Citation
Sector Planning and the Environment : Is Florida’s sector planning process reducing negative impacts associated with urban development?

Material Information

Title:
Sector Planning and the Environment : Is Florida’s sector planning process reducing negative impacts associated with urban development?
Creator:
Simpson, John-Michael
Place of Publication:
[Gainesville, Fla.]
Publisher:
Department of Landscape Architecture, College of Design, Construction and Planning, University of Florida
Publication Date:
Language:
English
Physical Description:
Project in lieu of thesis

Thesis/Dissertation Information

Degree:
Master's ( Master of Landscape Architecture)
Degree Grantor:
University of Florida
Committee Chair:
Carr, Margaret H
Committee Members:
Hoctor, Thomas Scott

Subjects

Subjects / Keywords:
West Bay ( local )
Land use ( jstor )
Land development ( jstor )
Agricultural land ( jstor )

Notes

Abstract:
Human developments can cause many negative impacts on the ecosystems around the world. As the human population grows, it will require more land and resources which may result in the degradation of natural lands. Development has occurred at a quick rate in the United State and today only two-fifths of the continental U.S. contains natural land cover (Shaffer and Stein 2000). The development of natural land can result in habitat fragmentation which has helped to cause the extinction of amphibians, birds, invertebrates and mammals (Orff 2011). Recently, the State of Florida has created the Sector Planning Program that claims to potentially reduce negative environmental impacts while also improving the economic, social and fiscal development in the existing communities. ( ,, )
Abstract:
The Sector Planning Program began in 1998 and has since been utilized in several large scale developments. This project examined sector planning to see if its implementation has resulted in reduced habitat fragmentation, protected or restored landscape connectivity, and protection for ecosystem services such as water management. In order to test the results of sector planning, four cases studies were analyzed in GIS. The analyses identified the various impacts on three types of land-uses that may be caused by each development: agriculture, conservation and urban. The developments being studied are Farmton, Plum Creek Alachua County, the West-Bay Sector Plan, and Restoration. Restoration is unique because it has two designs; the first design from 2006 was sprawling and inefficient and the second design from 2009 is more compact and protects more land than the 2006 plan. Farmton was also used as a test case to explore the relative character and quality of four alternative plans for the property. These alternate plans will then be analyzed with the same GIS models that were used in the case studies to allow for comparison so that trends in developmental impacts may be identified.
Abstract:
Each case study was found to significantly impact habitat fragmentation, landscape connectivity and ecosystem services. The West-Bay Sector Plan caused the most impacts when compared to the other developments. The 2009 Restoration plan was the least impactful development in this study and the improvements from the first iteration of the design were impressive. This project found that the Sector Planning Program does not significantly reduce environmental impacts caused by urban development. Instead, the developments studied for this project will likely cause significant reduction in connectivity and ecosystem services with an increase in urban sprawl. However, the Restoration project leaves hope that if a land developer really wishes to be more environmentally friendly, less impactful urban planning is possible.
General Note:
Landscape Architecture terminal project

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright John-Michael Simpson. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
1022120880 ( OCLC )

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Sector Planning and the Environment reducing negative impacts associated with urban development? A Thesis Project Presented in Partial Fulfillment of the Requirements for the Degree of Master of Landscape Architecture By John Michael Simpson Committee Margaret Carr Thomas Hoctor University of Florida School of Landscape Architecture and Planning March 2015

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2 | Page Special Thanks To: Peggy Carr Tom Hoctor Cathy Davis Max Deledda Erika Mayer

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3 | Page Table of Contents Table of Contents ................................ ................................ ................................ ............................... 3 Abstract ................................ ................................ ................................ ................................ ............. 7 Chapter 1: Introduction ................................ ................................ ................................ ...................... 9 Research Questions ................................ ................................ ................................ ................................ 10 Chapter 2: Literature Review ................................ ................................ ................................ ............ 13 Part I: Conservation Issues ................................ ................................ ................................ ...................... 13 Biodiversity ................................ ................................ ................................ ................................ ......... 13 Fragmentation ................................ ................................ ................................ ................................ ..... 18 Corridors and Connectivity ................................ ................................ ................................ ................. 22 Edge Effects ................................ ................................ ................................ ................................ ......... 28 Ecosystem Servic es and Water Protection ................................ ................................ ......................... 32 Part II: Planning Issues ................................ ................................ ................................ ............................ 34 Reserve Design ................................ ................................ ................................ ................................ .... 34 Road Network Planning ................................ ................................ ................................ ...................... 39 Urban Planning ................................ ................................ ................................ ................................ .... 43 Part III: Plan ning Processes in Florida ................................ ................................ ................................ ..... 46 Sector Planning ................................ ................................ ................................ ................................ ... 46 Development of Regional Impacts ................................ ................................ ................................ ...... 47 Comprehensive Plan Amendments ................................ ................................ ................................ ..... 49 Part IV: Geographic Information Systems (GIS) ................................ ................................ ...................... 50 GIS Overview ................................ ................................ ................................ ................................ ....... 50 Chapter 3: Methodology ................................ ................................ ................................ .................. 53 Part I: Case Study Analysis ................................ ................................ ................................ ...................... 53 Case Study Selection ................................ ................................ ................................ ........................... 53 Case Stu dy Evaluation ................................ ................................ ................................ ......................... 54 Case Study Methods ................................ ................................ ................................ ........................... 55 Case Study Results Analysis ................................ ................................ ................................ ................ 61 Part II: Farmton Analysis ................................ ................................ ................................ ......................... 61 Site Selection ................................ ................................ ................................ ................................ ....... 61

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4 | Page Farmton Suitab ility Goal Outline ................................ ................................ ................................ ........ 63 Suitability for Agriculture Land Use ................................ ................................ ................................ .... 65 Suitability for Conservation Land Use ................................ ................................ ................................ 67 Suitability for Urban Land Use ................................ ................................ ................................ ............ 69 Conflict Analysis ................................ ................................ ................................ ................................ .. 72 Alternate Plans ................................ ................................ ................................ ................................ .... 72 Analysis of the Alternate Plans ................................ ................................ ................................ ........... 74 Part IV: Limitations ................................ ................................ ................................ ................................ .. 74 Chapter 4: Case Study Results ................................ ................................ ................................ ........... 75 Part I: Case Study Introduction ................................ ................................ ................................ ............... 75 Farmton Plan ................................ ................................ ................................ ................................ ....... 76 Plum Creek ................................ ................................ ................................ ................................ .......... 79 West Bay ................................ ................................ ................................ ................................ ............. 81 Restoration ................................ ................................ ................................ ................................ .......... 84 Part II: Case St udy Results ................................ ................................ ................................ ....................... 91 Impacts to Agriculture Land Uses ................................ ................................ ................................ ....... 92 Impacts to Conservation Land Uses ................................ ................................ ................................ ... 92 Impact to Urban Land Uses ................................ ................................ ................................ ................ 94 Chapter 5: Farmton Analysis Results ................................ ................................ ................................ . 95 Part I: Farmton Suitability Results ................................ ................................ ................................ ........... 95 Agriculture Suitability ................................ ................................ ................................ .......................... 95 Cons ervation Suitability ................................ ................................ ................................ ...................... 96 Urban Suitability ................................ ................................ ................................ ................................ . 97 Conflict Grid ................................ ................................ ................................ ................................ ........ 97 Part II: Farmt on Alternative Plans ................................ ................................ ................................ ........... 98 Alternate Plan #1 ................................ ................................ ................................ ................................ 98 Alternate Plan #2 ................................ ................................ ................................ ................................ 99 Alternate Plan #3 ................................ ................................ ................................ .............................. 100 Alternate Plan #4 ................................ ................................ ................................ .............................. 101 Part III: Alternate Plan Analysis ................................ ................................ ................................ ............. 101 Context Area Analysis ................................ ................................ ................................ ....................... 102 Development Area Analysis ................................ ................................ ................................ .............. 102

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5 | Page Chapter 6: Discussion ................................ ................................ ................................ ..................... 103 Part I: Impact Analysis ................................ ................................ ................................ ........................... 103 Agri culture Impacts ................................ ................................ ................................ ........................... 103 Conservation Impacts ................................ ................................ ................................ ....................... 105 Urban Impacts ................................ ................................ ................................ ................................ ... 114 Part II: Farmton Suitability Analysis ................................ ................................ ................................ ...... 117 A: Agricultural Suitability ................................ ................................ ................................ .................. 117 Conservation Suitability ................................ ................................ ................................ .................... 122 Urban Suitability ................................ ................................ ................................ ............................... 123 Conflict Grid ................................ ................................ ................................ ................................ ...... 125 Farmton Alternate Plans ................................ ................................ ................................ ................... 125 Visualizing Density ................................ ................................ ................................ ............................ 128 Chapter 7: Conclusions ................................ ................................ ................................ ................... 131 Conclusions ................................ ................................ ................................ ................................ ........... 131 Ideas for Further Research ................................ ................................ ................................ .................... 134 Final Thoughts ................................ ................................ ................................ ................................ ....... 135 Appendix A: GIS Tool Descriptions ................................ ................................ ................................ 137 Processing Tools ................................ ................................ ................................ ................................ .... 137 Conversion Tools ................................ ................................ ................................ ................................ ... 140 GIS Sources and Descriptions ................................ ................................ ................................ ................ 141 Appendix B ................................ ................................ ................................ ................................ .... 143 Part I: Case Study Context Data ................................ ................................ ................................ ............ 143 Agriculture Impacts ................................ ................................ ................................ ........................... 143 Conservation Impacts ................................ ................................ ................................ ....................... 145 Urban Impacts ................................ ................................ ................................ ................................ ... 153 Part II: Case Study Development Data ................................ ................................ ................................ .. 154 Agriculture Impacts ................................ ................................ ................................ ........................... 154 Conservation Impacts ................................ ................................ ................................ ....................... 156 Urban Impacts ................................ ................................ ................................ ................................ ... 165 Part III: Farmton Alternative Context Data ................................ ................................ ........................... 166 Agriculture Impacts ................................ ................................ ................................ ........................... 166 Conservation Impacts ................................ ................................ ................................ ....................... 168

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6 | Page Urban Impacts ................................ ................................ ................................ ................................ ... 176 Part IV: Farmton Alternate Development Data ................................ ................................ .................... 177 Agriculture Impacts ................................ ................................ ................................ ........................... 177 Conservation Impacts ................................ ................................ ................................ ....................... 179 Urban Impacts ................................ ................................ ................................ ................................ ... 188 Appendix C ................................ ................................ ................................ ................................ .... 189 Farmton Suitability Analysis ................................ ................................ ................................ .................. 189 A: Agriculture Suitability Analysis ................................ ................................ ................................ ......... 190 B: Conservation Suitability Analysis ................................ ................................ ................................ ...... 220 C: Urban Suitability Analysis ................................ ................................ ................................ ................. 239 Appendix D: Farmton Alternate Plans ................................ ................................ ............................. 275 Farmton Current Plan ................................ ................................ ................................ ........................... 276 Farmton Alternate Plan #1 ................................ ................................ ................................ .................... 277 Fa rmton Alternate Plan #2 ................................ ................................ ................................ .................... 278 Farmton Alternate Plan #3 ................................ ................................ ................................ .................... 279 Farmton Alternate Plan #4 ................................ ................................ ................................ .................... 280 Bibliography ................................ ................................ ................................ ................................ .. 281

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7 | Page Abstract Human developments can cause many negative impacts on the ecosystems around the world. As the human population grows, it will require more land and resources which may re sult in the degradation of natural lands. Development has occurred at a quick rate in the United State and today only two fifths of the continental U.S. contains natural land cover (Shaffer and Stein 2000). The development of natural land can result in hab itat fragmentation which has helped to cause the extinction of amphibians, birds, invertebrates and mammals (Orff 2011). Recentl y, the State of Florida has created the Sector Planning P rogram that claims to potentially reduce negative environmental impacts while also improving the economic, social and fiscal development in the existing communities. The Sector Planning P rogram began in 1998 and has since been utilized in several lar ge scale developments. T his project examined sector planning to see if its implementation has resulted in reduced habitat fragmentation, protected or restored landscape connectivity, and protection for ecosystem services such as water management. In order to test the results of sector planning, four cases studies we re analyzed in GIS. The analyses identified the various impacts on three types of land uses that may be caused by each development : agriculture, conservation and urban. The developmen ts being studied are Farmton , Plum Creek Alachua County , the West Bay Se c tor Plan, and Restoration. Restoration is unique because it has two designs; the first design fr om 2006 was sprawling and inefficient and the second design from 2009 is more compact and protects more land than the 2006 plan. Farmton was also used as a test case to explore the relative character and quality of four alternative plans for the property. These alternate plans will then be analyzed with the same GIS models that were used in the case studies to allow for comparison so that trends in developmental impacts may be identified. Each case study was found to significant ly impact habitat fragmentation, landscape connectivity and ecosystem services. The West Bay Sector Plan caused the most impacts when compared to the other developments. The 2009 Restorat ion plan was the least impactful development in this study and the improvements from the first iteration of the design we re impressive. This project found that the Sector Planning Program does not significant ly reduce environmental impacts caused by ur ban development. Instead, the developments studied for this project will likely cause significant reduction in connectiv ity and ecosystem services with an increase in urban sprawl. However, the Restoration project leaves hope that if a land developer really wi shes to be more environmentally friendly, less impactful urban planning is possible.

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9 | Page Chapter 1: Introduction "Our human economy utilizes, consumes, converts, burns, or clear cuts annually more than 40 percent of the total NPP [net primary production] on land. In short, one species our own out of 5 million to 30 million species (no one is sure how many there are) is directly and indirectly claiming 40 percent of the earth's production for itself . " (Hawken 2010). Human actions o n this planet can cause considerable impacts to the various ecosystems around us. Humans overharvest flora, fauna and minerals; degrade and destroy countless acre s of habitat; greatly reduce the movements of species ; and have even begun to change the climate. These types of events are so common that they have been witnessed in almost every corner of our world (Sanderson et al. 2002). As people continue to develop a n d exploit the land they need to find ways to preserve an array of ecologically significant lands so that a high level of biodiversity and other ecosystem services provided by natural systems can be maintained. However, this may be a very difficult task be cause historically conservation efforts have been reactive rather than proactive (Groves 2003). T here have been various approaches to conservation and urban development; however, these new approaches are still continuing to cause various impacts to local ecosystems . Urban development s, along with the construction of roads in and around natural environments , are one of the greatest challenges to the protection of ecosystems today (Clevenger and Wierzchowski 2006). In order to help protect biodiversity ther e will need to be a shift in thinking by developers, urban planners and conservation planners . This is especially true in states like Florida where a very high rate o f population growth has led to high rate s of habitat destruction and fragmentation ( Noss a nd Cooperrider 1994, Hoctor et al. 2008, and Noss 1987). Interestingly, t he re is a long history of conservation practices from around the world. When people think of conservation they may envision large parks such as Yellowstone National Park or the Ever glades National Park. Yet, conservation has been around far longer than America. In fact, the first known laws protecting forests and game animals were enacted in India by Emperor Askoka around 250 BCE (Wright 1996). While many leaders and individuals und erstand the need Figure 1 1: An endangered Florida Panther. (www.wec.ufl.edu)

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10 | Page to conserve some aspect of the nature around us, they have not always approached conservation in a way that protects biodiversity. For example, conservation effo rts in America have largely focused on landscapes with a high scenic value rat her than focusing on unique ecosystems or biodiversity (Shaffer and Stein 2000). Planners often like to organize the world along geographic and geopolitical boundaries even though ecological systems rarel y hee d such lines (Groves 2003). Fortunately, many approaches to conservation are moving away from a focus on single sites and species to a focus on ecological systems. This can also be observed in Florida where $3.2 billion has been spent in order to protect a variety of natural areas for more than their scenic value (Shaffer and Stein 2000). Today, reducing habitat fragmentation is the target of many conservation efforts . Many conservation experts believe that the process of habitat fragmentation is a primar y cause of the current level of species extinction around the world ( Hoctor et al. 2008 and Noss 1987). Habitat fragmentation has many impacts on ecosystems which include reducing biodiversity, reducing the mobility of flora and fauna, and encouraging the isolation of populations (Larkin et al. 2004). While fragmentation can be caused through natural processes such as the formation of mountains, it is typically caused by human development. Both u rban sprawl and road development greatly contribute to habitat fragmentation. "As road networks extend across the landscape and their weave intensifies, natural areas become increasingly fragmented and impoverished biologically" (Clevenger and Wierzchowski 2006, pg. 502). Development has led to the extinction of at l east 500 native species in N orth America alone (Shaffer and Stein 2000 ). The numbers in Florida are just as alarming. Urban sprawl has led to a sharp decline in biodiversity at various levels ranging from genes to ecosystems (Harris and Scheck 1991 ). This is why planners and developers should begin to reconside r how they approach sit ing their developments in a world with fewer and fewer natural areas. Research Questions Throughout America, there are countless examples of the ways human developments damag e the natural systems that they inhabit . Unfortunately, many of the damages caused by humans, such as extinctions, are irreversible . One solution under development is improve d planning and design of urban areas to reduce impacts to the natural land. In F lorida, there have been numerous attempts to reduce the negative impacts of urban development. These include the development of regional impacts (DRIs) review process and the use of comprehensive plan s. Another is the Sector Planning Program which was crea ted in 1998 (Sector Planning Program 2015). This large scale planning program has been piloted and is now an officia l l y endorsed planning process that is being used in many areas around the state.

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11 | Page Question: Have sector plans, allowed under Florida Stat ute 163.3245, resulted in reduced habitat fragmentation, protected or restored landscape connectivity , and /or protection for valuable ecosystem ser vices such as water management? Hypothesis: As development become s more compact and less fragmented, it will have fewer impacts on the environment. Planning process es that succeed in promoting compact urban developments will also reduce environmental impacts by reducing habitat fragmentation and increasing or restoring connectivity and valuable ecosystem service s. The purpose of this thesis project is to investigate how effective sector planning is at reducing impacts. By learning how typical urban development degrades the environment, planners w ill be able to focus on better solutions and alternatives. In the future , planning and design must allow for the growth and success of human populations as well as native flora and fauna . The hypothesis will be tested by analyzing the impacts of multiple case studies that use different planning methods. If sector plans are effective at reducing impacts such as habitat fragmentation, then the plans utilizing these methods should produce the fewest impacts when compared to other large scale planning strategies. In total, this project will look at four case studies in the state of Florida. Two of the case studies are utilizing the sector planning program, one was reviewed by the development of regional impacts process and the last obtained approval through an amendment of a comprehensive plan. The case studies in this proje ct will be selected by looking at various factors of each potential case ' s development plans. These factors will include an analysis of fragmentation, conservation impacts, and changes to existing land uses. T hese case studies will help to illustrate som e of the negative and positive impacts of development on its surrounding systems. One case study will be selected from the group to undergo additional analysis. After a more detailed analysis of the focus case study, alternative plans will be developed bas ed on Land Use Conflict Identification S trategy analysis (LUCIS) (Carr and Zwick 2007). The case studies will provide examples of ways that planning and develop ment practices can be improved. S tandards and recommendations will be derived from the case study analysis.

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13 | Page Chapter 2: Literature Review Planning for the future can be a difficult task, especially when there is a large degree of uncertainty associated with what the future will bring. Today, planners are faced with a wide array of challenges that have not previously been encountered by our c ulture. Some of these challenges include global climate change, mass extinctions, and resource scarcity. This chapter will discuss some of the issues planners face today in detail. The subject of conservation will take the lead with issues involving biodiv ersity, fragmentation, connectivity, the effects of edges and ecosystem services . The next topic will involve planning strategies with a focus o n reserve design, road netw ork design, and urban planning and the third section will briefly discuss some planni ng programs in the State of Florida to include sector planning, developments of regional impacts and comprehensive planning. The final section will provide some basic information about the geographic information system that will be used in this project. Part I: Conservation Issues Biodiversity "More than 200,000 species have been formally documented for the United States....No other country equals the United States in its diversity of salamanders, freshwater mussels, or freshwater turtles, for instance, a nd our freshwater fishes and coniferous trees are also impressive on a global s cale" (Shaffer and Stein 2000). Biodiversity has become a focal subject in conservation planning in recent years in part due to experts finding that biodiversity is essential for the function of ecosystems and critical in the maintenance of life on the planet (Baydack et al. 1999). Many others have also come to the conclusion that many protected areas are simply not large enough to protect biodiversity over time (Hoctor et al. 2000 and Cooperrider 1991). However, before any meaningful discussion on biodiversity can begin there is a need to define the term for the purpose of this project. While the topic of biodiversity is very important it can also bring about a diverse array o f thoughts. The diversity of just the definition of biodiversity can be seen in Practical Approaches to the Conservation of Biological Diversity by Baydack, Campa and Haufler where 17 different definitions of the term are given! With such an assortment of definitions, it is not surprising that many of the sources define biodiversity in a similar method. Some definitions speak specifically to genetics while others remain very broad and vague. For example, in Conserving our heritage America's biodiversity, th e U.S. Forest Service broadly defined biodiversity simply as "the variety of life and its processes." On the other end of the spectrum, in Conserving biological diversity A strategy to maintain biodiversity and ecosystem function in the Northeas t, The U.S . Fish and Wildlife Service defines biodiversity as "the variety of life in an area, including genetic composition,

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14 | Page richness of species, distribution and abundance of ecosystems and communities, and the process by which all living things interact with one another and their environment." The term biodiversity comes from the phrase "biological diversity" which was first used in a formal method by Norse and McManus in 1980 (Baydack and Campa 1999). Norse and McManus's definition of the phrase contained two c oncepts which focused on genetic variation in a species and the number of species in a community. While all of the previous definitions are probably sufficient for this project, I would like to utilize the definition provided by E.O. Wilson in the introduc tion to Biodiversity II: Understanding and Protecting Our Biological Resources : "It is, in one sense, everything. Biodiversity is defined as all hereditarily based var iation at all levels of organization, from the genes within a single local population or species, to the species composing all or part of a local community, and finally to the communities themselves that compose the living parts of the multifa rious ecosystems of the world." This definition of biodiversity really covers all the various scales biodiversity could be used. It starts out in an incredibly vague statement , that biodiversity is everything , and then whittles it down from a very large scale of ecosystems to a very small scale of genetics. Biodiversity is a complex term and it is a ter m that is applicable at almost any scale. Some have explained the word in terms of levels such as a gene s, species, and ecosystems (Cooperrider 1991). These levels are essentially a biological scale with genetics being the smallest scale which builds speci es who then build the ecosystems. Another way to look at biodiversity is through its geographic scale. Poiani et al. (2000) listed four scales of biodiversity in geographic terms which were: 1) local geographic (meters to thousands of hectares), 2) Interme diate Geographic (hundreds to tens of thousands of hectares), 3) coarse geographic (tens of thousands to millions of hectares) and 4) regional geographic (millions of hectares or more). Thinking in terms of geographic scale is important because biodiversit y levels can be very different at these scales and the types of species and ecosystems in these areas will be changing. For example, a local geographic scale would contain species like the Bay checkerspot butterfly (Euphydryas editha bayensis) which may no t be able to travel far whereas a species like the Florida black bear that is able to travel great distances would be listed in a coarse or regional geographic scale (Poiani et al. 2000). The geographic scale is important because the approaches to maintain biodiversity in a small forest with a few species and single habitat type is very different than the approach needed to maintain biodiversity levels of a region composed of nu merous species and ecosystems. Along with the various scales of biodiversity it has three main components which include composition, structure and function (Groves et al. 2002). These components are also described by Noss (1990) and in his description the composition component contains the species and genetic elements of diversity. The structure component centers on how various elements are arraigned and it includes the pattern and complexity of the systems or communities while the function component focuses on time sensitive elements su ch as gene flow, evolutionary processes and disturbance cycles. Basically, these components allow biodiversity to again follow

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15 | Page another scale where the species elements form patterns in the ecosystem and then changes in that ecosystem may be seen over time. After looking at both the definition and scale of the concept of biodiversity, its importance is hard to discredit. However, having only a definition of the term does not convey enough of its meaning and importance to conservation practices. Biodiversity is important in all locations and across all scales of life. Value can be f ound in all scales and levels of biodiversity and this value can be described in economic terms. For example, biodiversity has provided a wide array of plants and microorganisms that are valuable to the medical field. One quarter of prescription drugs have an active ingredient that is composed of plants and 3000 antibiotics are made from microorganisms (Noss and Cooperrider 1994). People also utilize the biodiversity on the planet by harvesting large amounts of food by hunting and fishing. The amount of foo d collected from the world's oceans is staggering. In 19 88, 100 million tons of food were extracted from fisheries around the globe (Noss and Cooperrider 1994). Clearly, maintaining high levels of biodiversity will benefit the global economy as well as the ecosystems of the world. Economics are just one reason to preserve biodiversity. The environmental services provided through biodiversity are a little harder to put a price tag on. The varieties of ecosystems that exist each provide different types of s ervices. Some of the basic benefits provided by various Figure 2 1: Florida has a significantly high level of biodiversity as demonstrated in this map from The Nature Conservancy. (www.secpnc.wordpress.com)

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16 | Page ecosystems are air and water filtration, stormwater drainage and recreation opportunities (Bolund and Hunhammar 1999). Forests can help with air quality by reducing the amount of CO2 in the atmosphere and the same trees and plants in a forest can help to absorb water after a storm. Wetlands also provide a great way to control stormwater and they can also help to filter out contaminants in the water at the same time. Proper management of ecosystem servi ces is a great way to help planners with problems such as water quality which will be discussed later in this chapter. When looking at the world around us it is important to remember how much we need the natural lands for all the activities mentioned abo ve. By maintaining high levels of biodiversity it will be possible to meet the diverse economic demands for natural resources while at the same time protecting the functionality of the ecosystems around the world (Baydack and Campa 1999). So why is biodive rsity so important to ecosystem functionality? To start, an ecosystem encompasses a wide assortment of relationships and components that create a product that is greater than the sum of its parts (Noss and Cooperrider 1994). The world is a highly complica ted system that people may never be able to truly understand how all the components (species) of the world really interacts. Therefore, it is very possible that a particular species may be vital to the function of an ecosystem without being noticed. Then, if that one species or group of species is removed it may cause the system to collapse. Without the protection of the various species, ecosystems and processes around us it is possible that ecosystems will degrade to the point where they cannot function (C ooperrider 1991). Unfortunately, there are many threats to biodiversity today and these threats are largely the results of human actions. Some factors that may threaten biodiversity are water quality, human development, livestock overgrazing, extraction process, fragmentation, and climate change (Cooperrider 1991). Of these threats, human development is essentially the largest threat to biodiversity because it is often the cause of fragmentation, poor water quality, over consumption and even climate chan ge. With global populations continuing to rise, the demand for natural resources have created many of the conservation issues that are being faced today (Baydack et al. 1999). Human actions and developments have also caused the loss of many species around the world. Developments help to fragment the land causing extinctions around the world and in North America where more than 500 species have been lost and overall this represents a significant reduction in biodiversity at a global scale (Sha ffer and Stein 2000, Noss 1987 , and Baydack et al. 1999). Figure 2 2: Pictured above are the results of some human behaviors that can have an impact on a regions biodiversity levels. (Smokestacks: www.maxisciences.com/pollution/wallpaper), (Fish kills: www.glogster. com), (Clear cuts: wikipedia.org/wiki/Clearcutting)

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17 | Page Some regions are facing more threats to biodiversity than others and one such region is Florida. The state of Florida continues to experience a large influx of people and the state also has a very high rate of development to support its increasing populati on and this has led to an erosion of native biodiversity in the state (Harris and Scheck 1991). This loss in biodiversity is occurring at multiple scales including genetic losses, population losses and ecosystem losses (Harris and Scheck 1991). With variou s ecosystems and species being lost at an unprecedented rate, it is important for the development of a more holistic concern and response to environmental planning in the future (Cooperrider 1991). In the past conservation efforts worked to protect lands that were most beneficial to human use such as scenic landscapes or areas that contained a needed resource for human development. This has gradually changed and in the 1970's, biodiversity conservation began to focus on the protection of hotspots of biodi versity like the Hawaiian Islands and today it is focusing on the protection of genes and populations throughout various types of habitats (Poiani et al. 2000). Now, more research is showing the importance of protecting larger and more connected landscapes as a key to combat threats to biodiversity. The need for larger and more connected landscapes can be seen in states like Florida where rapid growth in population has seen the destruction of habitat that may best be countered by a connected network that is implemented at a large scale (Hoctor et al. 2000) As mentioned previously, conservation efforts have typical worked to protect individual parks and scenic landscapes across the country. These protected areas may be relatively small like Hot Spring Nation al Park in Arizona which is only 5,550 acres (22.46 km 2 ) or they may be incredibly large like Alaska's Wrangell St. Elias National Park which is the largest national park in America at 13,175,799.41 acres (53,320 km 2 )(NPS 2013). However, these parks were not designed to protect diversity which is why it is not surprising that evidence has been found that they are ineffective at maintaining biodiversity over time. Fortunately, the practice of conserving biodiversity is now a major force behind many project s and land management goals (Noss and Cooperrider 1994). By recognizing the complexity of the ecosystems around the world and working to develop a comprehensive approach that can function at various scales it will be possible to conserve the current levels of biodiversity around the world (Cooperrider 191 and Hoctor 2003). "The long term success of biodiversity conservation efforts will hinge on local communities' embracing the need for healthy ecosystems and flourishing wildlife populations. It will also depend on an enlightened economics that has learned to value not just individual species but the very fabric of biodiver sity" (Shaffer and Stein 2000).

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18 | Page Fragmentation As the human population continues to grow, more land will be required to support the race. This land may be utilized for food production, transportation, manufacturing, housing, business opportunities and even recreational activities. However, these activities will also have impacts on the natural areas that remain in proximity to human de velopments. The rate of development in America is rather surprising and this has resulted in a large reduction of natural lands. In fact, it is estimated that only two fifths of the continental United States contains natural land cover (Shaffer and Stein 2 000). If development continues and the remaining natural lands are not protected, development will cause the land to be fragmented into smaller and smaller pieces. Eventually the land may become so fragmented that it will not be possible to support any fun ctioning ecosystem. So what is fragmentation and why is it so vital for biodiversity and the persistence of various populations? Well, fortunately, fragmentation is a much easier term to define than biodiversity. The Oxford English Dictionary defines fra gmentation as: "the process or state of breaking or being broken into small or separate parts." So habitat fragmentation occurs when a patch of habitat is broken into smaller and smaller pieces. While the process of fragmentation is very simple, the effect s of that process are very complicated. Habitat fragmentation can cause the reduction of viable habitat, the reduction in species mobility, increases of eurytopic and opportunistic species and increased human presence (Noss and Harris 1986). Each of these impacts can reduce the beneficial levels of biodiversity in any region. Habitat fragmentation is very detrimental to the quality of existing habitats and many experts agree that the most serious threat to biodiversity is the process of habitat fragmentat ion ( Hoctor 2003 and Noss 1987). Some natural causes of fragmentation include streams and rivers cutting through a landscape or a mountain range that slowly divides a region. These natural processes are very slow and most species are able to handle the pace of change. Another natural process that moves more quickly could be a wild fire. As the fire burns an area it can leave cleared space next to forested areas. However, the most damaging causes of fragmentation are caused by anthropogenic events which include the development of road networks, utility lines, urban sprawl, drainage ditches and even fence lines (Noss and Harris 1986). These long linear structures can impact populations by reducing the connectivity between habitat fragments while also reducing the size of the ream ing patches. These smaller remaining patches may then become unoccupied over time due to increases in mortality and reductions in recolonization (Trombulak and Frissell 2000).

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19 | Page The reduction in core habitat and connectivity between othe r patches of habitat is one of the greatest issue s caused by fragmentation. In large, most of the co ncern for species loss due to fragmentation centers on a nimals yet plants can also b e impac ted . Various plants rely on animals for seed dispersal and they may also need areas t o migrate in order to survive a warmer climate . While fragmentation can spell do om for plant species it can more quickly impact wide ranging animals that may be referred to as area sensitive species (Harris 1985). All species have a functional minimum habitat requirement and when their habitat becomes too fragmented they may begin to perish. For example, many of Florida's bird species that rely on hardwood forests will not reproduce in forest fragments when they are located in a matrix of agricultural land (Harris and Scheck 1991). It is possible for a species to be able to exist in a small patch although; if that same patch is unable to support breeding activities then the population within that patch will have effectively become a sink population. Birds are not the only species that can be heavily impacted by habitat fragmentation. W ide ranging animals face an array of impacts in a matrix of highly fragmented lands. Large carnivores are especially vulnerable to the impacts of fragmentation due to their "low population densities, wide ranging movements, and the potential for conflicts with humans" (Dixon et al. 2006, 156). These animals often require large areas for migration or food purposes and the fragmentation of the land can cut off their migration routes or their access to food. For instance, the Florida black bear requires a larg e amount of land partially due to changes in their foraging habitat thought the seasons (Hoctor 2003). Black bears have even been recorded traveling as far as 83 km (51.5 miles) in order to reach a desired resource and that movement was not for dispersal p urposes (Hoctor 2003). Some impacts of fragmentation on the Florida black bear can be seen in the genetics of the remaining populations. Today, the Florida black bear has developed five larger sub populations in Florida, Georgia and Alabama due to the isol ating effects Figure 2 3: These are diagrams, made from aerials photos taken of forests in the Willamette National Forest, show how fragmentation can occur over time (Harris 1984, 39).

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20 | Page of habitat fragmentation (Hoctor 2003). While fragmentation has greatly impacted the Florida black bear population it has had much greater consequences for another well known carnivore. The Florida panther has also been affected by fragmenta tion due to its restrictions on panther movements. Increases in forest patchiness and fragmentation have been connected to the high levels of variability in the population of the Florida panther (Maehr et al. 2002). Fragmentation has really impacted the pa nther's ability to move between patches of habitat. Human development and infrastructures have created many barriers for panthers that are very difficult to cross. These barriers may take various forms and one of the most common forms is a highway. Highway s and roads are often a source of mortality for both panthers and black bears that attempt to cross them (Harris 1985). These systems can create very abrupt changes to an environment while continuing to fragment the area into large pieces. More significant ly though, these systems also disrupt and alter wildlife patterns along with the functions of the ecosystem they are fragmenting (Clevenger and Wierzchowski 2006). The development of roads can cause a wide range of issues for all species in an ecosystem an d their additional impacts will be discussed later in this chapter. Canals are another form of infrastructure that can create a highly impermeable barrier to panther movements. The Caloosahatchee River, which was extended to he lp control water levels in La ke Okeechobee, now has a wide channel that is capable of accommodating shipping along with step banks that make even reaching the water a difficult task (Maehr et al. 2002). This canal, which is over 400 feet wide in some locations, presents a significant barrier to dispersal for the Florida panther. The river helps to stop movement into central Florida and also helps to fragment the habitats regularly used by panthers. Areas south of the Caloosahatchee contain forested habitats with buffer patches in large patches that support the current breeding population of the Florida panther while the habitats north of the river are progressively isolated and fragmented (Kautz et al. 2006).This is a great example of ho w fragmentation can prevent a species' ability to recolonize an area that they previously inhabited. While a small group of male panthers have been recorded crossing this large canal, it is still very doubtful that the more cautious females will ever cross the infrastructure without some form of human int ervention (Kautz et al. 2006). "No small isolated population can maintain its dem ographic and genetic integrity indefinitely, thus modification to the environment that preclude natural movement patterns between habitat areas may be as devastatin g in the l ong run as is direct destruction of the habitat" (Harris and Scheck 1991). Figure 2 4: The Caloosahatchee River Basin is 1,400 square miles and is 70 miles long. This river is also known as the C 43 Canal. (http://www.protectingourwater.org/watersheds/map/caloosahatchee/)

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21 | Page The above quote really sums up what has happened in south Florida in regard to the panther population. Due to fragmentation of their habitat, panthers were left isolated in the eve rglades. The source of the fragmentation, roads and canals, made it very difficult for the panthers to move into new habitats while their population numbers were continuing to fall. The population finally reached a point where inbreeding was threatening th e survival of the Florida panthers. Evidence of this inbreeding could be seen in the physical traits of the panthers which included kinked tails and undescended testicles (Land and Lacy 2000). To combat this inbreeding, eight female panthers from Texas wer e introduced into Florida in 1995 (Land and Lacy 2000). This act increased the genetic diversity of the population in a way that could have occurred naturally if the Florida panthers were able to interact with the Texas panthers as they have in the past. T he result was a huge success for the Florida panthers and has increased the population nearly threefold (Fei et al. 2011). The Florida panthers demonstrate how fragmentation can destroy species even when its processes do not destroy all the viable habita t the species needs to survive. Beier (1996) presents another example of how fragmentation can impact a species. Beier found that a population of cougars went extinct by 1990 after they were isolated due to urbanization that occurred in the 1970s. When a s pecies is unable to roam freely it may not be able to meet its food requirements and it may also not be able to maintain enough species interaction to counter interbreeding ( Hoctor 2003 and Harris 1985). The current state of the Florida panther population also shines a bit of light on the fact that it is not too late to save various species from the effects of fragmentation. As time moves forward planners are moving away from historic planning practices of conserving areas just for their ability to produce a needed resource (Waller 199 1 ). This change in perception is happening in America as well as other countries. Europe as a whole has been paying more attention to the environment and this can be seen in countries like Germany where they are working to use more renewable energy sources. The Netherlands are also focusing on new approaches to infrastructure so that the environment is better protected. One specific program being implemented in the Netherlands involves the practice of forestry and is described by Dramstad (1996). The Dutch are using simulation models to plan their timber plantations. The models determine better locations for particular tree species and more importantly the models also have helped to cluster the plantations into larger habitats r ather than keeping them in small patches. They then use these larger tracts of forests to act as stepping stones which are more helpful for dispersal movements (Dramstad 1996). Using simulation models is an effective way to structure large scale conserva tion planning. The case study in the Netherlands is a great example of how more planners are beginning to work against fragmentation. Florida is also discovering new ways to reduce fragmentation on a regional scale. The state of Florida may have one of the highest rates of human population growth but it has also been spending an equally impressive amount of money to conserve la nd across the s tate ( Shaffer and Stein 2000 and Noss 1987 ). Florida has conducted a few studies that have identified important lands for conservation purposes. These studies involve the identification of critical lands and water otherwise known as CLIP (Critical Lands and Waters

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22 | Page Identification Project ). Other studies, such as the FEGN project (Florida Ecological Greenways Network), als o involve the identification of wildlife corridors to help maintain connectivity between fragmented lands. The CLIP and FEGN projects that are being carried out in Florida show how a region can work to combat fragmentation when it deems it important. However, it is important to note that while the state of Florida has be en outspending the rest of the United States on conservation focused projects, the amount being spent is still insignificant when compared to other areas of spending. While Florida spent $320 million a year (roughly $3.2 billion) to conserve land in the 19 90s, the annual budget for the state was $45 billion in 1998 (Shaffer and Stein 2000). In fact a single B 2 stealth bomber costs approximately $2 billion so for the price of a couple of stealth bombers we could easily fund ambitious habitat acquisition pro jects around the country (Shaffer and Stein 2000). Corridors and Connectivity "If native fauna and flora are to be maintained in perpetuity in human dominated landscapes such as exists in Florida there will need to be widespread adoption of the faunal movement corridor principle" (Harris and Scheck 1991, 204). One of the best ways to combat the fragmentation of natural lands is to increase connectivity with the use of corridors. By serving as linkages between existing reserves and various protected areas, corridors can help to improve a population's resilience in the face of climate change. The use of corridors to connect fragmented habitats may be the best option to work against the Figure 2 5: CLIP identifies and assigns priority on various types of lands that are important for conservation. This map is from the CLIP 3.0 Te chnical report. (www.fnai.org/clip.cfm)

