

steps: special element mapping, representation analysis, and area-dependent species

analysis. Although these steps were incorporated in the Ecological Network delineation

process, there are still gaps in the analysis. The model benefited from previous analyses

of habitat needed to protect potentially viable populations of 30 focal species. Cox et al.

(1994) however, limited the strategic habitat conservation area recommendations for the

Florida panther to within or near the area currently occupied by the known breeding

population in southwest Florida. Their recommendations for the Florida black bear were

limited to expanding the habitat base for the five largest populations left in the state.

These recommendations are essential, but a large connected reserve network in Florida

will significantly enhance survival prospects for these umbrella species, as well as the

ecological integrity of the landscapes they would occupy (Harris et al. 1996b; Maehr

1997b; Maehr et al. 2001a; Maehr et al. 2001b; Maehr et al. 2002b).

Although the Ecological Network model has identified connected landscapes that

may provide functional connectivity and promote the re-establishment of statewide

populations, species-specific analyses should be conducted for both the Florida panther

and black bear to establish this possibility better. Broad landscape analyses of

connectedness are useful, but species-specific analyses are essential for determining

potential for connectivity of particular populations and identifying minimal viable areas









for metapopulations (Beier 1995; Maehr and Cox 1995; Beier 1996; Beier and Noss

1998).

One of the most discussed issues in the model development process was

determination of minimum hub size. Several reviewers felt that areas at least as small as

400 ha should also be considered because areas need not be 2,000 ha or larger to be

ecologically significant and because the completed Ecological Network could draw

attention away from the conservation significance of smaller, isolated tracts. Isolated

sites can contain critical elements of biodiversity that should be protected as part of a

statewide reserve system (Shafer 1995).

One of the most important steps within a reserve design process is a thorough

representation of all native ecological communities and species (Noss and Cooperrider

1994). Not all important sites and species are contained within the model: results did not

include globally imperiled pine rocklands in southeast Florida (Snyder et al. 1990) and

oak scrub tracts along the Lake Wales Ridge that support many rare and endemic species.

More work is required to assess the needs of specific rare species and natural

communities, especially in aquatic systems (Hoehn 1998).

Another important consideration in a reserve design process is identification of

potential core areas, corridors, and buffers (Harris 1984; Noss and Harris 1986; Noss and

Cooperrider 1994; Soule and Terborgh 1999). In the Ecological Network delineation

process, hubs were used as destinations, but they cannot typically be considered

equivalent to core areas, where core areas are defined as reserves managed exclusively or

primarily for conserving biological diversity (Scott et al. 1993; Noss and Cooperrider

1994). The few managed areas in Florida that might meet this definition include The









Nature Conservancy and National Audubon Society preserves, some designated

wilderness areas, national parks, and state preserves. Yet, many of these areas allow uses

contradictory to core area ideals; or suffer from external threats or disruption of natural

ecological processes (including fire suppression) and changes in hydrologic regimes

(such as in Everglades National Park).

There is a need to identify other areas within the Florida reserve system that might

also be managed with greater emphasis on biodiversity. Much of the land identified in

the Ecological Network is managed for multiple uses. Except in south Florida, much of

public land area in Florida is within National Forests and military reservations where

biodiversity is only one of many management objectives (Noss and Cooperrider 1994).

Although strides have been made under the rubric of ecosystem management on military

reservations (Gordon et al. 1997) and to some extent within the National Forest system

(Salwasser et al. 1996).

Even though there are extremely important and high quality natural communities

found on private lands, much has been converted to conifer plantations or rangelands

(Kautz 1993). These areas may be the buffer areas of a future Florida conservation

reserve system, but the model did not include the specific identification of buffer areas.

In some cases, there may be a need to identify buffers for narrower corridors and potential

bottlenecks especially around network components in central and south-central Florida

(Figure 2-4). Although these network elements are primarily surrounded by low intensity

agriculture currently, their function could be endangered if land uses intensify.

Identification of core areas and buffers will be an important part of the reserve

design process in Florida. However, the focus for now should be on prioritizing lands for









protection from conversion to more intensive uses because of rapid human population

growth and the consequent habitat loss and fragmentation. This raises questions about

how much land must be protected to meet biodiversity conservation objectives (Noss

1996; Soule and Sanjayan 1998). Furthermore, guidelines are needed so that the most

critical lands are protected first. Although Florida has committed at least $300 million

per year since 1990 for land acquisition and related conservation efforts, the

approximately 4.4 million ha within the Ecological Network might require at least 3 to 4

decades to protect at current funding levels.

Such a need for setting priorities also involves the debate about the importance of

protecting corridors versus protecting core areas of high-quality habitat (Simberloff and

Cox 1987; Noss 1987c; Simberloff et al. 1992; Hobbs 1993; Beier and Noss 1998). How

are state conservation decision-makers to choose between these alternative strategies?

The Florida Greenways Project provides some insight. First, these approaches are not

mutually exclusive. Prioritization of land protection can include both considerations.

Landscape linkages that also contain high quality habitats needed to maintain viable

populations of sensitive species can be identified.

The high degree of overlap among the ecological greenways network model

results, Strategic Habitat Conservation Areas, and priority sites identified by the Florida

Natural Areas Inventory suggests that this will occur frequently (Figure 2-7). Then,

landscape linkages most significant for facilitating connectivity for wide-ranging species

and isolated sites containing critical elements of biodiversity should also be identified as

priorities. Though additional debate about landscape linkage and corridor projects is

likely, connectivity has been accepted as a critical reserve design principle (Harris et al.









1996b; Beier and Noss 1998). Because natural landscapes are generally connected, the

burden of proof for not including connectivity should be on those remaining skeptical

about the need to protect landscape linkages and corridors and not vice versa (Noss

1987c: Noss 1991; Beier 1996; Beier and Noss 1998). There would always be the option

to sever linkages in the future if deemed necessary, but the opportunity to protect existing

landscape linkages or to restore them will diminish rapidly as Florida's human population

continues to grow.