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23 | Page impacts of habitat fragmentation, reduce isolation and encourage the colonization of various species (Dixon et al. 2006 and Larkin et al. 2004). Connect ivity may be a more functional way to maintain biodiversity as well because even the largest national parks have been losing species (Harris 1985). While studying the local loss of species in various national parks, experts have found that only an intercon nected system of parks can function in preserving fauna diversity ( Hoctor 2003 and Harris 1985). Corridors and landscape connectivity are very important for the protection of both flora and fauna species. It is especially important in light of the fact t hat the habitat matrix around the world has been changing from a landscape that was dominated by natural areas to a matrix of land that is dominated by a human dominated landscape (Harris and Scheck 1991). Corridors can bring many benefits to fragmented an d unconnected landscapes. They are able to increase movement between isolated patches of habitats, they can aid interactions between flora and fauna and they also augment the exchange of genetics between po pulations (Dixon et al. 2006). The concept of landscape connectivity and the development of corridors have proven to be difficult to implement around the country. Planners and city managers often side with developers even though many of these people, including strong critics of corridor s, understand that configuring habitats in a way that increases connectivity also enhances recolonization efforts and population viability (Beier and Noss 1998). Unfortunately, our market based economy places the needs of the free market ahead of the needs of the environment. Many markets cause real harm to the environment by hiding the true costs of products and services (Hawken 2010). This can be seen in various urban development plans around the country as well as in the state of Florida. There is a very specific example of growth and development being valued more by a city than the protection of an imperiled species in Beier (1996). In this article about metapopulation models, Beier discusses how the city of Anaheim approved a development plan that would ruin a wildlife corridor (the Coal Canyon Corridor) that was needed in order to protect the pumas in that region. Even after Beier was able to convince the city to acknowledge that development at the mouth of the corridor would destroy the corridor, the c ity still approved the plan "because other jurisdictions could destroy other parts of the corridor" (Beier 1996, 314). The case in Anaheim is a clear example of how many debates over conservation of wildlife corridors play out in real life. Even though th ere has not been a study that demonstrates conservation corridors causing negative impacts, many still fight the implementation of connected natural systems (Beier and Noss 1998). With many studies and experts suggesting that corridors help to provide bene fits to species i n the landscape, it is important to learn how corridors can be designed to maximize those benefits and how these corridors are actually being used successfully (Beier and Noss 1998). To begin this design process, corridors first need to be sited in the landscape. The location of a corridor can determine if it will be effective or not. For carnivores and many animals, connectivity is needed in order to allow for movement around some type of barrier (Noss et al. 1996). These barriers could be something natural such as a river, mountain range, or a fragmented landscape. However, the more common barriers to animal

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24 | Page movements are human developments. The above mentioned developments may include roads, urban sprawl, or utility corridors. While the location of a corridor is very important, it is also import to focus on the dimensions of the corridor or the level of connectivity needed in a specific landscape. The key here is a specific landscape because the size of a corridor and the amount of connec tivity a landscape needs really depends on the targeted species the corridor is meant to benefit. Target species needs to be identified when sizing a corridor due to the high variability in habitat needs from different species (Bennett 1999). Some species like raccoons and opossums are tolerant of anthropogenic areas and environments while other species such as cougars will actively avoid urban developments and roads whenever possib le (Bennett 1999 and Noss 1987 ). While corridors will need to provide speci fic types of habitats for the species they intend to convey, they will also need to vary in size to accommodate those species. The sizing of a corridor is a heavily debated element of a corridor's design. Due to costs, planners and designers push to know e xactly how small a corridor can be made and still maintain its functionality; however, it is very difficult for scientists to know for certain how small a corridor can be. For example, it has been suggested that a corridor designed for panther use should b e anywhere from 100 meters (330 feet) to 1,000 meters in width (3,280 feet) (Beier 1995 and Kautz et al. 2006). To further illustrate the variability in space demands, an animal like a salamander may only require a few small culverts with a radius of a few feet due to their limited ability to traverse large core areas in a single generation (Beier et al. 2006). With so much variability between species, how can a proper size be determined for a wildlife corridor? This question can be answered based on rese arch of the targeted animal's behaviors and based on the location of the corridor itself. The real key to sizing a corridor appears to be found in the ratio of the corridors length to width. A corridor may be functional even if it is less than 100 feet wid e when two isolated patches of habitat are only a few hundred feet away from each other. In 1991, a series of underpasses were added to I 75 in south Florida. These underpasses, which were 70 80 feet wide, functioned as small corridors to allow various spe cies to cross the highway which was about 160 feet long (Jansen et al. 2010). While very short corridors can be quite narrow, longer corridors will require wider widths. These longer distances however bring more debate into the design process. For instance , while Kautz et al. (2006) states that a panther corridor that is 6 km (3.7 miles) long should be 0.5 1 km (0.3 0.6 miles) wide Beier (1995) states that for distances less than 7 km (4.3 miles), a corridor can be as narrow as 0.4 km (0.25 miles). The two sizes are pretty close but 100 meters (330 feet) can make a big impact to the effectiveness of the corridor as well as its overall costs. When a medium sized corridor of 5 to 10 km in length can have some variance in the needed width what will happen when a corridor is being designed across an entire state like Florida? Unsurprisingly the amount of variance is even more pronounced. Harris and Scheck (1991) suggest that such a corridor with a length of hundreds of kilometers, where various plant and an imal species may migrate, would need to be anywhere from tens of kilometers wide to the entire basin of the St. John's River. The general idea being brought up repeatedly in the research

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25 | Page is that a wider corridor is better. Broad and heterogeneous linkages will be able to provide higher and more functional levels of connectivity than a narrow and well defined corridor (Noss et al. 1996). Unfortunately, the answer: build the corridor as wide as possible is the opposite of the designers approach to make it as small as possible in order to reduce costs. So why do animals need such wide corridors in the first place? Habitat requirements are the main reason that a significant amount of land is required for species to move large distances. Some animals can move v ery large distances in a short amount of time however, most animals move at a slow pace or are simply too small to move large distances. Smaller vertebrates like lizards and toads may take many generations to move into a new core habitat (Beier et al. 2006 ). Therefore, if these species enter into a corridor that will take three generations to traverse, the habitat within that corridor needs to sustain at least three generations of that species. While a lizard will not require a very large amount of space a predator like the Florida panther will require an extensive amount of land. Being a larger and more mobile animal, a panther can traverse distances of hundreds of kilometers, especially during dispersal events. In fact, in a study by Maehr et al. (2002) , one panther in Florida was found to have dispersed 224.1 km (139.25 miles) over a seven month period. This panther, number 62, moved out of the everglades and traveled as far north as Brevard County before returning to an area just north of the Caloosaha tchee River. In total, #62's journey took about two and a half years to complete and provided two very significant data points. First, #62 was the first documented panther to cross the Caloosahatchee River. The crossing of the Caloosahatchee River is an ev ent that was documented by two more panthers during this study. The second and possibly more significant data that came from this panther's journey was that his collar locations fell within the boundaries of the Florida ecological network 87% of the time. While #62 is currently an outlier in panther dispersals, it does show how far a panther can go when there is a corridor system that allows for its movement. Fortunately, panther #62 is not the only panther found to be utilizing wildlife corridors. In a s tudy of juvenile panthers in California, Beier (1995) found that five out of nine dispersing juvenile panthers used corridors. These young panthers used an array of corridors ranging from culverts and road underpasses to larger natural corridors like the a forementioned Coal Canyon Corridor. One particular cougar in this study, named M6, was a frequent visitor of corridors. M6 was documented using the Coal Canyon Corridor at least 22 times and he also used a vehicle underpass on 4 separate occasions and a cu lvert 18 times (Beier 1995). Sadly, some panthers that utilize corridors that intersect roads will not get a chance to use them multiple times. While M6 was very successful in his use of corridors, M10 was killed crossing a road in the Coal Canyon Corridor (Beier 1995).

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26 | Page Even though #62's (from Maehr's study) last signal was only about 25 km (15.5 miles) from the point where he crossed the Caloosahatchee, he spent years along a functional corridor (Maehr et al. 2002). This is why a corridor that is designed for panther use requires so much space. If a panther is to survive a number of yea rs inside a corridor then it will need to have enough land within that corridor to sustain the normal functions of that feline. For male panthers, the average adult range is approximately 250 km 2 and female panthers require about 5 km 2 (Beier 1995). With a sufficiently wide corridor, a panther (or other large mammal) can travel greater distances over a greater amount of time. These extra distances and amounts of time will also require nodes or temporary points to habitat while moving to a permanent territor y. Nodes built into a corridor will require even more space but they can provide vital resources that are normally distributed in non random locations in a landscape (Noss and Harris 1986). When thinking about the habitat needs of a wide ranging mammal, it is easy to see why corridors that traverse a significant distance require an equally significant amount of habitat. Figure 2 6: This map shows the movements made b from December 1997 until July 2000. (Maehr et al. 2002, 193).

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27 | Page Corridors help to promote genetic interchange between separated populations of species and they greatly increase the chance of a species survival ( Hoctor 2003 and Harris 1985). The effect corridors have on a population's ability to persist can be seen in a study focused on grizzly bears (Ursus arctos) that is described in Carroll (2006). The study compared how well the grizzly bears would f are in two different situations involving the Yellowstone to Yukon region. The first scenario looked at how the bears would respond to a doubling of the regions park size and the second scenario the connectivity of the parks was doubled. The result wa s tha t in response to the increase of the size in the parks the bear population saw a 47% and 57% increase in projected bear persistence while doubling the connectivity resulted in an increase of 81% and 350% in bear persistence (the first percentage refers to a developed landscape and the second refers to a semi developed landscape). Increasing connectivity is shown to be more effective than adding protected lands and this is primarily because a connected landscape can better support a population over a longer time scale (Carroll 2006). The effects of time on an isolated species can be seen in the aforementioned situation in south Florida with regard to the panther population. Increasing connectivity in a landscape with corridors can drastically increase the size of a habitat. This can be seen in a north Florida case that focused on the Pinhook Swamp. This case, found in D ramstad (1996) and Bennett (1999) , shows the benefits of joining two large conservation areas. These areas are the Okefenokee Swamp National Wildlife Refuge and the Osceola National Forest which are less than 10 miles apart. This corridor plan is comprised of three parts: 1) the Okefenokee Swamp which is about 400,000 acres, 2) the Osceola Forest which is about 160,000 acres and the Pinhook Swamp which is only 60,000 acres. By adding a broad five mile corridor resulted in the creation of 620,000 acres of co nnected land that may now be suitable for sustaining populations such as black bears or panthers in the long term (Dramstad 1996). While the level of connectivity in an area is only one factor in determining the ability of a species to persist in a fragme nted landscape (Carroll 2006), it is an important factor. It is especially important when considering possible changes to the world due to climate change. By connecting various areas or reserves, linkages can help to counter climate change (Bennett 1999). As the world continues to warm, animals may need to move further north or into higher terrain in order Figure 2 7: This is a map of the Pinhook Swamp corridor in northern Florida (Bennett 1999, 183).

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28 | Page to survive and find adequate food and habitat. A connected landscape can allow and facilitate range shifts which maximize species persistence (Bennett 19 99). These species movements over local and regional scales will become critical as the global climate continues to change (Poiani et al. 2000). Edge Effects Transitions exist all around us and they can be amazing experiences . Transitions bring about a tension that adds interest to anything. Life would get very boring if the view outside of a window was always the same day after day. Thankfully, the world is full of heterogeneity and has resulted in many types of edges between many types of environments . With these edges come transitions between habitat types and this section will delve into the issues around the transitions between edges and the effects they can have on various species. We encounter edges each and every day in the environments around us. Some of these edges have a high le vel of contrast that can be startling and others may have an area that smoothly transitions between two vastly different ecosystems in a beautiful and calming way. Since the world is not a homogenous system there will always be changes in the landscape at varying degrees and at varying scales. These changes in the landscape result in boundaries between vegetation patterns which may be created with the use of three different mechanisms: "Three mechanisms produce vegetation boundaries in the landscape: (1) a patchy physical environment, such as a mosaic of soil types or land forms; (2) natural disturbances, including wildfire and tornado; and (3) human activities, such as clear cutting and development for housing" (Forman 1995). No matter how they are created , edges have impacts on the surrounding landscapes and the species that inhabit them. At time s these edge effects are beneficial to the landscape and biodiversity and other times they can be detrimental to the entire system. The transition area between t wo edges can create a very diverse ecological zone with a high potential for productivity (Davis 2013). The space between two different environments may lead to the Figure 2 8: This diagram illustrates the variety of edge combinations that can occur in a forest. The greater the contrast between the left and right condition, the greater the edge effect (Harris 1984, 132).

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29 | Page development of new species that try to take advantage of the unique landscape that was crea ted by the interaction of the edges. These interactions can create a high level of diversity in both plant and animals species along the ecotones (Harris 1988). The increases in biodiversity along some ecotones have led to the belief that contrasts in the landscape are beneficial to the environment and biodiversity as a whole. While some edges do benefit the environment, there are many other edges that do not exhibit any beneficial impacts to the landscape (Forman 1995). In general, an area of habitat can be placed into one of two groups : core and edge. Core habitats are located in the center of a patch and the species that live in the core areas are often unable to be successful in the edge habitats. The edge habitats are in the areas between the core hab itats and are may contain a more diverse group of species that are often more opportunistic in nature. Probably the most successful species today is an edge species: humans (Forman 1995). As humans we like to sprawl out and fragment the landscape with vari ous types of development. These actions and development styles increase edge habitat and work to eliminate the values and services that may be derived from large patches or core habitats (Forman 1995). So how do edges provide benefits to an ecosystem? He rbivores , especially game animals like deer, tend to be attracted to edge habitats (Harris 1988). The high density and variety of herbivores around an edge also attract many predators that may be looking for an easy meal. Various predators such as raptors or canines enjoy edge habitats so much that these are as have been called "ecological traps" due to the high levels of predation that occurs (Forman 1995). All the activity in an edge environment really adds to its interest and recreation value as well. The benefits edges have on increasing game species has caused many game managers to "create as much 'edge' as possible because wildlife is a product of the places where two habitats meet" (Harris 1988, 330). There has been a large amount of research focused o n the edge effect and it is clear that many edges can be beneficial to the environment but it is also becoming clear that these edges can be just as detrimental in the right conditions. The problem edge habi tats pose is the many impacts they can have on core habitat areas. These impacts are especial ly damaging in areas of high contrast or sharp edges between the landscapes. While in the past sharp edges did not appear to have a great effect on the land it is now known that these sharp edges can allow the intrusion of abiotic and biotic forces that ca n cause a reduction of the biological value of the habitat (Harris and Scheck 1991). While sharp edges may be caused by natural events like wildfires; today, they are most commonly caused by human actions. Human actions taking place outside of core habitat areas may create the greatest Figure 2 9: Here we see two diagrams showing the relationship between core and edge habitat. As the surface area of natural land increases, the amount of edge habitat also increases. (Dramstad 1996, 31).

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30 | Page threats to various types of natural areas (Noss and Harris 1986). Some of the most common developments that are threatening the landscape via edge impacts are linear structures. These developments are typically roads, canal s and utility corridors that create very long lines of high contrast in the landscape which can cause adverse impacts on the na tural integrity of a landscape . Roads are especially harmful because their impacts can resonate far into the ecosystems that they fragment while they also allow for even greater access into areas for exploitive activities (Trombulak and Frissell 2000). The construction of roads greatly increases the amount of edge habitat due to their shape and this results in a reduction in interio r habitat for edge sensitive species (Clevenger and Wierzchowski 2006). The distance these impacts may resonate into a core area depends on the type of activities and the habitat itself. However, in can be expected that the impacts may carry 5 km (3.1 mile s) into a habitat and that these impacts may reach even further when considering wide ranging animals and the seeds they may be transporting (Harris and Scheck 1991). Edges not only cause impacts that ripple into another habitat but they can also stop sp ecies in that same habitat from moving to new areas. Many edges act like a selective membrane that creates a barrier for some species and acting as a filter for othe rs (Forman 1995). M any bird species do not like to be around edge environments and some wil l not even cross a small edge. In fact, fewer bird species are found in edge conditions that contain tree gaps (Forman 1995). Large predators also dislike artificial edges and this can be seen in the behavior of panthers in California. It has been found th at adult panthers will not utile habitat peninsulas that are surrounded by dense urban areas (Beier 1996). Development can reduce the permeability of an edge through changes in land use. As development intensifies more land use may also intensify and low i ntensity lands (agriculture and silviculture) may become more developed and further reduce the connectivity in a landscape while also increase the impacts from the edge habitats (Hoctor et al. 2000 and Larkin et al. 2004). While the past actions of land and game managers focused on increasing edge conditions in order to increase the densities of game animals, some are now focusing on buffering areas with strong edge impacts. With wildlife management focusing more on plant and nongame conservation research has exposed the fact that many characteristics found in edge environments are undesirable (Harris 1988). Some of the methods being used to protect core habitats from edge impacts are to add buffer zones so that the core area is more insulated and protecte d. The basic process is essentially creating a softer transition between the edges rather than keeping the sharp contrasts that often exist around human developments. There can be many benefits to simply adding a buffer zone between habitats with high co ntrast. Buffers can help to reduce the amount of invasive and domesticated species that can be brought into a core habitat from an edge and they can also reduce the amount of pollution and trespassing that often occurs with human activity (Noss 1987 ). Buff er strips can be very helpful in the protection large predators. In confrontations with humans a large predator may feel cornered and could be aggressive and buffers are useful in reducing the amount of potential interactions between people and animals (No ss et al. 1996). Another benefit of buffer zones is

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31 | Page the creation of a new habitat. This new habitat that is created by the buffer area can act as a supplement for species that are in need of protection in the core habitat . By adding buffers to the landscape it is also possible to add recreation value to the land. Land uses such as nature trails and restored ecosystems are a lower intensity than road and housing developments. These areas may buffer the core habitat while als o allowing for the movement of plants and animals, yet if they are too narrow and contain disruptive activities such as the use of recreational vehicles; they may not include species that have a higher demand for conservation (Harris and Scheck 1991). In o rder to allow movements of plants and animals these areas would need to be wide enough so that the species are not being intimidated or removed by the users of the parks (Harris and Scheck 1991). Buffers could also be paired with the removal of nonessentia l roads that can contribute to road kills, fragmentation and poaching (Hoctor et al. 2000). It is important to continue to increase our understanding of edge effects and how different habitats interact with each other. Now that some research is showing that not all edge conditions are beneficial to all species there will be a need to protect enough core habitats to Figure 2 10: The above design gradually reduces the intensity of human activity as developments increase their proximity to the natural vegetation. This allows for better protection of core habitat are as (Dramstad 1996, 44).

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32 | Page support the species which are impacted by edge conditions. Wide ranging species like carnivores will greatly be nefit from the reduction of ne gative edge effects due to their need for areas that are relatively free of human actions and impacts (Noss et al 1996). Ecosystem Services and Water Protection Ecosystems provide many services that are often unnoticed by the general public. Some of th ese valuable services include gas regulation (CO2 and O2), climate regulation, erosion control, food production, and even water treatment (O'Brien 2010). While all of these services are important for the health of our ecosystems and our populations, one se rvice has risen above the others in the public eye. The importance of water treatment and protection is a service that people of all backgrounds can agree on. Fresh water is required for a vast array of human activities and it is not a plentiful resource. Water is used for drinking, cooking, cleaning, irrigation and even manufacturing. Although water is vital for various human activities it is also wasted in many ways. In fact, our waste has led to water shortages around the world. Many regions were expect ed to have some form of water shortage over the last decade even in the absence of drought (Glennon 2009). In face of these shortages, many regions are beginning to look for new ways to secure water and ensure its protection. The typical response by water management districts is to restrict water usage or promote conservation programs. However, as water problems become more common, some water districts are looking for new methods to protect their water sources. The Southern Nevada Water Authority (SNWA ) is one example of a water district that is has found new ways to conserve water. While this district does utilize various conservation efforts such as rate increases and water restrictions, they are also looking to planning options to reduce demand (Webb er 2013). The most notable programs being used at the SNWA involve future planning and landscape ordinances. The water authority implemented a program to replace turf grass and promote more natural vegetation in residential and commercial zones (Webber 201 3). This helps reduce the amount of water being wasted on irrigation while also promoting the use of native plants which can help to provide more habitat for native species. The SNWA has also been looking into the future when planning and forecasting its water supplies. This has allowed them to be more flexible when unexpected changes occur and has also allowed for various policies and procedures to be implemented that have allowed them to manage their water resources more successfully (Webber 2013). Whi le the SNWA has focused more on human consumption of water, others are focusing on water treatment and ground water recharge. Ecosystems can help considerably with both of these goals. "The ability of healthy watersheds to moderate water flows and purify d rinking water supplies is one of their most tangible and valuable services." (Postel and Thompson 2005). Wetlands in particular are able to provide many valuable services when left in their natural state. Wetlands and the vegetation they contain can be ver y useful in removing contaminants from water. This ability allows them to function as an active purifier that helps to limit negative

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33 | Page impacts from agriculture and urban areas (Chan et al. 2006). As wetlands remove pollution from water they also absorb a lo t of water which can help reduce the amount of runoff downstream thus helping to prevent or reduce flooding. Conservation of wetlands and forests can be very helpful and beneficial for water regulation and flood control (Chan et al . 2006). Lands that hel p improve and protect water quality can also provide conservation and economic services. When wetlands, marshes and forests are protected various habitats are also protected which help to protect biodiversity. Riparian systems provide habitat for many land dwelling animals as well as fish and aquatic invertebrates. Safeguarding fisheries can support recreation and tourism activities as well as that fishing industry (Postel and Thompson 2005). These lands also provide economic services by reducing costs and maintenance needs. One study have found that water treatment costs were 50% lower in an area with 60% forest cover versus an area with only 30% forest cover (Postel and Thompson 2005). There is one project in Gainesville, Florida that helps to illustrate the importance and benefits of using functioning ecosystems to improve and protect water quality. The Paynes Prairie Sheetflow Project is working to restore water flow into Paynes Prairie National Park. The north end of this park has been channelized which has allowed untreated stormwater to enter into the prairie and into the aq uifer (Pearson and Rankeillor 2013). In order to reduce the amount of pollution entering into the prairie, Gainesville, SJRWMD and Florida Department of Transportation has come together to design a park that will treat the water using artificial wetlands. The main Figure 2 11: This is a map of the proposed Paynes Prairie Sheetflo w Restoration project. The project uses wetlands to help improve water quality. (www.cityofgainesville.org/)

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34 | Page goal of the park is to reduce the nitrogen loads from urban runoff and this option was found to be cheaper than improving the city's water treatment plant (Pearson and Rankeillor 2013). This park will hopefully open in 2015 and is already attracti ng horses from the prairie as well as several species of birds such as woo d storks (Mycteria americana). Part II: Planning Issues Reserve Design "Old questions about how large a single reserve must be,... have largely given way to new questions regardin g the optimal scale of the entire network of conservation lands, their relationship to surrounding lands, how lands in all categories are actually managed, and whether the overall management regime is capable of maintaining ecological integrity" (Noss et a l. 1996). Reserve design is important in the protection of biodiversity and ecosystems functions. There have been many different approaches to reserve design and there continue to be new approaches as scientist s learn more about how ecosystems function. As human development continues to consume more natural lands there will be an increasing need for well designed and well protected lands that can support a wide array of flora and fauna while also allowing the ecosystems to continue to function. As reserve d esign continues to change, it can be hoped that conservation efforts will continue to become more proactive and less reactive like they currently tend to be (Groves et al. 2002). The practice of land management first came to fruition due to the need to p rotect valuable lands from overconsumption. This practice can be seen in the passing of the first wildlife protection laws in India that protected game animals and the forests they required to live (Wright 1996). Often, lands are only protected once the pu blic realizes that they need the land for resource extraction or its scenic value. Protecting lands for extraction of resources is very common and many professionals have focused their conservation efforts on the protection of species (plants or animals) t hat are directly used by humans (Waller 1991). Further evidence of the reactive nature of conservation planning lies in the United States own game conservation laws. The original conservation laws were enacted as a reaction to a decline in the amount of ga me species and even early forest reserve legislation was a reaction to the degradation of public and private forests (Cooperrider 1991). In many ways, the United States has been a leader in conservation and reserve design. While biodiversity has not been a great importance in conservation decisions, this nation has still protected a large amount of land that contains many treasures that have tremendous value for recreation and resource management (Shaffer and Stein 2000). Unfortunately these scenic landsc apes are not where reserve designers should focus in the future. These scenic landscapes often contain lands that are unwanted by developers or they are lands that the general public would work to protect without the need for help. Fortunately, today conse rvation experts and reserve designs are reacting to an increased appreciation of the values of biodiversity and this is

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35 | Page causing many to look at conserving areas with higher levels of genetic diversity (Cooperrider 1991). Hopefully, as time moves forward co nservation efforts will continue to place more importance on biodiversity so that we are not doing a better job of protecting the scenic landscapes instead of protecting endangered species and unique ecosystems (Shaffer and Stein 2000). Today, reserves e xist at a variety of scales that range f rom 5,550 acres to 13,175,799 acres ( NPS 2013). Some parks and reserves are heavily managed while others are left in a more natural element. In Florida, 17% of core conservation lands are strictly managed and this nu mber drops to 5% if the Everglades National Park is removed (Hoctor et al. 2000). Conservation levels typically vary from state to state. In 1994, approximately 7 million acres of land (about 1/5 of the state) were under conservation and this was enough la nd to meet the needs of only 14 of the state's 44 focal species (Shaffer and Stein 2000). That fact helps to illustrate just how much land is required to protect an array of species throughout a region. In order to support a large carnivore for just a few decades a reserve would need to be between 1,000 10,000 km 2 and if that carnivore is to survive for a long term an area larger than 100,000 km 2 would be required (Noss et al. 1996). 100,000 km 2 is an incredibly large amount of space to be provided in a single reserve. In fact , that converts to 24, 710,538 acres which is 11 million acres larger than the largest park in the country! This is why reserve designs need to move away from single parks to a connected system of parks (Noss et al 1996). The need for a well connected reserve system similar to the FEGN is continuing to grow. The failure to protect land in an adequate amount combined with the fragmentation human development causes has led to a high loss of species. "Nearly one quarter of the world's mammals, one third of the amphibians and more than one tenth of bird species are threatened with extinction" today (Orff 2011, 1). These high levels of species loss have resulted in the disruption of natural ecosystems and landscapes which is why more ecologists are working to consider the spatial patterns that exist in a landscape in order to maintain the functions of the ecosystems (Noss and Harris 1986). However, reserve design and land use plann ing faces many threats and obstacles that can be difficult to overcome until a greater appreciation for the process is cultivated. Many of the difficulties in implementing an effective reserve design lay in the process of planning. In the past the process to plan a reserve simply involved the protection of a large area of land with the hopes that it would be large enough to support and sustain the species that existed within it. Today, experts now realize that these reserves do not function properly when they are only planned whi le isolated from their surroundings and from the development of the land over a period of time (Harris and Scheck 1991). Reserves will interact with the surrounding lands and can be significantly impacted by the matrix of the landscape around the preserve. This is why the planning process should involve a comprehensive approach that looks at the surrounding lands and the impacts that may influence the reserve in the future.

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36 | Page The process of designing a reserve can be a time intensive venture due to the complexity of the design process. Designing a reserve requires a large amount of information and is an iterative process that must remain flexible so that it can incorporate new information (Hoctor et al. 2000). In general, a functional reserve design will need to be conducted at a scale that not only protects habitat and ecosystems b ut also allows compatibility between the various land uses that may exist in the plan (Hoctor 2003). There are numerous principles to reserve design and these principles may overlap while some are more focused on particular process es and data sets than oth ers. One simple approach to reserve design outlines three principles for the conservation of biodiversity: representation, resilience, and redundancy (Groves et al. 2002; Shaffer and Stein 2000). A reserve design meets the principle of representation by in cluding as many species and habitats types as possible that are found in the region. The design fulfills the resilience principle by ensuring that the species and habitats that are being conserved are able to persist into the future and a redundant design will provide multiple reserves so that if one fails there is another redundant reserve that can continue to protect species. A more complex framework for reserve design has been proposed by Groves et al. (2002). This planning framework contains seven step s with the first step being the identification of conservation targets. The first step is important for deciding the scope and scale of protection to be provided by the reserve. The second step is the collection of data and identifying gaps in the data. Th e third step is the creation of conservation goals which should be realistic and may occur at a smaller scale than the identification of conservation targets which would be at a more regional scale. The fourth step utilizes gap analysis to determine what i s currently being conserved in existing reserves and conservation areas. The fifth step is similar to Shaffer and Stein's second principle and focuses on the evaluation of the conservation targets ability to persist. Next, the sixth step of the framework w ould produce a portfolio of reserve areas so that a Figure 2 12: The FEGN project identifies areas t hat are significant for preserving connectivity in the state of Florida. (www.fnai.org/clip.cfm)

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37 | Page network of conservation areas can be designed. This step is important because a functional reserve may need to be a large and integrated network in order to conserve species (Hoctor 2003). The final step to the framework proposed in Groves et al. (2002) is the identification of priority areas for conservation. By utilizing the information and results of the first six steps the designers can identify and propose areas that would be important areas that may present a stronger need for conservation. This framework is a good process for identifying areas needed for conservation and it is also a nice method for designing an integrative reserve system. Along with the various principles a reserve should have the re are also some characteristics that can be found in a functional reserve network. Four characteristics for a functional reserve design are listed in Poiani et al. (2000): First, the reserve area should be sized based on the needs of a focal species. Seco nd, the reserve area needs to be capable of maintaining the processes of the ecosystem (both biotic and abiotic) over a time frame that is relevant to the reserve's conservation goals. Third, the reserve area may include human uses but it is advisable to l imit the activities of people due to the impact such activities may have on the ecosystems. Finally the fourth characteristic is the need for management or restoration practices in the reserve to maintaining the functionality of the ecosystem that is being protected. The use of these four traits in a functional conservation area can be very effective especially when combined with a focus on a focal species or a group of focal species. By having a focal species to protect it will be easier to create conser vation goals and to determine how much space is required for the reserve. Focal species that require diverse habitats and large areas may also ensure the protection of smaller species that have more specific needs (Poiani et al. 2000). It may also be helpf ul in determining how much connectivity the reserve may need as well as what management regimes it may require. Management schedules are very important in the maintenance of an ecosystems function. For example, a reserve designed to protect long leaf pines , which help to create a fire adapted ecosystem, may require fires to prevent dense woody undergrowth that can impact the pine ecosystem (Hoctor et al. 2006). The required management routines and the habitat needs of the species will really guide how a res erve is designed. Without a focal species in mind, it will be difficult to determine what core habitat areas will be needed and the proper size of corridors and buffering distance that are all important to consider in the design of any reserve (Hoctor et a l. 2000). The proper identification of core habitat and buffer zones can also be important in combating fragmentation due to lands being converted to more intensive uses (Hoctor et al 2000). Determining the size and scale of a reserve is very important i n determining what kinds of species and habitats will be able to be conserved. In general, as reserve size is concerned, bigger is better because the larger reserve networks will be able to contain a more thorough representation of the species and habitats located in a region (Hoctor et al. 2000). Small reserves can also be helpful when created as a network. By grouping several smaller, well connected reserves a system can be formed which may be easier to create than a s ingle large reserve (Hoctor 2003 and Noss 1987 ). When considering a reserve system over an individual reserve, it can be even more useful to have a particular species in mind. By focusing on a wide ranging

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38 | Page species such as a carnivore, a planner may be able to protect the longer distances spec ies may disperse (Noss et al. 1996). Wide ranging species will also require more land to protect and this can help to increase the size of the reserve system. It has been estimated that as much as 20% of a region may need to fall under a reserve system in order to fully conserve biodiversity (Groves et al. 2002). Another important component to a reserve design is its shape. Core areas of habitat can easily be impacted by edge environment and the shape of a reserve can determine how much edge a reserve has . Ideally, a reserve would be more circular in shape and would avoid being convoluted or have various folding areas that could increase the surface area of the core habitat (Dramstad 1996). The surface area of a reserve contains the edge habitats; thus, th e longer the perimeter of a reserve the more edges it will have compared to core habitat. It is also important to provide buffers between the core habitat and urban areas. These buffers can be used to combat negative edge effects and they can also be used to restrict human activities that may impact the focal species that are being protected. In this situation it is best to have two buffers one that is an active use buffer that would be located next to urban areas and a passive use buffer that would be betw een the active area and the core habitat (Dramstad 1996). The shape and required amount of buffer zones needed in a particular reserve will largely be dependent on the context of the land outside the reserve system. The landscape around the reserve will help to determine what lands require protecting and may also influence how the lands are protected. Conservation and reserve plans that occur at a regional scale will require an array of data that may include population and development trends, ownership pa tterns, habitat analysis and conservation targets (Groves et al. 2002). Reserve designs that work to protect multiple species and habitats and that are based on multiple criteria will proved a more ideal design than one which simply focuses on a single dat a set (Noss et al. 1996). The context and location of a reserve is very important in regard to the planning of buffer and core habitat areas. Landscape ecology has shown that the spatial context of an area is significant and experts have also recognized ho w important context can be in the management of biodiversity (Hoctor et al. 2006). If the reserve will exist near an urban context there may be more roads and developments that need to be buffered. It is better to plan for core habitat areas to be in areas without roads or areas that have a very low road density to protect the species and habitat from harassment and persecution from people (Noss et al. 1996). The presence of roads in a reserve can increase road kills and has also been found to cause the los s of some spe cies such as wolves (Noss 1987 ). Reserve systems may require a significant amount of land to sufficiently protect all the species and habitats in a region and they may need to be even larger to provide areas of redundancy. However, a reserve can still significantly improve the protection of a community even if a few important species or habitats are unable to be preserved (Hoctor et al. 2000). Reserve systems may also be improved by cooperating with private landowners. Through the use of ince ntives and rewards, landowners who value protecting the environment may be more willing to contribute to conservation goals and projects which will be necessary when they own land that may be critical in the preservation of biodiversity (Harris 1985). By u tilizing the principles and frameworks listed above as well as collaborating with various agencies and landowners it will

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39 | Page still be possible to maintain high levels of biodiversity around the world. Reserves are important because just saving one species isn 't enough; it is important that the systems and landscape patterns are conserved as well (Shaffer and Stein 2000). Road Network Planning "The impacts of roads on natural environments and the means of mitigating such damage are undoubtedly one of the mos t important land and wildlife conservation challenges of this new century" (Clevenger and Wierzchowski 2006). Roads are an increasingly vital component of human infrastructure. Our transportation networks provide commercial services by aiding shipment of goods; they provide emergency services by functioning as evacuation corridors and they also allow the general public to move freely across vast distances. The various services provided by roads have led the United States to build 13,107,812 km (8,144,816 m iles) of travel lanes with an average width of 3.65 m (12 feet) (Trombulak and Frissell 2000). In south Florida, there are 1300 km (807 miles) of highways which occupy 1160 km 2 (286,642 acres) (Maehr et al. 2002). As roads remain a vital component to human development they will continue to be spread across the landscape. Unfortunately, l arge scale road construction has led to the destruction of at least 4,784,351 hectares of land that previously provided support to various types of flora and fauna (Trombula k and Frissell 2000). Road networks can have a wide variety of impacts on the landscape. Yet, even though there is an abundance of road networks around the world, it is seldom that pre construction data is ever gathered about a landscape before a road is placed in the area (Cle venger and Wierzchowski 2006). The lack of data about a habitat before a road is built can make it more difficult for researchers to prove that the roads may be the cause of an ecosystem's problems but there is still plenty of evidence to implicate the roa ds. Both paved and dirt roads can cause changes to an ecosystem, increase the exploitation of the environment, fragment the landscape, create Figure 2 13: This is a map of the highways that are located throughout the state of Florida.

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40 | Page barriers for species movements, and act as a source for species mortality. With roads being constructed at rates o f 6 km (3.7 miles) per day, it is important that we learn how to plan networks in a way that has fewer impacts to the landscape (Harris and Scheck 1991). As one of the most prominent urban features in the landscape, roads are able to influence the landsc ape in many ways (Clevenger and Wierzchowski 2006). When a road cuts through a landscape it can create significant changes to the microclimates, soils, hydrology, and species behavior in the areas where the road is built (Trombulak and Frissell 2000). The construction of a road involves the removal of vegetation, alteration to hydraulic movements, and the addition of foreign materials such as concrete or asphalt. These roads will then require maintenance which can introduce another set of contaminants into the ecosystem. Heavy metals, salt nutrients and organic molecules will likely be introduced in landscapes during and after the construction of a road and these can adversely impact the landscape as well as the health of streams that are located around a ro ad (Trombulak and Frissell 2000). Along with changing an ecosystem, roads also provide access to remote areas and allow for more efficient exploitations of the land (Trombulak and Frissell 2000). These exploits may be in the harvesting of game species, t rees, and various minerals. The removal of resources from an ecosystem can cause even more damage especially if species are over harvested and completely removed from an area. The extraction process that is encouraged by road development can have high impa cts to large carnivores. Large carnivores like grizzly bears are less likely to survive in an area that is more intensively used by humans due to various potential conflicts between the two species (Noss et al. 1996). Wolves are also impacted by road netwo rks and can even be wiped out in areas with higher road densities. A study in northern Wisconsin found that wolves will disappear from areas that have a road density greater than .93 miles of road per 1 squ are mile of habitat (Noss 1987 ). The presence of r oads in a landscape can effectively act as an indication tool for the health of a habitat i n regard to large carnivores. As shown in the Wisconsin example, as the road density in a landscape increases the suitability of the habitat in that same landscape w ill decline for carnivores (Noss et al. 1996). Road development is also efficient at fragmenting the landscape as mentioned previously in this chapter. Highways and roads are often suspected of causing the fragmentation of natural lands (Clevenger and Wierzchowski 2006). The long linear shape of a road makes it an easy tool to split lar ge habitats into many smaller pieces. Roads are often built at low cost and rarely include elevated areas to allow species to pass beneath or above them. Highways can be even worse due to large field of vision requirements that help to create large shoulde rs along the road with little vegetation. When a high speed, multi Figure 2 14: This underpass under Fl. State Road 46 uses an elevated road along with fencing to funnel wildlife under the road. (wikipedia.org/wiki/Wildlife_crossing)

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41 | Page lane road is placed through a forest it can create a long line of high contrast edge habitat for miles along the forest. Fragmentation of the natural lands and the degradation of ecosystems will continue to occur as road development continues to weave across the landscape (Clevenger and Wierzchowski 2006). As roads continue to fragment the landscape they also continue to create edge conditions that also impact the landscape. The artificial edges that are created by roads can isolate species while also encouraging invasive species to move into the landscape . The creation of more edges along with the fragmentation of core habitat areas can significantly reduce the amount of viable habitat for many species especially those that are edge sensitive (Clevenger and Wierzchowski 2006). The typical edge effects that impact an ecosystem as previously discussed can all be found along road networks. The roads provide a hard edge that can allow for the r esonation of impacts well into core habitats, the reduction of species mobility, and it may even change the behavior of the species that interact with the edge (Hilty et al. 2006 and Trombulak and Frissell 2000 and Clevenger and Wierzchowski 2006). Activit y along roads can cause animals to be cautious of the environment. Many species will only attempt road crossings at night yet these crossings can further be impacted by the presence of artificial lights. Species that move through habitats at night will avo id artificial lighting and the presence of such light can inhibit their foraging behaviors as well (Beier 1995 and Hilty et al. 2006). While the hard edges can increase the edge effects along a road corridor they can also help to turn the same roads into barriers. Barriers can impact long distance dispersals which are necessary in the process of ensuring a species ability to persist over large scales of time (Harris and Scheck 1991). Many studies have found that dispersing animals will avoid roads which h elp to show how effective they act as barriers. Beier (1995) contains a study showing how juvenile panther avoid roads and arti ficial lighting and Noss (1987 ) discusses a study in Arizona that demonstrated how panthers avoid roads whenever possible. Roads with many lanes and high traffic volumes will be a stronger barrier than smaller and lower volume roads. A road can also become less of a barrier if it is designed with a system of underpasses. After the installation of underpasses to I 75 in south Florida , panthers and other species were able to safely move under the interstate highway. This project turned the interstate into a more permeable barrier that reduced mortality and reduced fragmentation for several species (Foster and Humphrey 1995). While road s have been identified as a potential barrier in many linkages, the creation of more permeable solutions are only effective when they are cited in areas that will be utilized by various species (Beier et al. 2006). Somewhat surprisingly, roads can have s ome benefits to species. Some species are able to find road networks helpful for migration, food resources, and for the regulation of body temperature. However, roads typically become a double edged sword for the few species that they help. Roads can actua lly enhance the movement of caribou but they also increase their chances of being killed in a collision with a vehicle (Trombulak and Frissell 2000). Small birds and snakes find the heat generated by roads to be rather alluring and are often struck by cars while enjoying the microclimate along the road (Trombulak and Frissell 2000). Many species are killed along roads

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42 | Page by both natural predation and through vehicle collisions. While virtually all drivers have seen road kill at some point, many do not realize just how many animals are killed along road networks. Paynes Prairie , located in Alachua County, Florida is a large wetland that has been fragmented by two major highways. I 75 and U.S. 441 run in a north south direction along the western side of Paynes P rairie. In the 1990's, U.S. 441 had several underpasses added to allow for greater movement of water and species between the two halves of the prairie (Anonymous 2000). In a rare event, data was collected on the volume of road kills along the road before t he construction of the underpasses. During one of the studies that took place over 4.5 years, 13,000 snakes (weighing a collective 1.3 tons) were killed along U.S. 441(Harris and Scheck 1991). The death of 13,000 snakes over a span of 4.5 years equals an a verage of just under 8 snake deaths per day along only about 3 miles of road. Unfortunately, roads cause the death of many other species throughout the state of Florida. In southern Florida, road kills greatly limit the recovery of the American crocodile ( Crocodylus acutus) and road kills are also the largest mortality source for the Florida black bear and Florida panther (Trombulak and Frissell 2000 and Noss et al. 1996 and Harris 1985). Since roads often cause the degradation of ecosystems, removal of n atural resources, fragmentation, barriers to species movement and wide spread deaths of many animals, it is important that planners work to mitigate the negative impacts roads create. Changes in road design can help to lessen the impacts of roads on an eco system. By planning areas along the road to allow for wildlife crossing it is possible to reduce the barrier effects roads may have on species movements (Noss and Harris 1986). Since carnivore populations tend to have low densities, mortality can limit the ir success in an environment and this mortality can be reduced by limiting developments that block habitats or cause the species to exhibit avoidance behaviors (Carroll 2006). Roads that run parallel to wildlife corridors and habitats rather than perpendic ular to the habitats can reduce fragmentation and continue to allow species movements. The process of removing nonessential roads or even selectively relocating some roads may also help to reduce the negative effects roads may cause (Hoctor et al. 2000 and Trombulak and Frissell 2000). While there are ways to mitigate and reduce the impacts of roads on the landscape it may not be possible to create a road network that does not cause harm to the environment. For example, roads will likely persist as a sign ificant source of mortality for wide ranging animals that need to cross roads in order to survive (Trombulak and Frissell 2000). Roads may still cause damage even if they are mitigated and remediated which is why s ome have seen the importance of avoiding p rojects that involve the construction of major new roads (Trombulak and Frissell 2000 and Hoctor et al. 2000). Perhaps it is time for a new approach in thinking in regards to the dev elopment of road networks. It would be nice if planners reduced their focu s on how design ing road network s in natural lands and instead think about whether a road network should exist in natural lands.

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43 | Page Urban Planning Throughout history each major civilization has had its own famous cities. The Egyptians have Cairo, the Greeks have Athens, the Romans have Rome, the British have London and America has New York. Each of these cities has brought large amounts of people together to exchange goods, services and knowledge. Today, there are around 4,000 cities with populations greater than 100,000 people (Angel 2012). As the human population continues to grow, its demand for natural resources will continue to present challenges to the maintenance of biodiversity (Baydack et al 1999). The negative impacts human developments have on the environment are the reason why planners must exercise caution when planning for future developments to support our species. This section will look at how urban growth has been managed in the past, how it is being managed today, and why plans that feature s mart growth principles will be needed now and in the future. With transit routes, utility corridors and sprawling development littered across the world, humans have an ever increasing presence in natural lands. Unfortunately, the influences that humans ex ert on the landscape are some of the greatest threats natural areas face (Noss and Harris 1986). In the past, there have been many calls to reduce or contain human developments and most of these calls have failed to have any effect on controlling urban dev elopment. Some of the first attempts at controlling urban sprawl came in London during the reign of Queen Elizabeth the First (Angel 2012). In 1545, London's population was around 70,000 and further increased to 1,000,000 by 1800 and it further exploded to 10,000,000 by 2000 (Angel 2012). Clearly even the queen of England has been unable to slow growth in large urban regions. The growth in London has consumed 226,400 hectares (2,264 km2) of land over 200 years (Angel 2012). Without a great focus on the futu re, London is now a city that has a high density and has been very successful. Another great city which has experienced a large growth in population and urban development while also becoming very successful is New York City. New York has taken a differen t approach to growth; instead of trying to contain or stop development, the city went ahead and planned areas for growth to occur. In 1807, the city of New York designed a gridded road network that would allow for as much as a sevenfold increase in urban d evelopment (Angel 2012). By thinking of the future, New York was able to control its growth while helping to create a more organized city. While New York and London approached growth in two different ways, they both became dense and successful cities and t hey have both lost density in recent years as more of their population moves to the surrounding suburbs (Angel 2012). Over the years, many cities and regions have lacked strong development plans and this has led to an increase in urban sprawl around the world. "In many cases local land use regulation were adopted without any clear picture of their ultimate consequences when implemented" (Arendt et al. 1994, 44). Increases in urban sprawl can often been seen in states like Florida but they are also found i n European countries. In particular, over the last 60 years there has been a significant increase in the levels of urban sprawl found in Europe (Angel et al. 2012). As sprawling

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44 | Page developments have increased urban density has decreased and as densities decre ase urban environments become less organized and more fragmented (Angel 2012). This fr agmentation helps to increase impacts that urban developments have on surrounding natural lands. This effect can be exacerbated as the same developments become less dense and c onsume more natural lands. With about two fifths of the United States remaining under natural cover, planners are changing the strategies they use in the process of land development (Shaffer and Stein 2000). Some planners and experts are worried about the effects urban developments are having on the environment and other are simply responding to a growing group of people who want a new approach to urban design. Many states and regions are now attempting to reverse the post World War II development trends that have decentralized urban regions (Arendt et al. 1994). These changes in attitudes have allowed for the development of new strategies and policies. Thanks to the adoption of terms like sustainability and smart growth, there have been more calls for compact development, higher dens ities, mixed use zoning and even the re development of brownfield sites (Angel 2012). There have been many responses to the impacts of urban sprawl that range from new calls for reduced development to better planning of future development. Angel (2012) pr ovides many arguments for better planning and the continuation of urban development. The Planet of Cities contains many examples where cities were simply unable to stop growth throughout history. By looking at the past attempts to control growth the author has come to the conclusion that urban growth should not be contained but rather markets should be allowed to determine how cities grow over time. The strategies presented in Angel (2012) typically involve improvements to the planning of road and transit n etworks. With only 27.3% of the U.S. population living within urban areas dense enough to support transit, "a reasonable goal for the coming decades may be to double the share of the urban population living at transit sustaining densities" (Angel 2012, 34) . In order to accommodate future development, Angel (2012) looks to urban planning in New York to propose that more arterial road grids be planned along the edge of urban areas. These grids would: 1) have total coverage around the urban area; 2) would have connectivity; 3) the roads Figure 2 15: This is a map of all the urban lands as identified in the CLC data from the Florida Fish and Wildlife Conservation Commission.

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45 | Page would be spaced in 1 km intervals for ease of walking; 4) the roads would have a wide right of way so that land would not have to be purchased again in the future; and 5) the area would be progressively improved over time. Sim ilar to Angel, 1000 Friends of Florida released a report that has proposed the incorporation of transit planning in urban planning in order reduce sprawl. In a report title Smart Growth for Florida's Future , the linking of transit and land use planning is recommended for the development of compact cities that may reduce the energy that is expended by commuters (Anonymous 2009). Throughout Smart Growth for Florida's Future , the concept of smart growth is promoted in urban planning. In the report, there are s ix goals associated with smart growth which are meant to reflect the values that are believed to be held by the majority of Americans. These six goals are: 1) greater neighborhood livability; 2) better access with less traffic; 3) cities, suburbs and towns that are not only successful but thriving; 4) shared benefits across communities; 5) lower costs and taxes; and 6) the preservation of natural lands by keeping open space open (Anonymous 2009). Other researchers have come to different conclusions about how to better plan urban development but they largely utilize plans that allow for continued growth. Arendt et al. (1994) suggests the creation of more flexible land uses along with regulatory agencies that respond not only to the landscape but to the soci al structure of a region as well. The basic idea in Rural by Design is to avoid zoning and regulatory processes that are overly confining to development. While it is important to design plans that can offer more flexibility it is also important to remember that some developers may still want to adjust the plans to better suit their standard development plan (Arendt et al. 1994). Sustainability is also a key part of many new strategies to urban planning and some of these strategies include: the reduction of vehicle miles traveled; promoting the conservation of agricultural, natural and rural land uses; water conservation through the use of xeriscaping; the preservation of existing buildings to reduce the demand for new building materials; and the promotion of green technologies (Pattison 2009 B). Those who wish to protect biodiversity and ecosystem functionality often approach urban planning at larger scales and with a greater level of integration. In order to promote a greater compatibility between land uses as well as protect natural resources, urban and conservation planning will need to be conducted at a sufficiently large scale (Hoctor 2003). By looking at scales that cover an entire region, planners will be less likely to make choices without acknowl edging the context of the developments. It can be unethical to make planning decisions in a vacuum without proper considerations of the development's surroundings (Harris and Scheck 1991). Still, some believe that the process of protecting species and func tional ecology will require some development limits due to the fact that "smart growth does not stop or limit growth" (Compas 2012). The reason sustainable planning and smart growth principles are needed is due to the impacts that sprawling developments have on both the environment and the residents living in the region. Sprawling and fragmented developments cause disturbances to vegetation and wildlife that

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46 | Page surround the edges of the development (Angel 2012). The further a development occurs from an urban center the greater its fragmentation and the more energy it will need to consume in order to transport goods and people (Angel et al 2011 and Angel 2012). More sustainable growth focuses on more compact urban development which can bring many benefits. A m ore compact urban area will require less land so it may be easier to preserve the rural and natural lands which can help with carbon sequestration, biofuel development, and passive recreation opportunities (Anonymous 2009). Through the promotion of smart g rowth it may also be possible to offset global climate change by protecting natural lands that provide valuable ecosystem services and through the encouragement of walking and cycling which may occur more often in compact cities (Pattison 2009 A and Ange l 2012). More compact developments that are paired with higher densities and greater habitat conservation can accommodate the worlds growing populations with few er impacts to the surrounding landscapes. By continuing to recognize the complexities of ecosystems and making realistic projections of land requirements in urban areas it may be possible to work towards reducing the loss of biodiversity while also improving methods of urban development (Cooperrider 1991 and Angel et al. 2011). Fortunately, cities naturally tend to become more compact as they grow which is one reason why they have often shown great efficiency throughout history (Angel 2012). Part III: Plan ning Processes in Florida Sector Planning The sector planning program was created in 1998 and in 2011, under Chapter 2011 139 changed the program by amending some of its requirements and ending its pilot status (Sector Planning Program 2015). Before the c reation of the sector planning program, large land use plans were reviewed by process such as the Development of Regional Impacts (DRI) program or though comprehensive plan amendments . T hese programs focus on large scale urban and regional planning project s and work to reduce negative impacts on the environment or negative impacts to people in the region. "[Sector Plans] shall provide the principles, guidelines, standard, and strategies for the orderly and balanced future economic, social, physical, enviro nmental, and fiscal development of the area that reflects community commitments to implement the plan and its elements. (163.3177 2014). The sector planning program offers the ability to create comprehe nsive long term plans that can be utilized on a lands cape scale (Powel, Hunter, and Rhodes 2014). Sector plans look well into the future and many have a time horizon that looks 50 years into the future. This new planning tool has several components and there have also been a few changes that were made when t he process left the pilot phase.

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47 | Page There are two main components to a sector plan. The first is a long term master plan and the second is a detailed specific area plan (DSAP). During the first phase, a plan is developed for a region and land uses as well a s general density targets are identified. Policies are then created that help to guide the development and the protection of natural resources (Sector Planning Program 2015). Sector plans are then approved by both local and state govern ments and adopted in s comprehensive plan. In phase two, more detail is added in the form of a DSAP. DSAPs have a minimum size of 1,000 acres and are implemented with local governments function ing in a manner similar to DRIs (Sector Planning Program 2015). DSAPs ca n be completed over time and in separate pieces. For example, only approximately half of the West Bay Sector plan has undergone the DSAP process. The DSAP has to be completed before any development can occur. In order to test the utility of the sector pl anning program, a pilot program was designed. During the pilot phase this program was optional and required a written agreement with the state (Powell, Hunter and Rhodes 2014). The size limit f or the pilot program was 5,000 acres and DSAPs were a minimum o f 1,000 areas although both of these req uirements could be reduced if the Department of Community Affairs (DCA) agreed to allow it (Powell, Hunter and Rhodes 2014). The West Bay Sector Plan was one of the few completed pilot project s and was formally adopt ed in 2003. Some incentives of the pilot program included increased collaboration between various agencies and an exemption from the DRI review process ( Powell, Hunter and Rhodes 2014). The pilot program ran from 1998 until 2011. In 2011 the sector planni ng proc ess was permanently adopted by the legislature and i t con tained a few changes to the pilot sector planning process. The first change involved increasing the minimum size for a sector plan from 1,000 acres to 15,000 acres but the minimum s ize for DSA Ps were still set at a minimum of 1,000 acres. The finalized program also removed some of the review and oversight from the pilot program. This include s removing the need to obtain advanced approval from a state agency and removing the requirement for DSAPs to be subject to a compliance review from the state (Powell, Hunter and Rhodes 2014). After the approval of a sector plan, the densities and land uses that were allowed will be able to be developed at any time in the future under the conditions set forth in the plan. While the original developer may decide not to develop the lands, any person of company that buys the land will be entitled to build out to the densities listed in the approved sector plan. Development of Regional Impacts The Developm ent of Regional Impact process was implemented by the Florida Environmental Land and Water Management Act of 1972 which was meant to protect the natural resources in the State of Florida (Committee of Community Affairs 2011 and Firth 1985). This 43 year ol d process is periodically reviewed by the Florida Government to assess its functionality and continued need. The last review conducted in 2011 found that the process was still useful in ensuring that rural communities continue to build effectively (Committ ee of Community Affairs

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48 | Page 2011). The DRI process, like the se c tor planning process, is meant to encourage more efficient urban planning while also protecting natural resources. DRIs differ from the comprehensiv e planning process because they consider extraju risdictional impacts , which is a valuable aspect of the process (Committee of Community Affairs 2011) "Development of Regional Impacts (DRIs) are developments which, because of their character, magnitude, or location, are presumed to have a substantial eff ect upon the health, safety, or welfare of citizens of more than one county. The variety of projects that can fall under DRI status include large scale planned development, airport expansions, office and industrial parks, mi ning operations, and sports and entertainment facilities." (Developments of Regional Impacts 2012). The DRI review process can be an expensive and time consuming process with the process occasionally taking years to complete . Developers have claimed that the routinely takes two years an d can cost millions of dollars to complete (Nicholas 2000). The entire process involves working with regional planning councils and local government agencies. There are 11 regional planning councils in Florida that represent the many different regions in t he state (Committee of Community Affairs 2011). After a development has been approved under the DRI process it will receive vesting rights. This means that any approved levels of development will always remain possible even if changes to the DRI process and the laws that allow for its use are changed in the future. Under Florida Statute 163.3167(8) it is in this act shall limit or modify the rights of any person to complete any development that has been authorized as a development of Figure 2 16: This chart illustrates the DRI process and identifies the length of time the steps may take to complete. (Committee of Community Affairs 2011, 5)

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49 | Page tee of Community Affairs 2011, 7). Overall, the DRI process has been successful although it is slowly being phased out and replaced by more localized planning process. A 2000 study of the DRI process found that DRI applications were rejected only 7% of t he time, approved 84% of the time, and approved without conditions 9% of the time (Nicholas 2000). With 93% of applications being approved through the DRI process, it is hard to see this as a program that significantly impacts development in Florida. Com prehensive Plan Amendments The comprehensive planning process is used across the nation. This planning process helps to set up goals and frameworks to help guide physical development and community services (Randolph 2012). The comprehensive planning process was first adopted in the State of Florida in 1975 with the adoption of t he Local Government Comprehensive Planning and Land Develo pment Regulation Act. This act required local governments to adopt and implement a comprehe nsive plan (Nicholas 2000). A standard comprehensive plan has three key functions: 1) a vision for the future developed with some community input; 2) a legal foundation for growth management that has been adopted formally by elected officials; and 3) an an alytical and technical basis for local programs (Randolph 2012). The adopted plans in Florida also have three basic goals: to meet the requirements of the state comprehensive plan, handle growth in an appropriate manner, and be responsive to the needs of Significant changes were brought to the program under the State and Regional Planning Act which was passed in 1985. One of the aims of the new act was to prevent urban and suburban sprawl. S prawl has been defin ed as: and rural areas. It frequently invades land important for environmental and natural resource protection. Sprawl is typically manifested by one or more of the follo wing patterns: leapfrog development; ribbon or strip development; or large expanses of low of Transportation 2013 , 24) The Comprehensive Planning Act is a very complex law wi th a high level of detail that specifies the many processes and procedures involved with the creation and implementation of a comprehensive plan. In summary, there are eight main parts to the law that are required to be a part of any comprehensive plan: (1) capital improvements; (2) future land use; (3) traffic circulation; (4) sanitary sewer, solid waste, drainage, potable water, and aquifer recharge; (5) conservation of natural resources; (6) recreation and open space; (7) housing; and (8) intergovernme ntal coordination

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50 | Page Comprehensive plans are reviewed by the Department of Community Affairs (DCA). The DCA checks to see if the proposed plans are compliant with the state plans. If the plan was not found to be in compliance, it was pos sible to impose sanctions; however, this process was effectively ended by Governor Chiles in 1990 (Deyle 1998). Even when allowed, sanctions were rarely used and the review process has typically involved negotiations when plans were not in compliance. Co mprehensive plans are updated on a r egular basis and changes can be made through amendments. In the past, it was only possible to pass an amendments twice in a given year but this restriction was removed in 2011 (Florida Land Development Regulation 2011). When changes to a local comprehensive plan are made they are also reviewed by the state which has process also includes the concept of concurrency. This requires that the services needed for a development, such as transportation, schools, and other infrastructure be available concurrent with development (Randolph 2012). Part IV: Geographic Information Systems (GIS) GIS Overview Geographic information systems are powerful tools that can be used for creating maps and analyzing large amounts of geographic data. The GIS program used for this entire project is ESRI's ArcMap 10.1. This mapping program allows for two types of data: vect or and raster. Vector data is represented in three feature classes: points, lines, and polygons which are all based on a coordinate system. The program uses coordinates (typically in an X, Y format) to create the three feature classes. A point consists of a single X and Y coordinate and may also include a z value to define elevation. Point data only provides a location and does not have an area, length or perimeter. Schools and hospitals are often represented as point data. The next feature class is a line which requires at least two pairs of X and Y coordinates. These features may also include a z value and will create a vertex that possesses a length. However these features still do not have an area or a perimeter. Roads, rivers and pipes are data types th at will often be represented as a line. When you combine a series of lines you can create a polygon feature class which has an area and a perimeter. Water bodies and county boundaries are typical examples of polygon features. Raster data is based on cell s rather than coordinates and are more similar to pixels on a screen. All the cells in a raster grid are the same size but they may have different values. These cells are arranged into rows and columns and each cell represents information about the area it is covering. The cell size of a raster data set will determine the accuracy of the data. Larger cells will reduce file sizes and speed up processing time but smaller cells will provide more accuracy. Raster cell values occur in two types: discrete values and continuous values. Discrete values are associated with integer values or whole numbers and can be used to illustrate data that is individually distinct or has a distinct boundary. An example of a discrete data set would be land use data. Continuous dat a sets are represented with floating point values and the values are

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51 | Page constantly changing over a surface. Common types of continuous data are elevation data and euclidean distance data. Each data type has its own strengths and weaknesses. In general, vect or data is more accurate however raster data is more suitable for analysis. Various types of vector data can be combined to create networks. For example, a water infrastructure network can be created by taking a line shape file that represents water pipes and combining that with a point shape file that represents a water source, a water valve, or a destination (sink). On the other hand raster data sets can be stacked on top of each other and then tools can analyze the information in the various cells. Suita bility analysis is conducted by taking multiple suitability raster grids, placing them above each other, and then performing a calculation that creates a new set of values to represent the input values. Raster data can be more flexible and more efficient w hen conducting complex analyses if many data layers are needed (Carr and Zwick 2007). This project utilizes both raster and vector data sets and each data type have been useful for different operations. Much of the data used in the case study analysis wa s vector based while most of the data used and created in the suitability analysis was raster based. In order to complete several tasks, much of the existing vector data would need to be converted into a raster format and occasionally some raster data woul d need to be converted into a vector format. There are multiple options for converting vector data into raster data and vice versa. Most conversions involved converting vector data into raster data for analysis purposes. All of the original raster data w as created with a cell size of 15 meters. This means that each raster cell was a square with 15 meter sides. The 15 meter cell size was maintained throughout the entire project. Along with a standard output cell size, each data set was projected using the Albers Conical Equal Area. There are many organizations in the state of Florida that freely distribute GIS data and most of my data was obtained from government run sites such as the St Johns River Water Management District. I also obtained a great deal of data from a non profit organization called The Florida Natural Areas Inventory (FNAI). See appendix A for a complete description, list, and source of all the data used in this project. A complete listing of GIS tools will also be included in appendix A.

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53 | Page Chapter 3: Methodology In order to determine the effectiveness of sector planning in the state of Florida, this project will use a geographic information system (G IS) to analyze the four case studies to ide ntify impacts on the environment, ecosystem services and existing urban character. This chapter will explain the process involved with the case study analysis as well as the suitability analysis that will be used to help create alternate plans for the Farmton development. The chapter will conclude w ith a short list of limitations that were encountered during the project. Figure 3 1: This diagram represents the basic process the methodology for this project will follow. Part I: Case Study Analysis Case Study Selection This project will look at four developm ents and analyze their impacts on surrounding lands. The selected case studies are located in three separate areas in Florida. One study is located in the panhandle, another is located in north central Florida and two are located along the east coast of the state. Each case study was selected based on six aspects of development which are listed below. One exception was made in regards to the Restoration development. Restoration meets five of the six crite ria but falls short on the criteria . Given that two different plans were developed for it, it is included even though small, because if demonstrates the potential advantage of more compact design . Both of the Restoration p roject iterations will be analyzed to see how a more compact design can reduce impacts to the environment.

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54 | Page Case Study Selection Criteria The selected cases should: 1) Be a sector plan , DRI, or other state approved planning process . 2) Occur in a previously undeveloped location. 3) Propose the develop ment of more than 8,000 dwelling units. 4) Be located on a site of more than 15,000 acres. 5) Be located in a priority area as identified by the FEGN project. 6) Occur in an area that contains valuable habitat that may be impacted by development. 7 ) Make a claim about being a "green" or otherwise "sustainable" type of development. The case study selection also depended on the availability of data. Even if a development project met all six criteria, it would not be a suitable case if GIS data were not read ily available for the site. Case Study Evaluation Each case study was analyzed in GIS in order to determine what impacts the developments will have on the land around it. A series of operations were used to determine the impacts to three land use types present in each case study landscape. These were agriculture, natural, and urban lands. In the following sections, the processes and tools used to analyze the development projects will be discussed in detail. In order to begin the evaluation of the case studies there were a few operations that needed to be completed so that each evaluation would include some context and not isolate the developments. All the analysis was conducted at two scales. The first scale was at the site level and the second scale i ncluded an area extending ten miles around the site. This was accomplished by buffering each property and using that buffer to define the larger study area. By defining a larger study area, it was possible to see how the individual developments impacted th e lands around them as well as the lands within each development . This following section will discuss the methods and approaches used to analyze and compare the various case studies used in the project. During this process 20 different tools in GIS were used to help analyze each case. Each case underwent the same procedures in order to keep the data consistent and replicable. The data analysis was conducted twice for each study area. The first run of each analysis looked at the study areas without any new development and only used the existing land use and cover data. The second run inserted the proposed land u ses in order to identify change . The majority of the case study analysis involved identifying changes to the acreage of a data se t due to development. This was completed in two ways depending on the type of data being used. When working with vector data, a new field was added to the attribute table and then the acreage of the data was calculated with a simple function called calculate geomet ry. Rast er data cannot be assessed with the calculate geometry function so instead utilized the field calculator. With the

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55 | Page field calculator it was possible to convert the cell count of the raster data into acres. Since each 15m x 15m cell is 225 m 2 the acreage was calculated with the following expression: 0.55598*[count]. The count equals the number of cells in a data set and 0.055598 equals 225 m 2 so if a data set has a count of 18 cells the conversion will reveal that it is 1 acre in size (0.05559 8*18=1). The final results were arranged into an excel file for easy comparison and storage of the data. Each case study spreadsheet had four columns which contained a space for the pre development data, the post development data, the amount of change as well as the percent of change between the developed and undeveloped conditions. This excel file was useful in reducing math errors and resulted in a clear and simple analysis format. Case Study Methods Developments can cause many impa cts on the existin g landscape and t his project will look at impacts to agriculture, conservation and urban areas. Below is a list of the changes that will be identified and quantified with the use of GIS analysis. Much of the analysis will focus on identifying changes to c onservation needs. The analysis will identify the change in a data set based on area (in acers), distance (in meters), and the number of a given element. Agriculture Impacts A 1: Identify changes to fragmentation levels in working landscapes. A 1.1: Fin d the number of connected agriculture lands before development. A 1.2: Find the number of connected agriculture lands after development. A 2: Identify changes to the quantity of working landscapes. A 2.1: Compare the changes to the amount of crop lands p re and post development A 2.2: Compare the changes to the amount of pasture lands pre and post development. A 2.3: Compare the changes to the amount of timber lands pre and post development. A 2.4: Compare the changes to the amount of specialty lands p re and post developm ent. Conservation Impacts B 1: Identify changes to fragmentation levels in natural lands. B 1.1: Find the number of connected natural lands before development. B 1.2: Find the number of connected natural lands after development. B 2 : Identify changes to the quantity of natural lands. B 2.1: Compare the changes to the amount of proposed conservation land pre and post development. B 2.2: Compare the changes to the amount of priority natural communities pre and post development. B 2.3: Compare the changes to the amount of strategic habitat conservation areas pre and post development.

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56 | Page B 2.4: Compare the changes to the amount of fragile coastal resources pre and post development. B 2.5: Compare the changes to the amount lands designated as biodiversity priorities pre and post development. B 3: Identify changes to the edge habitat areas. B 3.1: Compare the changes to edge habitat pre and post development. B 3.2: Compare the cha nges to intact lands in buffer zones pre and post development. B 4: Identify impacts to linkage priorities. B 4.1: Compare changes to FEGN identified priority lands pre and post development. B 4.2: Compare changes to CLIP landscape priorities pre and pos t development. B 5: Identify impacts to water management lands. B 5.1: Compare changes to functional wetlands pre and post development. B 5.2: Compare changes to aquifer recharge areas pre and post development. B 5.3: Compare changes to significant sur face water areas pre and post development. B 5.4: Compare changes to lands with natural floodplain functions. Urban Impacts C 1: Compare changes to urbanized lands. C 1.1: Find the amount of developed land before development. C 1.2: Find the amount of developed land after development. C 2: Compare changes to the proximity of proposed developments to existing urban areas. C 2.1: Identify the distance between urban areas before development. C 2.2: Identify the distance between urban areas after develop ment. Ag riculture Impact Methods Preparation: In order to begin assessing the impacts to agriculture areas, data was extracted from the land use cover map (CLC_v3_Poly from FWC.com). All agriculture land uses were selected and made into separate data s ets. The agriculture data was grouped into four classes: livestock production, crop production, timber production, and specialty production. After this data was extracted from the land use map it was then clipped to a ten mile study area around each case s tudy and it was clipped to the property boundaries of the development site. Next, attribute fields were added to the data's attribute table so the acreage of the data could be calculated. A 1: The patch analysis of the existing agriculture was completed with the use of the region group tool. The statistics of the patch data was then recorded and compared. Due to rounding issues the minimum patch size would always result in a 0 so the only statistics that were recorded were the number of patches, the large st patch and the average patch size. Then the proposed development areas were used to erase any data in the impacted areas and the process was repeated. A 2: The quantity analysis used the agriculture data from the land use cover as well as a raster data set that detailed areas of existing and potential sustainable forestry (forstry_v4 from

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57 | Page FNAI.org). The data was clipped to the study areas and then the acreage was calculated. Finally, the development area was used to erase any data that would be impacted and the acreage was recalculated. C onservation Impact Methods Preparation: Conservation needs and priorities were defined based on the data produced by the Florida Natural Areas Inventory (FNAI). The majority of the data from FNAI was in raster format with the exception of existing conservation lands (FLMA_201412 from FNAI.org) and proposed conservation lands (FFBOT_201408 from FNAI.org). Land use data was a lso used in order to define intact lands and developed lands in each study area. B 1: Impacts to habitat fragmentation has been measure in two ways. The first method involves a process called percolation theory. The second analysis method involved patch s ize analysis in the same manner as A 1. B 1.1: This theory was used to "describe how small branching molecules form larger and larger molecules. This polymerization process may lead to gelation, that is to the formation of a network of chemical bonds spa nning the whole system." (Stauffer and Aharony 1994, 4). Percolation theory can be used in both three dimensional and two dimensional grids. The basic process involves a grid or lattice that has two values. One cell type is occupied and the other cell type is unoccupied. For this project intact lands are considered occupied and developed lands are unoccupied. The theory looks at the ratios between occupied and unoccupied cells and tries to determine at what ratio will there likely be a connection that allow s percolation through the lattice. The critical value for a two dimensional lattice is 59.2746 % (Stauffer and Aharony 1994). As a cluster of occupied cells approaches the threshold of 59%, it will statistically find a path to allow it to percolate through its grid . Intact lands were defined as undeveloped lands, low intensity agricultural lands and utility corridors. Developed lands consisted of roads and urban areas. In order to weed out roads that were not a complete barrier to wildlife movement an expand and shrink function was performed on the intact land raster data set. This allowed connections between intact areas that were fragmented by roads with 2 or fewer lanes. The fragmentation of each study area was analyzed at three scales with the focal statistic function (calculating the majority value). The smallest focal area was 105 meters by 105 meters, the second focal area was 1,005 meters by 1,005 meters and the largest focal area was set to 10,005 meters by 10,005 meters. After the amount of int act lands and developed lands were obtained the ratio between the two were identified. This was completed by simply dividing the number of intac t lands by the total area. L ands that fell below 59% may not provide connectivity based on the percolation theor y.

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58 | Page B 1.2: The second method to analyze the fragmentation of conservation utilized a patch size analysis. This process used the intact lands data set and then used the same methods as the ag riculture patch analysis. Region group was used to group the intact lands and then the data was reclassified into six categories ba sed on the size of each patch. B 2: This step used identified potential changes to five different data sets which were all obtained from FNAI.org. These steps all looked at the acreage of the data before development and then removed data that occurred in the areas of proposed development with an erase or clip function. B 2.1: Proposed conservation was defined by the FFBOT_20 1408 data set from FNAI.org. This data was clipped to the study area and its acreage was assessed. Then the proposed development data was used to erase any proposed conservation and the acreage was reassessed. B 2.2: Priority natural communities were def ined by the natcom_clip3 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The Figure 4 0.59, 0.65, and 0.75 respectively. Notice that the largest cluster percolates through the lattice from top to bottom in this example when p >

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59 | Page acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 2.3: Strategic habitat areas were defined by the shca_ff_v4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed . To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 2.4: Fragile coastal resources were defined by the coast_v4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 2.5: Biodiversity priorities were defined by the biodivrp_clp3 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development are as. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 3: Urban edge impacts were analyzed in two steps. The first step looked at the changes to the amount of edge conditions after deve lopment and the second step looked at how much of the edge habitat contained intact land. This process used the land use cover data to define developed lands and intact lands in the same manner as B 1. Edge habitats were classified at two scales the first being 100 meters and the second being 300 meters. B 3.1: All developed lands were buffered to determine the amount of edge conditions in the study area. B 3.2: The edge conditions were analyzed by combining the buffer zones and the intact land data set . The buffer zones were converted into raster data and reclassified as follows: 1=Edge and 0=Not Edge. The intact land raster was reclassified to the following values: 1=Intact Lands and 0=Not Intact. Thus a result of 1, 1 = Edge, Intact and a result of 1, 0 = Edge, Not Intact. This step was only utilized in the site level analysis. B 4: Linkage priorities were defined by the FEGN (grnwat_v4 from FNAI.org) and CLIP Landscape Priorities (lndscprp_clp3 from FNAI.org) data sets. B 4.1: The FEGN data was clip ped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determi ne the changes.

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60 | Page B 4.2: The CLIP Landscape Priorities data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 5: The process for identifying impacts to water management areas included four data sets that were each obtained from FNAI.org. B 5.1: Functional wetland areas were defined by the wetlands_v 4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculate d and removed from the existing acreage to determine the changes. B 5.2: Aquifer recharge areas were defined by therecharge_v4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impac ted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. B 5.3: Significant surface waters were defined by the surfwat r_v4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calcul ated and removed from the existing acreage to determine the changes. B 5.4: Natural floodplain functions were defined by the floodpl_v4 data set from FNAI.org. The raster data was clipped to the study area and then its acreage was assessed. To calculate the impacted lands another clip was performed using the proposed development areas. The acreage of the resulting data was then calculated and removed from the existing acreage to determine the changes. Urban Impact Methods Preparation: Urban impacts were analyzed in two ways. C 1 analyzed changes to urban patch sizes and C 2 analyzed changes to the proximity of urban areas. Both city limits (par_citylm_2011 from FGDL.org) and the existing land use cover (CLC_v3_Poly from FWC.com) were used to define urban areas. C 1: The patch analysis of urban lands was completed with the use of the region group tool. The statistics of the patch data was then recorded and compared. Due to rounding issues the minimum patch size would always result in a 0 so the only statis tics that were recorded were the

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61 | Page number of patches, the largest patch and the average patch size. Then the proposed development areas were added to the urban lands and the process was repeated. C 2: The euclidean distance function was used to determine th e distance from the city limits. The INT function was used on the output raster to convert the data from floating point to an integer format. The average distance was found from the attribute statistics. The proposed development areas were then added to th e existing urban lands and the process was repeated. Case Study Results Analysis In order to compare the impacts caused by the case studies, each set of data was placed into an excel spreadsheet so that the numbers could be easily compared to each othe r. In total, there are 41 points of analysis for each case study. The cases will be looked at in two ways; which developments had the highest amount of change and which had instances of no change. These will both be based on the percentage of change in eac h development so that the comparisons are more applicable with the Restoration development. It will be possible for multiple projects to have no impact on a given analysis but one project will have the most impacts. The amount of land being impacted will b reak any ties that occur when looking at the most impactful sites. The lands being analyzed will include only new development and new conservation lands. The Miami Corp and Plum Creek Development proposals each contain land that is already under conservat ion. These lands will be removed from the calculations so that the projects can be compared in a fair manner. In total, there were 42 impact analyses for the context area and 45 impact analyses conducted for the site area. For each case study. A pie char t and bar graph will be used to compare the performance of the case studies. Part II: Farmton Analysis Site Selection The primary reason that the Farmton development was selected for the development of alternate plans was due to the severe impact its c urrent configuration poses to the Florida Ecological Greenways Network (FEGN).While the other case studies also have the potential to cause severe impacts to the FEGN, the Farmton project is impacting an area that may be vital for the movement of species from south Florida such as the Florida black bear and the Florida panther. This project was also identified as the most impactful project by the case study analysis which helped to validate its selection for further analysis.

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62 | Page In order to develop suitable options for the Farmton property, the LUCIS method was utilized. The Land Use Conflict Identification Strategy (LUCIS) is a goal driven GIS model that produces a spatial representation of probable patterns of future land use divided into several categorie s which are listed below (Carr and Zwick 2007, 10). This land use analysis model is thoroughly outlined in "Smart Land Use Analysis" written by Peggy Carr and Paul Zwick. This model for land use analysis identifies a reas of conflict between three types of land use, Agriculture, Conservation, and Urban land uses. These categorie s were based on an earlier land use classification model by Eugene P. Odum who presented four types of lands uses: Productive, Protective, Compromise and Urban/Industrial (Carr and Zw ick 2007). The results of the LUCIS analysis formed the basis for the development of alternatives. For this project, ArcMap 10.1 was used to build and run the various models used to conduct the suitability analysis. There are five main steps to the LUCIS model and the results of these five steps are used to identify areas of potential conflict in a study area (Carr and Zwick). The Five Steps of LUCIS (Carr and Zwick 2007) 1) Goals and Objectives Define goals and objective that become the criteria for determining suitability. 2) Data Inventory Identify data resources potentially relevant to each goal and objective. 3) Suitability Analyze data to determine relative suitability for each goal. 4) Preference Combine the relative suitabilities of each goal t o determine preference for the three major land use categories. 5) Conflict Compare the three land use preferences to determine l ikely areas of future land use conflict. For the first step of the LUCIS method an outline of goals, objectives and sub object ives was written for each land use type. A model was built for each objective and sub objective and then another set of models were built to combine the objectives into goal s and then those goals were combined into land use suitability raster data sets. Fo r a detailed list of each goal and objective along with an image of th e data, see appendix C . For more details about the LUCIS method

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63 | Page F armton Suitability Goal Outline A: Identify Lan ds Suitable for agriculture. A 1: Identify lands suitable for livestock production. A 2: Identify lands suitable for crop production. A 3: Identify lands suitable for timber production. B: Identify lands suitable for conservation. B 1: Identify lands s uitable for biodiversity conservation. B 2: Identify lands suitable for protecting water quality. B 3: Identify lands suitable for protecting connectivity. B 4: Identify lands suitable for permanent conservation. C: Identify lands suitable for urban development. C 1: Identify lands suitable for residential use. C 2: Identify lands suitable for commercial use. C 3: Identify lands suitable for industrial use. The second step of the LUCIS method involved search ing for various types of GIS data. Fortunately, the state of Florida has an extensive library of GIS data and almost every county in the state provides data in an easily assessable manner. In order to conduct the suitability analysis data was needed that s howed existing land uses, existing conservation needs and assessments as well as an outline of the existing Farmton property. Much of the data used in this project was obtained from organizations such as the Florida Natural Areas Inventory (FNAI), the Flor ida Geographic Data Library (FGDL) and the St. Johns River Water Management District (SJRWMD). Since the case studies were in different locations across the state, much of the data that had already been gathered covered the entire state of Florida. In orde r to use this data it was first clipped to a ten mile buffer of the Farmton property. This buffer allowed for land uses outside of the property to have an impact on the suitability analysis so that the property was viewed in context and not in a vacuum. Yo u can find a complete listing of all data used along with its source an d date of release in appendix A . Suitability analysis was conducted by taking the existing GIS data and using models to analysis the data and reclassifying it based on the interested for the three land use types. These suitabilities are normally determined with stakeholder input or by consulting various experts. For the project, many of the suitabilities were defined based on the existing conditions of existing development. For example , in order to determine to a suitable proximity to roads for livestock production a function called euclidean distance was performed on a road data set. This creates a raster data set that illustrates all the distances from a road. Next, all existing lives tock production land uses would be extracted from a land cover data set. Then the zonal statistics function would be used to create a table that gives the average distance and the standard deviation that the existing livestock areas are found from roads. T his data is then used to reclassify the road distance into a suitability scale.