Another challenge is to retrofit the existing highway system in Florida and to plan

future road projects to be as compatible as possible with the protection of a statewide

reserve system. The Florida Department of Transportation has made significant progress,

including construction of a comprehensive system of underpasses where Interstate 75

crosses the Big Cypress National Preserve that is allowing Florida panthers and many

other species to cross under the highway safely (Foster and Humphrey 1992). One

underpass has been constructed at a black bear roadkill hotspot in central Florida; and

more are planned (Roof and Wooding 1996). A comprehensive assessment of all

potential interfaces between major roads and priority ecological conservation areas for

future mitigation (e.g., lengthening existing bridges and culverts, constructing new

wildlife underpasses) coordinated with the Ecological Network modeling process has also

recently been completed (Smith 1999). However, there is still a need to avoid major new

road projects, several of which now threaten important elements of the Ecological

Network.

Reserve design is an iterative process that must continually consider new

information. Work on refining and enhancing a Florida reserve network is progressing in









several projects and scales. Florida's federal GAP analysis project was just recently

completed, and the Florida Fish and Wildlife Conservation Commission continues to

analyze additional species. These and other projects likely will identify priorities that

should be addressed in future iterations of a state reserve system plan, and, as always,

field assessments of priority sites need to be done as part of the protection process. As

land development continues, loss of habitat must be monitored and conservation plans

adjusted as necessary. Finally, considering Forman's "ethics of isolation" (1987), work at

the next scale is being conducted with Region 4 of the U.S. Environmental Protection

Agency to identify a regional ecological conservation network for the southeastern United

States (Hoctor et al. 2002), which could lead to coordination with other efforts to identify

and protect reserve networks in North America (Soule and Terborgh 1999).














CHAPTER 3
LANDSCAPE CONNECTIVITY FOR THE FLORIDA BLACK BEAR

Introduction

The Florida black bear is the most common of four documented wide-ranging

species found in Florida at the time of European exploration and settlement of North

America. The bison and red wolf disappeared from Florida before the early 1900s

primarily because of persecution (Humphrey 1992). The only breeding population of the

Florida panther is now relegated to extreme southwestern Florida in a small population

that is threatened by habitat loss and fragmentation caused by residential, commercial,

industrial, and agricultural development (Maehr 1997b; Maehr et al. 2001a; Maehr et al.

2001b; Maehr et al. 2002a). In contrast, the Florida black bear remains in five larger and

several smaller sub-populations across Florida, southern Georgia, and Alabama (Brady

and Maehr 1985). Although its range has also been drastically reduced, a regional

landscape approach to Florida black bear conservation could result in the protection of a

statewide metapopulation with a strong likelihood of survival into the future. Further, it

can serve as a flagship and umbrella species for landscape-level conservation in Florida

that may greatly enhance the protection and restoration of native biodiversity.

Landscape ecology has lead to a significant broadening in the focus of

conservation research, planning, and management (Forman 1987; Turner 1989; Forman

1995; Pickett et al. 1997). Coupled with the growth of this discipline is an increasing

awareness of the spatial needs and landscape considerations involved in protecting viable

populations of large carnivores and other wide-ranging species (Schoen 1990; Noss et al.

54









1996; Samson and Huot 1998). Landscape ecology is increasingly necessary due to the

importance of habitat heterogeneity and the large spatial scales needed to maintain many

species. Effective conservation of wide-ranging species depends on a landscape focus

that incorporates natural levels of spatial and temporal heterogeneity, while minimizing

the negative effects of artificial edges and barriers (Harris et al. 1996a). Wide-ranging

species such as the Florida black bear require large areas to support functional

demographics (Maehr et al. 200 b).

Black bear are species of the landscape because of their large home ranges and

typical dependence on more than one vegetation association or ecological community

type (Harris and Kangas 1988; Schoen 1990; Maehr 1997a; Samson and Huot 1998).

Schoen (1990, p. 146) explicitly linked bear management to landscape ecology:

In fact, a narrow concept of habitat may be inapplicable for bears, which are
wide-ranging creatures of landscapes rather than habitat types per se. Clearly,
the normal movements of bears are so extensive that bear habitat must be
evaluated and managed on a landscape scale often exceeding thousands of square
kilometers .... Even in large areas, managers should be as concerned about the
composition and status of the surrounding habitat as they are about the area they
wish to conserve.

Habitat loss and fragmentation is another key reason for landscape-level

management (Wilcox and Murphy 1985; Wilcove et al. 1986; Harris and Silva-Lopez

1992). Essentially all bear species have been impacted by habitat loss and fragmentation

that has resulted in range contractions, smaller populations, and populations that are more

isolated from one another (Schoen 1990; Mattson 1990; Noss et al 1996).

The direct impact that the outright loss of habitat on black bears is obvious: less

habitat means fewer bears. However, the effects of fragmentation are more subtle, yet

pernicious. As habitat patches become smaller, bear populations also are reduced in size,

and populations become more isolated or often completely separated. This can lead to









several processes adversely affecting the survivability of small populations: demographic

stochasticity, inbreeding, negative edge effects, and catastrophic events (Harris and Silva-

Lopez 1992). Even if a small population does persist, it will probably lose genetic

diversity through genetic drift, and, therefore, have a reduced ability to survive future

environmental changes.

Habitat loss and fragmentation have resulted in vast reductions in the area

occupied by the black bear. It used to be found throughout North America where

sufficient forest cover existed (Maehr 1984b; Pelton 1986). As forests have been cleared

for development, occupied black bear range has receded into more remote, inaccessible

areas such as mountains, boreal forests, and large swamps. In the eastern United States

and especially the southeast, black bear habitat is quickly being relegated to only

scattered, large public lands (Pelton 1986).

The range of the Florida black bear shows the same trend of contraction and

fragmentation (Hellgren and Maehr 1992; Cox et al. 1994). The Florida black bear is

now restricted to approximately 27% of its former range in seven "more-or-less separate"

populations (Kasbohm and Bentzien 1998) including those in southeast Georgia and

southwest Alabama. In Florida, the bulk of the former and existing range of the black

bear, large forests are being whittled away and fragmented. Although approximately

40% of bear habitat in Florida is in public ownership, habitat on private lands are under

ever-increasing development pressure as human populations continue to grow. Kasbohm

and Bentzien (1998) suggest that four of the existing populations (Apalachicola, Osceola-

Okefenokee, Ocala, and Southwest Florida) are viable, though they acknowledge that at

least two of these (Ocala and Southwest Florida) will suffer habitat loss and population

reductions due to continued rapid habitat loss and fragmentation.









Land development trends near Jacksonville and in the panhandle (such as new St.

Joe Company residential development) suggest that Kasbohm and Bentzien

underestimate the future loss of habitat in the other two populations. Florida currently

has 16 million human residents and is projected to add 3 million more by 2010. In

addition, the comprehensive growth management plans for the entire state would allow

approximately 100 million people and at the current growth rate Florida could

theoretically reach a human population of 455 million by 2099 (Nicolas and Steiner

2000). Though Florida likely cannot attain such a population, the threat of habitat loss

and fragmentation over the coming decades is severe. Based on land use trends, the

approximate rate of annual deforestation has been estimated as high as 60,000 ha per year

(Harris and Scheck 1991). More recent estimates of rural land loss (including both

agricultural lands and natural communities) using aerial photography and satellite

imagery indicate that approximately 52,000 ha are being destroyed each year through

conversion to residential, commercial, and industrial development (Reynolds 1999,

Florida Division of Forestry 2001). At this rate, at least 25% of remaining private rural

lands (over 2.4 million ha) will be converted to intensive development in the next 50

years.

In addition, the pattern of loss is as important as the actual amount lost. For

instance, depending on where habitat loss actually occurs, the smaller bear populations

that now exist may become completely isolated and potentially extirpated. New

development can sever areas that now serve as links between various bear populations or

subpopulations including the Chassahowitzka, Highlands, St. Johns, Eglin, and

Southwestern Alabama populations.









Regardless of the opinion of Kasbohm and Bentzien regarding population

viability (1998), Cox et al. (1994) determined that a long-term, minimally viable

population of Florida black bear requires at least approximately 200,000 to 400,000 ha of

suitable habitat. Only the Apalachicola, Okefenokee, and Southwest Florida populations

currently have protected habitat exceeding the lower end of this threshold. Furthermore,

these estimates of viability are based on minimum populations of 200 bears. Other

estimates indicate that once widespread species may need effective populations of at least

500 to 5000 to maintain long-term viability and evolutionary potential (Franklin 1980;

Lande 1995; Noss et al. 1997). Clearly, no existing contiguous complex of existing

protected areas is large enough to support Florida black bear populations of this size.

The need for regional landscape approaches to conservation has resulted in

increasing attention to the design and protection of reserve networks that incorporate

landscapes apportioned into functional networks of reserves, multiple-use buffer zones,

and landscape linkages (Harris 1984; Noss and Harris 1986; Noss and Cooperrider 1994;

Harris et al. 1996b; Soule and Terborgh 1999). Although the primary goal of such

reserve systems is conserving all biological diversity, landscape ecology and regional

conservation strategies are especially relevant to conservation of carnivores and other

wide-ranging species. In a study focused on conservation strategies for carnivores in the

Rocky Mountains, Noss et al. (1996, p. 955-956) elucidate the importance of regional

conservation approaches:

The overwhelming message from population viability studies of large carnivores
is that conservation planning must be undertaken at vast spatial scales and must
consider connectivity. .. If maintaining viable populations of species that have
large home ranges and are vulnerable to human activities is an objective, then the
conservation planner must grapple with the design and management of entire
landscapes. Thus a zoning approach has come to dominate conservation









strategies for large carnivores. Zoned landscapes should include refugia that are
strictly protected, but they will often be dominated by multiple-use lands.

These principles are directly applicable to conservation and management efforts

for the Florida black bear. One of the primary goals for its conservation should be

maintenance and restoration of functional connections among bear populations across the

state. In this chapter, the best opportunities to maintain or restore such connectivity were

explored using a GIS function called least cost path (LCP). These methods are similar to

those to delineate the Florida Ecological Network, but in this case were specifically

designed to test potential landscape connectivity for the Florida black bear. Different

methods for conducting LCP analyses are also assessed. These analyses are then used to

identify the highest quality habitat and the best opportunities to maintain and restore

connectivity among populations within Florida.

Florida Black Bear Ecology

Taxonomy and physical characteristics

Merriam described the Florida black bear as a full species, Ursusfloridanus

(1896). It is now considered to be a subspecies, Ursus americanusfloridanus (Hall

1981). There is some question about the validity of the Florida black bear's taxonomic

status as a subspecies. However, recent investigations by the U.S. Fish and Wildlife

Service regarding the validity of the Louisiana black bear, which included comparisons to

the Florida black bear, reinforced its subspecies status (Federal Register 1990).

The Florida black bear is almost always black and sometimes has a whitish chest

patch. Florida black bears are an apparent exception to Bergmann's rule with females

weighing an average of about 82 kg and males weighing an average of about 113 kg

(Maehr and Wooding 1992). Florida males occasionally obtain masses up to 300 kg









(Maehr and Wooding 1992). Both the averages and maximum masses are on the upper

ends of masses for all North American black bears reported by Pelton (1982).