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64 | Page The suitability scale is a numerical range from 1 to 9. All data needs to be reclassified into a 1 to 9 scale in order to compare the various suitabilities. In this scale a 1 will represent a low suitability while a 9 represents a high suitability. "This range is large enough to accommodate the subtle differences needed to determine suitability between individual features and narrow enough to be managed by the experts and unde rstood by the general public" (Carr and Zwick 2007, 60). Throughout this project high suitability values will be represented with a green color, medium values will be represented with a yellow color, and low values will be represented with a red color. A fter values and suitability has been assigned to the various objectives and data sets the fourth step can begin. Preference is determined by analyzing all the objectives and goals. For this process it is again common to use stakeholder feedback to determin e the weights of the goals and objectives. The stakeholders would be asked to rate which goal they think would be more important using a preference grid. Using the urban goals as an example the stakeholders could find that residential development is three times as important as industrial development but only twice as important as commercial development. Then these ratings can be averaged the goals can be combined using a weighted sum function or a raster calculator expression. The end result is a raster dat a set that shows the suitability for development of a particular land use that can be compared to other land uses in order to determine which lands uses are more preferred in a study area. Suitability Criteria Determining what land uses will be suitable for any given piece of land can be a difficult process. There are many factors that can make one piece of land very suitable for one land use and totally unsuitable for another. Unfortunately it is rather uncommon for a specific piece of land to be only su itable for one use which is why one of the fundamental assumptions of the LUCIS method is that conflict is inevitable in the process of determining land use suitability (Carr and Zwick 2007). By assuming the conflict will be inevitable, the LUCIS method si mply aims to identify what lands are suitable for each land use and compare that suitability with other land uses. In this way the resulting conflict grid is not making a determination about what should be done with a particular property. The conflict grid is simply showing what may or may not be a suitable land use for the site. In order to determine the suitability for various land uses on the Farmton site, many different variables were considered. These variables and their importance will be described in this section of the project and the corresponding data la yers can be found in appendix A . In an ideal world these variables and corresponding levels of importance would be identified by experts and various stakeholders; however, for this project the var iable were selected based on discussions and input from University of Florida Faculty. Some variables were also added or eliminated based on available GIS data and time constraints.

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65 | Page Suitability for Agriculture Land Use The agricultural land use suitab ility was broken down into three categories: livestock production, crop production, and timber production. Each category looked at both the physical suitability of the land for agricultural production as well as the economic suitability of the land for pro duction. Each category had the physical suitability weighted at 70% and the economic suitability weighted at 30%. The productivity of the land was valued as more important than the location and value of the land for this project. Suitability for Production Livestock production was weighted at 40% compared to the other two categories and did not focus on different levels of intensity. This land use received a higher weight than crop production due to its lower impact on the environment. Crop prod uction was weighted at 20%. This is because crop production can have more negative impacts on the landscape and is also due to the fact that there is no existing crop production on the site. In general crop production had a low level of representation arou nd the Farmton study area. Timber production was weighted at 40%. Timber production is very well represented on the Farmton site. Timber production lands also tend to be compatible with conservation needs which is why this land use was weighted twice as high as crop production. Physical Suitability The physical suitability for agriculture production was weighted at 70%. The ability for the land to be productive was based on three suitability data sets: soils, existing production, and existing land use. Soil Suitability Typically, well drained soils are more suitable for agriculture land uses when compared to poorly drained soils. However, when the soils become excessively well drained, they become less suitable. Some poorly drained soils can also be suitable for livestock and timber production so each land use received a slightly different rating based on the drainage class for the soils. The need for irrigation was also important for each production type. The irrigation class, drainage class and farm land class were all weighted evenly to determine the soil suitability. Soil suitability was weighted at 50%.

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66 | Page Existing Production Areas that are already being used for agriculture production are inherently more suitable for continued production. Existin g production was weighted at 10% because it will be recounted when looking at the existing land use suitability. Existing Land Use There are several land uses that are incompatible with agriculture production. Areas with urban land uses are unlikely to b e suitable for agriculture production so urban land uses were given a low suitability value. Open lands and natural lands were given a moderate suitability value and existing agriculture use was given the highest suitability value. If the lands are already being used for agriculture, less effort is required to continue using the lands for agriculture purposes. Economic Suitability The economic suitability was based on three categories which included land value, proximity to major roads, and proximity to m arkets. This suitability data set was weighted at 30% compared to the physical suitability of the study area. Suitable Land Value Agriculture land use often requires a large amount of land and the value of that land can be a significant variable in suitability. In general lower land values are more suitable for any land use. In order to obtain an unbiased rating for land values a zonal statistics table was created based off the land values of the existing agriculture. Zonal statistics objectively det ermines suitable land values based on the existing conditions of the study area (Carr and Zwick 2007).Existing land values were obtained from parcel data and converted to a price per acre based on the just value of the parcels. This suitability surface was weighted at 20%. Proximity to Major Roads Road proximity received a fairly high rating of 40% due to the need for roads to transport any agricultural goods. The zonal statistics as a table function was again utilized to help provide a more objective rati ng of the suitability of road proximity. Proximity to Markets Market proximity received a weight of 40%. Each agriculture use has a different market associated with it. While all agricultural products may eventually end up in a home they are not typicall y sold directly to the end consumer. Livestock and timber products must first be processed in order to be consumed. For this reason livestock markets were defined as meat packing plants and timber markets were defined as sawmills and lumber yards. Crops re quire less processing and can be sold to end consumers so their markets were defined as city limits. The zonal statistics as a table function was again utilized to help provide a more objective rating of the suitability of market proximity.

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67 | Page Suitability f or Conservation Land Use Several factors influence how suitable land may be for conservation purposes and many of these factors have been identified and prioritized in the Florida Natural Areas Inventory. The process for identifying suitability for conserv ation simply involved a reclassification of data that has already been created for FNAI. The majority of the data from FNAI has already been prioritized in some form. For example, functional wetlands have been given various priority levels based on their l evel of importance. Significant Lands for Biodiversity As discussed in chapter 2, biodiversity is very important for conservation and the rating of this goal helps to reflect that. Whenever a suitability value of nine is identified it will be kept as a n ine when combined with the other goals. All other values obtained from this goal were given a weight of 25%. This goal is comprised of four objectives which each focus on a different aspect of biodiversity and each receives a different weight. Strategic Habitats Strategic habitats were defined by the data set SHCA_FF_v4. The strategic habitats were categorized into five priority levels. These were reclassified based on which levels were present in the study area so that they were ranked based on their pri ority levels. This objective received a weight of 30%. Potential Habitat Richness Areas of potential habitat richness were defined by the data set phrich_clip3. The potential habitat richness areas were categorized into the number of species present in a given area. These were reclassified based on the various species levels in the study area so that they were ranked based on the potential number of species. This objective received a weight of 10%. Rare Species Areas with rare species were defined by th e data set fnaihab_v4. The rare species habitats were categorized into six priority levels. These were reclassified based on which levels were present in the study area so that they were ranked based on their priority levels. This objective received a weig ht of 30%. Priority Natural Communities Priority natural communities were defined by the data set natcom_clip3. The natural communities were categorized into four priority levels. These were reclassified based on which levels were present in the study ar ea so that they were ranked based on their priority levels. The community priority data was augmented with an inclusion of land use data. The priority areas all received a weight of 9 6 while other land uses were given lower weights and these two data sets were combined with a raster calculator function. This objective received a weight of 30%.

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68 | Page Significant Lands for Protecting Water Quality The protection of water quality is very important in Florida. The Farmton site also contains many wetlands and provides significant ecosystem services in the form of water treatment and conservation. For these reasons this goal was given a conditional statement that is identical to the statement for the biodiversity goal. Whenever a suitability value of nine is ide ntified it will be kept as a nine when combined with the other goals. To add more weight to the significance of water quality, each of the two objects were combined using a maximum value approach. If a cell contains two values then the higher of the two va lues will remain. All other values obtained from this goal were given a weight of 25%. Surface Waters Lands with significant surface waters were defined by three data sets which included function wetlands (wetlands_v4), significant surface waters (surfwa tr_v4), and natural floodplain functions (floodpl_v4). Each of these data layers were reclassified based on their priority level and them combined with a weighted sum. Each was given an approximate weight of 33%. Ground Water Significant areas for ground water protection were defined by the data set recharge_v4. The aquifer recharge data was categorized into six priority levels. These were reclassified based on which levels were present in the study area so that they were ranked based on their priority le vels. This objective was not weighted. Due to the importance of water quality protect this data set was combined with the surface waters using a maximum value approach. Significant Lands for Protecting Connectivity Connectivity improves the ability of a species to persist and allows for species migration. Two objectives allowed for the identification of lands that would be significant for the protection of landscape connectivity. Connectivity has been identified as a vital component in the protection of v arious species in chapter 2 and has been weighted to reflect its importance. The connectivity goal was weighted at 40% which is higher than any of the other conservation goals. Wildlife Corridors The Florida Ecological Greenway Network has identified sev eral areas critical to maintaining connectivity in the state of Florida. These corridor priorities were identified by the grnway_v4 data set and was reclassified based on the priority levels. This objective was given a weight of 75%. Landscape Integrity Areas with landscape integrity were defined by the data set lsinteg_clip3. Lands with high integrity were categorized into nine priority levels. These were reclassified based on which levels were present in the study area so that they were ranked based on their priority levels. This objective received a weight of 25%.

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69 | Page Significant Lands for Permanent Conservation At 10%, this is the lowest weighted conservation goal. It is comprised of two objectives which evaluate the proximity of land to existing conserv ation lands as well as the location of proposed conservation projects. Proximity to Existing Conservation The process for evaluating suitable proximity to existing conservation lands was somewhat complex and introduced a small amount of subjectivity to t he suitability surface. However, the proximity to existing protected lands is still very important which is why this objective is weighted at 75%. This evaluation process looked at both the distance from existing conservation land as well as the quality of the land. The distances were grouped into 4 categories and given a corresponding value that diminished as the distance increased. Then the existing land use cover was reclassified based on the intensity of the land use. Natural lands were values higher th an developed lands. These two data sets were then merged with a combine function. After performing the combine the various combinations were reclassified to their final values. The basic idea is that a land use that was valued as a nine ye t was more than 2 would still have some importance for permanent conservation so it would receive a slightly higher value than 1. A list of the combinations as well as their va lues can be found in appendix C . Proposed Conservation Lands The Florida Forever Board of Trust ees has identified several areas for future conservation based on the presence of "outstanding natural resources, opportunity for natural resource based recreation, or historical and archaeological resources" (FNAI.o rg ). These sites were given a value of n ine and all other land was given a value of 1. This objective was weighted at 25%. Suitability for Urban Land Use There are various types of urban land uses. In the LUCIS method, urban land uses are broken down into five specific uses which include residential, office and commercial, retail, and industrial (Carr and Zwick 2007). The land use data used in this project does not differential between commercial, office, and re tail so they were combined into one category. Due to this limitation only three urban land uses were identified which include residential, commercial, and industrial. Similar to the agricultural suitability, these land uses were each rated based on their p hysical and economic suitabilities. The physical suitability for urban land uses was weighted at 60% while the economic suitability was weighted at 40%. Residential development is often dependent on land value as well as the proximity to various services , and employment opportunities. The suitability surface for residential development will look at both physical needs for construction as well as common needs for a residential development to economically feasible. This land use is weighted at 50% which is just slightly higher than both commercial and industrial development.

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70 | Page Commercial development requires many of the same physical needs as residential development. However, their needs begin to differ when looking at economic suitability. For example, the presence of schools has little impact on commercial land uses while the proximity to roads will be more important to retail services. This resulted in some small changes to the economic suitability needs for commercial development and this land use was als o weighted slightly less than residential land use. Commercial land use received a weighting of 25%. Industrial development received a few minor adjustments for its economic suitability as well which included the addition of rail proximity for shipping p urposes. Otherwise this suitability surface was very similar to the commercial objective although its sub objective did receive different weights. Industrial land use was weighted at 25%. Physical Suitability All three urban land use types used the same rating system for their physical suitability. The physical suitability was based on two suitability surfaces that were comprised of a soil suitability analysis and an identification of hazardous flood zones. These two suitability surfaces were weighted at 50% each. Soil Suitability Poorly drained soils can have a higher risk of moisture and are typically less suitable for development (Obrien 2010). Soils with a higher drainage rating were given a higher suitability value and soils that were not limited fo r development were also given a higher suitability value. Both the soil's drainage class and ENGLRSDCD rating were weighted at 50%. Flood Zones Flooding can cause significant damage to structures and construction is normally not allow or severely limited in 100 year floodplains. Thus, the higher the flood risk the lower the suitability for potential development. Lands inside the 100 year flood pla in were given the lowest suitability value and lands inside the 500 year floodplain were given a moderate suitability value. Lands outside the floodplain received the highest suitability value. Economic Suitability The economic suitability for each land use type was weighted at 40%. Each land use looked at five to six variables to determine economic suitability and each were weighted in slightly different ways. Suitable Land Value As mentioned in the agriculture suitability section, lower land values ar e more suitable for any land use. Zonal statistics was again used to objectively determine suitable ranges for land value for each urban land use. Land values were weighted at 10% for both residential and industrial land uses. Its weight was increased to 2 0% for commercial land use.

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71 | Page Proximity to Roads Roads are just one of many infrastructures that are needed to support urban development (Carr and Zwick 2007). For this reason, roads have been given a high weight for each land use. For residential land use road proximity received a weight of 20%. Commercial land uses also rely on roads for customers and the transportation of goods so roads were given a weight of 25%. Industrial land uses need roads in order to ship their products and for their employees so their proximity to roads received the highest weight at 30%. The zonal statistics as a table function was again utilized to help provide a mor e objective rating of the suitability of road proximity. Proximity to Rail Proximity to railroads was only used in the industrial land use goal. This is due to a lack of rail networks in the study area. While railroads can be a nuisance for residential d evelopment, the only railroads were well outside of the study area to negatively impact residential development. Zonal statistics was utilized to provide the ranges for suitability for industrial use and the proximity was weighted at 20%. Proximity to Sc hools and Hospitals Schools and hospitals can be very important for residential development. The suitability levels for the proximity to these services were determined with the use of the zonal statistics function. The proximity to schools and hospitals we re run independently of each other and then combined with a weighted sum. Schools were given a higher weight at 60% and hospitals were given a weight of 40%. Together this sub objective was given a weight of 20%. Proximity to Recreation Areas Parks and r ecreation services, like schools and hospitals, are mostly geared toward residential land uses so they were only included in the residential suitability analysis. All park and trail data was converted to points and then the zonal statistics function was us ed to reclassify suitable distances to the recreation areas. This sub objective was given a weight of 15%. Proximity to Existing Residential Land Use Proximity to residential land use was included in both commercial and industrial suitability. Commercial land use needs residential development as a source for customers and employees. Industrial land uses also need residential development for employees however industrial land uses are also somewhat incompatible with residential land uses so distances within 1/2 mile of residential land uses were given a lower suitability and all other distances was rated based on the results of the zonal statistics function. Both sub objective weighted residential proximity at 10%. Proximity to Existing Commercial Land Use Commercial land0uses can be seen as a service for residential development and often commercial development occurs around existing commercial development. The analysis of both commercial suitability and residential suitability weighted commercial proximity at 20%. As

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72 | Page typical in this process, the zonal statistics function was utilized to obtain an objective way to reclassify the distance for each objective. Proximity to Existing Industrial Land Use Proximity to industrial areas was only used in the analysi s of industrial suitability. This sub0objective received a weight of 10% and was reclassified based on the results of a zonal statistics function. Proximity to Existing Water Services Water services are needed for any type of development and local water sources are typically preferred to wells so each suitability study included the presence of water services in its analysis. Each land use received a different weighting based on the need of water services. Since residential developments require less water they receive the lowest weight of 15%. Commercial proximity to water services received a weight of 25% and industrial received a weight of 20%. The distances from water sources were again ranked with the use of a zonal statistics function. Conflict Analysis The creation of a conflict grid is a very simple process. After all three land use suitability surfaces have been created each one has areas removed that will not change in the future. These areas include existing conservation lands, developed l ands and open water. Next, each suitability surface is reclassified in order to change them from a scale of 1 9 to a scale of 1 3. Now each suitability surface will contain three values. A value equal to one represents a low preference while a value of thr ee represents a high preference. Next the agriculture suitability surface is multiplied by 100, the conservation suitability surface is multiplied by 10 and the urban suitability surface remains unchanged. This combines each value so they can be easily com pared and identified. The results will all have three digits and each will represent a preference value for a particular land use. Number in the 100's column represent agriculture while numbers in the 10's column represent conservation and finally numbers in the 1's column represent urban preference. Thus, a value of 111 indicates low preference for all three land uses and a high level of conflict. A value of 131 represents a high preference for conservation and a low level of conflict. Finally a value of 2 12 represents a moderate preference for agriculture and urban development as well as a moderate level of conflict. Alternate Plans The conflict grid created from the land use suitability analysis was used to help determine w h ere development should be l ocated on the Farmton Property. A color scheme was selected to help illustrate the location of the preferred land use s . The areas that had a high or moderat e preference for agriculture were given a blue color. The areas which had a high or moderate prefere nce for conservation received a green color while the areas that had a high or mo derate

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73 | Page preference for urban received a red color. All areas of conflict (equally preferred for at least two of the land uses) were given a grey color. After the conflict gri d was finalized, some base data was added to the map to help further clarify land use decisions. Roads were added to the map so that development could be placed in more accessible areas. Existing conservation lands and mitigation banks were also added so t hat development could be placed in areas that were not already protected while also being able to provide buffer areas around conservation lands. Seeing the existing conservation lands also helped in determining where corridors might be useful in connectin g fragmented lands with wildlife corridors. Four alternative plans were made for the Farmton project and each plan was analyzed with the same models that were developed for the case studies. By using the same analysis method s these plans are compared wi th the original Farmton plan to see if the alternati ves reduce or increase impacts . Each plan was designed using a basic set of goal and objectives. The only variable to change between each plan is the target densities and the foot print of the project. G oals for the Alternative Farmton Plan 1) Keep development away from conservation lands and mitigation banks. 2) Refrain from developing land south of the Maytown Road. 3) Increase important corridors to a width of at least 1 mile. 4) Maintain multiple corr idors among nodes . 5) Create a more compact urban structure with less fragmentation. Each alternative plan has a different level of development and density. The first alternate maintain s the proposed densities and occupies the same area as the approved pl an albe it in a different configuration. The second alternate double s densities of the proposed plan by reducing the amount of developed la nd by 50%. The third alternate use s a hybrid approach and reduce s the village areas by 50% while only reducing the tow n center, mixed us e, and work place districts by 2 5%. The final alternate plan fo cuses on being the most sustainable development for the site. It restrict s development to one location in each county and proposes a new number of dwelling units to reflect an acceptable amount of density. This plan has the most differences from the current proposal for the site.

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74 | Page Analysis of the Alternate Plans In a manner similar to the case studies, the alternate plans for the Farmton site were analyzed and placed into a spreadsheet. Once placed alongside one another, it was possible to see which plan had the greatest reduction in impacts caused by the developm ent. Each plan was compared to see which were the most impactful and which had the most occurrences of no change to the study area. Each of these analyses looked at the entire Farmton property including the mitigation banks. Part IV : Limitations This p roject contains a few limitations. Most of the limitations involved a lack of data or time necessary to complete a given task. Data availability was the greatest limitation in this project and even though Florida has a robust GIS data library, it was not a lways possible to find current or accurate data. The accuracy of the data is this project is fairly high but there is always a loss in accuracy in the use of raster data. Data availability had an impact on both the case study analysi s and the suitability analysis. The biggest limitation was due to the availability of road data. The Farmton plan has proposed a series of road improvements that will likely fragment large portions of the development. However , there is no GIS data to reflect the design of the r oads. It was possible to obtain a low quality map of the proposed roads; however, due to time constraints it was not feasible to create data based off of those maps. The lack of road data associated with the Plum Creek and West Bay projects led to the remo val of road density calculations in the case study analysis. Time and hardware availability was another limitation while performing GIS analysis. The computer used to run the GIS program handled most of the analysis with ease; however, some of the focal statistics analyses were unable to be c ompleted in a timely fashion at the standard 15 meter cell size. The 10,00 0 area focal statistics analysis used in B 1required 10 12 hours to complete. Therefore, these steps were performed with the cell size increa sed to 30 meters in order to reduce the processing time. While this project aimed to look at a variety of factors that influence development , many economic factors were not included in the analyses. One example of this can be seen in the analysis of urba n suitability. The data being used to identify existing land use did not differentiate between commercial, offices, retail, or services. Due to this limitation, office, retail , and other commercials uses were grouped into one category. Demand for each land use type is also not being considered in the project. Finally, it is important to note that the suitability analysis of the Farmton site only involves the site itself. The analysis does NOT reflect the suitability for development on a regional scale. It i s very possible that the entire site may be very suitable or very unsuitable when looking at a larger scale.

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75 | Page Chapter 4: Case Study Results The analysis for this project has produced a significant amount of data that can be interpreted in several ways. This chapter will first introduce the reader to the case studies and the current proposals that are being analyzed. Next, the results of the analysis will be presented. The data will be presented in the order it was discussed in chapter 3. For a more detai led look at specific numbers and data sets for both the cases studies, please see appendix B. Part I: Case Stud y Introduction In order to evaluate the effectiveness of sector planning in Florida, the following four case studies were analyzed to identify impacts they may cause to the existing landscape. This section will provide some information about where these case studies are located, some of the controversies associated with the projects, as well as a description of the proposed developments. The cases that were selected for analysis are the Miami Corporation's Farmton Plan, St. Joe's West Bay Sector Plan, Plum Creek's Envisio n Alachua and GS Florida's Restoration. Both the West Bay Restoration development used the DRI review process and the Farmton Plan underwent the comprehensive plan amend ment process. The impact analysis only looks at the land in these projects that will be changed. Any lands that are were already under conservation were not included in the analysis. The three planning processes being used by the case studies in this pro ject are very similar to each other. Both the Sector Planning Program and the DRI review process result in an planning and environmental impacts. These processes ma y seem like separate entities but they all operate in similar ways in the State of Florida. In general, the DRI process is considered to be the most restrictive of the three planning processes and the Sector Planning Program is the most recent planning pro gram in Florida.

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76 | Page Farmton Plan The Farmton planned development is located along the east coast of central Florida. The site stretches north to Edgewater and extends south toward Scottsmoor. This land is largely undeveloped and has many wetlands, timber farms and some very low density residential development. Matt Reed, a journalist with Florida Today gave a description of the property after visiting it in early 2013: "On a tour of the sprawling Farmton property last week, I watched a wading bird weave t hrough cypress trees and knees that line every yard of the anci ent, meandering Deep Creek. Ring s appeared in the tannin hued water when an alligator ducked below the surface. The only sound was the crunch of oak leaves as I stepped closed for a better view ." (Reed 2013). The Miami Corporation owns a bout 59,000 acres in Brevard and Volusia County and these lands are managed for various resources that include timber, oil, gas, hunting and grazing (Farmton Plan n.d.) . 47,500 acres are located in southern Volu sia County while 11,500 acres are located in northern Brevard County. The process to adopt the Farmton plan took several years. The process began in 2006 and culminated with final approvals being granted in March, 2013 (Farmton Plan n.d.). The Farmton pr oject has been very controversial due to the potential impacts its development would have on the exi s ting habitats in the region. However, in spite of many criticisms the plan has also received many awards. These awards include the Agriculture Environmenta l Leadership Award, the State Agriculture Award (2013), the Florida Planning & Zoning Association's Innovation Award (2011) and others. The Farmton plan clearly has some supporters but it also has many critics such as Carl Persis who has stated that the Fa rmton site is not the place to build so many homes and that more work needs to be done to revitalize existing urban areas instead (Hatfield 2010). Some have been concerned about how development on the property may impact wetlands and mitigation banks (Andr ews 2011). Currently, the Miami Corp. is being sued over an amendment made to the permit for the Farmton Mitigation Bank. This amendment allowed the Miami Corp. to remove approximately 1,100 acres of land from the designated mitigation bank. These acres were not yet act ive and the wording in Florida S tate law does allow for the change (Pulver 2014). The quest ion focuses on the S tate s authority when the mitigation banks also fall under federal permits. The Sierra Club, who has filled the lawsuit, also bel ieves the Farmton Plan should not have received development credits for lands that are in mitigation banks since the company already makes money by selling mitigation credits (Pulver 2014). The vast majority of the Farmton property is located on lands th at are part of the FEGN. 55,626 acres of l and in the Farmton property are classified as a P EGN and 2,088 acres are classified as a P riority 2. This development contains the most significant lands for connectivity in th is entire study.

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77 | Page Development Numbers The Farmton plan comprehensive plan. The approved development allows for several land uses each with its own target density. The densities throughout t he site range from a low of 3 units per acre to a high of 24 units per acre. The plan will contain a gateway district of mixed use development , a work place district focus ed on employment areas and housing, a town center that will contain the highest densi ties, and a network of villages with village centers which will be for residential . Farmton Plan Developed Dwelling Units Non Residential Size in Acres Volusia County Conservation N/A N/A 31,876 Acres Developed 23,100 4,700,000 15,081 Acres Brevard County Conservation N/A N/A 8,286 Acres Developed 2,306 1,200,000 3,376 Acres Grand Totals 25,406 5,900,000 58,619 Acres

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78 | Page Farmton Land Use Map (Approved)

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79 | Page Plum Creek Plum Creek's Envision Alachua plan is located in eastern Alachua County near Newnans Lake. While Plum Creek owns property throughout the county, their proposed development is all located to the east of the lake and north west of Hawthorne. At approximately 65,000 acres, this is the second largest project in this study and at 15,000 acres, it has the third largest amount of proposed development. Plum Creek has several fragments of timber and conservation land scattered around Alachua County . This development has been very controversial in Gainesville as well as the greater Alachua County area. Many people have posted signs in their yard in the same manner they would post political candidate signs. Plum Creek has created the Envision Alachua campaign to promote their view of the project which they claim will help create jobs and increase de velopment in eastern Alachua County. They believe their plan will help revitalize Hawthorne and East Gainesville (Plum Creek n.d.). The promise of jobs and economic growth is often cited by those who support the development and some are willing to see chan ges to the county's comprehensive plan in order to attract more jobs to the region (Watkins 2014). Opponents worry about the environmental impacts the development may cause, including to water quality . Others suggest the plan may not provide enough prote ction for the other natural resources in the area (Watkins 2014). Some believe this site is not economically viable due to a lac k of infrastructure in eastern Alachua County (Watkins 2014). Development Numbers Plum Creek, which is using the sector planni ng process, is proposing the widest range of building densities for their development. The lowest proposed densities will be 1 unit per 5 acres and the highest density will be around 40 50 units per acre (Plum Creek 2014). The proposal also includes the ad dition of 15.5 million square feet of commercial and industrial development. It is also important to note that approximately half of the lands they propose to keep in conservation already are protected by conservation easements. For this reason, existing c onservation lands have been removed from the case study analysis of the Plum Creek project. Plum Creek Developed Dwelling Units Non Residential Size in Acres Conservation N/A N/A 46,085 Acres Developed 10,500 15,500,000 14,048 Acres Grand Totals 10,500 15,500,000 60,134 Acres

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80 | Page Plum Creek Land Use Map (Proposed)

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81 | Page West Bay At approximately 74,000 acres, the West Bay Sector Plan is the second largest development analyzed in this project and it is in the process of becoming even larger. It is located around West Bay in the Florida panhandle. The nearest significant developme nts are Panama City and Panama City Beach to the east and south respectively . This plan was the result of collaborations between St. Joe, Bay County and the Panama Airport Authority. St.Joe is a corporate real estate developer that own s a large amount of l and in the Florida panhandle mostly used for timber production (St.Joe n.d.). The current West Bay plan was approved in 2003 as a pilot in Florida's sector planning program. It proposes the largest amount of development of any of the cases in this study while protecting the smallest percentage of land, yet the vision of Bay County Comprehensive Plan claims to focus on protecting the environment with this development plan. "The West Bat Area Sector Plan will protect ecological systems and provide connectiv ity to West Bay. These ecological systems will link wildlife habitat and environmental resources through interconnected corridors." (Bay County 2009). Much of the controversy surrounding this project centers on environmental concerns. Some residents in Bay County have expressed concern about water quality issues (Hasselbrink 2004). Others have worried that if St. Joe focuses its development to attract retirees that the project may be similar to The Villages (Garman 2014) , widely recognized as a sprawling fo rm of urban development . This project will focus on potential impacts that may be caused by the already approved West Bay sector plan , but it is important to mention some new developments related to the site. On April 11, 2014, St. Joe announced an expan sion to the West Bay project and is now referring to the site as the Bay Walton Sector Plan. The Bay Walton proposal will add about 45,000 acres to the West Bay plan and will spill over into Walton County. If approved the project would extend to Choctawhat chee Bay wh ich is about 17 miles west of West Bay. This new plan represents a significant change; however, it will not be assessed it this study due to a lack of time and information. For more information about this plan see the webpage: www.bay waltonsect orplan.com Development Numbers The West Bay sector plan was a pilot in The Sector Planning Program and contains several different land uses which include agriculture, an airport, business centers, a low impact residential area, town centers, villages, and conservation lands. The highest proposed density is currently listed at 20 units per acre and the lowest density of 1 unit per 3 acres will occur in the Low Impact areas. The plan also calls for more than 37 million square feet of industrial and commercia l development (Bay County 2009).

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82 | Page West Bay Developed Dwelling Units Non Residential Size in Acres Conservation N/A N/A 39,268 Acres Developed 27,631 37,866,708 34,718 Acres Grand Totals 27,631 37,866,708 73,986 Acres Bay Walton Land Use Map (Proposed)

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83 | Page West Bay Land Use Map (Approved)

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84 | Page Restoration Restoration is a planned community loca ted in Edgewater, Florida that lies directly north of the Farmton proper ty. The planned development sits just west of I 95 and is surrounded by valuable wetland and uplands and is currently undeveloped. Resto ration is a unique develop ment in this study both due to its size and the planning process employed for its approval . At the time of Restorations proposal, it did meet the criteria for the sector planning pilot program; however, the program was not mandatory so the developer either chose not to use the program or was unable to enter it for some other reason. While this project is significantly smaller than the other case studies it was approved through the DRI process . Two plans were created for Restoration that are drastically di fferent from one another. The first plan which was proposed in 2006 is a sprawling development that, at first glance, appears to be a typical Florida development that could have many potential impacts on the landscape. The second plan, completed in 2009 , p roposed a more compact community that has the potential to reduce impacts to the surrounding landscape. The lead designer for this project was Canin Associates and they worked with Program for Resource Efficient Communities to redevelop the alternativ e plan . The first design fo r the Restoration community was rejected through the DRI process due to its sprawling nature. Some residents from Edgewater believed it was going to be a large and empty development ( Lelis 2011). Some have applauded the compact re design with its focus on preserving the wetlands and ecosystems west of the development (Lelis 2011). The Program for Resource Efficient Communities has also conducted various studies on the Restoration project and has outline d many of the improvements and efficiencies made in the 2009 plan. Development Numbers The Restoration plan , approved under the DRI review process, was designed as a mixed use transit oriented development. The 2006 plan contained densities around 2.6 uni ts per acres while the 2009 plan increased those densities to 6 units per acre (Jones n.d.). The final plan calls for 8,500 units which will include single family homes, apartments, townhouses, duplexes and so forth. They are proposing to develop 1.3 mill i on square feet of retail and service land uses as well as 1.8 million square feet for industrial and office use (Canin Associates 2009). Restoration Developed Dwelling Units Non Residential Size in Acres 2006 Plan Conservation N/A N/A 2,810 Acres Developed 8,500 3,215,163 2,375 Acres 2009 Plan Conservation N/A N/A 3,531 Acres Developed 8,500 3,215,163 1,655 Acres Grand Totals 8,500 3,215,163 5,186 Acres

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85 | Page Restoration (2006) Land Use Map (Not Approved)

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86 | Page Restoration (2009) Land Use Map (Approved)

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87 | Page Farmton Analysis Area Map

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88 | Page Plum Creek Analysis Area Map

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89 | Page West Bay Analysis Area Map

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90 | Page Restoration Analysis Area Map

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91 | Page Part II : Case Stud y Results The following section will present the results of the case study analysis. The results presented here will be a summary of the data collected in this project. All of the data for both the case stud ies can be found in appendix B. The cases were studied at two scales; a context scale and a site scale. The context area for each case study extends 10 miles from the project property boundaries. This allows the analysi s to show how the development may influence and be influenced by the surrounding lands. The site level analysis will only look at the property involved with each proposed development minus any land that is currently under conservation . For each data set, a rea will be measure in acres and distance will be measure in meters. The following process will also be applied to the alternative plans for the Farmton pro ject. As a general rule, the impacts identified in the context study were concentrated when reduci ng the study area to the projects property boundaries. As a result, the impacts appear to be worse at smaller scales. Surprisingly, two sites really stand out in the impact analysis and these two sites are the Farmton plan and the West Bay sector plan. The se two projects were consistently the most impactful development projects. When looking at the developments at a regional scale the West Bay Sector Plan was found to cause the most impacts; however, the Farmton Plan caused the most impacts when only looking at the development area. The 2006 Restoration plan was also found to be v ery impactful at the site scale. The Restoration projects both stood out when looking at the analyses that did not show any impact. Both projects had the highest occurrences of no impact at all scales of analysis. Figure 4 1: These pie charts show how often each case study was found to cause the most impacts. The change in scale drastically changed how impactful a development was.

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92 | Page Figure 4 2: These bar graphs show how often each case study was found to contain no changes or impacts to the existing landscape. The context analysis looked at 42 points of data while the development analysis looked at 45 points of data. Each project could receive a maximum of 42 for the context area or 45 for the development area. West Bay was found to cause impacts in almost every analysis while the Restoration proposals contained no changes. Impacts to Agriculture Land Uses A 1 Impacts to Agriculture Patch Size The first set of analyses looked at the size of agriculture patches in e ach study region. With the exception of Restoration 2009, each case study has had an impact to the existing agriculture patches. At both the regional and site scale, the Restoration 2006 case performed the worst. The least impactful development was Restora tion 2009. The 2009 design of the Restoration project showed significant improvement when compared to the 2006 proposal. A 2: Impacts to the Quantity of Agriculture Lands The impacts were pretty varied between each development and the majority of the agr iculture impacts occurred on timber production lands. On a percentage basis, the most impactful site was the Restoration 2006 plan. However, the West Bay plan impacted the most land. Impacts to Conservation Land Uses B 1 A: Impacts on Conservation Fragme ntation This step looked at the percentages of land in each study area that is developed or undeveloped. Then following the percolation theory as outlined in chapter 3, an y result above 59% would indicate that a path would likely exist to allow movement th rough the development. Each site measured above 80% in the pre developed state and only the 2009 Restoration proposal stayed above 59% in the post developed state . Both the Farmton plan and West Bay sector plan only came above the percolation threshold whe n fragmentation was analyzed at the scale of 10,000 meters. When looking at the context area , all case studies remained above the 59% threshold.

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93 | Page B 1 B: Imp acts to Conservation Patch Size Conservation patch sizes were grouped into six categories ranging fro m 75 acres to above 10,000 acres. This results do not include changes to the size of individual patches and only focuses on how many patches of a particular size exist in the study area. Most of the changes occurred in patches that were smaller than 75 acres. The greatest amount of change to patch sizes again occurred on the West Bay site and the Farmton site. B 2: Impacts to Existing Habitat Five habitats were analyzed for the step and one of them appears to have been unnecessary. While coastal resources did exist in the Farmton, Restoration and West B ay study areas, the West Bay Sector Plan was the only site to have any impact. Overall each site had some impacts on the existing habitats but they appeared to be minimal. The West Bay sector plan caused the most impacts when including the lands around the property but the Farmton site had the most impacts when looking only at the devilment area. B 3: Impacts to Edge Habitat The analysis of the edge habitat was actually a little surprising. The data rarely showed an increase in edge habitat unless the urban area was also included in the calculation. An explanation for these results will be given in the next chapter. Extra data points were added to this imp act analysis due to the issues that were experienced when looking at only the area of the edge habi tat. Interestingly, the data shows that both of the Restoration projects caused the greatest increases in edge conditions. This is one instance where there are significant differences between the context area analysis and the developed area analysis. The development area analysis looked at both the acreage of the edge habitat as well as its condition. The land located in the edge habitat was either intact or not intact. This helps to show just how effective this edge area can function as a buffer zone. At this scale the Farmton plan showed the greatest impacts when compared to the other developments. B 4: Impacts to Wildlife Corridors The impacts to proposed FEGN lands were fairly minimal when only looking at the context area. In fact, the impacts were le ss than 10%. However, these numbers increase d significantly when isola ted to just an individual site. The 2009 Restoration plan performed the best and only impacts 24% of lands vital for connectivity while all other developments impacted between 45% 52% o f the lands. Farmton caused the most impacts and this is even more significant because most of its impacts occurred on priority 1 lands.

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94 | Page B 5: Impacts to Water Resources When looking at the context area, West Bay was the most impactful site in every categ ory. The West Bay development had twice the impacts as the next closest case study. This was completely changed when only looking at the development areas as the Farmton development was found to cause the most impacts in each category. However, at this sma ller scale each development was found to cause significant impacts to water resources. Impact to Urban Land Uses C 1: Impacts to Urban Patch Size When including the context area most of the development had very little impact with the exception of the Wes t Bay sector plan. At the site level, each case caused a significant level of impacts. The sector plans each caused the most impacts in one category. The 2009 Restoration plan also caused a significant amount of change to the average patch size. C 2: Impa cts to Urban Proximity Both of the Restoration projects were able to decrease the average distance to nearby cities. This result may be comprised though due to the developments location. This data set was unable to return any results for Rest oration when i solating the site because the site is located in the city of Edgewater . The Farmton plan and Plum Creek Sector plan cause the most impacts in this analysis.

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95 | Page Chapter 5: Farmton Analysis Results Part I : Farmton Suitability Results The suitability for the Farmton analysis has helped with the creation of a conflict grid. This grid was intended to help identify the preferences for various lands uses on the Farmton property. After the conflict grid was created, four alternate plans were created in an attempt to reduce the impacts of development on the region. Those alternatives were then analyzed in the same manner as the case studies and information about their results can be found in the previous section of this chapter. This section w ill report on the results of the various suitability analyses as well as the proposed alternate plans. Additional i mages of the suitability and conflict data can be found in appendix C. Agriculture Suitability The suitability results for agriculture production were very similar for each type of agriculture. Overall, the most suitable lands for agriculture were located in the southern half of the property. There are two large bands in the north half of the property that are typically found to be very unsuitable for agricultural land uses and these areas contain several wetlands and are currently being used as mitigat ion banks. When lo oking at the physical suitability for productive lands, the only data set that showed much variance is the existing production lands. Timber production is far more common on this site than livestock and crop production. The suitability surfaces for soils a nd existing lands uses are almost identical between livestock, crop and timber production. The economic suitability surfaces were also very similar for all agriculture uses. In terms of physical suitability, all agriculture land uses had areas of significa nt suitability. However, crop production appears to be much less suitable in this area when compared to li vestock and timber production. Figure 5 1: Agriculture Suitability Map. See appendix C for the results of each goal, objective and sub objective.

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96 | Page Conservation Suitability The conservation suitability analysis has shown a high preference for conservation on the Farmton site. Most of the data sets have very high suitability levels. Yet there are some conservation goals that resulted in a low suita bility. These data sets include lands with priority natural communities, lands with significant surface waters, and proposed lands for future conservation. Of these, the first two data sets showed more moderate levels of suitability while the lands for fut ure conservation data set were largely unsuitable. When compared to the final suitability surfaces for agriculture and urban land uses, conservation was the clear winner. There was very little land that was found to be unsuitable for conservation. I woul d also like to note that there was an alternate version of the conservation suitability grids. This alternate grid gave extra weight to objective B 3.1 and the Goal B. In the second version, any lands that were a 9 in B 3.1 would remain a 9 when combined w ith B 3.2. This did noticeably increase the suitability level for B 3 but the difference was negligible when combined with the other three goals. For this reason the original weighting was used in the end analysis. Figure 5 2: Conservation Suitability Map. See appendix C for the results of each goal, o bjective and sub objective.

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97 | Page Urban Suitability The suitability for urban land uses on the Farmton site is very low. Almost every data set returned poor results with the exception of the land value suitability analysis. There is some physical suitability for urban land uses but there is very little economic suitability. The majority of land that is suitable for urban land use is located along the eastern edge of the site and the center of the site. The existing urban development and road infrastructure were the biggest influences on urban suitability. Conflict Grid The results of the conflict grid were pretty surprising. The most abundant land use preference was for conservation. In the south end of the property there was also a significant amount of preference for agriculture land use, yet there was virtually no pre ference for urban land uses. The areas in conflict on this map includes lands in high and moderate conflict. Figure 5 3: Urban Suitability Map. See appendix C for the results of each goal, objective and sub objective. Figure 5 4: Land Use Conflict Map. See appendix C for the results of each goal, objective and sub objective.