Habitat use and food habits

The Florida black bear uses a wide variety of forest types such as pine flatwoods,

hardwood and mixed swamps, cabbage palm forests, sand pine scrub, hardwood

hammocks, and even mangroves (Maehr and Wooding 1992; Maehr 1997a). Open

sandhills are only used occasionally (Wooding and Hardisky 1988).

Denning sites are typically ground nests found in areas of dense shrubs such as

saw palmetto thickets or within swampy areas on higher ground (Wooding and Hardisky

1992). Tree cavities are important denning sites in other regions and may also be used by

Florida bears, although past and present timber practices have greatly reduced the

availability of such trees (Pelton 1982; Weaver et al. 1990; Maehr and Wooding 1992).

The Florida black bear is omnivorous, but plant matter dominates as a food

source. Black bears typically follow the phenology of plants in selecting food items

seasonally (Amstrup and Beecham 1976; Landers et al. 1979; Pelton 1982; Pelton 1986).

In spring the major food item is usually new green leaves and shoots of various plant

species. Soft mast such as berries and other fruits are the major food items during

summer; and hard mast such as acorns usually dominate fall/winter diets. The Florida

black bear exhibits similar trends, but the typically mild climate results in soft mast being

available over longer periods of time (Maehr and Brady 1984a; Maehr and Wooding

1992; Stratman 1998; Scheick 1999; Stratman and Pelton 1999). Saw palmetto (Seronoa

repens) fruits are heavily used in late summer and fall; with cabbage palm (Sabal

palmetto) hearts, tupelo (Nyssa spp.) fruits, acorns (Quercus spp.), blueberries

(Vaccinium spp.), blackberries (Rubus spp.), and gallberry (Ilex glabra) also important









(Maehr and Brady 1984a; Maehr and Brady 1984b; Maehr and Wooding 1992). Animal

matter makes up a smaller, but regular, part of the diet and includes wasps (Vespula spp.),

bees (Apis mellifera), ants (Campanotus abdominalisfloridanus), and vertebrates such as

armadillos (Dasypus novemcinctus) and feral pigs (Sus scrofa) in Florida.

Social structure and home ranges

The black bear is usually solitary except during courtship/mating and when

females are with cubs. Depending on the region, season, sex, and food availability, home

ranges of individual bears can be fairly exclusive (Young and Ruff; Rogers 1987), but in

most situations there is often a great degree of overlap (Reynolds and Beecham 1977;

Garshelis and Pelton 1981; Wharburton and Powell 1985; Klenner 1987; Mollohan and

Lecount 1989). Data collected on the Florida black bear indicate extensive overlap of

home ranges in the Ocala and Osceola National Forests and southwest Florida (Wooding

and Hardisky 1988; Maehr 1997a).

Home ranges for adult males are considerably larger than for adult females, and

male territories will overlap the ranges of several females (Pelton 1982). Over the black

bear's continental distribution, home ranges vary widely likely in relation to habitat

quality (Pelton 1982). Home range size for Florida black bear are average compared to

other regions: average adult male and female home range size were calculated in recent

studies to be 170 km2 and 28 km2 (Wooding and Hardisky 1988) and 283 km2 and 54

km2 (Maehr 1997a) respectively.

Reproduction

The black bear, like other bear species, has one of the lowest reproductive rates

known among terrestrial mammals (Jonkel and Cowan 1971; Bunnell and Tate 1981;

Eiler et al. 1989). Sexual maturity is reached at about 3 to 5 years of age, although first









reproduction can be as late as 7 to 8 years (Bunnell and Tait 1981; Pelton 1982). Florida

black bear females usually produce their first cubs at 3 or 4 years (Maehr and Wooding

1992).

Breeding usually peaks in June and July, although in some areas it may begin as

early as May or last through early September (Pelton 1982; Eiler et al. 1989; Maehr

1997a). Females are induced ovulators; and implantation is delayed until late fall (Pelton

1982). Parturition occurs in the den during winter. Typical cub production is usually 2,

although litters of 3 and 4 also occur (Pelton 1982; Maehr 1997a). Females normally

produce young every other year, although seasonal mast failures may eliminate

reproduction in some years (Rogers 1987).

Seasonal movements, dispersal, and connectivity

Seasonal movements and dispersal are the most important considerations for a

landscape-based approach to conserving the Florida black bear. After winter denning and

throughout the fall, black bears steadily increase in activity, and home ranges usually

expand accordingly (Rogers 1987). In some areas, this can include complete shifts in

home ranges as food availability shifts spatially (Garshelis and Pelton 1981; Klenner

1987; Mollohan and Lecount 1989; Maehr 1997a). Florida black bear in the Ocala

National Forest usually shift from pine flatwoods during winter and spring to sand pine

scrub in the summer and fall; whereas bears in Osceola National Forest mainly utilize

swamps (Wooding and Hardisky 1988).

Seasonally increasing adult male activity patterns are likely related to both

reproductive effort in the summer and foraging requirements in the fall. The greater

mobility of male black bears makes them much more susceptible to roadkill or hunting

and poaching (Pelton 1982; Rogers 1987). One adult male Florida black bear moved 35-









km out of its normal home range during the breeding season (Wooding and Hardisky

1988). Long distance movements by females are rarer, although one relocated adult

female Florida black bear in the panhandle moved 77 km (Wooding et al. 1992). In

Minnesota, black bears (both males and females) moved considerable distances out of

normal home ranges to use more abundant food resources in the late summer and fall

(Rogers 1987). Movements up to 83 km (with an average of 29.5 km) were recorded to

reach one particular resource, and one adult male traveled 201 km in 13 weeks, which is

the longest movement recorded for a non-dispersing bear (Rogers 1987).