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98 | Page Part II : Farmton Alternative Plans The original plan for the Farmton property involves several land uses and varying levels of density ranging from 4 units per acre to 24 units per acre. The four alternate plans that are being shown below are attempting to reduce the impacts caused by development in various ways. Two plans reduce impacts by increasing densities and reducing development area while another simply relocates the development. The final plan will restrict development to a single area in each county and the number of dwelling units will be adjusted to achieve an acceptable density for the development. Each plan will have its own strengths and weaknesses and those will be discussed in more detail in chapter 5. The section below will contain a description of how these plans were developed and what goals they were able to meet. Alternate Plan #1 The first alt ernate plan maintained the current acreage of the original development plan. Various parts of the development were moved and adjusted in order to meet the goals that were outlined in chapter 3. The current Farmton plan includes large areas of required ope n space and those were also included in this alternate plan. All the land uses proposed in the Farmton plan are also proposed in this alternate plan in the same amount and at the same density. This plan was only able to meet three out of the five goals o utlined in the previous chapter. It may not be possible to meet the conditions of the first goal while fulfilling the other four. I did place development in the northern mitigation bank. This is part of the development that is currently being disputed by t he Sierra Club (Werley 2014). The only changes to the gateway district included adding some mandatory open space to use as a buffer. Some significant development south of Maytown Road was required to provide the same amount level of density that has been proposed for this site. However, a significant amount of open space was added to the land south of the road to help reduce and impacts to the corridor in that region. The first alternate plan was successful in creating corridors that are at least one mile in width. There are two corridors that are one mile in width: the corridor running north south through the Figure 5 5: Farmton Alternative Map #1. See appendix D for a larger version.

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99 | Page middle of the property and the corridor running east west al ong the south western edge of the site. In order to enlarge the north south corridor, the central island of development was shifted to the east and merged with the town center and work place district. Unfortunately, this process eliminates the smaller corr idor that ran through the project. The corridor located between the development located in Brevard County and Volusia County was also widened. However it is still only half of a mile in width. Finally development was condensed along the Maytown Road so tha t there would be a mile of undeveloped land along the south western edge of the property. This will allow a connection to the Volusia Conservation Corridor. This alternative plan contains three significan t corridors which will allow multiple avenues of t ravel for the area's wildlife. However, each of these corridors has a road that could potentially cause fragmentation. This is especially true of the Maytown Road. In the current plan for the Farmton development there are a total of seven areas of develo pment. In the first alternate plan the development was reduced to six areas. The removal of the central development island resulted in two larger developments in the center of the site instead of three development areas. Alternate Plan #2 Alternate pla n #2 reduced the proposed Farmton development area by 50%. These reductions will essentially double the densities on the property. Each land use type was reduced by 50% so that the difference between each area remains proportional. This plan met every goal but may have resulted in densities that will be unsuitable for the region. The reduction in development area has allowed for all the development on the site to be located ou tside of the mitigation banks and proposed conservation areas. With so little land needed, it was also possible to remove the development south of Maytown Road while still allowing for a buffer zone around the existing mitigation banks. The reduction in am ount of developed land in Brevard County allows for a very wide corridor moving east west. In fact, both major corridors are two miles wide at their openings; however, the north south corridor is just over a mile wide at its north end. The small corridor i n the north west corner also saw some improvements in this design iteration. Overall, this design achieved the best results from a conservationist's viewpoint. Figure 5 6: Farmton Alternative Map #2. See appendix D for a larger version.

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100 | Page Alternate P lan #3 The third alternate plan used a hybrid approach to determine to development area. All land uses were reduced in size and recieved a coresponding bost in density but they were not equal. The village areas were reduced in size by 50% while the other dev elopm ent areas were only reduced by 2 5%. This resulted in a plan that is a comprimise between the existing plan and the second alternate. While this plan was not able to fulfil all the goals outline in chapter 3, it was able to met four of the five which i s an improvement to the first alternate. As in the second alternate plan, this plan does not have any development located in mitigation banks or proposed conservation areas. However, some development did have to be placed south the the Maytown road. This development was kept to a minimum in order to reduce any potential impacts on the corridor that runs from the east to west. The north south corridor still varies between 1 2 miles in width which should allow adequate wildlife movement. The corridor north of the Brevard County development is 1/2 mile in width. The corridors in this design should provide mulitpile movement options for local wildlife. This plan as not able to provide as many buffers along the edge of the mitigation banks but it does work to reduce urban fragmentation. While the origional plan has seven areas of development this plan and the second alternate only have five areas of development. In the end, this design has a lot of improvments compared to the first alternate plan but was unabl e to reduce the unrban impacts as much as the second plan. Figure 5 7: Farmton Alternative Map #3. See appendix D for a larger versi on.

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101 | Page Alternate Plan #4 The fourth alternate plan reduced the amount of dwelling units on the property. The development in Volusia County was consolidated to the west to keep the development as close to an existing urban area (Deltona) as possible. Deltona was picked over Edgewat er due to the location of the mitigation banks. Oak Hill was not chosen due to its smaller size. Development was allowed in Brevard County so that they would not feel ignored and the development was kept out of any proposed lands for conservation. This pla n is a drastic change from the current plan and also offers the greatest reductions to impacts. This plan does not add any development in the existing mitigation banks and all development is also located at least 100 meters away from the mitigation banks . There are significant improvements to the corridors in the property. In fact the site is essentially one large corridor that could easily accommodate wide ranging carnivores like the Florida black bear. Part III: Alternate Plan Analysis After creating GIS data for the four alternate plans, they were each analyzed in the same manner as the other case studies. The data was then entered into a spreadsheet so that the alternates could be compared to each other. Not surprisingly the worst performer in this a nalysis was the first alternate. Since the plan was almost the same size as the current Farmton plan, it produced similar levels of impacts. There were only a few times when the first alternate performed better than the other three. Otherwise, each alterna te typically performed better as its development footprint was reduced. The design that had the fewest impacts on the landscape in both the context analysis and development analysis was the fourth alternate. While the first alternate performed the worst out of the new plans it typically performed slightly better than the current plan. All the data for the alternate plans can be found in appendix B. Figure 5 8 : Farmton Alternative Map #4 . See appendix D for a larger version.

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102 | Page Context Area Analysis In the context analysis each alternate plan had the most impacts at least once. In to tal there were only three times when the first alternate plan was not the most impactful. In the analysis of conservation patch size, alternates 2 and 4 we re the most impactful one time. The only significant data point where alternate 1 was not the most im pactful was in the analysis of floodplain functions. Alternate 1 was the most impactful overall for water management lands but alternate 3 impacted the most priority 3 floodplains. Development Area Analysis The development level analysis produced similar results to the context area. As with the case study analysis, looking only at the property area increased the amount of impacts being identified in the analysis. There were only five times when the first alternate plan was not causing the most impacts. On e of these events involved the priority 3 floodplains and another involved a tie between the third and fourth alternate. The last two times are found in the analysis of edge habitat. Alternate 3 and 4 each had one data point where the changes in edge condi tions were potentially worse than the first alternate.

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103 | Page Chapter 6 : Discussion Part I: Impact Analysis This section of chapter 6 will discuss the results from chapter 4 and 5 . Each analysis will be discussed and grouped into two parts. The first part will examine the results of each case study and the second part will review the changes between the alternate Farmton plans. Overall, there were a few trends that appear to hold a great deal of significance. The West Bay sector plan is typically found to be the most impactful plan when looking at the acreage of lands being impacted. However, there are also many instances when the 2006 Restoration plan causes far more impact than any other development while impacting a much smaller amount of land. This is why impacts were measured in both acres of change and percent of change. The truth is, the Restoration development is a much smaller site than the other developments, thus making the impacts associated with the development se em artificially low. By measuring the percentage of change occurring on the site it can be directly compared to the other developments in a more accurate manner. Even though Restoration is a small site, its imp acts are just as significant because over time small developments will become larger developments which will have a greater impact on the landscape. In order to understand the full scope of impacts, it will be important to look at what lands are being af fected. This is especially true when analyzing the conservation impacts. Most of the data sets define conservation priorities and may include 5 7 priority levels. Some developments impact a large amount of a particular habitat but if most of those impacts occur in very low priority lands they may not actually be as bad as a site with fewer impacts that all occur on high priority lands. The following discussion will attempt to highlight when a greater impact is diminished due to the priority lands the impact s occur on. The four alternative plans for the Farmton Plan also displayed some standard trends. As expected the alternate plan that performs the worst was the first alternate. In general, as the footprint of developed lands decre ase the impacts also decrease. The first alternate perform ed in a very similar man ner to the current plan while the other alternate plans result ed in th e fewest impacts . When the second third and fourth plans perform poorly it is typically due to impacts being reallocated to h igher priority lands. Agriculture Impacts Overall, the impacts to agricultural land uses were concentrated on timber production. The impacts on livestock and crop production were very minimal in each case study and the impacts to specialized agriculture such as nurseries and vineyards was almost non existent. The level of

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104 | Page impacts on timber land is not surprising though when you consider that companies like Plum Creek and the Miami Corp. have traditionally been in the business of managing timber lands. A 1: Impacts to Agriculture Patch Size Case Studies When looking at the context area of the case studies, two developments were significantly more impactful on the patch sizes of agricultural lands. Farmton and the 2006 Restoration plan had significant cha nges to all three data points in the patc h size analysis. Each study caused impacts to both the number of patches and the average patch size. However, Plum Creek and the West Bay sector plan did not have any impact on the maximum patch size. The impacts that were identified in the context analysis were found to be much worse when looking at the site alone. The 2006 Restoration site really stood out when looking at impacts inside the project boundaries. The impacts were far higher than any other developmen t when looking at the percentage of change. While Restoration may have had the greatest impacts, each development contain significant impacts on the patches of agricultural land. Farmton Alternatives With one exception, the alternate plans were able to re duce the impacts to the patch sizes of agriculture land. The first alternate added one more patch when restricting the analysis to the property. The second and fourth alternatives did return the best results, but the third alternate also performed very wel l. The reduction of development area really helped to reduce impacts on the site. A 2: Impacts to the Quantity of Agriculture Lands Case Studies When looking at how each development will impact agriculture land use, it is clear that these lands are not very useful for crop and specialty production. The reduction of timber land was the most common and significant impact in each case study. Specialty agriculture and crop production land uses received very small impacts from development. In fact, the combin ed impacts to both crop a nd specialty agriculture were 39 acres. 39 acres is rather insignificant when the smallest development is just over 5,000 acres in size. Pasture lands have also fared rather well in this study. Only 76 acres of improved pasture wil l be impacted by the current proposed developments. The amount of impacts to crop, livestock and specialty production lands is very reasonable on each site. Timber lands, however, are another issue. While each site had only minimal impacts to other agric ultural uses, they each contained significant impacts to lands for timber production. The impacts to timber lands identified by land use cover ranged from 618 to 21,316 acres. This is an incredible amount of land when you realize that only one development will utilize that much land. Potential areas for sustainable timber production were also heavily impacted by the development plans. The West Bay sector plan again stands out for its impacts in this category. Not only does this plan impact the largest acrea ge of sustainable timber production, but most of its impacts occur on the highest priority lands. The Farmton plan also causes some significant impacts to

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105 | Page sustainable forestry but they do not contain any impacts to priority 1 lands. Instead their impacts o ccur on priority 2 and 3 level lands which is why they are the second most impactful site. The 2009 Restoration plan will be the least impactful development on timber production in terms of both the amount of land impacted as well as the percentage of land impacted. This is significant because the 2006 plan would have had a significant impact on timber lands. The impacts to timber land are very significant when considering wildlife connectivity. While most timber lands are managed they are also very compat ible with conservation. These lands are not as intensively managed as croplands and many wide ranging predators and other wildlife will use these lands to forage and disperse. Farmton Alternatives T he current Farmton plan only causes significant impacts to timber lands. The alternative plans follow suit and only two of the new plans cause any additional impacts to pasture lands. The impacts to pastures are very minimal and are at most impacting 3 acres of land. This is somewhat significant since the prop erty only contains 20 areas of pasture land, but this seems to be an acceptable loss. The Farmton property does contain a large amount of timber land. According to the land use cover data, there are almost 27,700 acres of timber land on the site and the first alternate plan does impact just over 10,000 of those acres. This is only a small improvement over the current plan which impacts 500 more acres. This is one data set that requires a thorough look at the individual priority levels that are impacted. W hen comparing the alternate plans to the current plan they all reduce the amount of impacts on sustainable timber production however they sometime increase the impacts on one priority level in order to decrease another. Even with those increases the altern ate plans do perform better that the current plan with only one exception. The alternate plans still include many impacts but they are an improvement over the current plan when looking at impacts to agriculture land uses. Conservation Impacts The impact s to conservation areas were very significant. Farmton easily cause d the most impacts though West Bay and Restoration (2006) were a close second. There were a few areas that did not receive many impacts, but these w ere typically due to location. For example, t he fragile coastal resources only receive d impacts from the West Bay sector plan . It was very rare to see any particular conservation category without significant impacts. B 1A : Impacts on Conservation Fragmentation Case Studies Four of the case studies were found to fall below the perc %. It was also ev ident that the larger scales worked to improve the ratio of intact to developed lands in each case study. It was surprising to amount of change between the two Resto ration plans. Only

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106 | Page 54% of the 2006 Restoration plan contains intact land while the 2009 plan increases this to 73%. The compact design of the 2009 plan protects a lot of natural lands while still allowing a significant amount of development. The fact that the development it also located closer to existing urban area should also reduce infrastructure costs for the development. When looking at the fragmentation levels of each project with the surrounding context area, there were very few impacts. However, t he impacts increased significantly when the fragmentation of the site was analyzed. The most drastic changes occurred on the Farmton develo pment. The change from 94% to 44 % is alarming. It is important to realize that any development project has the abilit y to really increase the potential fragmentation when developers allow widespread, sprawling designs. It is encouraging to see that the redeveloped plan for Restoration performed better than each of the other developments for this data set. Farmton Alter natives When analyzing the fragmentation of natural lands within the context of the Farmton property, there was very little change between each plan. The difference between each plan was never more than a few percentage points. The only significant changes came when looking only of the development site. The best perfor mer in this study was the fourth alternate plan, which was expected. This data shows that each plan allows for adequate movement although it will still important to ask which types of wildlife will be able to utilize the paths. B 1B : Impacts to Conservation Patch Size Case Studies The vast majority of impacts identified by this analysis occur on patches of land with an area of less than 75 acres. The West Bay sector plan continues its trend o f being the most impactful site, change. The significant impact that can be identified by this analysis is the amount of intact land that is being developed. For e xample, the Farmton plan is impacting 16,996 acres of intact land while the site itself will only contain 18,457 acres of development. The development total is also including some land that will be left as mandatory open space which mean that almost the en tire development will occur on previously undeveloped lands. Over half of the Plum Creek development will be occurring on intact lands. West Bay will be allocating 74% of its developed land on previously intact habitat. The changes that occur between the context study and the development study are not very too great when looking at this data set. It would be nice to know how particular patches have changed after t he development. The really significant data from this study lies in the amount of intact land being developed. These developments are clearing occurring in areas that have seen very little development in the past. This is another instance were the Farmto n plan caused the most impacts on a percentage basis while the 2009 Restoration plan has made the least impactful design. The improvements made in the 2009 plan have been very impressive throughout this project.

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107 | Page Farmton Alternatives The alternative plans displayed the typical trend with each alternative plan causing fewer impacts than the original plan. Each alternate plan actually cause a sharp reduction in patches less than 75 acres but this does not seem to be a negative impact. Each plan greatly reduc ed the impacts on intact lands so it would appear that the 75 acre patches may have actually increased in size or combined with larger patches rather than being eliminated by development. Otherwise, there were no changes to any other patch size. There is a small calculation issue involved with the development study area. The current plan and the first alternate plan both result in an increase to patches with an area between 1,000 and 10,000 acres. Without development, a patch of this size does not occur an d it was not possible to obtain a percentage of change because it is not possible to divide by zero. The errors are represented by blank cells. B 2: Impacts to Existing Habitat Case Studies Habitats that are beneficial for biodiversity received the highe st level of impacts from each case study. Strategic habitats were also highly impacts while fragile coastal resources were only impacted by the West Bay development. Coastal resource lands appear in the Farmton and Restoration projects as well but only the West Bay development is close enough to the coast to have an impact. Even then the impacts are minimal . This is a data set that could have been removed from this analysis. Overall, the Farmton plan again caused the most impacts; however, it is important to note the performance of the sector plans as well. While the West Bay and Plum Creek sector plans were not causing the most impacts they are only preforming slightly better in these analyses. In particular, there are many times when the West Bay plan is causing many impacts to higher priority lands than the Farmton Plan. The Farmton plan is impacting 52% of the biodiversity areas contained on the site while the West Bay plan is only impacting 45%; however, the West Bay impacts occur on more valuable land s so they two developments are effectively tied in this category. Farmton Alternatives The coastal resources land data set was removed for the Farmton analysis. As in previous studies, each alternate plan reduced impacts in each category. The second and fourth alternate plan s continues to outperform the other two and both the second and third plans did an excellent job in reducing impacts to proposed conservation lands. In theory they should have eliminated all impacts to these lands and the identified im pacts are likely due to an error. The data was created in AutoCAD without the boundaries of the proposed conservation land. The intention of the design was to not include any development in the proposed conservation lands located in Brevard County.

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108 | Page B 3: Impacts to Edge Habitat Case Studies When looking at the changes to edge habitat areas, most of the developments actually reduced the amount of land in edge conditions. This is due to changes in surface area around the urban developments. As the urban area increased the amount of edge decreased even though the impacts of edge habitat were increasing. The amount of edge habitat is in fact lower after development but the amount of core habitat is also significantly lower. When adding the urban area to the edg e area there was always an increase which helped to see how the core habitat was likely shrinking. Due to some of the issues in measuring edge habitat; a different method was utilized when focusing on the developments themselves. This examination also looked at the condition of the edge habitat along with the amount of edge habitat existing before and a fter development. The 2006 Restoration project showed the highest increase in edge conditions although most of its edge habitat was intact as well. The edge habitat in Plum Creek was in the worst condition. The edge at both 100 meters and 300 meters contai ned a significant amount of non intact land that will reduce the effectiveness of the edge habitat to act as a buffer. Farmton Alternatives The Farmton alternative p lans continue to demonstrate the same trends. It is becoming very clear that simply reducing the foot print and utilizing higher density development will decrease impacts on the landscape. It is also clear that even with reductions to development there are still Figure 6 1: The corridors in both the West Bay plan (left) and Plum Creek (right) proposal are not wide enough to allow core habitat. The yellow represents edge conditions that extend 300 meters from developed lands.

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109 | Page significant impacts to the ecosystems. Each plan contains a significant level of impact to the amount of edge habitat and the condition of the edge habitat. B 4: Impacts to Wildlife Corridors Case Studies Wildlife corridors are very important for many types of flora and fauna. The area around each case study contains a significant amount of land that has a hig h priority for use as a wildlife corridor or for other landscape priorities. This is also a deceiving data set because the number s make the West Bay plan appear to clearly be the most impactive design at a larger scale . Howev er, the Farmton plan is causing the most impacts to the FEGN. The Farmton p lan is causing impacts to 18,088 acres of land in the FEGN and of those 18,088 acres 17,583 are occurring on priority one linkages. The remaining 505 acres of impacts occur on priority two linkages. On the other hand, the West Bay plan will impact approximately 28,000 acres of land priorities for the FEGN. None of those impacts occur on priority one linkages and only 5,255 acres are in priority 2 linkages. The bulk of the impacts, 23,000 acres, occur on the lowest priority linkages. The West Bay sector plan actually demonstrates an effective way to develop around the FEGN network. The plan proposes its development south of the critical linkages on its property and proposes agriculture land uses to the north. Thes e land uses are much more compatible with wildlife conservation efforts and are helping to reduce the developments impacts on the FEGN. The impacts being caused by West Bay are less significant than those caused by the Farmton plan. Figure 6 2: The Farmton plan greatly re stricts access to the Volusia Wildlife Corridor along the south western portion of the property.

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110 | Page The story is very simi lar when looking at the landscape priorities in each case study area. The Farmton plan is the only development that will cause impacts to priority one lands. The 17,000 acres of land that will be impacted by the Farmton plan is approximately half the amoun t being impacted by West Bay, yet all of West Each development is causing significant impa cts, but Farmton is causing more impacts by affecting higher quality lands in lower quantities. The follow ing pages will show two maps. These maps show the Farmton and West Bay development outlines above the FEGN locations. This will help to demonstrate how much more impact the Farmton plan will have on the FEGN when compared to the West Bay sector plan.

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111 | Page Farmton FEGN Map Figure 6 3: This is a map showing potential impacts to the FEGN.

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112 | Page West Bay FEGN Map Figure 6 4: This is a map showing potential impacts to the FEGN.

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113 | Page Farmton Alternatives Since the current Farmton plan is causing a significant amount of impact to lands that support wildlife corridors it is important that the alternate plans work to reduce these impacts. In regards to the green way priorities, each alternate plan succeeds in reducing impacts to both priority one and two linkages. In fact, the alternates almost eliminate all impacts on the priority two linkages. However, it was not possible to eliminate all impacts to the FEGN priorities on this site. This site is a very important location for potential wildlife movement and any development will cause significant impacts. Overall, each alternate also reduced impacts to the landscape priorities in the area. The only exception is that each slightly increase d the amount of impacts occurring on priority four lands. The third alternate has the highest increase in impacts to this priority level. B 5: Impacts to Water Resources Case Studies For the most part, there are very few impacts to the water resources in the context area of each development. The West Bay sector plan is the only developme nt with significant impacts to water resources. A t 8.1%, it caused twice the impacts when compared to the Farmton plan. Plum Creek and Restoration both contain few impacts to water resource lands. Significant lands for aquifer recharge and surface water are constantly hit the hardest by each of these developments. This is especially true for West Bay which impacts just over 34,000 acres of each land type. The Restoration plan almost reduces its impacts on water resources by half and most of these improvem ents are due to reduced impacts in the lands for aquifer recharge and surface waters. This results of this data is most likely due to the low development potential of water resource lands. Lands with wetlands, floodplains and surface waters are likely to b e difficult and expensive to develop. Farmton Alternatives With the abundance of wetlands on the Farmton property it is virtually inevitable that any development will cause some impacts to th e water resources in the area. When including the context area the percentage of impacts was very low and remained below 4%. This figure greatly increased to 27% when isolating the property. The best performer in every category was the fourth alternate plan and the second alternate plan also performed very well. Final ly, while the first alternate did reduce its overall impact on water resources lands it increased its impact on functional wetlands. It would appear that the development potential on these lands is very low which may explain why there are few impacts to the lands in general. Due to many local and federal regulations, it is very difficult to obtain permits to develop wetlands and it would also be unwise to locate development in natural floodplains.

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114 | Page Urban Impacts Urban impacts were fairly minimal and typically involved an increase in the urban foot print. This increase in urban area actually resulted in reductions in urban fragmentation. However, many studies showed increases in the proximity to nearby cities. C 1: Impacts to Urban Patch Size Case Studies When looking at the results from the urban patch size analysis it would appear that most of the developments have little impact on the size of urban lands. This was not true with the West Bay sector plan. When in cluding the context area it was the worst performer in each category. The increases to urban patches cause by the West Bay plan were far greater than any other case that was studied for this project. While this site significantly increase the size of the p atches, it was able to reduce the amount of patches as well. The images alone of the changes to the urban area in the West Bay project are very telling of just how large the development really is. The Plum Creek sector plan also contain significant impact s when only looking at the development area. This was also true of the 2009 Restoration plan. Almost every case was able to reduce the amount of urban patches which is reducing the urban fragmentation to a degree. They are reducing the patches because they are filling in the land between existing urban developments. The 2006 plan for the Restoration site actually recorded no change for two of the three categories and they only changed the average patch size by one acre which is pretty insignificant. Farmt on Alternatives The amount of land being added in each alternate plan is significant. While each alternate plan was an improvement compared to the current plan, the first alternate was only slightly better. The difference is pretty negligible. Overall, the impacts caused by each plan were very similar and the second and third plans did not reduce the amount of patches nearly as well as the first plan. This is due to a large area in the center of the property which is defined as an existing urban area even t hough it remains undeveloped. This may have been an incorrect designation and if this process was to be repeated I would recommend removing the area from the calculations.

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115 | Page Figure 6 5 : The changes to the amount of urban land in the West Bay Sector Plan are very impressive. After development, there will essentially be a ring of urbanized land around the bay. The only plan that proposes de velopment near existing development is the 2009 plan for the Restoration project. The Farmton Plan Restoration Development Plan (2009) West Bay Sector Plan Plum Creek Sector Plan

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116 | Page C 2: Impacts to Urban Proximity Case Studies The developments being discussed in this project are typically located a significant distance from existing cities. The on e exception is the Restoration project which is located in Edgewater Florida. Since the entire Restoration site is located inside the city limits of Edgewater, its results were unchanged when looking only at the site. There is some change in the context ar ea analysis. By increasing the development inside of the city, the average proximity was reduced by a small amount. C 2: Impacts to Urban Proximity Case Studies The developments being discussed in this project are typically located a significant distance from existing cities. The one exception is the Restoration project which is located in Edgewater Florida. Since the entire Restoration site is located inside the city limits of Edgewater, its results were unchanged when looking only at the site. There is some change in the context area analysis. By increasing the development inside of the city, the average proximity was reduced by a small amount. The Farmton development produced some interesting results. When looking at the context area, Farmton increase d the average proximity by the highest amount yet when the site was isolated, it actually reduced the average distance to urban areas. This is due to the developments proximity to the border of the city of Edgewater. There is a small cluster of development that will occur just south of the Restoration project and that may be helping to reduce the impacts in the study. Plum Creek and West Bay both increased the average distance to urban areas by a similar amount, however, the organization of the Plum Creek p roperty has had a large influence on distance when isolating the development area. Since the Plum Creek property is fragmented it allows for a wide range of distance values. This data may be more accurate if only the central area of the Plum Creek project was used. Farmton Alternatives Each alternate plan was able to reduce the changes to urban proximity when compared to the current plan. The fourth alternate plan performed the best and the first alternate performed the worst as expected. Unfortunately, an issue was encountered with the GIS data or model that was used to analyze the development area. Each data set contained significant visual changes but the values would remain unchanged.

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117 | Page Part II: Farmton Suitability Analysis A: Agricultural Suitability In general, the most suitable areas for agriculture are located in the southern half of the site. There are also many suitable areas just north of Maytown Road and the north east corner of the property is very unsuitable for production. The existing timber production in the region had strongly influenced the suitability levels for agricultural development. Due to the location of mitigation banks and existing wetlands, developing this site will likely impact many of the lands that show a high suitability for agriculture production. A 1: Suitability for Production Livestock The majority of suitable land for agriculture is located in the center of the property. This is most likely due to the influence of roads, existing agriculture (timber production) and the presence of drier soils. The north end of the property is very unsuitable for production. This area contains some of the wettest soils and it is also the furthest from existing developments and infrastructure. Crops While there are many areas on the Farm ton property that have been identified as suitable for crop production, this land use is clearly the least preferred. The fact that crop production is not currently occurring on the site speaks volumes about the suitability for crop production. Crop produc tion was also underrepresented in the region around the property as well. Timber The suitability for timber production in the area was interesting. The results were certainly better when compared to crop production but they were not necessarily better th an livestock production. While the livestock suitability surface contains many moderate and high levels of polarized suitability index. There are many areas o f moderate suitability but most of the areas are either very suitable of not suitable. This is surprising when considering how much timber production is occurring on the property. A 1.1: Physical Suitability for Production Livestock There are large areas on the Farmton site that are physically suitable for livestock production. Much of that suitability lies south of the Maytown road and north of the mitigation banks. Very little land in the mitigation banks are found to be suitable for anything other than conservation and agriculture is no exception. While most of the suitable lands are concentrated in the south, there is a path of suitability that extends to the north. While this path is fragmented, it helps to highlight a potential ridge and area of drie r land running through the site. This is important because low intensity livestock production can be compatible with conservation land uses. Migrating animals may utilize unimproved pastures as corridors or as temporary habitat.

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118 | Page Crops The physical traits of the Farmton property show a significant amount of land that is suitable for crop production. As with livestock, most of these lands are located in the southern half of the property and away from wetlands. The soil and existing land use data are having t he greatest influence over these results due to their higher weights. Timber While the livestock production suitability surface is rather polarized and the crop production surface shows a lot of moderate level suitability, the timber suitability surface shows very subtle changes when moving from high to low levels of suitability. This data has a very even mix of the various suitability levels, perhaps due to the fact that a large portion of the property is already being used for timber production. A 1.1 .1: Soils Livestock The areas with the highest soil suitability for livestock production were located in the southern end of the site. There is a significant amount of low soils with low suitability throughout the site and this is due to the large amount o f very poorly drained soils which are found in wetlands. The low suitability areas are almost all occupied by the wetlands that are spread around the entire property. Crops Crop production requires a higher drainage class than livestock production, which reflected in the suitability analysis. The suitability range falls on a scale of 1 8. The allocation of more suitable soils follows the same pattern as the livestock suitabil ity due to the location of poorly drained soils and wetlands. Timber The soil ratings for timber production were the same as those used for crop production. Both land uses can tolerate poorly drained soils while preferring well drained soils. These resul ts are identical to the livestock suitability. A 1.1.2: Existing Production Livestock This data set highlights how little land is currently being used for livestock production. This is an indication that this area may not actually be very suitability for livestock production. It is possible to produce livestock on this property, but it may be more difficult and without enough profitability to justify the expense. This data set was given a low weight as it will be recounted in the next step. This also keep s the overlay negative values from being too strong of an influence on the final suitability surface.

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119 | Page Crops the final suitability to reflect that no one ha s been willing to use the land for crop production thus far. Timber This site has a significant amount of timber production already occurring. In fact there is more timber production than any other agricultural or urban land use on this site. A great deal of this production also occurs in the areas that the Farmton plan will focus their development. Timber production is showing a clear preference among the agriculture land uses and its use it widely distributed across the property. The areas without existi ng production are very wet and typically contain wetlands and marshes. A 1.1.3: Existing Land Use Livestock The existing land uses across the site provide a diverse level of suitability values. The strong presence of existing timber production really inc reases the suitability for livestock production based on existing agriculture production. The very wet are remaining unsuitable in each analysis of the physical suitability while this analysis allows for wetlands and marshes to be given a higher value even though they are in a low suitable drainage class. Crop This suitability set resulted in the most even distribution of suitability values. The existing timber lands continue to significantly increase the suitability for all production types on this prope rty. The lands in the mitigation bank also continue to contain low suitability values throughout the agricultural analyses. Timber This data set was very similar to the livestock data. Wetlands and marshes are shown as less suitable when compared to live stock and this has resulted in a polarized suitability surface. Most of the land is either very suitable or unsuitable for timber production based on existing land uses. There are only a few areas that receive a moderate ranking due to the limited data tha t was selected to be a level 5. A 1.1: Economic Suitability for Production Livestock The economic suitability for livestock production is really centered around the roads on the Farmton Property. The roads were given a high weighting so this is not a surprise. The road suitability data also aligned well with the market suitability data whi ch resulted in the lowest suitability being located to the northern end of the property. The north end of the property has few roads and markets which is why the suitability is so low.

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120 | Page Crops The market and road proximity data heavily influenced the resul ts of this study. The highest suitabilities were located along the roads and the north edge of the property. Aside from those areas, the economic suitability was far lower for crop production than both livestock and timber production. This appears to be du e to the heavy reliance on existing urban areas and infrastructure to support crop production. Timber The Farmton site shows the highest economic suitability levels for timber production. This is further supported by the fact that the majority of current agriculture production involves timber farms. The land is situated near multiple timber markets and is also located near several major roads which should help timber farms to deliver their products to consumers. Every data set of economic conditions showe d favorable preference for timber production in this project. A 1.2.1 : Land Value In terms of land value, there are essentially no constraints to any development on the Farmton site. The land value of the property is very low which makes it very suitable for all land uses. The areas that have an increased land value all occur near roadways or existing development. Crops The crop suitability values were almost identical to the suitability values for livestock production. The suitable land values were actu ally even lower for crop production but the results were still the same. There are no discernable differences between the data. Timber Timber production requires the lowest land prices to be suitable for timber use. The lower price suitability allowed for a significant change from the first two data sets. The areas that were slightly less suitable were all near areas of existing development and roads. There are also two large areas that appear to have been parceled out to influence some urban development a nd these two locations where only slightly less than very suitable compared to the rest of the property. A 1.2.2 : Road Proximity Livestock The locations of major roads result in a pretty high level of suitability for livestock. One major road cuts right through the center of the site and I 95 is running along the eastern edge of the property so about half of the site is highly suitable for production based on road proximity. Crops This suitability data is very similar to the livestock production data. T he most significant change is that the suitability levels drop more quickly as the distance from the roads increases. This shows that crop production prefers to exist in areas that have ample road access when compared to livestock and timber production.

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121 | Page Timber The suitability for timber production is again very similar to livestock production. The data shows that timber production can be slightly further from roads than livestock production. It might be interesting in the future to look at the influence o f highways versus major roads to see if the highway proximity would be more valuable than major roads in the region. A 1.2.3 : Market Proximity Livestock There were no existing livestock markets in the 10 mile context area so the context area was increased to 50 miles for this analysis. Even with this change, there was a large range of suitabilities for this data set. One important note is that the market p roducing a high suitability area in Brevard County may currently be closed. Crops The markets for crop production were defined as city limits and this had a significant impact on the economic suitability for crop production. The north edge of the Farmton property borders the city of Edgewater and that resulted in the northern half of the property being very suitable for crop production. The cities to the south and west of the property are a significant distance away from the Farmton site so they did not h ave much influence on the data. This is appropriate because some cities, such as Scottsmoor and Oak Hill, are very small and would likely not provide a significant market for agriculture products. Timber The Farmton property has several saw mills and lum ber yards near that site and a large majority of the site is very suitable for timber production based on the proximity to markets. The southern half of the site had the most suitability but the northern half also has a very significant amount of high suit ability. The middle of the site is very unsuitable for production which is curious because a significant amount of timber production occurs in the center of the property. It might be possible that market proximity is not overly important for timber product ion in this region. It should also be noted that the analysis area for this suitability was increased to 50 miles in the same manner that occurred in the livestock analysis. A 3.3 : Potential for Sustainable Timber Production This analysis only occurred f or timber production. Over half the Farmton site has been identified as a priority area for potential sustainable timber production with a significant amount of these lands being used for timber production. There are no priority one areas, but the priority 2 and 3 areas are highly represented on the property. They form two large sections with the higher priorities being located in the southern half of the property. This follows the typical trend of agriculture production being more suitable in the bottom ha lf of the property where the soils are better drained.

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122 | Page Conservation Suitability The final conservation suitability grid showed a strong preference for conservation throughout the Farmton property. While many of the conservation goals showed an array of suitability values, the final gird only contained moderate to high levels of suitability in significant amounts. The areas that contained moderately suitable lands were located in and around Brevard County. This is an area that will result in agriculture preference in the final conflict grid. Most of the conflict grid identifies conservation as the preferred land use and after looking over this suitability grid it is not surprising. Significant Lands for Biodiversity There is a wide range of suitable lan ds for protecting biodiversity on the Farmton property. The most significant lands were for the protection of strategic habitats. They contained the highest levels of suitability and significantly influenced the rest of the data. The least influential data set involved potential habitat richness. This data set was given a lower weight than the other three, but its suitability index was similar to both the rare species data and the natural communities data. The southern half of the site was strongly influe nced by the combination of B 1.1 and B 1.4. Both of these suitability surfaces showed very low to moderate suitability in Brevard County and this was evident in the combination of the objectives. The northern half of the property was more influenced by B 1 .1 and B 1.3. Significant Lands for Water Quality This suitability surface has very few low suitability areas. This is due to the method of combining objectives. By only keeping the highest values, extra weight was given to suitable lands for protecting water quality. While there are several areas that are not very suitable for protecting surface waters, these were eliminated when combined with the ground water priorities. One area on the site was consistently unsuitable for water protection and it was lo cated in Brevard County. This land is a lake and is a part of a mitigation bank so it should remain undeveloped even though it may not be significant for water protection. Significant Lands for Protecting Connectivity This was a critical data set for con servation suitability. In, fact it was the most influential data set in the combined suitability grid. The two objectives that were used in this goal showed very high suitability levels for conservation purposes. The Farmton property contains many signific ant lands for both landscape connectivity and integrity. In the combined goal, the suitability grid only displayed values at the extreme ends of the scale. Even then, the highest values dominated the surface and occupied more than 75% of the property. Suitable Lands for Permanent Conservation This data set contains some level of bias and preference when sorting the data in objective B 4.1. Mitigation banks were considered to be conservation land in this analysis which significantly improved the suitabil ity values. Objective B 4.2 carried very little weight but still had significant

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123 | Page influence over the combined goal. The objective tempered the suitability in the northern half of the site and brought the suitability values to a more moderate level. Urban Suitability The final combination of each urban land use suitability produced a fairly wide range of suitability values. Many of the values were in the moderate to low range but there is a compelling amount of high suitability levels across the property. There are several large areas of land that show a very low suitability for urban development and most of these are currently being used as mitigation banks and the bulk of the higher suitability levels are located in the center of the property. What was really surprising, though, was the fact that the current Farmton plan occupies some of the most suitable areas for development based on this analysis. This is especially true in Volusia County where there is only one location without development that is sh own as suitable by this map. However, the proposed developments in Brevard County do not follow the suitability map as well. Most of the suitable lands for urban land use are located at the southernmost edge of the property and this area is currently being utilized as a mitigation bank. After looking at this suitability grid, it is becoming clear why the Miami Corp has focused its developments in the center of the property. Urban Land Use Suitability Each suitability surface for urban land use return approximately the same results. Most of the suitable lands continued to be located along the major roads. This is due to the high weights road received but it is also because the soil suitability was typically better along the roads as well. It is quite po ssible that the main road crossing the site was designed by following the more developable soils and land. Each land use suitability surface also showed moderate levels of suitability for lands that were outside of the floodplain. Roads, floodplains and so ils were the main influences on urban land0use suitability in this study area. Physical Suitability The physical suitability data was the same for all three urban land uses. Overall, much of the site is not physically suitable for urban development. Almo st half of the property is inside the 100 year floodplain and very few soils are suitable for development. There is a significant amount of land located outside of the floodplain and those areas do show up as relatively suitable for development. Although, most of the land outside of the floodplain is also on poorly drained soils which helps to bring the suitability values down. Surprisingly, the current development plan for the Farmton property closely follows the lands which are more suitable for u rban lan d uses. This is because a large portion of unsuitable land is located in mitigation banks.

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124 | Page Soil Suitability There are very few areas that contain soils which are very suitable for urban land uses. There is also only one area that has highly suitable soi ls that will be developed under the current Farmton plan. Most of the suitable soils that are located north of Maytown Road will all fall under conservation land uses with the current development plan. With the significant presence of wetlands and floodpla ins on this property it is not surprising that there are so many unsuitable soils on the site. Flood Zones There were very few areas in the 500 year flood zones and at least half of those occur in the mitigation bank in Brevard County. Many of the lands outside of the floodplain are lands that are currently being used for timber production. These lands are also showing a moderate preference for development in the soils suitability so they are significantly drier than the surrounding wetlands. Economic S uitability In general, the economic suitability for urban land uses was very low across the Farmton property. The presence of roads and water infrastructure had the greatest effect on the economic suitability of the study area. Residential The economic suitability for residential land uses is very low. The few areas that are suitable economically are located near edges of the property. The suitability is higher in these areas for a few reasons. First, these corners are in close proximity to existing urban areas and these areas contain many features that increase the suitability for residential land use. Parks, schools, hospitals, commercial land uses, major roads, and water services are all located in proximity to the eastern corners of the F armton property. These features are desirable for residential development for various reasons. Water and road infrastructure can reduce the costs of developing the land and school, hospitals, parks and shopping areas are all desirable amenities for new res idents. While the land value was certainly very suitable across the entire site, it was not given enough weight to overpower the low suitabilities often contained in the other sub objectives. Even the high suitability levels in sub objective C 1.2.2 were only able to raise the overall suitability to a moderate level. Commercial The economic suitability for commercial land uses was significantly higher than residential use, yet overall, the suitability is moderate to low throughout the site. The biggest influencers on commercial suitability were roads, existing commercial, and water services. Land value and proximity to residential land uses had little to no impact on the economic suitability for commercial development.