Dispersal usually refers to the movement of animals away from their area of

origin (Brown and Gibson 1983). Black bear dispersal usually occurs at 2 to 4 years of

age (Pelton 1982; Rogers 1987). Subadult females usually stay in the immediate area of

their mother's home range; whereas subadult males may disperse widely, either in

response to social pressure from resident adult males (Pelton 1982), or socially

independent reasons (Rogers 1987). In a sample of 51 subadults in Alaska, all male

subadults dispersed, whereas only 3% of the subadult females dispersed (Schwartz and

Franzmann 1992). In Minnesota, dispersal distances ranged from 13 to 219 km and

averaged 61 km (Rogers 1987). There was also evidence of a dispersal event over 324-

km (Rogers 1987). In north-central Florida, the dispersal of 4 subadult males ranged

from 22 to 56 km (Wooding and Hardisky 1988). Another subadult male moved 140 km

in southwest Florida (Maehr et al. 1988). The longest known dispersal distance of a

subadult female in Florida covered 60 km in south Florida (Maehr 1997a).

Dispersal is an important demographic factor that has a key role in population

regulation (Kemp 1974; Bunnell and Tait 1981; Lecount 1982; Beecham 1983; Rogers

1987). In Alberta, 26 adult males were removed in an experimental study area, and a









large number of subadult males quickly moved in to take their territories (Kemp 1974).

Other studies indicate that many transient sub-adult males routinely travel through

occupied territories (Beecham 1983; Rogers 1987). This wide-ranging behavior of sub-

adult males is a key factor in linking regional bear populations. Such dispersal may

currently link several populations of the Florida black bear. Habitat protection,

restoration, and population re-introduction in key areas could establish a statewide

metapopulation.

Corridors and landscape linkages (areas that link larger core reserves) are a

primary method for designing reserve networks to facilitate connectivity (Harris 1984;

Harris and Scheck 1991; Noss and Cooperrider 1994; Harris et al. 1996b; Soule and

Terborgh 1999). For the Florida black bear, these landscape features serve at least three

purposes related to connectivity:

* To facilitate daily or seasonal movements

* To allow dispersal that might facilitate gene flow between populations, buffer small
populations, or recolonize vacant areas

* To allow range shifts in response to vagaries of food supply, catastrophic events, or
long-term environmental change (Noss 1993).

Functional connectivity is more likely in corridors that not only support

movement but home ranges as well (Harrison 1992; Noss and Cooperrider 1994; Noss et

al. 1996). Based on the average home range requirements for a male Florida black bear, a

corridor would have to be at least 13 km wide for a square home range or 9 km wide if

the home range was twice as long as wide. Landscape linkages could be much bigger.

The best regional example of such a linkage is the Pinhook Swamp, which connects the

Osceola National Forest and the Okefenokee National Wildlife Refuge. Though forest

and other primary habitat is preferred, landscape linkages for the Florida black bear can









include a mixture of habitats and low-intensity land uses (e.g., most types of agriculture)

(Maehr et al. 1988; Maehr 1997a).

Methods

The potential for protecting functional landscape linkages between bear

populations and additional areas of habitat in Florida was assessed using the least cost

path (LCP) function. Least cost path results selected from 17 Cost Surfaces were then

combined with a black bear habitat model (developed using multiple logistic regression

and also used to create several Cost Surfaces) to identify the area with the potential to

support a statewide metapopulation (Figure 3-1).

LCP function is a raster-based algorithm available in ESRI's Arc-Info GRID,

ArcView Spatial Analyst, or ArcGIS software. It is an optimization function that seeks

the least costly route between a source and a destination. Typically this algorithm has

been used to find the optimal path for linear infrastructure (including roads and

transmission lines). LCP analysis can also be applied to identifying landscape linkages

between conservation areas to maintain or restore connectivity between wildlife

populations.

Identifying LCPs first requires the development of a cost surface, which is a raster

map in which every cell (or pixel) is ranked for its potential suitability for

accommodating a particular function. In the case of ecological connectivity, a cost

surface ranks each cell based on its potential to support a functional ecological

connection. Cells within the study area can be ranked using as many variables as deemed

relevant for determining connectivity potential. These variables can include intrinsic

qualities (such as the land use of the cell) or landscape or context values (such as whether

the cell is part of a large forest block or near a large urban area).

















Develop cost
elation
sur faces


Figure 3-1. Process used to identify the land area with the potential to support a
statewide black bear metapopulation


Goah Identify lands in
Florida.with the potential to
support a statewide mnetapoipidation
of the Florida black bear


Identify landscape
linkage epporhtmdties


Identify Itghest quality
habitat and optimal landscape
lhikages to fnctionally
comieet all bear populations










There are several issues regarding the use of LCP for identifying landscape

linkages to be discussed. The LCP function minimizes the accumulated cost of traveling

through cells. Therefore, it attempts to minimize the distance traveled and the number of

high cost cells that must be traveled through to get from the source to the destination.

Hence, the range of values used in a cost surface may greatly affect the relative

significance of distance versus cell cost or vice versa for determining the LCP. For

example, if a cost surface was constructed where all cells within the study area were

given the same cost (e.g., a value of 1 which correlates to the lowest cost, and therefore,

the most suitable cells), the function would return an LCP that was a straight line (the

shortest distance) between the source and the destination. In this case, cell suitability has

no bearing on the resulting LCP; and therefore distance is the only factor considered.

However, if a wider range of values is used to represent the differences among cells with

high or low suitability, then cell suitability, or cost, becomes more important for

determining the LCP. Thus a primary question when developing cost surfaces is how to

incorporate a range of input values that appropriately balances both cell cost and

accumulated distance when determining LCPs. Other questions for constructing cost

surfaces include the following:

* How are features such as major roads and large water bodies best included within cost
surfaces to represent their potential impedance to functional connectivity?