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125 | Page The highly suitable lands in this data set are all located along roads and areas the border water service districts. The proximity to existing commercial has brought large portions of the property to at least a moderate level of suitability. Surprisingly, the areas that are currently prop osed for the town center and work place district show up as unsuitable for commercial development. This may cause impacts to the economic viability to the Farmton development. Industrial The economic suitability for industrial use is similar to the previ ous urban land uses. The only areas with high suitability are located along transportation corridors. This is mostly due to the fact that roads received a relatively high weight in each analysis when compared to the other sub objectives. While the presence of a rail line to the east of the site did have some influence over the final suitability surface, roads has the most influence. The proximity to existing land use had very little influence over this objective. Conflict Grid The final conflict grid rea lly highlights the high level of preference for conservation lands on the Farmton property. The conflict grid also contains a large amount of conflict in both Volusia and Brevard County. Visually, it is very difficult to identify the areas with an urban pr eference. Often the areas are less than an acre in size, but there are a few that can be spotted with a sharp eye. Due to the low amount of urban preference it was difficult to determine areas that should be used for urban development. In the end, each are a had to be investigated to help determine suitable places to allocate urban development. The results from the conflict grid help to demonstrate that this property may not be a suitable site for such a large scale development. Farmton Alternate Plans Ea ch alternate plan resulted in reduced impacts in nearly every category. The bes t performing plan was the fourth alternate which also had the smallest footprint. As discussed in chapter 4, the alternate plans also achieved many of the design goals found in chapter 3. In the end, the third plan really seems to be the most suitable for the site is development is to occur without a change in dwelling units . The plan works to significantly reduce urban impacts while not causing a dramatic increase in density in the area. The fourth plan really succeeds at reducing the projects foot print while still allowing for an acceptable amount of development. During the process of creating these alternate plans for the Farmton property a few items became very clear. To b egin with, there are very few options for development on this property. The existing mitigation banks really constrain development options along with the constant presence of wetlands throughout the site. This is especially true in Brevard County where muc h of the land is already under a conservation easement. The only thing to do with the development in Brevard was to reduce its foot print. The data being used in this project showed the existence of an area along the western border of Brevard County as an area of development. The current

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126 | Page plans show this area as conservation, so it was always considered it to be open space in when conducting the various calculations. In order to complete the first plan, development had to be allocated inside the mitigation bank to maintain the corridors throughout the rest of the property. The gate way area remained unchanged because that area is the most suitable in the mitigation bank. The original, though, also reflects on the 2006 Restoration plan. In the 2006 Restorati on plan, a road would have been able to link to the proposed spine road in the Farmton development. Today, that area of development does not exist. The 2009 plan for Restoration moved all of the development far to the east and that connection no longer mak es any sense. This is surprising because the Restoration plan has been approved well in advance of this current Farmton design. It is unclear why the Miami Corp. has not changed the location of the gateway development especially since its development is st ated to be the first phase of this project. The second and third alternate plans for this project were significantly easier to produce. The reductions in development simplified the land allocation process. Having less development also made the process of widening corridors and add buffer zones less of a chore. Because these plans were easier to complete, it was also possible to alter and adjust the plans several times to try to create a better version. The fourth plan drastically reduced the development footprint of the project. In total, there would be less than 5,500 acres of development which would actually still support a large amount of residences at relatively low densities. Several iterations of a ll three plans were created during this project and these three represent the best iteration for each plan. The analyses above should help to corroborate that statement as well. At this point it is important to discuss the density of the Farmton plan and its alternatives. The density for each plan was calculated by simply dividing the proposed number of dwelling units by the amount of developable land. The developable land is the area of proposed development minus the wetlands that exist on the site. This averages out the density across the entire site which was necessary due to limitation in the data. Currently the only two areas of development have a specific amount of dwelling units. Depending on the need for schools, the gateway district proposes betwe en 2,287 4,692 dwelling units and 2,306 dwelling units have been proposed for Brevard County. All other development areas only discuss a cap in density without any concrete numbers for dwelling units. Without a clear proposal about how many units will be allocated in each land use area, a average density level was used to compare the different alternatives. The current plan is targeting a minimum density level of approximately 3 units per acre; however, the above process shows that the average density a cross the whole site as proposed would result in a density closer to 2 units per acre. The first alternate plan would result in an average building density of approximately 2.25 units per acre. The second alternate would result in an average density of 3.7 5 units per acre and the third plan would bring the average density to 3 units per acre. If the dwelling units are not changed, then the fourth alternate would result in an average building density of 6 units per acre.

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127 | Page This is actually the target density o f the village areas as proposed in section FG 3.8 of the Farmton Local Plan . Since this density is significantly higher than the other alternate it is proposed that this alternate may have a reduced amount of units. With 16,000 units in Volusia County and 2,000 units in Brevard County, there would be an average density of 4. 2 5 units per acre. Farmton Plan Developed Dwelling Units Non Residential Size in Acres Density Volusia County Conservation N/A N/A 31,876 Acres N/A Developed 23,100 4,700,000 15,081 Acres 2.5 Units per Acre Brevard County Conservation N/A N/A 8,286 Acres N/A Developed 2,306 1,200,000 3,376 Acres 1 Unit per Acre Grand Totals 25,406 5,900,000 58,619 Acres 2 Units per Acre Farmton Alt #1 Developed Dwelling Units Non Residential Size in Acres Density Volusia County Conservation N/A N/A 32,289 Acres N/A Developed 23,100 4,700,000 14,668 Acres 2.35 Units per Acre Brevard County Conservation N/A N/A 8,290 Acres N/A Developed 2,306 1,200,000 3,372 Acres 1 Unit per Acre Grand Totals 25,406 5,900,000 58,619 Acres 2.25 Units per Acre Farmton Alt #2 Developed Dwelling Units Non Residential Size in Acres Density Volusia County Conservation N/A N/A 39,279 Acres N/A Developed 23,100 4,700,000 7,678 Acres 4 Units per Acre Brevard County Conservation N/A N/A 9,906 Acres N/A Developed 2,306 1,200,000 1,756 Acres 1.8 Units per Acre Grand Totals 25,406 5,900,000 58,619 Acres 3.75 Units per Acre Farmton Alt #3 Developed Dwelling Units Non Residential Size in Acres Density Volusia County Conservation N/A N/A 37,635 Acres N/A Developed 23,100 4,700,000 9,322 Acres 3.3 Units per Acre Brevard County Conservation N/A N/A 9,661 Acres N/A Developed 2,306 1,200,000 2,001 Acres 1.6 Units per Acre Grand Totals 25,406 5,900,000 58,619 Acres 3 Units per Acre Farmton Alt #4 Developed Dwelling Units Non Residential Size in Acres Density Volusia County Conservation N/A N/A 42,495 Acres N/A Developed 16,000 4,700,000 4,462 Acres 4.6 Units per Acre Brevard County Conservation N/A N/A 10,751 Acres N/A Developed 2,000 1,200,000 911 Acres 2.9 Units per Acre Grand Totals 18,000 5,900,000 58,619 Acres 4.25 Units per Acre

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128 | Page Visualizing Density The next few pages will help to illustrate the densities that have been discussed. These images are from the book Visualizing Density by Julie Campoli and Alex S. MacLean. The authors compiled a series of aerial images to help others to understand resident ial density. The following images are taken directly from their book.

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131 | Page Chapt er 7 : Conclusions The state of Florida is a magical state. There are so many interesting plants and animals scattered in every corner of the peninsula. With approximately 8,400 miles of coastline, wild swamps filled with rivers of grass, theme parks, and adventures to space, it is not surprising wh y so many people visit and move to Florida ea ch year! (Coastal Resources n.d. ). This project is not intended to stop growth in the S tate of Florida, instead it is meant to help planners and designers find a balance between urban expansion and conservation. Now t hat Florida is the third most populous state in the count r y, it is becoming even more important that developments are planned in a manner that promotes the health and well being of humans and the environment. Conclusions After a great deal of tho ught and analysis, a few conclusions can be made about the effectiveness of sector planning as well as the benefits of large scale master planning. These conclusions are based on both the research that was conducted in the literature review as well as the results from the various analyses that were performed in this project. Sector planning has not significantly helped to reduce the negative impacts associated with urban development and urban sprawl. One of t he worst performing development s in this proj ect was approved through the sector planning process. While it was one of the pilot projects, this still helps to show that the process has been unable to significantly reduce the impacts associated with urban development and urban sprawl. The Plum Creek P roposal is currently facing a tough fight in order to gain approval even though it had fewer impacts when compared to the West Bay plan. While Plum Creek is a better plan than West Bay, it will still cause a significant amount of change to a largely undeve loped area. The Plum Creek Plan really only looks enticing due to the large amount of conservation lands being included in the proposal. However, as mentioned earlier, most of these lands are already under conservation so it is unclear why these are being cons idered in the development plan. During the analysis section of this project, the Plum Creek property was assessed in three ways. The first time analysis was performed on the site, all of the Plum Creek property was use and the results artificially imp roved the results for the development. After removing the existing conservation from the analysis the potential impacts that could be caused by the development became very clear. By adding existing conservation lands into the proposal, Plum Creek is mislea ding the public about the impact of their proposed development. Many people cite the

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132 | Page amount of land being protected by developments like Farmton but they are often unaware of how much of that land was already under protection. While the sector planning process appears to have a few issues, it is not the only design process that was found to be ineffective at reducing the negative impacts cau sed by urban developments. The comprehensive plan amendment process that was used for the Farmton Plan seems to be even less effective at reducing impacts on the environment . If the Farmton property is developed as proposed there will be many impacts to the ecosystem in the area. The greatest of these impacts will be focused on lands vital to water quality protection a nd lands that provide connectivity to native wildlife. The plan that really stood out when compared with the others was the 2009 Restoration Proposal. The process that led to that design really helped to reduce impacts on the environment and that is true on both a regional scale and the site scale. The work Canin Associates completed with the Program for Resource Efficient Communities is impressive. Not only did they focus on the impacts that the development would have on the surrounding wetlands and habi tat, but they also looked at how each parcel could reduce their water and energy consumption. The Restoration project shows one example of how the DRI review process has succeeded in reducing impacts to the environment in a more effective way than the sect or planning process. The use of an iterative design and analysis process can greatly reduce the impacts of an urban development. The Restoration development was an excellent case to study in this project. Having two proposed development plans to compar e highlighted the improvements that c an be made to large scale projects. The first plan for the Restoration site had the potential to cause significant impacts to the region and the revised plan greatly reduced those impacts. Throughout this study it was c lear that the revised version of the Restoration project would create significantly fewer impacts to the landscape while also helping to reduce urban sprawl. The 2009 plan is the most compact design in the entire project and this results in the largest per centage of connected conservation lands remaining intact . The use of iterative design also resulted in improvements in the alternative designs for the Farmton site. The second and third alternate plans have a clear advantage over the current plan due to their reductions in development area, but the first alternate plan was also able to reduce impacts in most of the categories. Hopefully th is exercise will help planners and developers rethink their design process. By using tools like GIS, it is possible to identify potential areas of impact and conflict in a given study area. This information can then be utilized to help shape a design that causes fewer negative impacts while still allowing for growth and development.

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133 | Page Sustainable and green design goals are becoming more marketable throughout the state of Florida. Each development that was studied in this project made a claim about being a sustainable development or aimed to achieve a lower impact design. These projects have worked to increase some cons ervation lands while also proposing some lower impact land uses. The planning process in Florida also reflect s a desire to create more sustainable urban areas that not only benefit people but also work to protect the landscape. Even though green technolo gies and sustainable developments are becoming more marketable, it does not appear th at these developments are implementing the programs in an effective manner . At the moment the sustainable movement can seem like nothing more than a new public relations s pin on old styles of development. Plum Creek and Farmton are particularly guilty of this. Each development has boasted about all the land they will be conserving with the approval of their projects. What they fail to mention is that a high percentage of th e land is already protected under some form of conservation easement. The way some of these developers have represented their contributions to conservation lands is pretty appalling. For example, the Farmton plan claims that the approval of their develop ment plan will add as much as 46,000 acres of land into conservation (Farmton Plan N.D.). Of this land, which is about 78% of the site, only 22,000 acres is new for conservation. Three large mitigation banks already account for 24,000 acres of conservation land and they were created in 2000 which is more than 10 years before the Farmton Plan was approved (Bolado 2015). Even though these banks were always going to remain in conservation, the Farmton plan proposal has been able to include them in their calcul ations and many people cite these numbers for why the plan should be accepted and applauded. The conservation easements associated with the Farmton plan are significant, but it should be made clear how much is actually being added that was not already un der conservation. This is also an issue with the Plum Creek proposal. Plum Creek likes to state how much land they will add to permanent conservation but a significant amount of that land was protected by conservation easements long before this plan was ev estimated the value of the land to be placed in conservation betwee n $600 million and $1.1 o not provide enough context to properly inform the public about these t ransactions (Farmton Plan n.d.). Developmen ts that occur on previously undeveloped lands will likely cause significant impacts to the existing landscape. This is a n obvious st ateme nt but it does need to be made . Any development will cause some impacts to the ecosystem and the wildlife that inhabi ts it. Each case study had significant impacts on the land even when their development areas were significantly reduced and rearranged. It appears that we will not be able to eliminate our impacts on the world but we may

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134 | Page not have to. It is important to rem e mber that people are part of ecosystem s . Humans depend on the landscape for many resources and even though our presence may not always help the landscape, eliminating humans from the equation is definitely the wrong answer. If anything, this project goes to show that planning and development process can be improved and it is best that everyone keeps striving to improve and move forward so that humans can be a more beneficial component in the ecosystems around the world. Ideas for Further Research When designing the alternate plans for the Farmton project, it became clear that the all the In the future, it would be nice to include an analysis of the eco nomic motivation for these developments. Why do the developers feel these lands are economically viable for development despite the often low suitability in the area? What would be the value to the developers and property owners if these lands were utilize d for continued timber production? Would these developers be willing to not develop these lands if they received a form of compensation for ecosystems services such as flood control or water treatment? The economic motivation for development in these lands is not very clear and i t will be interesting to see if some of these approved plans are developed in the future. It is possible that the market will not support the intended land uses. These projects may also present an opportunity to learn more about h ow various construction practices impact the landscape. Knowing that the lands in the Farmton, Restoration and West Bay projects are likely to become developed in the future, it would be wise to start documenting these lands. A significant problem with eco logy studies seems to be that there is not enough data taken about projects before development of construction began. Without adequate data about the pre development conditions, it can be difficult to draw concrete conclusions about any studies that involv e these sites after development has occurred. The more information that can be gather about these sites the better. It would be interesting to have a study about how these ecosystems change during the process of development. It would also be nice to cond uct a suitability analysis at a larger scale. One limitation with this project is that the suitability analysis that was conducted for the Farmton property only looked at the property itself. It is very likely that a regional suitability analysis would sho w thee whole property as very unsuitable for any urban development. It would also be interesting to look at the suitability for the regions around each of the other sites as well as the entire sta te. More research should be conducted to learn more about wh at makes different location s suitable for development so that land use decisions can be made in a more transparent and scientific method that will allow for healthier communities and ecosystems.

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135 | Page Final Thoughts While conducting the researc h and analyses for this project, it was surprising to see the impacts these developments can cause to natural lands. It has become clear that some of these developments are at least looking in some of the right places when they locate their developments but it still see ms unclear why they think their particular property is suitable for development. When looking at the results of the Farmton analysis in combination with the restrictions for possible development on that site, it is clear how why they placed their developmen ts in the current configuration. There are really no alternatives using the same acreage that will produce significantly better results. The Farmton development is essentially using all the land that could ever be used for development in that area and then claiming that they are just giving away the rest of the land for conservation. The truth is that they probably could not any market. So why are these developments being proposed now when most of these lands have been very productive for many years? With the exception of the Restoration project, these case studies all occur on lands that have been historically managed for timber production. Both Plum Creek and Miami Corp are large timber companies and each owns a significant amount of land in Florida and across the country. Maybe these lands are not as productive as they once were or maybe the companies are simply responding to market demands. Now that Florida is the third largest state in term s of population, there will likely continue to be a significant demand for low density developments across the state. Many of the lands being considered for development in the case studies represent some of the only lands that remain available for greenfield development. Plum Creek seems very interested in using their development to revitalize Eastern Alachua County but they only seem to be interested in helping by developing new lands. It would be better for the environment if more attention was brought to redeveloping existing urban areas. It might be possible for some of these large companies to sell some of their lands while also purchasing nearby urbans lands. This process would certainly involve more paperwork and higher c osts, but it would also seem to be in line with some of their goals for achieving more sustainable communities. These large scale developments are allowing for the continuation of sprawl and this can be seen in the comparisons made between projects like Walton plan with The Villages. The Villages is a large retirement community which is often used as a typical example of urban sprawl and the new Bay Walton plan aims to develop at the same scale as The Villages but at a lower density (Garman 2014). When looking at these projects at the site scale, they do not always appear to be sprawling developments. In fact both West Bay and Farmton are proposing developments with centralized areas of development that is aimed to create more walkable commun ities that are geared toward mass transit options. However, if you look at these same

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136 | Page Coast. Oak Hill, which is a very small town in southern Volusia County is about six miles from a significant urban area. Farmton will reduce that distance to less than four miles. The distance between Deltona and Oak Hill is 16 miles and the Farmton devel opment will be placed right between these two urban areas. It would appear that more needs to be done to educate the public and politicians about the various scales of urban sprawl. Sprawl can occur at a site scale and a larger regional scale and the plann ing approaches to combat sprawl will be different at each scale. development can create fragmented urban areas that cause greater habitat fragmentation, more edge conditions and can reduce ecological functions (Benedict and McMahon 2006). Final ly, it is surprising how little these case studies work to promote green infrastructure planning. A green infrastructure approach to planning can have many benefits to both the environment and people. The ecosystem services that can be protected with green infrastructure planning can help reduce costs for development while also providing more multifunctional spaces. Green infrastructures can help protect functioning ecosystems which in turn can provide a variety of economic benefits such as recreational opp ortunities, increased property values, and even decreased costs associated with public infrastructure (Benedict and McMahon 2006). The results of this project will hopefully led others to believe that some of these developments should not be completed. No t because they will impact the ecosystems but because they just do not make sense logically or economically. Humans can be better stewards of the land than we have been over the last couple of centuries. The technology exists to help us make better decisio ns but we may lake th e motivation to do so. Surely in the future, planners, developers and ultimately consumers will continue to place a higher value on sustainable behaviors.

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137 | Page Appendix A: GIS Tool Descriptions There are many tools and process that can be used in GIS to conduct various types of analyses. In order to complete the analyses in the project 20 different tools were used in GIS. The function of these tools will be explained in this section and each desc ription originates from the tool help inside the ArcMap 10.1 program. Processing Tools Processing tools allow for data to be manipulated, created, or changed so that they may provide different types of analysis. These tools typically only work on either vector data or raster data. Some tools however, work on any data type or they may have a tool for each type. Buffer This tool can be used in many ways and for many purposes. In th is project it was used to create study areas and to identify edge habitat. This tool only works with vector data, however Clip using one or more of the features in another The clip tool extracts data from an input feature based on the extent or overlay of a clip feature. It is often used to extract data for a particular location such as a study area. There are two clipping tools; one is used for vector data and the other is used for raster data and they both perform the same essential function. Combine Combines multiple rasters so that a unique output value is assigned to each unique combinatio n This tool a useful raster analysis tool that can show what values are present in a single cell location. The data it returns can be very simple or complex depending on the number of values that are entered in the input data sets. Di ssolve This tool was mainly utilized to prepare data for aesthetic and graphic purposes and can only be used on polygon data.

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138 | Page Erase polygons of the erase features. Only those portions of the input features falling outside the erase features outside boundaries are This tool simply erases data based on the shape of the erasing feature. This was often used to remove existing land uses that would contain new development in each case study. The erase tool can only be used with vector data but a mask tool exists that performs a similar function for raster datasets. Euclidean Distance This tool identifies distances between objects in a manner similar to buffer. It takes a vector data source and returns a continuous raster data set. The cell size of the output raster and maximum di stance can be manually changed. This tool is frequently used throughout this entire project and is very useful. Expand This tool was useful for filling in gaps in raster sets in a co ntrolled manner. This tool only works with raster data. Focal Statistics This is a very useful and powerful analysis tool for raster data. How ever, caution should be taken when assigning the neighborhood size. This function can take hours to complete when a large analysis area is chosen with a small cell size. INT This tool w as used to allow statistics operation to be performed on Euclidean data sets without the use of zonal statistics as a table. INT only functions with floating point raster datasets. Intersect d/or feature classes will be written This tool was useful for selecting overlapping data such as wetlands that occur on proposed developments.

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139 | Page Merge In this project the merge tool was typically used to prepare dataset for analysis. Sometimes data can be downloaded by county and the data can be combined so all the information is in on file. Raster Calculator ingle Map Algebra expression using Python syntax in a calculator like This is one of the most powerful raster processing tools in ArcMap. This allows for the execution of very complex conditional statements along with various other calculation s. Syntax errors can be common with this tool and may be difficult to solve, but this tool is invaluable during suitability analyses. Reclassify This tool is very useful for assigning new values to an existing data set. It can also be used to remove and add data to existing raster data. This tool is used in virtually every step of the suitability analyses. Region Group cell belongs is This tool was very useful when conducting patch size analyses. The input raster data used for this tool must all contain the same value. Shrink fied number of cells by replacing them with the value of the Weighted Sum This is a common tool that is used to combine various objective and sub objectives in the suitability analyses of this project. It allows for each data set to be given a deferent weight that totals to 100%. This tool only functions with at least two raster data sets.

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140 | Page Zonal Statistics This tool creates a raster data set that reflects the statistics of the input data sets. It can provide the mean, majority, maximum, median, minimum, minority, range, standard deviation (STD), sum, or variety statistics for the input data. Zonal Statistics as a Table This tool was usefu l for determining the means and STD of various data sets during the suitability analysis of the Farmton plan. This tool works with both raster data and vector data and only returns an attribute table. Conversion Tools Conversion tools are needed when a pa rticular tool requires a different type of data. Typically these tools were used to create raster version of existing data to use in the suitability analyses in the second half of this project. Feature to Point generated from the representative locations of input This tools allow vector data to be converted to a point shape file. Point shape files can be more useful for some GIS analyses. Points, lines, and polygons may be converted into points, altho ugh this tool functions better with polygons. Feature to Raster This tool allows vector data to be converted into raster data. There will be a loss in accuracy during this conversion. The tool will allow the use r to select the output size and which attribute field to convert. This tool was often used during the suitability analyses. Raster to Polygon This tool simply converts raster data into vector data. The output feature will be a polygon. This tool was rarely used but it is sometimes necessary to convert raster data to vector data.

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141 | Page GIS Sources and Descriptions Display Data File Name Layer Description Source Date Created cntbnd_jul11 County Boundaries FGDL.org Jul 11 majrds_oct14 Major Roads FGDL.org Oct 14 majhwys_oct14 Major Highways FGDL.org Oct 14 Fl_Water_Clip Waterbodies FGDL.org Jun 08 mjrivp Waterbodies FGDL.org Jul 99 Master Plan Data File Name Layer Name Source Date Created Farmton_plan Farmton Land Use Plan Tom Hoctor Unknown Plum_Agric_LU Plum Creek Agriculture ARC GIS online Jul 14 Plum_Conserv Plum Creek Conservation ARC GIS online Jul 14 Plum_Poten_Con Plum Creek Potiential Conservation ARC GIS online Jul 14 Plum_Prop Plum Creek Property Boundaries ARC GIS online Jul 14 Plum_Rural_LU Plum Creek Rural Land Use ARC GIS online Jul 14 Plum_Urban_LU Plum Creek Urban Land Use ARC GIS online Jul 14 2007_Sector_Plan West Bay Sector Plan Bay County Unknown land_use_2006_Restoration 2006 Restoration Land Use Plan Canin Unknown land_use_2009_Restoration 2009 Restoration Land Use Plan Canin Unknown Generic Data File Name Layer Name Source Date Created CLC_v3_Poly CLC_v3_Poly FWC.com Oct 14 Agriculture Data File Name Layer Name Source Date Created forstry_v4 Sustainable Forestry FNAI.org Dec 14 public_pinelands_mar13 Public Pinelands FGDL.org Mar 13

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142 | Page Conservation Data File Name Layer Name Source Date Created flma_201412 Fl. Managed Lands FNAI.org Dec 14 ffbot_201408 Proposed Conservation Lands FNAI.org Aug 14 recharge_v4 Aquifer Recharge FNAI.org Dec 14 fr_rch_v4 Forestry for Recharge FNAI.org Dec 14 surfwatr_v4 Significant Surface Waters FNAI.org Dec 14 wetlands_v4 Functional Wetlands FNAI.org Dec 14 grnway_v4 Green Way FNAI.org Dec 14 shca_ff_v4 Strategic Habitat Conservation Areas FNAI.org Dec 14 fnaihab_v4 Rare Species Habitat Conservation Priorities FNAI.org Dec 14 natcom_v4 Under represented Ecosystems FNAI.org Dec 14 floodpl_v4 Natural Flood Plain Function FNAI.org Dec 14 coast_v4 Fragile Coastal Resources FNAI.org Dec 14 biodivrp_clp3 CLIP Biodiversity Priorities FNAI.org Feb 14 clip_prio_v3 CLIP Priorities FNAI.org Feb 14 lndscprp_clp3 CLIP Landscape Priorities FNAI.org Feb 14 srfwtrrp_clp3 Surface Water Resource Priorities FNAI.org Feb 14 phrich_clip3 Potential Habitat Richness FNAI.org Clip 2.0 lsinteg_clip3 Landscape Integrity Index FNAI.org Feb 14 natcom_clip3 Priority Natural Communities FNAI.org Feb 14 wetlnd_habitat_volusia Wetlands Located in Volusia SJRWMD.com 2003 welnd_habitat_brevard Wetlands Located in Brevard SJRWMD.com 2003 mitigation_banks Mitigation Bank Boundaries Florida DEP Oct 14 concorridor Volusia Conservation Corridor Volusia.org 2007 Urban Data File Name Layer Name Source Date Created developed2004 Developed Lands FNAI.org 2004 nrcs_soils_jun12 NRCS Soils FGDL.org Jun 12 pwsab Public Water Service Area Boundaries SJRWMD.com Feb 06 dfirm_fldhaz_mar14 Flood Hazards and Floodplains FGDL.org Mar 12 existing_trails_jul12 Existing Trail Networks FGDL.org Jul 12 gc_hospitals_feb13 Hosptial Locations FGDL.org Feb 13 gc_parks_aug14 Park Locations FGDL.org Aug 14 gc_schools_may12 School Locations FGDL.org May 12 par_citylm_2011 City Limits FGDL.org 2011 parcels_2014 Parcel Data FGDL.org 2014 stpark_may11 State Parks FGDL.org May 11 rails_transtat_2014 Rail Locations FGDL.org 2014

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143 | Page Appendix B This section contains the full break down of all the data that was collected during the case study analysis. The formatting will be the same as in chapter 4. This a ppendix will be broken into two parts. Part one will contain the data for the context area data of the case studies. Part II will contain the development area data from the case studies. Part I: Case Study Context Data Agriculture Impacts A 1 : Patch Size Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 5,368 5,727 359 6.7% 4,444 4,751 307 6.9% Maximum Patch Size Acres 10,927 10,927 0 0.0% 2,217 2,217 0 0.0% Average Pa tch Size Acres 50 44 5 10.3% 37 30 7 18.6% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 1,072 1,492 420 39.2% 1,072 1,232 160 14.9% Maximum Patch Size Acres 3,616 3,362 254 7.0% 3,616 3,362 254 7.0% Average Pa tch Size Acres 43 30 13 30.7% 43 37 6 14.2% Farmton Units Pre Post Change Percent Number of Patches Number 1,915 2,271 356 18.6% Maximum Patch Size Acres 3,617 3,131 486 13.4% Average Patch Size Acres 38 27 11 28.2%

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144 | Page A 2 : Agriculture Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture Acres 27,504 27,483 21 0.1% 731 731 0 0.0% 183313: Im proved Pasture Acres 61,786 61,723 63 0.1% 1,575 1,564 11 0.7% 18333: Tree Plantations Acres 161,965 150,686 11,279 7.0% 160,966 139,650 21,316 13.2% Pub lic Timber Acres 39,221 39,220 1 0.0% 47,208 47,045 163 0.3% Sustainable Timber (Totals) Acres 291,285 279,396 11,889 4.1% 272,183 243,670 28,513 10.5% Pri ority 1 Acres 2,064 2,064 0 0.0% 56,970 43,663 13,307 23.4% Priority 2 Acres 96,030 86,324 9,706 10.1% 107,948 102,278 5,670 5.3% Pri ority 3 Acres 131,120 129,083 2,037 1.6% 94,097 84,799 9,298 9.9% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Pri ority 5 Acres 62,071 61,925 146 0.2% 13,168 12,930 238 1.8% Specialty (Totals) Acres 14,760 14,760 0 0.0% 1,447 1,429 18 1.2% 183 32: Orchards/Groves Acres 2,396 2,396 0 0.0% 24 24 0 0.0% 18334: Nurseries Acres 1,264 1,264 0 0.0% 1,176 1,176 0 0.0% 183 35: Other Agriculture Acres 11,100 11,100 0 0.0% 247 229 18 7.3% TOTALS Acres 596,521 573,268 23,253 3.9% 484,110 434,089 50,021 10.3% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture Acres 497 497 0 0.0% 497 497 0 0.0% 183313: Im proved Pasture Acres 10,021 10,021 0 0.0% 10,021 10,021 0 0.0% 18333: Tree Plantations Acres 31,171 29,583 1,588 5.1% 31,171 30,553 618 2.0% Pub lic Timber Acres 11,323 11,323 0 0.0% 11,323 11,323 0 0.0% Sustainable Timber (Totals) Acres 81,282 79,345 1,937 2.4% 81,282 80,323 959 1.2% Pri ority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 4,047 4,047 0 0.0% 4,047 4,047 0 0.0% Pri ority 3 Acres 58,204 56,267 1,937 3.3% 58,204 57,245 959 1.6% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Pri ority 5 Acres 19,031 19,031 0 0.0% 19,031 19,031 0 0.0% Specialty (Totals) Acres 4,217 4,217 0 0.0% 4,217 4,217 0 0.0% 183 32: Orchards/Groves Acres 686 686 0 0.0% 686 686 0 0.0% 18334: Nurseries Acres 2,667 2,667 0 0.0% 2,667 2,667 0 0.0% 183 35: Other Agriculture Acres 864 864 0 0.0% 864 864 0 0.0% TOTALS Acres 138,511 134,986 3,525 2.5% 138,511 136,934 1,577 1.1%

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145 | Page Farmton Units Pre Post Change Percent 18331: Cropland/Pasture Acres 1,327 1,327 0 0.0% 183313: Improved Pasture Acres 23,702 23,700 2 0.0% 18333: Tree Plantations Acres 36,953 26,213 10,740 29.1% Public Timber Acres 15,496 15,485 11 0.1% Sustainable Timber (Totals) Acres 135,501 121,647 13,854 10.2% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 15,652 11,995 3,657 23.4% Priority 3 Acres 80,951 70,847 10,104 12.5% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 38,898 38,805 93 0.2% Specialty (Totals) Acres 10,239 10,239 0 0.0% 18332: Orchards/Groves Acres 5,216 5,216 0 0.0% 18334: Nurseries Acres 3,455 3,455 0 0.0% 18335: Other Agriculture Acres 1,568 1,568 0 0.0% TOTALS Acres 223,218 198,611 24,607 11.0% Conservation Impacts B 1 : Fragmentation Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Total Cell s Acres 764,851 764,851 0 N/A 446,227 446,280 53 N/A Developed Cells Acres 278,368 287,408 9,040 3.2% 122,333 143,969 21,636 17.7% Intact Cel ls Acres 486,483 477,443 9,040 1.9% 323,894 302,311 21,583 6.7% Percentage (100 meters) N/A 64% 62% 0 1.9% 73% 68% 0 6.7% Total Cell s Acres 764,863 764,862 1 N/A 475,104 475,127 23 N/A Developed Cells Acres 239,503 252,754 13,251 5.5% 106,716 135,052 28,336 26.6% Intact Cel ls Acres 525,360 512,108 13,252 2.5% 368,388 340,075 28,313 7.7% Percentage (1,000 meters) N/A 69% 67% 0 2.5% 78% 72% 0 7.7% Total Cell s Acres 764,867 764,867 0 N/A 558,368 558,368 0 N/A Developed Cells Acres 131,702 166,848 35,146 26.7% 91,175 123,789 32,614 35.8% Intact Cel ls Acres 633,165 598,019 35,146 5.6% 467,193 434,579 32,614 7.0% Percentage (10,000 meters) N/A 83% 78% 0 5.6% 84% 78% 0 7.0% Intact Lan d Totals Acres 486,680 476,014 10,666 2.2% 316,971 291,023 25,948 8.2% 75 Acres Number 2,103 2,272 169 8.0% 662 654 8 1.2% 250 Acres Number 41 45 4 9.8% 19 19 0 0.0% 500 Acres Number 7 8 1 14.3% 0 1 1 N/A 1,000 Acre s Number 4 4 0 0.0% 2 3 1 50.0% 10,000 Acres Number 7 8 1 14.3% 4 7 3 75.0% Above 10,0 00 Acres Number 2 2 0 0.0% 4 3 1 25.0%

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146 | Page Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Total Cell s Acres 233,500 233,501 1 N/A 233,500 233,501 1 N/A Developed Cells Acres 72,289 74,622 2,333 3.2% 72,289 73,635 1,346 1.9% Intact Cel ls Acres 161,211 158,879 2,332 1.4% 161,211 159,866 1,345 0.8% Percentage (100 meters) N/A 69% 68% 0 1.4% 69% 68% 0 0.8% Total Cell s Acres 256,308 256,289 19 N/A 256,289 256,309 20 N/A Developed Cells Acres 76,716 78,963 2,247 2.9% 78,963 78,301 662 0.8% Intact Cel ls Acres 179,592 177,326 2,266 1.3% 177,326 178,008 682 0.4% Percentage (1,000 meters) N/A 70% 69% 0 1.3% 69% 69% 0 0.4% Total Cell s Acres 284,738 284,738 0 N/A 284,738 284,737 1 N/A Developed Cells Acres 79,243 80,790 1,547 2.0% 79,243 80,443 1,200 1.5% Intact Cel ls Acres 205,495 203,948 1,547 0.8% 205,495 204,294 1,201 0.6% Percentage (10,000 meters) N/A 72% 72% 0 0.8% 72% 72% 0 0.6% Intact Lan d Totals Acres 158,128 155,794 2,334 1.5% 158,128 156,802 1,326 0.8% 75 Acres Number 1,076 1,090 14 1.3% 1,076 1,321 245 22.8% 250 Acres Number 6 6 0 0.0% 6 7 1 16.7% 500 Acres Number 4 4 0 0.0% 4 4 0 0.0% 1,000 Acre s Number 0 0 0 0.0% 0 0 0 0.0% 10,000 Acres Number 3 3 0 0.0% 3 3 0 0.0% Above 10,0 00 Acres Number 3 3 0 0.0% 3 3 0 0.0% Farmton Units Pre Post Change Percent Total Cells Acres 482,902 482,902 0 N/A Developed Cells Acres 144,801 161,976 17,175 11.9% Intact Cells Acres 338,101 320,926 17,175 5.1% Percentage (100 meters) N/A 70% 66% 0 5.1% Total Cells Acres 524,201 524,201 0 N/A Developed Cells Acres 150,773 169,398 18,625 12.4% Intact Cells Acres 373,428 354,803 18,625 5.0% Percentage (1,000 meters) N/A 71% 68% 0 5.0% Total Cells Acres 573,562 573,561 1 N/A Developed Cells Acres 102,548 105,779 3,231 3.2% Intact Cells Acres 471,014 467,782 3,232 0.7% Percentage (10,000 meters) N/A 82% 82% 0 0.7% Intact Land Totals Acres 330,529 313,331 17,198 5.2% 75 Acres Number 2,336 2,411 75 3.2% 250 Acres Number 31 31 0 0.0% 500 Acres Number 6 6 0 0.0% 1,000 Acres Number 2 2 0 0.0% 10,000 Acres Number 8 8 0 0.0% Above 10,000 Acres Number 3 3 0 0.0%

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147 | Page B 2 : Habitat Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 66,920 66,833 87 0.1% 16,352 16,342 10 0.1% Natural Co mmunities Acres 100,119 99,773 346 0.3% 56,448 56,007 441 0.8% Strategic Habitats Acres 355,223 345,762 9,461 2.7% 235,959 213,227 22,732 9.6% Pri ority 1 Acres 0 0 0 0.0% 631 631 0 0.0% Priority 2 Acres 150,405 150,354 51 0.0% 179,623 159,051 20,572 11.5% Pri ority 3 Acres 163,244 153,924 9,320 5.7% 36,447 35,059 1,388 3.8% Priority 4 Acres 2,010 2,010 0 0.0% 6,709 6,634 75 1.1% Pri ority 5 Acres 39,564 39,474 90 0.2% 12,549 11,852 697 5.6% Coastal Resources Acres 0 0 0 0.0% 9,528 9,397 131 1.4% Bio diversity Acres 663,760 649,981 13,779 2.1% 379,091 346,588 32,503 8.6% Priority 1 Acres 49,397 49,397 0 0.0% 52,297 52,234 63 0.1% Pri ority 2 Acres 159,092 156,539 2,553 1.6% 181,466 160,768 20,698 11.4% Priority 3 Acres 227,900 219,227 8,673 3.8% 37,343 35,756 1,587 4.2% Pri ority 4 Acres 177,076 174,860 2,216 1.3% 85,687 76,498 9,189 10.7% Priority 5 Acres 50,295 49,958 337 0.7% 22,298 21,332 966 4.3% TOT ALS Acres 1,186,022 1,162,349 23,673 2.0% 697,378 641,561 55,817 8.0% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 51,890 51,890 0 0.0% 51,890 51,890 0 0.0% Natural Communities Acres 41,463 41,268 195 0.5% 41,463 41,318 145 0.3% Strategic Habitats Acres 147,764 145,713 2,051 1.4% 147,764 146,709 1,055 0.7% Priority 1 Acres 9,989 9,989 0 0.0% 9,989 9,989 0 0.0% Priority 2 Acres 92,616 90,851 1,765 1.9% 92,616 91,927 689 0.7% Priority 3 Acres 33,599 33,313 286 0.9% 33,599 33,233 366 1.1% Priority 4 Acres 80 80 0 0.0% 80 80 0 0.0% Priority 5 Acres 11,480 11,480 0 0.0% 11,480 11,480 0 0.0% Coastal Resources Acres 14,016 14,016 0 0.0% 14,066 14,066 0 0.0% Biodiversity Acres 211,629 209,251 2,378 1.1% 211,629 210,270 1,359 0.6% Priority 1 Acres 26,402 26,402 0 0.0% 26,402 26,402 0 0.0% Priority 2 Acres 97,601 95,709 1,892 1.9% 97,601 96,777 824 0.8% Priority 3 Acres 45,878 45,449 429 0.9% 45,878 45,421 457 1.0% Priority 4 Acres 35,341 35,284 57 0.2% 35,341 35,264 77 0.2% Priority 5 Acres 6,407 6,407 0 0.0% 6,407 6,406 1 0.0% TOTALS Acres 466,762 462,138 4,624 1.0% 466,812 464,253 2,559 0.5%

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148 | Page Farmton Units Pre Post Change Percent Proposed Conservation Acres 24,905 24,099 806 3.2% Natural Communities Acres 82,919 81,629 1,290 1.6% Strategic Habitats Acres 297,155 283,022 14,133 4.8% Priority 1 Acres 9,752 9,752 0 0.0% Priority 2 Acres 193,597 181,769 11,828 6.1% Priority 3 Acres 70,699 68,394 2,305 3.3% Priority 4 Acres 343 343 0 0.0% Priority 5 Acres 22,764 22,764 0 0.0% Coastal Resources Acres 22,071 22,071 0 0.0% Biodiversity Acres 436,142 417,758 18,384 4.2% Priority 1 Acres 37,620 37,620 0 0.0% Priority 2 Acres 207,441 194,753 12,688 6.1% Priority 3 Acres 100,858 95,409 5,449 5.4% Priority 4 Acres 74,892 74,648 244 0.3% Priority 5 Acres 15,331 15,328 3 0.0% TOTALS Acres 863,192 828,579 34,613 4.0% B 3 : Edge Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 214,903 214,801 102 0.0% 137,485 131,908 5,577 4.1% Edge 300 m eters Acres 418,689 415,228 3,461 0.8% 282,910 265,433 17,477 6.2% Edge and Urban 100 meters Acres 353,864 367,639 13,775 3.9% 221,367 246,379 25,012 11.3% Edg e and Urban 300 meters Acres 557,650 568,066 10,416 1.9% 366,792 379,905 13,113 3.6% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 54,892 55,980 1,088 2.0% 54,892 54,820 72 0.1% E dge 300 meters Acres 110,581 111,804 1,223 1.1% 110,581 109,942 639 0.6% Edge and Urban 100 meters Acres 105,479 108,852 3,373 3.2% 105,479 160,652 55,173 52.3% Edg e and Urban 300 meters Acres 161,168 164,676 3,508 2.2% 161,168 161,774 606 0.4% Farmton Units Pre Post Change Percent Edge 100 meters Acres 111,064 111,670 606 0.5% Edge 300 meters Acres 217,672 217,000 672 0.3% Edge and Urban 100 meters Acres 202,358 220,105 17,747 8.8% Edge and Urban 300 meters Acres 308,966 325,436 16,470 5.3%

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149 | Page B 4 : Connectivity Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 412,653 401,534 11,119 2.7% 316,922 288,481 28,441 9.0% Priority 1 Acres 2,689 2,689 0 0.0% 157,403 157,403 0 0.0% Priority 2 Acres 8,943 8,943 0 0.0% 55,342 50,087 5,255 9.5% Priority 3 Acres 222,580 211,461 11,119 5.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 72,385 72,385 0 0.0% 0 0 0 0.0% Priority 6 Acres 106,056 106,056 0 0.0% 104,177 80,991 23,186 22.3% Landscape (Totals) Acres 566,821 552,797 14,024 2.5% 384,637 350,312 34,325 8.9% Priority 1 Acres 2,690 2,690 0 0.0% 156,345 156,345 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 269,816 258,704 11,112 4.1% 72,173 66,338 5,835 8.1% Priority 4 Acres 266,673 265,695 978 0.4% 148,371 121,492 26,879 18.1% Priority 5 Acres 27,642 25,708 1,934 7.0% 7,748 6,137 1,611 20.8% TOTALS Acres 979,474 954,331 25,143 2.6% 701,559 638,793 62,766 8.9% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 194,616 192,459 2,157 1.1% 194,616 193,537 1,079 0.6% Priority 1 Acres 95,716 95,716 0 0.0% 95,716 95,716 0 0.0% Priority 2 Acres 73,880 71,723 2,157 2.9% 73,880 72,801 1,079 1.5% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 3,743 3,743 0 0.0% 3,743 3,743 0 0.0% Priority 6 Acres 21,277 21,277 0 0.0% 21,277 21,277 0 0.0% Landscape (Totals) Acres 205,780 203,400 2,380 1.2% 205,780 204,421 1,359 0.7% Priority 1 Acres 95,009 95,009 0 0.0% 95,009 95,009 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 72,603 70,480 2,123 2.9% 72,603 71,551 1,052 1.4% Priority 4 Acres 31,714 31,457 257 0.8% 31,714 31,407 307 1.0% Priority 5 Acres 6,454 6,454 0 0.0% 6,454 6,454 0 0.0% TOTALS Acres 400,396 395,859 4,537 1.1% 400,396 397,958 2,438 0.6%

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150 | Page Farmton Units Pre Post Change Percent FEGN (Totals) Acres 392,316 374,228 18,088 4.6% Priority 1 Acres 180,664 163,081 17,583 9.7% Priority 2 Acres 153,763 153,258 505 0.3% Priority 3 Acres 2,470 2,470 0 0.0% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 3,605 3,605 0 0.0% Priority 6 Acres 51,814 51,814 0 0.0% Landscape (Totals) Acres 437,866 419,471 18,395 4.2% Priority 1 Acres 179,787 162,250 17,537 9.8% Priority 2 Acres 0 0 0 0.0% Priority 3 Acres 166,225 165,715 510 0.3% Priority 4 Acres 80,317 79,969 348 0.4% Priority 5 Acres 11,537 11,537 0 0.0% TOTALS Acres 830,182 793,699 36,483 4.4% B 5 : Water Management Land Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands (Totals) Acres 173,133 170,711 2,422 1.4% 141,938 133,695 8,243 5.8% Priority 1 Acres 38,341 38,341 0 0.0% 23,912 23,912 0 0.0% Pri ority 2 Acres 38,909 38,885 24 0.1% 18,317 18,116 201 1.1% Pri ority 3 Acres 51,023 50,327 696 1.4% 45,822 43,244 2,578 5.6% Priority 4 Acres 38,149 36,463 1,686 4.4% 48,065 42,632 5,433 11.3% Pri ority 5 Acres 3,697 3,681 16 0.4% 2,479 2,448 31 1.3% Priority 6 Acres 3,014 3,014 0 0.0% 3,343 3,343 0 0.0% Aqu ifer Recharge (Totals) Acres 733,892 719,845 14,047 1.9% 420,426 385,877 34,549 8.2% Priority 1 Acres 23,307 23,307 0 0.0% 2,384 2,313 71 3.0% Pri ority 2 Acres 80,906 80,730 176 0.2% 29,171 28,538 633 2.2% Priority 3 Acres 270,764 260,991 9,773 3.6% 84,913 81,294 3,619 4.3% Pri ority 4 Acres 210,296 206,484 3,812 1.8% 108,577 100,427 8,150 7.5% Priority 5 Acres 148,326 148,040 286 0.2% 113,601 101,857 11,744 10.3% Pri ority 6 Acres 293 293 0 0.0% 81,780 71,448 10,332 12.6% Surface Waters (Totals) Acres 694,760 680,721 14,039 2.0% 390,483 356,121 34,362 8.8% Pri ority 1 Acres 20,618 20,618 0 0.0% 19,451 18,794 657 3.4% Priority 2 Acres 78,043 77,341 702 0.9% 128,671 115,594 13,077 10.2% Pri ority 3 Acres 26,918 26,877 41 0.2% 39,753 33,294 6,459 16.2% Priority 4 Acres 250,241 244,615 5,626 2.2% 174,752 160,812 13,940 8.0% Pri ority 5 Acres 37,699 37,521 178 0.5% 5,297 5,297 0 0.0% Priority 6 Acres 173,889 168,975 4,914 2.8% 17,913 17,684 229 1.3% Priority 7 Acres 107,352 104,774 2,578 2.4% 4,646 4,646 0 0.0% Nat ural Floodplains (Totals) Acres 260,071 256,343 3,728 1.4% 184,604 169,333 15,271 8.3% Priority 1 Acres 42,467 42,467 0 0.0% 24,886 24,885 1 0.0% Pri ority 2 Acres 47,905 47,871 34 0.1% 19,932 19,621 311 1.6% Priority 3 Acres 69,170 68,494 676 1.0% 51,707 48,715 2,992 5.8% Pri ority 4 Acres 84,825 81,845 2,980 3.5% 79,021 67,134 11,887 15.0% Priority 5 Acres 9,732 9,694 38 0.4% 4,222 4,144 78 1.8% Pri ority 6 Acres 5,972 5,972 0 0.0% 4,836 4,834 2 0.0% TOTALS Acres 1,861,856 1,827,620 34,236 1.8% 1,137,451 1,045,026 92,425 8.1%

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151 | Page Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands (Totals) Acres 92,525 92,060 465 0.5% 92,525 92,119 406 0.4% Priority 1 Acres 27,042 27,042 0 0.0% 27,042 27,042 0 0.0% Priority 2 Acres 30,366 30,346 20 0.1% 30,366 30,358 8 0.0% Pri ority 3 Acres 20,128 19,983 145 0.7% 20,128 20,033 95 0.5% Priority 4 Acres 12,387 12,088 299 2.4% 12,387 12,087 300 2.4% Pri ority 5 Acres 1,370 1,369 1 0.1% 1,370 1,367 3 0.2% Priority 6 Acres 1,232 1,232 0 0.0% 1,232 1,232 0 0.0% Aqu ifer Recharge (Totals) Acres 227,314 224,934 2,380 1.0% 227,314 225,955 1,359 0.6% Priority 1 Acres 3,446 3,446 0 0.0% 3,446 3,446 0 0.0% Pri ority 2 Acres 15,948 15,910 38 0.2% 15,948 15,902 46 0.3% Priority 3 Acres 49,885 49,735 150 0.3% 49,885 49,696 189 0.4% Pri ority 4 Acres 62,138 61,529 609 1.0% 62,138 61,460 678 1.1% Priority 5 Acres 51,687 51,245 442 0.9% 51,687 51,244 443 0.9% Pri ority 6 Acres 44,210 43,069 1,141 2.6% 44,210 44,207 3 0.0% Surface Waters (Totals) Acres 209,602 207,223 2,379 1.1% 209,602 208,244 1,358 0.6% Pri ority 1 Acres 9,290 9,290 0 0.0% 9,290 9,290 0 0.0% Priority 2 Acres 9,388 9,388 0 0.0% 9,388 9,388 0 0.0% Pri ority 3 Acres 12,903 12,903 0 0.0% 12,903 12,903 0 0.0% Priority 4 Acres 37,317 37,317 0 0.0% 37,317 37,317 0 0.0% Pri ority 5 Acres 14,025 14,025 0 0.0% 14,025 14,025 0 0.0% Priority 6 Acres 57,862 57,129 733 1.3% 57,862 57,588 274 0.5% Priority 7 Acres 68,817 67,171 1,646 2.4% 68,817 67,733 1,084 1.6% Nat ural Floodplains (Totals) Acres 118,432 117,479 953 0.8% 118,432 117,748 684 0.6% Priority 1 Acres 24,951 24,951 0 0.0% 24,951 24,951 0 0.0% Pri ority 2 Acres 37,248 37,226 22 0.1% 37,248 37,242 6 0.0% Priority 3 Acres 26,523 26,298 225 0.8% 26,523 26,376 147 0.6% Pri ority 4 Acres 22,418 21,712 706 3.1% 22,418 21,889 529 2.4% Priority 5 Acres 3,550 3,550 0 0.0% 3,550 3,548 2 0.1% Pri ority 6 Acres 3,742 3,742 0 0.0% 3,742 3,742 0 0.0% TOTALS Acres 647,873 641,696 6,177 1.0% 647,873 644,066 3,807 0.6%

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152 | Page Farmton Units Pre Post Change Percent Functional Wetlands (Totals) Acres 208,130 203,586 4,544 2.2% Priority 1 Acres 92,449 92,337 112 0.1% Priority 2 Acres 53,129 52,602 527 1.0% Priority 3 Acres 34,939 33,843 1,096 3.1% Priority 4 Acres 21,904 19,104 2,800 12.8% Priority 5 Acres 3,317 3,308 9 0.3% Priority 6 Acres 2,392 2,392 0 0.0% Aquifer Recharge (Totals) Acres 451,754 433,358 18,396 4.1% Priority 1 Acres 22,149 22,149 0 0.0% Priority 2 Acres 38,726 38,359 367 0.9% Priority 3 Acres 90,288 84,934 5,354 5.9% Priority 4 Acres 111,191 104,168 7,023 6.3% Priority 5 Acres 96,588 93,964 2,624 2.7% Priority 6 Acres 92,812 89,784 3,028 3.3% Surface Waters (Totals) Acres 428,794 410,400 18,394 4.3% Priority 1 Acres 17,631 17,631 0 0.0% Priority 2 Acres 73,123 73,123 0 0.0% Priority 3 Acres 17,866 17,866 0 0.0% Priority 4 Acres 126,214 125,908 306 0.2% Priority 5 Acres 18,310 18,076 234 1.3% Priority 6 Acres 99,170 89,151 10,019 10.1% Priority 7 Acres 76,480 68,645 7,835 10.2% Natural Floodplains (Totals) Acres 233,300 223,954 9,346 4.0% Priority 1 Acres 91,745 91,575 170 0.2% Priority 2 Acres 56,956 56,272 684 1.2% Priority 3 Acres 39,676 37,902 1,774 4.5% Priority 4 Acres 32,806 26,101 6,705 20.4% Priority 5 Acres 6,592 6,579 13 0.2% Priority 6 Acres 5,525 5,525 0 0.0% TOTALS Acres 1,321,978 1,271,298 50,680 3.8%

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153 | Page Urban Impacts C 1: Urban Patch Size Impacts Plum Creek West Bay Sector Plan Units Pre Post Chang e Percent Pre Post Chang e Percen t Number of Patches Number 4,892 4,839 53 1.1% 3,152 2,898 254 8.1% Maximum Pa tch Size Acres 23,336 23,336 0 0.0% 20,773 33,292 12,519 60.3% Average Patch Size Acres 24 26 3 11.3% 20 31 11 53.7% Restoration 2006 Restoration 2009 Units Pre Post Chang e Percent Pre Post Chang e Percen t Number of Patches Number 1,808 1,808 0 0.0% 1,808 1,796 12 0.7% Maximum Pa tch Size Acres 7,723 7,723 0 0.0% 7,723 7,723 0 0.0% Average Patch Size Acres 25 26 1 4.9% 25 26 1 3.4% Farmton Units Pre Post Chang e Percent Number of Patches Number 4,667 4,591 76 1.6% Maximum Patch Size Acres 9,583 9,583 0 0.0% Average Patch Size Acres 17 21 4 23.4% C 2 : Urban Proximity Impacts Plum Creek West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Urban Proximity (Mean) Meters 3,046 3,536 490 16.1% 4,995 5,745 751 15.0% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Urban Proximity (Mean) Meters 1,609 1,538 71 4.4% 1,609 1,570 39 2.4% Farmton Units Pre Post Change Percent Urban Proximity (Mean) Meters 2,850 4,031 1,181 41.5%

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154 | Page Part II: Case Study Development Data Agriculture Impacts A 1 : Agriculture Patch Size Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 184 175 9 4.9% 623 727 104 16.7% Maximum Patch Size Acres 5,298 2,677 2,621 49.5% 1,599 736 863 54.0% Average Patch Size Acres 134 86 48 35.7% 51 21 30 58.8% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 47 472 425 904.3% 47 72 25 53.2% Maximum Patch Size Acres 1,358 161 1,197 88.1% 1,358 1,358 0 0.0% Average Patch Size Acres 50 2 49 96.8% 50 24 26 51.9% Farmton Units Pre Post Change Percent Number of Patches Number 240 240 0 0.0% Maximum Patch Size Acres 3,041 557 2,484 81.7% Average Patch Size Acres 71 26 45 63.4% A 2 : Agriculture Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture Acres 28 7 21 75.0% 0 0 0 0.0% 183313: Improved Pasture Acres 75 12 63 84.0% 11 0 11 100.0% 18333: Tree Plantations Acres 24,517 13,238 11,279 46.0% 32,049 10,733 21,316 66.5% Public Timber (Totals) Acres 19 18 1 5.3% 7,110 6,947 163 2.3% Sustainable Timber (Totals) Acres 26,571 14,682 11,889 44.7% 53,932 25,419 28,513 52.9% Priority 1 Acres 0 0 0 0.0% 19,894 6,587 13,307 66.9% Priority 2 Acres 20,500 10,794 9,706 47.3% 8,994 3,324 5,670 63.0% Priority 3 Acres 5,876 3,839 2,037 34.7% 24,690 15,392 9,298 37.7% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 195 49 146 74.9% 354 116 238 67.2% Specialty (Totals) Acres 0 0 0 0.0% 17 0 17 100.0% 18332: Orchards/Groves Acres 0 0 0 0.0% 0 0 0 0.0% 18334: Nurseries Acres 0 0 0 0.0% 0 0 0 0.0% 18335: Other Agriculture Acres 0 0 0 0.0% 17 0 17 100.0% TOTALS Acres 51,210 27,957 23,253 45.4% 93,119 43,099 50,020 53.7%

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155 | Page Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent 18331: Cro pland/Pasture Acres 0 0 0 0.0% 0 0 0 0.0% 183313: Improved Pasture Acres 0 0 0 0.0% 0 0 0 0.0% 18333: Tre e Plantations Acres 2,369 781 1,588 67.0% 2,369 1,751 618 26.1% Public Timber (Totals) Acres 0 0 0 0.0% 0 0 0 0.0% Sustainabl e Timber (Totals) Acres 2,950 1,013 1,937 65.7% 2,950 1,991 959 32.5% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 2,950 1,013 1,937 65.7% 2,950 1,991 959 32.5% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Specialty (Totals) Acres 0 0 0 0.0% 0 0 0 0.0% 18332: Orc hards/Groves Acres 0 0 0 0.0% 0 0 0 0.0% 18334: Nurseries Acres 0 0 0 0.0% 0 0 0 0.0% 18335: Oth er Agriculture Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 5,319 1,794 3,525 66.3% 5,319 3,742 1,577 29.6% Farmton Units Pre Post Change Percent 18331: Cropland/Pasture Acres 0 0 0 0.0% 183313: Improved Pasture Acres 20 18 2 10.0% 18333: Tree Plantations Acres 16,930 6,190 10,740 63.4% Public Timber (Totals) Acres 18 7 11 61.1% Sustainable Timber (Totals) Acres 22,416 8,562 13,854 61.8% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 7,089 3,432 3,657 51.6% Priority 3 Acres 15,077 4,973 10,104 67.0% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 250 157 93 37.2% Specialty (Totals) Acres 1 1 0 0.0% 18332: Orchards/Groves Acres 1 1 0 0.0% 18334: Nurseries Acres 0 0 0 0.0% 18335: Other Agriculture Acres 0 0 0 0.0% TOTALS Acres 39,385 14,778 24,607 62.5%

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156 | Page Conservation Impacts B 1 : Fragmentation Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 37,271 37,271 0 0.0% 71,826 71,860 34 0.0% Dev eloped Cells Acres 6,767 15,657 8,890 131.4% 12,432 33,993 21,561 173.4% Intact Cells Acres 30,504 21,614 8,890 29.1% 59,394 37,867 21,527 36.2% Percentage (100 meters) N/A 82% 58% 0 29.1% 83% 53% 0 36.3% Total Cells Acres 37,270 37,271 1 0.0% 74,238 74,239 1 0.0% Developed Cells Acres 4,001 14,667 10,666 266.6% 6,891 33,599 26,708 387.6% Intact Cells Acres 33,269 22,604 10,665 32.1% 67,347 40,640 26,707 39.7% Percentage (1,000 meters) N/A 89% 61% 0 32.1% 91% 55% 0 39.7% Total Cells Acres 37,271 37,270 1 0.0% 74,240 74,240 0 0.0% Developed Cells Acres 0 12,862 12,862 N/A 2 18,085 18,083 904150.0% Intact Cells Acres 37,271 24,408 12,863 34.5% 74,238 56,155 18,083 24.4% Percentage (10,000 meters) N/A 100% 65% 0 34.5% 100% 76% 0 24.4% Intact Land Totals Acres 30,496 19,876 10,620 34.8% 57,057 31,159 25,898 45.4% 75 Acres Number 168 106 62 36.9% 205 282 77 37.6% 250 Acres Number 8 9 1 12.5% 0 2 2 N/A 500 Acres Number 2 1 1 50.0% 0 1 1 N/A 1,000 Acres Number 5 5 0 0.0% 0 1 1 N/A 10,000 Acres Number 7 5 2 28.6% 3 2 1 33.3% Above 10,000 Acres Number 0 0 0 0.0% 1 1 0 0.0% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 5,183 5,183 0 0.0% 5,183 5,183 0 0.0% Dev eloped Cells Acres 86 2,407 2,321 2698.8% 86 1,408 1,322 1537.2% Intact Cells Acres 5,097 2,776 2,321 45.5% 5,097 3,775 1,322 25.9% Percentage (100 meters) N/A 98% 54% 0 45.5% 98% 73% 0 25.9% Total Cells Acres 5,183 5,183 0 0.0% 5,183 5,183 0 0.0% Developed Cells Acres 0 2,059 2,059 N/A 0 1,266 1,266 N/A Intact Cells Acres 5,183 3,124 2,059 39.7% 5,183 3,917 1,266 24.4% Percentage (1,000 meters) N/A 100% 60% 0 39.7% 100% 76% 0 24.4% Total Cells Acres 5,183 5,183 0 0.0% 5,183 5,183 0 0.0% Developed Cells Acres 0 0 0 0.0% 0 0 0 0.0% Intact Cells Acres 5,183 5,183 0 0.0% 5,183 5,183 0 0.0% Percentage (10,000 meters) N/A 100% 100% 0 0.0% 100% 100% 0 0.0% Intact Land Totals Acres 5,083 2,759 2,324 45.7% 5,083 3,770 1,313 25.8% 75 Acres Number 3 29 26 866.7% 3 1 2 66.7% 250 Acres Number 0 1 1 N/A 0 0 0 0.0% 500 Acres Number 0 1 1 N/A 0 0 0 0.0% 1,000 Acres Number 0 0 0 0.0% 0 0 0 0.0% 10,000 Acres Number 1 1 0 0.0% 1 1 0 0.0% Above 10,000 Acres Number 0 0 0 0.0% 0 0 0 0.0%

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157 | Page Farmton Units Pre Post Change Percent Total Cells Acres 35,001 35,001 0 0.0% Developed Cells Acres 2,483 19,486 17,003 684.8% Intact Cells Acres 32,518 15,515 17,003 52.3% Percentage (100 meters) N/A 93% 44% 0 52.3% Total Cells Acres 35,002 35,002 0 0.0% Developed Cells Acres 1,149 18,806 17,657 1536.7% Intact Cells Acres 33,853 16,196 17,657 52.2% Percentage (1,000 meters) N/A 97% 46% 1 52.2% Total Cells Acres 35,001 35,001 0 0.0% Developed Cells Acres 0 2,849 2,849 N/A Intact Cells Acres 35,001 32,152 2,849 8.1% Percentage (10,000 meters) N/A 100% 92% 0 8.1% Intact Land Totals Acres 32,477 15,481 16,996 52.3% 75 Acres Number 56 34 22 39.3% 250 Acres Number 1 3 2 200.0% 500 Acres Number 3 1 2 66.7% 1,000 Acres Number 0 2 2 N/A 10,000 Acres Number 2 4 2 100.0% Above 10,000 Acres Number 2 0 2 100.0% B 2 : Habitat Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Pro posed Conservation Acres 384 297 87 22.7% 4,458 4,448 10 0.2% Natural Communities Acres 1,334 988 346 25.9% 5,365 4,924 441 8.2% Strategic Habitats Acres 20,924 11,463 9,461 45.2% 51,432 28,700 22,732 44.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 544 493 51 9.4% 34,060 13,488 20,572 60.4% Priority 3 Acres 19,371 10,051 9,320 48.1% 10,186 8,798 1,388 13.6% Priority 4 Acres 8 8 0 0.0% 3,989 3,914 75 1.9% Priority 5 Acres 1,001 911 90 9.0% 3,197 2,500 697 21.8% Coastal Resources Acres 0 0 0 0.0% 3,298 3,167 131 4.0% Biodiversity Acres 36,842 23,063 13,779 37.4% 71,456 38,953 32,503 45.5% Priority 1 Acres 188 188 0 0.0% 163 100 63 38.7% Priority 2 Acres 4,332 1,779 2,553 58.9% 35,139 14,441 20,698 58.9% Priority 3 Acres 22,305 13,632 8,673 38.9% 14,596 13,009 1,587 10.9% Priority 4 Acres 8,479 6,263 2,216 26.1% 19,132 9,943 9,189 48.0% Priority 5 Acres 1,538 1,201 337 21.9% 2,426 1,460 966 39.8% TOTALS Acres 59,484 35,811 23,673 39.8% 136,009 80,192 55,817 41.0%

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158 | Page Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Pro posed Conservation Acres 0 0 0 0.0% 0 0 0 0.0% Natural Communities Acres 300 105 195 65.0% 300 155 145 48.3% Strategic Habitats Acres 4,713 2,662 2,051 43.5% 4,713 3,658 1,055 22.4% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 4,334 2,569 1,765 40.7% 4,334 3,645 689 15.9% Priority 3 Acres 379 93 286 75.5% 379 13 366 96.6% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Coastal Resources Acres 0 0 0 0.0% 0 0 0 0.0% Biodiversity Acres 5,187 2,809 2,378 45.8% 5,187 3,828 1,359 26.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 4,481 2,589 1,892 42.2% 4,481 3,657 824 18.4% Priority 3 Acres 617 188 429 69.5% 617 160 457 74.1% Priority 4 Acres 88 31 57 64.8% 88 11 77 87.5% Priority 5 Acres 1 1 0 0.0% 1 0 1 100.0% TOTALS Acres 10,200 5,576 4,624 45.3% 10,200 7,641 2,559 25.1% Farmton Units Pre Post Change Percent Proposed Conservation Acres 2,877 2,071 806 28.0% Natural Communities Acres 3,390 2,100 1,290 38.1% Strategic Habitats Acres 25,162 11,029 14,133 56.2% Priority 1 Acres 0 0 0 0.0% Pri ority 2 Acres 21,167 9,339 11,828 55.9% Priority 3 Acres 3,830 1,525 2,305 60.2% Pri ority 4 Acres 0 0 0 0.0% Priority 5 Acres 165 165 0 0.1% Coa stal Resources Acres 0 0 0 0.0% Biodiversity Acres 34,976 16,592 18,384 52.6% Pri ority 1 Acres 8 8 0 0.0% Priority 2 Acres 23,382 10,694 12,688 54.3% Pri ority 3 Acres 10,583 5,134 5,449 51.5% Priority 4 Acres 995 751 244 24.5% Pri ority 5 Acres 8 5 3 37.5% TOTALS Acres 66,405 31,792 34,613 52.1%

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159 | Page B 3 : Edge Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 4,313 3,173 1,140 26.4% 137,485 131,908 5,577 4.1% Edge 300 meters Acres 13,843 9,245 4,598 33.2% 282,910 265,433 17,477 6.2% Edge and Urban 100 meters Acres 5,455 20,647 15,192 278.5% 221,367 246,379 25,012 11.3% Edge and Urban 300 meters Acres 18,419 33,259 14,840 80.6% 366,792 379,905 13,113 3.6% Total Edge Acres 4,313 3,173 1,140 26.4% 17,060 10,897 6,163 36.1% Intact in Edge Acres 3,637 2,860 777 21.4% 14,441 9,171 5,270 36.5% Non Intact in Edge Acres 673 316 357 53.0% 2,630 1,723 907 34.5% Total Edge Acres 13,843 9,245 4,598 33.2% 41,706 23,519 18,187 43.6% Intact in Edge Acres 11,449 8,414 3,035 26.5% 35,053 19,871 15,182 43.3% Non Intact in Edge Acres 2,401 838 1,563 65.1% 6,659 3,645 3,014 45.3% TOTALS Acres 78,346 91,170 12,824 16.4% 1,126,103 1,092,451 33,652 3.0% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 54,892 55,980 1,088 2.0% 54,892 54,820 72 0.1% Edge 300 meters Acres 110,581 111,804 1,223 1.1% 110,581 109,942 639 0.6% Edge and Urban 100 meters Acres 105,479 108,852 3,373 3.2% 105,479 160,652 55,173 52.3% Edge and Urban 300 meters Acres 161,168 164,676 3,508 2.2% 161,168 161,774 606 0.4% Total Edge Acres 451 1,376 925 205.1% 451 377 74 16.4% Intact in Edge Acres 451 1,331 880 195.1% 451 360 91 20.2% Non Intact in Edge Acres 0 45 45 N/A 0 16 16 N/A Total Edge Acres 1,361 2,133 772 56.7% 1,361 778 583 42.8% Intact in Edge Acres 1,361 2,076 715 52.5% 1,361 761 600 44.1% Non Intact in Edge Acres 0 55 55 N/A 0 16 16 N/A TOTALS Acres 435,744 448,328 12,584 2.9% 435,744 489,496 53,752 12.3% Farmton Units Pre Post Change Percent Edge 100 meters Acres 3,836 3,776 60 1.6% Edge 300 meters Acres 11,200 8,915 2,285 20.4% Edge and U rban 100 meters Acres 6,251 24,481 18,230 291.6% Edge and Urban 300 meters Acres 15,046 32,522 17,476 116.2% Total Edge Acres 3,836 3,776 60 1.6% Intact in Edge Acres 3,752 3,718 34 0.9% Non Intact in Edge Acres 86 60 26 30.2% Total Edge Acres 11,200 8,915 2,285 20.4% Intact in Edge Acres 10,987 8,736 2,251 20.5% Non Intact in Edge Acres 215 177 38 17.7% TOTALS Acr es 66,409 95,076 28,667 43.2%

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160 | Page B 4 : Connectivity Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent FEG N (Totals) Acres 25,871 14,752 11,119 43.0% 59,827 31,386 28,441 47.5% Priority 1 Acres 0 0 0 0.0% 8 8 0 0.0% Priority 2 Acres 0 0 0 0.0% 8,697 3,442 5,255 60.4% Priority 3 Acres 21,158 10,039 11,119 52.6% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 572 572 0 0.0% 0 0 0 0.0% Priority 6 Acres 4,141 4,141 0 0.0% 51,122 27,936 23,186 45.4% Landscape (Totals) Acres 36,521 22,497 14,024 38.4% 73,370 39,045 34,325 46.8% Priority 1 Acres 0 0 0 0.0% 10 10 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 22,697 11,585 11,112 49.0% 13,416 7,581 5,835 43.5% Priority 4 Acres 11,713 10,735 978 8.3% 57,707 30,828 26,879 46.6% Priority 5 Acres 2,111 177 1,934 91.6% 2,237 626 1,611 72.0% TOTALS Acres 62,392 37,249 25,143 40.3% 133,197 70,431 62,766 47.1% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent FEG N (Totals) Acres 4,904 2,747 2,157 44.0% 4,904 3,825 1,079 22.0% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 4,904 2,747 2,157 44.0% 4,904 3,825 1,079 22.0% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Landscape (Totals) Acres 5,188 2,808 2,380 45.9% 5,188 3,829 1,359 26.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 4,867 2,744 2,123 43.6% 4,867 3,815 1,052 21.6% Priority 4 Acres 321 64 257 80.1% 321 14 307 95.6% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 10,092 5,555 4,537 45.0% 10,092 7,654 2,438 24.2%

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161 | Page Farmton Units Pre Post Change Percent FEGN (Totals) Acres 33,996 15,908 18,088 53.2% Priority 1 Acres 33,451 15,868 17,583 52.6% Pri ority 2 Acres 545 40 505 92.7% Priority 3 Acres 0 0 0 0.0% Pri ority 4 Acres 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% Pri ority 6 Acres 0 0 0 0.0% Landscape (Totals) Acres 34,989 16,594 18,395 52.6% Pri ority 1 Acres 33,347 15,810 17,537 52.6% Priority 2 Acres 0 0 0 0.0% Pri ority 3 Acres 559 49 510 91.2% Priority 4 Acres 1,083 735 348 32.1% Pri ority 5 Acres 0 0 0 0.0% TOTALS Acres 68,985 32,502 36,483 52.9%

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162 | Page B 5: Water Management Land Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 10,603 8,181 2,422 22.8% 32,496 24,253 8,243 25.4% Priority 1 Acres 134 134 0 0.0% 1,361 1,361 0 0.0% Priority 2 Acres 1,026 1,002 24 2.3% 4,470 4,269 201 4.5% Priority 3 Acres 5,427 4,731 696 12.8% 11,874 9,296 2,578 21.7% Priority 4 Acres 3,973 2,287 1,686 42.4% 14,760 9,327 5,433 36.8% Priority 5 Acres 43 27 16 37.2% 31 0 31 100.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Aquifer Recharge Acres 36,036 21,989 14,047 39.0% 71,705 37,156 34,549 48.2% Priority 1 Acres 309 309 0 0.0% 163 92 71 43.6% Priority 2 Acres 1,058 882 176 16.6% 826 193 633 76.6% Priority 3 Acres 18,478 8,705 9,773 52.9% 5,772 2,153 3,619 62.7% Priority 4 Acres 9,284 5,472 3,812 41.1% 15,896 7,746 8,150 51.3% Priority 5 Acres 6,907 6,621 286 4.1% 22,526 10,782 11,744 52.1% Priority 6 Acres 0 0 0 0.0% 26,522 16,190 10,332 39.0% Surface Waters Acres 36,524 22,485 14,039 38.4% 72,993 38,631 34,362 47.1% Priority 1 Acres 328 328 0 0.0% 6,019 5,362 657 10.9% Priority 2 Acres 3,371 2,669 702 20.8% 30,463 17,386 13,077 42.9% Priority 3 Acres 1,215 1,174 41 3.4% 9,684 3,225 6,459 66.7% Priority 4 Acres 12,973 7,347 5,626 43.4% 26,442 12,502 13,940 52.7% Priority 5 Acres 1,404 1,226 178 12.7% 0 0 0 0.0% Priority 6 Acres 8,507 3,593 4,914 57.8% 385 156 229 59.5% Priority 7 Acres 8,726 6,148 2,578 29.5% 0 0 0 0.0% Natural Floodplains Acres 18,428 14,700 3,728 20.2% 44,783 29,512 15,271 34.1% Priority 1 Acres 448 448 0 0.0% 1,425 1,424 1 0.1% Priority 2 Acres 1,158 1,124 34 2.9% 5,110 4,799 311 6.1% Priority 3 Acres 6,508 5,832 676 10.4% 13,406 10,414 2,992 22.3% Priority 4 Acres 10,209 7,229 2,980 29.2% 24,762 12,875 11,887 48.0% Priority 5 Acres 105 67 38 36.2% 78 0 78 100.0% Priority 6 Acres 0 0 0 0.0% 2 0 2 100.0% TOTALS Acres 101,591 67,355 34,236 33.7% 221,977 129,552 92,425 41.6%

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163 | Page Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 2,301 1,836 465 20.2% 2,301 1,895 406 17.6% Priority 1 Acres 431 431 0 0.0% 431 431 0 0.0% Priority 2 Acres 475 455 20 4.2% 475 467 8 1.7% Priority 3 Acres 588 443 145 24.7% 588 493 95 16.2% Priority 4 Acres 804 505 299 37.2% 804 504 300 37.3% Priority 5 Acres 3 2 1 33.3% 3 0 3 100.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Aquifer Recharge Acres 5,188 2,808 2,380 45.9% 5,188 3,829 1,359 26.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 49 11 38 77.6% 49 3 46 93.9% Priority 3 Acres 234 84 150 64.1% 234 45 189 80.8% Priority 4 Acres 1,114 505 609 54.7% 1,114 436 678 60.9% Priority 5 Acres 1,730 1,288 442 25.5% 1,730 1,287 443 25.6% Priority 6 Acres 2,061 920 1,141 55.4% 2,061 2,058 3 0.1% Surface Waters Acres 5,187 2,808 2,379 45.9% 5,187 3,829 1,358 26.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 6 Acres 1,384 651 733 53.0% 1,384 1,110 274 19.8% Priority 7 Acres 3,803 2,157 1,646 43.3% 3,803 2,719 1,084 28.5% Natural Floodplains Acres 3,146 2,193 953 30.3% 3,146 2,462 684 21.7% Priority 1 Acres 431 431 0 0.0% 431 431 0 0.0% Priority 2 Acres 477 455 22 4.6% 477 471 6 1.3% Priority 3 Acres 845 620 225 26.6% 845 698 147 17.4% Priority 4 Acres 1,391 685 706 50.8% 1,391 862 529 38.0% Priority 5 Acres 2 2 0 0.0% 2 0 2 100.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 15,822 9,645 6,177 39.0% 15,822 12,015 3,807 24.1%

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164 | Page Farmton Units Pre Post Change Percent Functional Wetlands Acres 12,543 7,999 4,544 36.2% Priority 1 Acres 1,119 1,007 112 10.0% Priority 2 Acres 3,820 3,293 527 13.8% Priority 3 Acres 3,764 2,668 1,096 29.1% Priority 4 Acres 3,830 1,030 2,800 73.1% Priority 5 Acres 10 1 9 90.0% Priority 6 Acres 0 0 0 0.0% Aquifer Recharge Acres 35,006 16,610 18,396 52.6% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 1,247 880 367 29.4% Priority 3 Acres 11,209 5,855 5,354 47.8% Priority 4 Acres 13,347 6,324 7,023 52.6% Priority 5 Acres 4,691 2,067 2,624 55.9% Priority 6 Acres 4,512 1,484 3,028 67.1% Surface Wa ters Acres 34,987 16,593 18,394 52.6% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 16 16 0 0.0% Priority 3 Acres 0 0 0 0.0% Priority 4 Acres 1,089 783 306 28.1% Priority 5 Acres 457 223 234 51.2% Priority 6 Acres 18,799 8,780 10,019 53.3% Priority 7 Acres 14,626 6,791 7,835 53.6% Natural Floodplains Acres 20,633 11,287 9,346 45.3% Priority 1 Acres 1,305 1,135 170 13.0% Priority 2 Acres 4,514 3,830 684 15.2% Priority 3 Acres 5,434 3,660 1,774 32.6% Priority 4 Acres 9,362 2,657 6,705 71.6% Priority 5 Acres 18 5 13 72.2% Priority 6 Acres 0 0 0 0.0% TOTALS Acres 103,169 52,489 50,680 49.1%

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165 | Page Urban Impacts C 1 : Urban Patch Size Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 128 436 308 240.6% 459 213 246 53.6% Maximum Patch Size Acres 137 5,938 5,801 4234.3% 340 26,598 26,258 7722.9% Average Patch Size Acres 4 37 33 927.3% 6 137 132 2237.9% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Num ber of Patches Number 16 16 0 0.0% 16 4 12 75.0% Maximum Patch Size Acres 66 1,134 1,068 1618.2% 66 1,227 1,161 1759.1% Average Patch Size Acres 6 143 137 2192.0% 6 332 325 5204.0% Farmton Units Pre Post Change Percent Number of Patches Number 176 96 80 45.5% Maximum Patch Size Acres 898 4,567 3,669 408.6% Average Patch Size Acres 11 201 189 1677.1% C 2 : Urban Proximity Impacts Plum Creek Sector Plan West Bay Sector Plan Units Pre Post Change Percent Pre Post Change Percent Urban Prox imity (Mean) Meters 3,829 5,377 1,547 40.4% 7,463 7,892 428 5.7% Restoration 2006 Restoration 2009 Units Pre Post Change Percent Pre Post Change Percent Urban Prox imity (Mean) Meters 0 0 0 N/A 0 0 0 N/A Farmton Units Pre Post Change Percent Urban Proximity (Mean) Meters 11,155 10,336 819 7.3%

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166 | Page Part III: Farmton Alternative Context Data Agriculture Impacts A 1: Agriculture Patch Size Impacts Farmton Current Plan Units Pre Post Change Percent Number of Patches Number 1,915 2,271 356 18.6% Maximum Patch Size Acres 3,617 3,131 486 13.4% Average Patch Size Acres 38 27 11 28.2% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 1,915 2,115 200 10.4% 1,915 2,043 128 6.7% Maximum Patch Size Acres 3,617 3,219 398 11.0% 3,617 3,617 0 0.0% Average Patch Size Acres 38 29 8 22.3% 38 32 5 14.3% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 1,915 2,086 171 8.9% 1,915 1,972 57 3.0% Maximum Patch Size Acres 3,617 3,617 0 0.0% 3,617 3,617 0 0.0% Average Patch Size Acres 38 31 7 17.4% 38 35 3 7.3% A 2: Agriculture Impacts Farmton Current Plan Pre Post Change Percent 18331: Cropland/Pasture 1,327 1,327 0 0.0% 183313: Improved Pasture 23,702 23,700 2 0.0% 18333: Tree Plantations 36,953 26,213 10,740 29.1% Public Timber 15,496 15,485 11 0.1% Sustainable Timber (Totals) 135,501 121,647 13,854 10.2% Priority 1 0 0 0 0.0% Priority 2 15,652 11,995 3,657 23.4% Priority 3 80,951 70,847 10,104 12.5% Priority 4 0 0 0 0.0% Priority 5 38,898 38,805 93 0.2% Specialty (Totals) 10,239 10,239 0 0.0% 18332: Orchards/Groves 5,216 5,216 0 0.0% 18334: Nurseries 3,455 3,455 0 0.0% 18335: Other Agriculture 1,568 1,568 0 0.0% TOTALS 223,218 198,611 24,607 11.0%