* Should cost surfaces include more variables that may be relevant to ecological
connectivity; or can simpler surfaces including one or a few potentially critical
variables result in useful assessments of potential connectivity?

* When multiple variables are used in cost surfaces, do different methods of weighting
variables result in significant differences in LCPs?

* Could quantitative methods (rather than qualitative) methods create cost surfaces that
enhance the statistical basis of the LCP algorithm?










To evaluate these questions and to explore options for creating cost surfaces for

identifying opportunities for facilitating connectivity, seventeen cost surfaces were

created and used to run the LCP function to identify the best potential linkages among the

five largest Florida black bear populations across the state (Table 3-1). I compared the

relative performance of these cost surfaces. Then three cost surfaces were selected to

represent the best landscape linkage options for the five major populations. I also used

the three selected cost surfaces to analyze additional connectivity between the five largest

populations, smaller populations, and other areas that could support bear populations in

the future. All least cost path and habitat analyses were conducted using the raster

functions of ESRI's GIS software, and 90 m cell sizes were used because of the size of

the study area and because of computing limitations with various neighborhood and

regional analysis functions.

I created four major categories of cost surfaces. The first four cost surfaces

combine multiple criteria where variables are ranked individually using the same scale,

then combined to create one cost surface. Different weighting schemes were also applied

to create different versions of these multiple criteria cost surfaces.

The next five cost surfaces (Cost Surfaces 5 to 9) were simplified to include only

a few variables that were potentially most important for determining suitability for

connectivity (landcover type, patch size, proximity to large developed areas, and

proximity to roads). Variations include the following:

* Cost surfaces based primarily on forest

* All potential bear habitat

* Incorporation of major roads (highways) and open water bodies









* Combinations of habitat patch size, distance from development, and distance from
major roads.

The next six cost surfaces (Cost Surfaces 10 to 5) are modified versions of the

first 9 cost surfaces, where the range of values was expanded to test the influence of cell

suitability versus accumulated distance in determining LCPs. The ranges of values were

expanded by using various exponential functions.

The final two cost surfaces (Cost Surfaces 16 and 17) were created by running a

multiple logistic regression model to develop a statewide map of Florida black bear

habitat quality statewide. Black bear occurrences collected in radio telemetry studies of

four of the major populations, and over sixty landscape variables were compared in the

model. The two cost surfaces were based on slightly different models using different sets

of random locations in the multiple logistic regression analyses.

Multiple Criteria-Based Cost Surfaces

Multiple utility assignments (MUAs) are optimization surfaces that represent a

combination of more than one single criteria or utility assignments. Each single utility

assignment (SUAs) ranks suitability for a particular function based on a single criterion

on the same scale as all the other criteria. In these cost surfaces, all SUAs were ranked

on a scale from 1 to 10. MUAs are then created by combining all of the SUAs either with

or without weighting.

Cost Surface 1: multiple utility assignment with major roads and large open water
bodies

Cost Surfacel was created using 11 variables relevant to black bear habitat quality

and conservation to create an MUA with final ranks of 1 to 100. Major roads (those

within the Florida Intrastate Highway System) and large water bodies were included in

this cost surface by assigning them specific high costs above the value range of 1 to 100









Table 3-1. Seventeen cost surfaces used to assess landscape linkages for the Florida
black bear
Cost Description Value range
surface #
1 Multiple Utility Assignment (MUA) using 11 bear 1-200
habitat quality variables, major roads, large water
bodies.
2 Multiple Utility Assignment (MUA) using 11 bear 1-100
habitat quality variables.
3 Multiple Utility Assignment (MUA) using 11 bear 1-20
habitat quality variables, major roads, large water
bodies with a compressed value range.
4 Multiple Utility Assignment (MUA) using 11 1-20
weighted bear habitat quality variables, major
roads, large water bodies with a compressed value
range.
5 Ranked forest cover and other land cover and land 1-100
uses
6 Forest cover ranked by size class with other land 1-100
cover and land uses also ranked
7 Black bear habitat ranked by size class with other 1-100
land cover and land uses also ranked
8 Bear habitat ranked based on patch size, distance 1-100
from intensive development, and distance from
major roads
9 Bear habitat ranked based on patch size and distance 1-100
from intensive development
10 Cost Surface 3 transformed using the ArcView 3-22026
exponential function
11 Cost Surface 4 transformed using the ArcView 3-22026
exponential function
12 Cost Surface 10 with major roads and large water 3-22026
bodies added
13 Cost Surface 11 with major roads and large water 3-22026
bodies added
14 Cost Surface 8 transformed by squaring the original 1-10000
values
15 Cost Surface 9 transformed by squaring the original 1-10000
values
16 Multiple logistic regression bear habitat model 1-100
17 Alternative multiple logistic regression bear habitat 1-100
model









(200 and 150 respectively). Each SUA is based on a factor considered significant to

black bear habitat quality or more likely to provide a favorable design option for a

landscape linkage. For each SUA, every cell within the study area (the entire state) is

given a value from 1 to 10, with 10 indicating that the cell has the highest or best value

for that index and 1 indicating lowest value. The eleven indices used were the same as

those in Maehr et al. (1999), though minor modifications were made in the ranking of

some of the indices. The eleven indices used were as follows:

Primary and secondary black bear habitat. Using the Florida Fish and

Wildlife Conservation Commission (FWC) landcover data (Cox et al. 1994), potential

primary habitat was identified. Primary habitat was defined as all patches of pineland,

oak scrub, sand pine scrub, mixed hardwood, upland hardwood forest, cypress swamp,

mixed hardwood swamp, bay swamp and bottomland hardwood swamp greater than 14.8

ha (Mykytka and Pelton 1989; Cox et al. 1994). To incorporate smaller patches of

potential secondary habitat nearby, a one km buffer was created around primary habitat

and additional habitat (smaller blocks of primary habitat as well as dry prairie, sandhill,

shrub swamp, and shrub and brushland) located within the buffer were included (Cox et

al. 1994). In the index, primary habitat was ranked 10, secondary habitat was ranked 7,

and all other cells (areas) in the state were ranked 1.

Preferred habitat. Using the FWC landcover data as the input, natural and semi-

natural landcover types were ranked into three classes and all other land uses as a fourth

class based on their relative value as potential bear habitat (Maehr and Wooding 1992;

Cox et al. 1994; Maehr 1997a; Table 3-2).

Habitat block size. This SUA was created to rank areas based on the size of

potential habitat patches not fragmented by roads. Roads selected to delineate habitat









Table 3-2. SUA ranking land cover types based on preference as habitat
Habitat type Rank
Pineland (including pine plantation) 10
Sand pine scrub 10
Oak scrub 10
Mixed hardwood-pine 10
Upland hardwood forest 10
Cypress swamp 10
Mixed hardwood swamp 10
Bay swamp 10


Sandhill 7
Mangrove swamp 7
Shrub and brushland 7


Coastal strand 3
Dry prairie 3
Freshwater marsh and wet prairie 3
Salt marsh 3
Shrub swamp 3


All other land uses (agriculture and urban)









patches had traffic levels of 2500 or greater vehicles per day or were highway segments

with ten or more documented road kills. First, primary and secondary habitat from SUA

1 were combined. The highways included were considered to have high enough traffic

levels to serve as barriers or filters for bear movement or important mortality threats

(Brody and Pelton 1989; Wooding and Maddrey 1994). Contiguous potential habitat not

bisected by such roads were then grouped into ranked size classes (Table 3-3).

Habitat diversity. Areas with a higher diversity of plant communities will have a

higher probability of supporting a diverse array of food sources and act as a buffer during

mast crop failures (Pelton 1985; Rogers and Allen 1987; Mollohan and LeCount 1989;

Schoen 1990; Maehr and Wooding 1992; Samson and Huot 1998). This index was

created by first reclassifying the FWC landcover data into the following four categories:

* Forested wetlands (hardwood swamp, cypress swamp, bay swamp, mangrove swamp,
shrub swamp)

* Forested uplands (pineland, sand pine scrub, sandhill, upland hardwood forests, and
mixed hardwood-pine)

* Freshwater and saltwater marshes

* Low stature open brush uplands xericc oak scrub, dry prairie, coastal strand, and
shrub and brushland) (Cox et al. 1994).

Each cell was then ranked by the number of different habitat categories found within the

surrounding km2 (Table 3-4). Cells that were not considered bear habitat based on the

FWC landcover data were given the lowest value regardless of the diversity of habitats in

the surrounding area.

Distance from large areas of protected habitat. Larger areas of protected

conservation lands provide critical core areas to help maintain breeding populations of

black bear (Hellgren and Maehr 1992; Cox et al. 1994; Samson and Huot 1998). Areas









Table 3-3. Ranking of potential habitat based on patch size
Block size of potential habitat fragmented by high traffic Rank
highways and highways with bear roadkills
Potential black bear habitat block greater than or equal to 10
200,000 ha
Potential black bear habitat less than 200,000 ha and 9
greater than or equal to 100,000 ha
Potential black bear habitat less than 100,000 ha and 8
greater than or equal to 40,000 ha
Potential black bear habitat less than 40,000 ha and 7
greater than or equal to 20,000 ha
Potential black bear habitat less than 20,000 ha and 6
greater than or equal to 4,000 ha
Potential black bear habitat less than 4,000 ha and 5
greater than or equal to 2,000 ha
Potential black bear habitat less than 2,000 ha and 4
greater than or equal to 400 ha
All other potential bear habitat 3
All other cells in study area 1






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Table 3-4. Habitat diversity rankings
Habitat diversity/variety Rank
Four types of habitat 10
Three types of habitat 8
Two types of habitat 6
One habitat 4
Other cells 1









close to large blocks of protected bear habitat are likely to be used by bears, may provide

critical foraging habitat seasonally or during mast failures (Samson and Huot 1998), may

be critical for providing enough additional habitat to support viable populations (Cox et

al. 1994), and are more likely to be within dispersal distances of bears and, therefore,

more likely either to support part of a functional metapopulation or to be re-colonized

(Cox et al. 1994; Maehr 1997a).

Therefore, in this index, potential habitat (as identified in SUA 1) in blocks of

20,000 ha or greater within existing conservation lands (primarily public lands but also

include private preserves such as those owned by The Nature Conservancy, National

Audubon Society, and conservation easements) were identified (Cox et al. 1994).

Potential habitat needs to be emphasized because there are several areas across the state

including the Green Swamp Conservation Area and the Corbett Wildlife Management

Area that meet the criteria for potential habitat but do not currently support breeding

black bear populations. Proximity to all such conservation areas was modeled using

intervals based on typical dispersal distances for black bear (Rogers 1987; Maehr et al.

1988, Wooding et al. 1992; Cox et al. 1994; Maehr 1997a; Table 3-5).

Roadless areas. Roadless areas are more likely to provide optimal black bear

habitat by minimizing the chance of roadkills, providing large blocks of intact habitat,

and minimizing various forms of disturbance (Lentz et al. 1980; Quigley 1982; Pelton

1986; Brody and Pelton 1989; Kasworm and Manley 1990; Beringer et al. 1991; Clark et

al. 1993; Beecham and Rohlman 1994; Wooding and Maddrey 1994; Heyden 1997;

Powell et al. 1997; Martorello 1998; Orlando 2002). In this index, roadless areas were

identified using class 1 through class 4 roads found in the 1:24000 roads data for Florida

created by the U.S. Geological Survey (USGS). Class 5 roads, which are unimproved






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Table 3-5. Ranking of distance from protected bear habitat 20,000 ha or larger
Distance from protected bear habitat 20,000 ha or larger Rank
Areas < 20 km from core areas 10
Areas 20-40 km from core areas 7
Areas 40-60 km from core areas 3
Areas > 60 km from core areas 1









dirt roads frequently referred to as jeep trails, were not included. The identified roadless

areas were then broken into size classes and ranked by percentage of potential bear

habitat (using the methods from SUA 1 to identify habitat) found within each roadless

area (Table 3-6). Thresholds selected were based on a similar index created by Cox et al.

(1994) and recommendations on functional sizes of bear habitat blocks from Hellgren and

Maehr (1992).

Road density. Road densities, though related to roadless areas, more specifically

capture the potential intensity of disturbance associated with roads as the number of roads

increase. It may be possible for an area to not meet strict standards or definitions of

roadlessness yet support low enough road densities to provide functional habitat with low

or no disturbance to sensitive species. However, as road densities increase, the potential

for a variety of disturbances including roadkills, poaching, edge effects, and others

associated with vehicle traffic and human activity also tend to increase (Lyon 1983;

Brody 1984; Thiel 1985; Van Dyke et al. 1986; Mattson et al. 1987; McLellan and

Shackleton 1988; Mech et al. 1988; Brody and Pelton 1989; Mladenoff 1995; Trombulak

and Frissell 2000; Orlando and Maehr 2001). To create a road density index, the

linedensity function in the GRID module of Arc-Info was used to calculate road density.

Class 1-4 roads from USGS 1:24000 roads were included in the linedensity function to

calculate road density in the 2.6 km2 surrounding each cell within the study area.

Rankings were based on the recommendation by Pelton (1986) to maintain road densities

below 0.33 km/km2 to maintain high quality black bear habitat and the recommendation

that road densities should be maintained at least below 0.66 km/km2 to provide habitat for

wide-ranging species sensitive to road impacts (Noss and Cooperrider 1994) (Table 3-7).









Table 3-6. Roadless area ranks based on size of the roadless areas and the percentage of
bear habitat within roadless areas
Roadless area size and percentage habitat combination Rank
Roadless areas 4,000 ha or greater with greater than 70% 10
primary potential black bear habitat
Roadless areas 4,000 ha or greater with 40-70% primary 9
potential black bear habitat
Roadless areas 4,000 ha or greater with 10-40% primary 8
potential black bear habitat
Roadless areas 2000 ha or greater with greater than 70% 7
primary potential black bear habitat
Roadless areas 2000 ha or greater with 40-70% primary 6
potential black bear habitat
Roadless areas 2000 ha or greater with 10-40% primary 5
potential black bear habitat
Roadless areas 1000 ha or greater with greater than 70% 4
primary potential black bear habitat
Roadless areas 1000 ha or greater with 40-70% primary 3
potential black bear habitat
Roadless areas 1000 ha or greater with 10-40% primary 2
potential black bear habitat
Roadless areas below 1000 ha 1









Table 3-7. Ranking of road densities
Road density Rank
Less than 0.33 km/km 10
0.33 or greater and < 0.66 km/km2 9
0.66 km/km2 or greater and < 0.99 km/km2 8
0.99 km/km2 or greater and < 1.32 km/km2 7
1.32 km/km2 or greater and < 1.65 km/km2 6
1.65 km/km2 or greater and < 1.98 km/km2 5
1.98 km/km2 or greater and < 2.31 km/km2 4
2.31 km/km2 or greater and < 2.64 km/km2 3
2.64 km/km2 or greater and < 2.97 km/km2 2
2.97 km/km2 or greater 1










Distance from major roads. Larger roads with higher traffic levels cause

roadkills and can result in road avoidance and habitat fragmentation (Wooding and Brady

1987; Brody and Pelton 1989; Gilbert and Wooding 1994; Wooding and Maddrey 1994;

Maehr 1997a; Orlando and Maehr 2001). In this analysis, proximity to major roads was

modeled such that areas closer to such roads were ranked lower for corridor suitability.

As a conservative estimate, all roads with traffic levels of 2500 vehicles per day or

greater and additional road segments with 10 or more bear roadkills were included as

major roads. Ranking thresholds were created by using a sliding scale, where the most

intensive zones of potential impacts near roads were assigned the smallest intervals, and

other ranks were given equal intervals (Table 3-8).

Land use intensity. Intensity of land use is assumed to affect the potential

quality of areas as bear habitat (Mattson 1990; Schoen 1990). In this index, 1995 land

use data from each of Florida's five Water Management Districts were reclassified into

the following four general land use categories to depict level of land use intensity:

* All native or natural habitat including wetland and upland forests of all types,
marshes, prairies, etc.

* Low-intensity land use such as unimproved pastures, woodland pastures, pine
plantations, and areas that have been platted for development but still retain natural
cover types

* Moderate intensity land use including improved pastures, row crops, citrus groves,
etc.

* High intensity uses including all residential, commercial, and industrial land uses.

Though some natural communities included in the native category may not be used

frequently by bears, and some land uses in higher intensity classes such as pine plantation

can provide black bear habitat, these categories serve as a general indication for the






82


Table 3-8. Ranking of distances from major roads
Distance from major roads Rank
>7001 m 10
6001 m to 7000 m 9
5001 m to 6000 m 8
4001 m to 5000 m 7
3001 m to 4000 m 6
2001 m to 3000 m 5
1001 m to 2000 m 4
501 m to 1000 m 3
101 m to 500 m 2
0 m to 100 m 1