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167 | Page Farmton Alternate #1 Farmton Alternate #2 Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture 1,327 1,327 0 0.0% 1,327 1,327 0 0.0% 183313: Improved Pasture 23,702 23,699 3 0.0% 23,702 23,700 2 0.0% 1 8333: Tree Plantations 36,953 26,744 10,209 27.6% 36,953 30,796 6,157 16.7% Public Timber 15,496 15,463 33 0.2% 15,496 15,496 0 0.0% S ustainable Timber (Totals) 135,501 122,636 12,865 9.5% 135,501 128,472 7,029 5.2% Priority 1 0 0 0 0.0% 0 0 0 0.0% P riority 2 15,652 13,442 2,210 14.1% 15,652 14,890 762 4.9% Priority 3 80,951 70,330 10,621 13.1% 80,951 74,714 6,237 7.7% Priority 4 0 0 0 0.0% 0 0 0 0.0% P riority 5 38,898 38,864 34 0.1% 38,898 38,868 30 0.1% Specialty (Totals) 10,239 10,239 0 0.0% 10,239 10,239 0 0.0% 1 8332: Orchards/Groves 5,216 5,216 0 0.0% 5,216 5,216 0 0.0% 18334: Nurseries 3,455 3,455 0 0.0% 3,455 3,455 0 0.0% 1 8335: Other Agriculture 1,568 1,568 0 0.0% 1,568 1,568 0 0.0% TOTALS 223,218 200,108 23,110 10.4% 223,218 210,030 13,188 5.9% Farmton Alternate #3 Farmton Alternate #4 Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture 1,327 1,327 0 0.0% 1,327 1,327 0 0.0% 183313: Improved Pasture 23,702 23,699 3 0.0% 23,702 23,700 2 0.0% 1 8333: Tree Plantations 36,953 29,739 7,214 19.5% 36,953 33,701 3,252 8.8% Public Timber 15,496 15,480 16 0.1% 15,496 15,495 1 0.0% S ustainable Timber (Totals) 135,501 127,027 8,474 6.3% 135,501 131,173 4,328 3.2% Priority 1 0 0 0 0.0% 0 0 0 0.0% P riority 2 15,652 14,998 654 4.2% 15,652 15,641 11 0.1% Priority 3 80,951 73,158 7,793 9.6% 80,951 76,664 4,287 5.3% Priority 4 0 0 0 0.0% 0 0 0 0.0% P riority 5 38,898 38,871 27 0.1% 38,898 38,868 30 0.1% Specialty (Totals) 10,239 10,239 0 0.0% 10,239 10,239 0 0.0% 1 8332: Orchards/Groves 5,216 5,216 0 0.0% 5,216 5,216 0 0.0% 18334: Nurseries 3,455 3,455 0 0.0% 3,455 3,455 0 0.0% 1 8335: Other Agriculture 1,568 1,568 0 0.0% 1,568 1,568 0 0.0% TOTALS 223,218 207,511 15,707 7.0% 223,218 215,635 7,583 3.4%

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168 | Page Conservation Impacts B 1: Fragmentation Impacts Farmton Current Plan Units Pre Post Change Percent Total Cells Acres 482,902 482,902 0 0.0% Developed Cells Acres 144,801 161,976 17,175 11.9% Intact Cells Acres 338,101 320,926 17,175 5.1% Percentage (100 meters) N/A 70% 66% 0 5.1% Total Cells Acres 524,201 524,201 0 0.0% Developed Cells Acres 150,773 169,398 18,625 12.4% Intact Cells Acres 373,428 354,803 18,625 5.0% Percentage (1,000 meters) N/A 71% 68% 0 5.0% Total Cells Acres 573,562 573,561 1 0.0% Developed Cells Acres 102,548 105,779 3,231 3.2% Intact Cells Acres 471,014 467,782 3,232 0.7% Percentage (10,000 meters) N/A 82% 82% 0 0.7% 75 Acres Number 2,336 2,411 75 3.2% 250 Acres Number 31 31 0 0.0% 500 Acres Number 6 6 0 0.0% 1,000 Acres Number 2 2 0 0.0% 10,000 Acres Number 8 8 0 0.0% Above 10,000 Acres Number 3 3 0 0.0% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 482,902 482,902 0 0.0% 482,902 482,902 0 0.0% Dev eloped Cells Acres 144,801 161,557 16,756 11.6% 144,801 154,039 9,238 6.4% Intact Cells Acres 338,101 321,345 16,756 5.0% 338,101 328,863 9,238 2.7% Percentage (100 meters) N/A 70% 67% 0 5.0% 70% 68% 0 2.7% Total Cells Acres 524,201 524,201 0 0.0% 524,201 524,201 0 0.0% Developed Cells Acres 150,773 168,650 17,877 11.9% 150,773 160,735 9,962 6.6% Intact Cells Acres 373,428 355,551 17,877 4.8% 373,428 363,466 9,962 2.7% Percentage (1,000 meters) N/A 71% 68% 0 4.8% 71% 69% 0 2.7% Total Cells Acres 573,562 573,562 0 0.0% 573,562 510,562 63,000 11.0% Developed Cells Acres 102,548 107,041 4,493 4.4% 102,548 102,675 127 0.1% Intact Cells Acres 471,014 466,521 4,493 1.0% 471,014 407,887 63,127 13.4% Percentage (10,000 meters) N/A 82% 81% 0 1.0% 82% 80% 0 2.7% 75 Acres Number 2,336 1,409 927 39.7% 2,336 1,405 931 39.9% 250 Acres Number 31 31 0 0.0% 31 31 0 0.0% 500 Acres Number 6 6 0 0.0% 6 6 0 0.0% 1,000 Acres Number 2 2 0 0.0% 2 2 0 0.0% 10,000 Acres Number 8 8 0 0.0% 8 8 0 0.0% Above 10,000 Acres Number 3 3 0 0.0% 3 3 0 0.0%

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169 | Page Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 482,902 482,902 0 0.0% 482,902 482,902 0 0.0% Developed Cells Acres 144,801 155,864 11,063 7.6% 144,801 149,908 5,107 3.5% Int act Cells Acres 338,101 327,038 11,063 3.3% 338,101 332,994 5,107 1.5% Percentage (100 meters) N/A 70% 68% 0 3.3% 70% 69% 0 1.5% Tot al Cells Acres 524,201 524,201 0 0.0% 524,201 524,201 0 0.0% Developed Cells Acres 150,773 162,711 11,938 7.9% 150,773 156,813 6,040 4.0% Int act Cells Acres 373,428 361,490 11,938 3.2% 373,428 367,388 6,040 1.6% Percentage (1,000 meters) N/A 71% 69% 0 3.2% 71% 70% 0 1.6% Tot al Cells Acres 573,562 573,561 1 0.0% 573,562 573,562 0 0.0% Developed Cells Acres 102,548 102,674 126 0.1% 102,548 102,548 0 0.0% Int act Cells Acres 471,014 470,887 127 0.0% 471,014 471,014 0 0.0% Percentage (10,000 meters) N/A 82% 82% 0 0.0% 82% 82% 0 0.0% 75 Acres Number 2,336 1,412 924 39.6% 2,336 2,366 30 1.3% 250 Acres Number 31 31 0 0.0% 31 29 2 6.5% 500 Acres Number 6 6 0 0.0% 6 6 0 0.0% 1,000 Acres Number 2 2 0 0.0% 2 2 0 0.0% 10, 000 Acres Number 8 8 0 0.0% 8 8 0 0.0% Above 10,000 Acres Number 3 3 0 0.0% 3 3 0 0.0% B 2: Habitat Impacts Farmton Current Plan Units Pre Post Change Percent Proposed Conservation Acres 24,905 24,099 806 3.2% Natural Communities Acres 82,919 81,629 1,290 1.6% Strategic Habitats Acres 297,155 283,022 14,133 4.8% Priority 1 Acres 9,752 9,752 0 0.0% Priority 2 Acres 193,597 181,769 11,828 6.1% Priority 3 Acres 70,699 68,394 2,305 3.3% Priority 4 Acres 343 343 0 0.0% Priority 5 Acres 22,764 22,764 0 0.0% Coastal Resources Acres 22,071 22,071 0 0.0% Biodiversity Acres 436,142 417,758 18,384 4.2% Priority 1 Acres 37,620 37,620 0 0.0% Priority 2 Acres 207,441 194,753 12,688 6.1% Priority 3 Acres 100,858 95,409 5,449 5.4% Priority 4 Acres 74,892 74,648 244 0.3% Priority 5 Acres 15,331 15,328 3 0.0% TOTALS Acres 863,192 828,579 34,613 4.0%

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170 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 24,905 24,099 806 3.2% 24,905 24,904 1 0.0% Natural Communities Acres 82,919 81,679 1,240 1.5% 82,919 82,627 292 0.4% Str ategic Habitats Acres 297,155 283,588 13,567 4.6% 297,155 289,664 7,491 2.5% Priority 1 Acres 9,752 9,752 0 0.0% 9,752 9,752 0 0.0% Pri ority 2 Acres 193,597 182,463 11,134 5.8% 193,597 187,279 6,318 3.3% Priority 3 Acres 70,699 68,293 2,406 3.4% 70,699 69,526 1,173 1.7% Pri ority 4 Acres 343 343 0 0.0% 343 343 0 0.0% Priority 5 Acres 22,764 22,737 27 0.1% 22,764 22,764 0 0.0% Coa stal Resources Acres 22,071 22,071 0 0.0% 22,071 22,071 0 0.0% Bio diversity Acres 436,142 418,509 17,633 4.0% 436,142 426,715 9,427 2.2% Pri ority 1 Acres 37,620 37,620 0 0.0% 37,620 37,620 0 0.0% Priority 2 Acres 207,441 195,532 11,909 5.7% 207,441 200,991 6,450 3.1% Pri ority 3 Acres 100,858 95,437 5,421 5.4% 100,858 97,980 2,878 2.9% Priority 4 Acres 74,892 74,592 300 0.4% 74,892 74,796 96 0.1% Pri ority 5 Acres 15,331 15,328 3 0.0% 15,331 15,328 3 0.0% TOTALS Acres 863,192 829,946 33,246 3.9% 863,192 845,981 17,211 2.0% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 24,905 24,903 2 0.0% 24,905 24,904 1 0.0% Natural Communities Acres 82,919 82,545 374 0.5% 82,919 82,817 102 0.1% Str ategic Habitats Acres 297,155 288,182 8,973 3.0% 297,155 292,495 4,660 1.6% Priority 1 Acres 9,752 9,752 0 0.0% 9,752 9,752 0 0.0% Pri ority 2 Acres 193,597 186,429 7,168 3.7% 193,597 189,909 3,688 1.9% Priority 3 Acres 70,699 68,894 1,805 2.6% 70,699 69,727 972 1.4% Pri ority 4 Acres 343 343 0 0.0% 343 343 0 0.0% Priority 5 Acres 22,764 22,764 0 0.0% 22,764 22,764 0 0.0% Coa stal Resources Acres 22,071 22,071 0 0.0% 22,071 22,071 0 0.0% Biodiversity Acres 436,142 424,827 11,315 2.6% 436,142 430,773 5,369 1.2% Pri ority 1 Acres 37,620 37,620 0 0.0% 37,620 37,620 0 0.0% Priority 2 Acres 207,441 200,081 7,360 3.5% 207,441 203,695 3,746 1.8% Pri ority 3 Acres 100,858 97,081 3,777 3.7% 100,858 99,417 1,441 1.4% Priority 4 Acres 74,892 74,717 175 0.2% 74,892 74,712 180 0.2% Pri ority 5 Acres 15,331 15,328 3 0.0% 15,331 15,329 2 0.0% TOTALS Acres 863,192 842,528 20,664 2.4% 863,192 853,060 10,132 1.2% B 3: Edge Impacts Farmton Current Plan Units Pre Post Change Percent Edge 100 meters Acres 111,064 111,670 606 0.5% Edge 300 meters Acres 217,672 217,000 672 0.3% Edge and Urban 100 meters Acres 202,358 220,105 17,747 8.8% Edge and Urban 300 meters Acres 308,966 325,436 16,470 5.3%

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171 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 111,064 110,730 334 0.3% 111,064 111,183 119 0.1% Edge 300 meters Acres 217,672 215,404 2,268 1.0% 217,672 217,095 577 0.3% Edge and Urban 100 meters Acres 202,358 218,784 16,426 8.1% 202,358 211,792 9,434 4.7% Edge and Urban 300 meters Acres 308,966 323,458 14,492 4.7% 308,966 317,704 8,738 2.8% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 111,064 111,018 46 0.0% 111,064 110,912 152 0.1% Edge 300 meters Acres 217,672 216,376 1,296 0.6% 217,672 216,721 951 0.4% Edge and Urban 100 meters Acres 202,358 213,436 11,078 5.5% 202,358 207,373 5,015 2.5% Edge and Urban 300 meters Acres 308,966 318,793 9,827 3.2% 308,966 313,182 4,216 1.4% B 4: Connectivity Impacts Farmton Current Plan Units Pre Post Change Percent FEGN (Totals) Acres 392,316 374,228 18,088 4.6% Priority 1 Acres 180,664 163,081 17,583 9.7% Priority 2 Acres 153,763 153,258 505 0.3% Priority 3 Acres 2,470 2,470 0 0.0% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 3,605 3,605 0 0.0% Priority 6 Acres 51,814 51,814 0 0.0% Landscape (Totals) Acres 437,866 419,471 18,395 4.2% Priority 1 Acres 179,787 162,250 17,537 9.8% Priority 2 Acres 0 0 0 0.0% Priority 3 Acres 166,225 165,715 510 0.3% Priority 4 Acres 80,317 79,969 348 0.4% Priority 5 Acres 11,537 11,537 0 0.0% TOTALS Acres 830,182 793,699 36,483 4.4%

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172 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 392,316 374,984 17,332 4.4% 392,316 383,194 9,122 2.3% Priority 1 Acres 180,664 163,760 16,904 9.4% 180,664 171,549 9,115 5.0% Priority 2 Acres 153,763 153,335 428 0.3% 153,763 153,756 7 0.0% Priority 3 Acres 2,470 2,470 0 0.0% 2,470 2,470 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 3,605 3,605 0 0.0% 3,605 3,605 0 0.0% Priority 6 Acres 51,814 51,814 0 0.0% 51,814 51,814 0 0.0% Landscape (Totals) Acres 437,866 420,223 17,643 4.0% 437,866 428,433 9,433 2.2% Priority 1 Acres 179,787 162,948 16,839 9.4% 179,787 170,689 9,098 5.1% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 166,225 165,793 432 0.3% 166,225 166,215 10 0.0% Priority 4 Acres 80,317 79,945 372 0.5% 80,317 79,992 325 0.4% Priority 5 Acres 11,537 11,537 0 0.0% 11,537 11,537 0 0.0% TOTALS Acres 830,182 795,207 34,975 4.2% 830,182 811,627 18,555 2.2% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 392,316 381,186 11,130 2.8% 392,316 386,947 5,369 1.4% Priority 1 Acres 180,664 169,535 11,129 6.2% 180,664 175,295 5,369 3.0% Priority 2 Acres 153,763 153,762 1 0.0% 153,763 153,763 0 0.0% Priority 3 Acres 2,470 2,470 0 0.0% 2,470 2,470 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 3,605 3,605 0 0.0% 3,605 3,605 0 0.0% Priority 6 Acres 51,814 51,814 0 0.0% 51,814 51,814 0 0.0% Landscape (Totals) Acres 437,866 426,546 11,320 2.6% 437,866 432,493 5,373 1.2% Priority 1 Acres 179,787 168,678 11,109 6.2% 179,787 174,424 5,363 3.0% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 166,225 166,215 10 0.0% 166,225 166,225 0 0.0% Priority 4 Acres 80,317 80,116 201 0.3% 80,317 80,307 10 0.0% Priority 5 Acres 11,537 11,537 0 0.0% 11,537 11,537 0 0.0% TOTALS Acres 830,182 807,732 22,450 2.7% 830,182 819,440 10,742 1.3%

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173 | Page B 5: Water Management Land Impacts Farmton Current Plan Units Pre Post Change Percent Functional Wetlands Acres 208,130 203,586 4,544 2.2% Priority 1 Acres 92,449 92,337 112 0.1% Priority 2 Acres 53,129 52,602 527 1.0% Priority 3 Acres 34,939 33,843 1,096 3.1% Priority 4 Acres 21,904 19,104 2,800 12.8% Priority 5 Acres 3,317 3,308 9 0.3% Priority 6 Acres 2,392 2,392 0 0.0% Aquifer Recharge Acres 451,754 433,358 18,396 4.1% Priority 1 Acres 22,149 22,149 0 0.0% Priority 2 Acres 38,726 38,359 367 0.9% Priority 3 Acres 90,288 84,934 5,354 5.9% Priority 4 Acres 111,191 104,168 7,023 6.3% Priority 5 Acres 96,588 93,964 2,624 2.7% Priority 6 Acres 92,812 89,784 3,028 3.3% Surface Wa ters Acres 428,794 410,400 18,394 4.3% Priority 1 Acres 17,631 17,631 0 0.0% Priority 2 Acres 73,123 73,123 0 0.0% Priority 3 Acres 17,866 17,866 0 0.0% Priority 4 Acres 126,214 125,908 306 0.2% Priority 5 Acres 18,310 18,076 234 1.3% Priority 6 Acres 99,170 89,151 10,019 10.1% Priority 7 Acres 76,480 68,645 7,835 10.2% Natural Floodplains Acres 233,300 223,954 9,346 4.0% Priority 1 Acres 91,745 91,575 170 0.2% Priority 2 Acres 56,956 56,272 684 1.2% Priority 3 Acres 39,676 37,902 1,774 4.5% Priority 4 Acres 32,806 26,101 6,705 20.4% Priority 5 Acres 6,592 6,579 13 0.2% Priority 6 Acres 5,525 5,525 0 0.0% TOTALS Acr es 1,321,978 1,271,298 50,680 3.8%

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174 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 208,130 203,456 4,674 2.2% 208,130 205,829 2,301 1.1% Priority 1 Acres 92,449 92,337 112 0.1% 92,449 92,447 2 0.0% Priority 2 Acres 53,129 52,570 559 1.1% 53,129 53,015 114 0.2% Priority 3 Acres 34,939 33,433 1,506 4.3% 34,939 34,266 673 1.9% Priority 4 Acres 21,904 19,416 2,488 11.4% 21,904 20,399 1,505 6.9% Priority 5 Acres 3,317 3,308 9 0.3% 3,317 3,310 7 0.2% Priority 6 Acres 2,392 2,392 0 0.0% 2,392 2,392 0 0.0% Aquifer Recharge Acres 451,754 434,077 17,677 3.9% 451,754 442,320 9,434 2.1% Priority 1 Acres 22,149 22,149 0 0.0% 22,149 22,149 0 0.0% Priority 2 Acres 38,726 38,292 434 1.1% 38,726 38,531 195 0.5% Priority 3 Acres 90,288 85,269 5,019 5.6% 90,288 88,490 1,798 2.0% Priority 4 Acres 111,191 104,980 6,211 5.6% 111,191 108,016 3,175 2.9% Priority 5 Acres 96,588 94,047 2,541 2.6% 96,588 94,647 1,941 2.0% Priority 6 Acres 92,812 89,340 3,472 3.7% 92,812 90,487 2,325 2.5% Surface Waters Acres 428,794 411,153 17,641 4.1% 428,794 419,362 9,432 2.2% Priority 1 Acres 17,631 17,631 0 0.0% 17,631 17,631 0 0.0% Priority 2 Acres 73,123 73,123 0 0.0% 73,123 73,123 0 0.0% Priority 3 Acres 17,866 17,866 0 0.0% 17,866 17,866 0 0.0% Priority 4 Acres 126,214 125,890 324 0.3% 126,214 125,940 274 0.2% Priority 5 Acres 18,310 17,903 407 2.2% 18,310 18,089 221 1.2% Priority 6 Acres 99,170 91,432 7,738 7.8% 99,170 94,325 4,845 4.9% Priority 7 Acres 76,480 67,308 9,172 12.0% 76,480 72,388 4,092 5.4% Natural Floodplains Acres 233,300 226,190 7,110 3.0% 233,300 228,324 4,976 2.1% Priority 1 Acres 91,745 91,574 171 0.2% 91,745 91,742 3 0.0% Priority 2 Acres 56,956 56,255 701 1.2% 56,956 56,749 207 0.4% Priority 3 Acres 39,676 39,464 212 0.5% 39,676 38,735 941 2.4% Priority 4 Acres 32,806 26,798 6,008 18.3% 32,806 28,996 3,810 11.6% Priority 5 Acres 6,592 6,574 18 0.3% 6,592 6,577 15 0.2% Priority 6 Acres 5,525 5,525 0 0.0% 5,525 5,525 0 0.0% TOTALS Acres 1,321,978 1,274,876 47,102 3.6% 1,321,978 1,295,835 26,143 2.0%

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175 | Page Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 208,130 205,376 2,754 1.3% 208,130 207,064 1,066 0.5% Priority 1 Acres 92,449 92,447 2 0.0% 92,449 92,449 0 0.0% Priority 2 Acres 53,129 52,888 241 0.5% 53,129 53,098 31 0.1% Priority 3 Acres 34,939 34,167 772 2.2% 34,939 34,785 154 0.4% Priority 4 Acres 21,904 20,172 1,732 7.9% 21,904 21,030 874 4.0% Priority 5 Acres 3,317 3,310 7 0.2% 3,317 3,310 7 0.2% Priority 6 Acres 2,392 2,392 0 0.0% 2,392 2,392 0 0.0% Aquifer Recharge Acres 451,754 440,431 11,323 2.5% 451,754 446,379 5,375 1.2% Priority 1 Acres 22,149 22,149 0 0.0% 22,149 22,149 0 0.0% Priority 2 Acres 38,726 38,484 242 0.6% 38,726 38,634 92 0.2% Priority 3 Acres 90,288 87,990 2,298 2.5% 90,288 89,810 478 0.5% Priority 4 Acres 111,191 107,086 4,105 3.7% 111,191 109,776 1,415 1.3% Priority 5 Acres 96,588 94,348 2,240 2.3% 96,588 95,668 920 1.0% Priority 6 Acres 92,812 90,374 2,438 2.6% 92,812 90,342 2,470 2.7% Surface Waters Acres 428,794 417,475 11,319 2.6% 428,794 423,421 5,373 1.3% Priority 1 Acres 17,631 17,631 0 0.0% 17,631 17,631 0 0.0% Priority 2 Acres 73,123 73,123 0 0.0% 73,123 73,123 0 0.0% Priority 3 Acres 17,866 17,866 0 0.0% 17,866 17,866 0 0.0% Priority 4 Acres 126,214 125,940 274 0.2% 126,214 125,954 260 0.2% Priority 5 Acres 18,310 18,088 222 1.2% 18,310 18,078 232 1.3% Priority 6 Acres 99,170 93,708 5,462 5.5% 99,170 96,546 2,624 2.6% Priority 7 Acres 76,480 71,119 5,361 7.0% 76,480 74,223 2,257 3.0% Natural Floodplains Acres 233,300 227,429 5,871 2.5% 233,300 230,403 2,897 1.2% Priority 1 Acres 91,745 91,742 3 0.0% 91,745 91,745 0 0.0% Priority 2 Acres 56,956 56,607 349 0.6% 56,956 56,905 51 0.1% Priority 3 Acres 39,676 38,500 1,176 3.0% 39,676 39,467 209 0.5% Priority 4 Acres 32,806 28,478 4,328 13.2% 32,806 30,184 2,622 8.0% Priority 5 Acres 6,592 6,577 15 0.2% 6,592 6,577 15 0.2% Priority 6 Acres 5,525 5,525 0 0.0% 5,525 5,525 0 0.0% TOTALS Acres 1,321,978 1,290,711 31,267 2.4% 1,321,978 1,307,267 14,711 1.1%

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176 | Page Urban Impacts C 1: Urban Patch Size Impacts Farmton Current Plan Units Pre Post Change Percent Number of Patches Number 4,667 4,591 76 1.6% Maximum Patch Size Area 9,583 9,583 0 0.0% Average Patch Size Area 17 21 4 23.4% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 4,667 4,580 87 1.9% 4,667 4,622 45 1.0% Max imum Patch Size Area 9,583 9,583 0 0.0% 9,583 9,583 0 0.0% Average Patch Size Area 17 21 4 23.2% 17 19 2 12.7% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 4,667 4,603 64 1.4% 4,667 4,633 34 0.7% Max imum Patch Size Area 9,583 9,583 0 0.0% 9,583 9,583 0 0.0% Average Patch Size Area 17 20 3 15.5% 17 19 1 7.2% C 2: Urban Proximity Impacts Farmton Current Plan Units Pre Post Change Percent Urban Proximity (Mean) Meters 2,850 4,031 1,181 41.5% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Urban Proximity (Mean) Meters 2,850 3,964 1,114 39.1% 2,850 3,512 662 23.2% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Urban Proximity (Mean) Meters 2,850 3,628 778 27.3% 2,850 3,227 377 13.2%

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177 | Page Part IV: Farmton Alternate Development Data Agriculture Impacts A 1: Agriculture Patch Size Impacts Farmton Current Plan Units Pre Post Change Percent Number of Patches Number 327 359 32 9.8% Maximum Patch Size Acres 3,273 775 2,498 76.3% Average Patch Size Acres 63 28 36 56.1% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 327 360 33 10.1% 327 323 4 1.2% Maximum Patch Size Acres 3,273 1,047 0 68.0% 3,273 1,342 1,931 59.0% Average Patch Size Acres 63 29 34 53.6% 63 45 18 28.7% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 327 347 20 6.1% 327 315 12 3.7% Maximum Patch Size Acres 3,273 1,342 1,931 59.0% 3,273 3,273 0 0.0% Average Patch Size Acres 63 39 24 38.3% 63 56 8 12.3% A 2: Agriculture Impacts Farmton Current Plan Units Pre Post Change Percent 18331: Cropland/Pasture Acres 0 0 0 0.0% 183313: Improved Pasture Acres 20 18 2 10.0% 18333: Tre e Plantations Acres 20,727 9,987 10,740 51.8% Public Timber (Totals) Acres 20 9 11 55.0% Sustainabl e Timber (Totals) Acres 29,234 15,380 13,854 47.4% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 9,825 6,168 3,657 37.2% Priority 3 Acres 19,141 9,037 10,104 52.8% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 268 175 93 34.7% Specialty (Totals) Acres 1 1 0 0.0% 18332: Orchards/Groves Acres 1 1 0 0.0% 18334: Nur series Acres 0 0 0 0.0% 18335: Other Agriculture Acres 0 0 0 0.0% TOTALS Acr es 50,002 25,395 24,607 49.2%

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178 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture Acres 0 0 0 0.0% 0 0 0 0.0% 183313: Improved Pasture Acres 20 17 3 15.0% 20 18 2 10.0% 18333: Tree Plantations Acres 20,727 10,518 10,209 49.3% 20,727 14,570 6,157 29.7% Public Timber (Totals) Acres 20 13 33 165.0% 20 20 0 0.0% Sustainable Timber (Totals) Acres 29,234 16,369 12,865 44.0% 29,234 22,205 7,029 24.0% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 9,825 7,615 2,210 22.5% 9,825 9,063 762 7.8% Priority 3 Acres 19,141 8,520 10,621 55.5% 19,141 12,904 6,237 32.6% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 268 234 34 12.7% 268 238 30 11.2% Specialty (Totals) Acres 1 1 0 0.0% 1 1 0 0.0% 18332: Orchards/Groves Acres 1 1 0 0.0% 1 1 0 0.0% 18334: Nurseries Acres 0 0 0 0.0% 0 0 0 0.0% 18335: Other Agriculture Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 50,002 26,892 23,110 46.2% 50,002 36,814 13,188 26.4% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent 18331: Cropland/Pasture Acres 0 0 0 0.0% 0 0 0 0.0% 183313: Improved Pasture Acres 20 17 3 15.0% 20 18 2 10.0% 18333: Tree Plantations Acres 20,727 13,513 7,214 34.8% 20,727 17,475 3,252 15.7% Public Timber (Totals) Acres 20 4 16 80.0% 20 19 1 5.0% Sustainable Timber (Totals) Acres 29,234 20,760 8,474 29.0% 29,234 24,906 4,328 14.8% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 9,825 9,171 654 6.7% 9,825 9,814 11 0.1% Priority 3 Acres 19,141 11,348 7,793 40.7% 19,141 14,854 4,287 22.4% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 268 241 27 10.1% 268 238 30 11.2% Specialty (Totals) Acres 1 1 0 0.0% 1 1 0 0.0% 18332: Orchards/Groves Acres 1 1 0 0.0% 1 1 0 0.0% 18334: Nurseries Acres 0 0 0 0.0% 0 0 0 0.0% 18335: Other Agriculture Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 50,002 34,295 15,707 31.4% 50,002 42,419 7,583 15.2%

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179 | Page Conservation Impacts B 1: Fragmentation Impacts Farmton Current Plan Units Pre Post Change Percent Total Cells Acres 58,855 58,754 101 N/A Developed Cells Acres 3,328 20,233 16,905 508.0% Intact Cells Acres 55,527 38,521 17,006 30.6% Percentage (100 meters) N/A 94% 66% 0 30.5% Total Cells Acres 58,755 58,755 0 N/A Developed Cells Acres 1,358 19,073 17,715 1304.5% Intact Cells Acres 57,397 39,682 17,715 30.9% Percentage (1,000 meters) N/A 98% 68% 0 30.9% Total Cells Acres 58,754 58,754 0 N/A Developed Cells Acres 0 2,936 2,936 N/A Intact Cells Acres 58,754 55,818 2,936 5.0% Percentage (10,000 meters) N/A 100% 95% 0 5.0% Intact Land Totals Acres 55,631 38,527 17,104 30.7% 75 Acres Number 54 34 20 37.0% 250 Acres Number 0 0 0 0.0% 500 Acres Number 0 0 0 0.0% 1,000 Acres Number 0 2 2 N/A 10,000 Acres Number 0 0 0 0.0% Above 10,000 Acres Number 1 1 0 0.0% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 58,855 58,755 100 N/A 58,855 58,754 101 N/A Developed Cells Acres 3,328 19,701 16,373 492.0% 3,328 12,365 9,037 271.5% Intact Cells Acres 55,527 39,054 16,473 29.7% 55,527 46,389 9,138 16.5% Percentage (100 meters) N/A 94% 66% 0 29.5% 94% 79% 0 16.3% Total Cells Acres 58,755 58,755 0 N/A 58,755 58,754 1 N/A Developed Cells Acres 1,358 18,113 16,755 1233.8% 1,358 10,603 9,245 680.8% Intact Cells Acres 57,397 40,642 16,755 29.2% 57,397 48,151 9,246 16.1% Percentage (1,000 meters) N/A 98% 69% 0 29.2% 98% 82% 0 16.1% Total Cells Acres 58,754 58,755 1 N/A 58,754 58,754 0 N/A Developed Cells Acres 0 4,149 4,149 N/A 0 0 0 0.0% Intact Cells Acres 58,754 54,606 4,148 7.1% 58,754 58,754 0 0.0% Percentage (10,000 meters) N/A 100% 93% 0 7.1% 100% 100% 0 0.0% Intact Land Totals Acres 55,631 39,087 16,544 29.7% 55,631 46,455 9,176 16.5% 75 Acres Number 54 108 54 100.0% 54 54 0 0.0% 250 Acres Number 0 0 0 0.0% 0 0 0 0.0% 500 Acres Number 0 0 0 0.0% 0 0 0 0.0% 1,000 Acres Number 0 2 2 N/A 0 0 0 0.0% 10,000 Acres Number 0 0 0 0.0% 0 0 0 0.0% Above 10,000 Acres Number 1 1 0 0.0% 1 1 0 0.0%

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180 | Page Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Total Cells Acres 58,855 58,754 101 N/A 58,855 58,754 101 N/A Developed Cells Acres 3,328 14,142 10,814 324.9% 3,328 8,212 4,884 146.8% Intact Cells Acres 55,527 44,612 10,915 19.7% 55,527 50,542 4,985 9.0% Percentage (100 meters) N/A 94% 76% 0 19.5% 94% 86% 0 8.8% Total Cells Acres 58,755 58,755 0 N/A 58,755 58,754 1 N/A Developed Cells Acres 1,358 12,385 11,027 812.0% 1,358 6,661 5,303 390.5% Intact Cells Acres 57,397 46,370 11,027 19.2% 57,397 52,093 5,304 9.2% Percentage (1,000 meters) N/A 98% 79% 0 19.2% 98% 89% 0 9.2% Total Cells Acres 58,754 58,754 0 N/A 58,754 58,754 0 N/A Developed Cells Acres 0 0 0 0.0% 0 0 0 0.0% Intact Cells Acres 58,754 58,754 0 0.0% 58,754 58,754 0 0.0% Percentage (10,000 meters) N/A 100% 100% 0 0.0% 100% 100% 0 0.0% Intact Land Totals Acres 55,631 44,660 10,971 19.7% 55,631 50,584 5,047 9.1% 75 Acres Number 54 92 38 70.4% 54 53 1 1.9% 250 Acres Number 0 0 0 0.0% 0 0 0 0.0% 500 Acres Number 0 0 0 0.0% 0 0 0 0.0% 1,000 Acres Number 0 0 0 0.0% 0 0 0 0.0% 10,000 Acres Number 0 0 0 0.0% 0 0 0 0.0% Above 10,000 Acres Number 1 1 0 0.0% 1 1 0 0.0% B 2: Habitat Impacts Farmton Current Plan Units Pre Post Change Percent Proposed Conservation Acres 6,797 5,991 806 11.9% Natural Communities Acres 6,619 5,329 1,290 19.5% Strategic Habitats Acres 47,562 33,429 14,133 29.7% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 43,176 31,348 11,828 27.4% Priority 3 Acres 4,219 1,914 2,305 54.6% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 167 167 0 0.1% Coastal Re sources Acres 0 0 0 0.0% Biodiversity Acres 58,726 40,342 18,384 31.3% Priority 1 Acres 12 12 0 0.0% Priority 2 Acres 45,970 33,282 12,688 27.6% Priority 3 Acres 11,280 5,831 5,449 48.3% Priority 4 Acres 1,286 1,042 244 19.0% Priority 5 Acres 178 175 3 1.7% TOTALS Acr es 119,704 85,091 34,613 28.9%

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181 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 6,797 5,991 806 11.9% 6,797 6,796 1 0.0% Natural Communities Acres 6,619 5,379 1,240 18.7% 6,619 6,327 292 4.4% Strategic Habitats Acres 47,562 33,995 13,567 28.5% 47,562 40,071 7,491 15.7% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 43,176 32,042 11,134 25.8% 43,176 36,858 6,318 14.6% Priority 3 Acres 4,219 1,813 2,406 57.0% 4,219 3,046 1,173 27.8% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 167 140 27 16.2% 167 167 0 0.0% Coastal Resources Acres 0 0 0 0.0% 0 0 0 0.0% Biodiversity Acres 58,726 41,093 17,633 30.0% 58,726 49,299 9,427 16.1% Priority 1 Acres 12 12 0 0.0% 12 12 0 0.0% Priority 2 Acres 45,970 34,061 11,909 25.9% 45,970 39,520 6,450 14.0% Priority 3 Acres 11,280 5,859 5,421 48.1% 11,280 8,402 2,878 25.5% Priority 4 Acres 1,286 986 300 23.3% 1,286 1,190 96 7.5% Priority 5 Acres 178 175 3 1.7% 178 175 3 1.7% TOTALS Acres 119,704 86,458 33,246 27.8% 119,704 102,493 17,211 14.4% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Proposed Conservation Acres 6,797 6,795 2 0.0% 6,797 6,796 1 0.0% Natural Communities Acres 6,619 6,245 374 5.7% 6,619 6,517 102 1.5% Strategic Habitats Acres 47,562 38,589 8,973 18.9% 47,562 42,902 4,660 9.8% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 43,176 36,008 7,168 16.6% 43,176 39,488 3,688 8.5% Priority 3 Acres 4,219 2,414 1,805 42.8% 4,219 3,247 972 23.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 167 167 0 0.0% 167 167 0 0.0% Coastal Resources Acres 0 0 0 0.0% 0 0 0 0.0% Biodiversity Acres 58,726 47,411 11,315 19.3% 58,726 53,957 4,769 8.1% Priority 1 Acres 12 12 0 0.0% 12 12 0 0.0% Priority 2 Acres 45,970 38,610 7,360 16.0% 45,970 42,824 3,146 6.8% Priority 3 Acres 11,280 7,503 3,777 33.5% 11,280 9,839 1,441 12.8% Priority 4 Acres 1,286 1,111 175 13.6% 1,286 1,106 180 14.0% Priority 5 Acres 178 175 3 1.7% 178 176 2 1.1% TOTALS Acres 119,704 99,040 20,664 17.3% 119,704 110,172 9,532 8.0%

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182 | Page B 3: Edge Impacts Farmton Current Plan Units Pre Post Change Percent Edge 100 meters Acres 5,254 5,532 278 5.3% Edge 300 meters Acres 15,706 14,559 1,147 7.3% Edge and Urban 100 meters Acres 7,732 25,151 17,419 225.3% Edge and Urban 300 meters Acres 18,184 34,179 15,995 88.0% Total Edge Acres 5,254 5,532 278 5.3% Intact in Edge Acres 5,171 5,473 302 5.8% Non Intact in Edge Acres 85 59 26 30.6% Total Edge Acres 15,706 14,559 1,147 7.3% Intact in Edge Acres 15,483 14,358 1,125 7.3% Non Intact in Edge Acres 223 199 24 10.8% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 5,254 4,695 559 10.6% 5,254 5,257 3 0.1% Edge 300 meters Acres 15,706 13,080 2,626 16.7% 15,706 15,012 694 4.4% Edge and Urban 100 meters Acres 7,732 23,745 16,013 207.1% 7,732 16,984 9,252 119.7% Edge and Urban 300 meters Acres 18,184 32,131 13,947 76.7% 18,184 26,738 8,554 47.0% Total Edge Acres 5,254 4,695 559 10.6% 5,254 5,257 3 0.1% Intact in Edge Acres 5,171 4,640 531 10.3% 5,171 5,189 18 0.3% Non Intact in Edge Acres 85 55 30 35.3% 85 69 16 18.8% Total Edge Acres 15,706 13,080 2,626 16.7% 15,706 16,984 1,278 8.1% Intact in Edge Acres 15,483 12,853 2,630 17.0% 15,483 14,824 659 4.3% Non Intact in Edge Acres 223 223 0 0.0% 223 185 38 17.0% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Edge 100 meters Acres 5,254 5,050 204 3.9% 5,254 5,036 218 4.1% Edge 300 meters Acres 15,706 14,292 1,414 9.0% 15,706 14,755 951 6.1% Edge and Urban 100 meters Acres 7,732 18,569 10,837 140.2% 7,732 12,611 4,879 63.1% Edge and Urban 300 meters Acres 18,184 27,811 9,627 52.9% 18,184 22,329 4,145 22.8% Total Edge Acres 5,254 5,050 204 3.9% 5,254 5,050 204 3.9% Intact in Edge Acres 5,171 5,000 171 3.3% 5,171 4,988 183 3.5% Non Intact in Edge Acres 85 51 34 40.0% 85 49 36 42.4% Total Edge Acres 15,706 18,569 2,863 18.2% 15,706 18,569 2,863 18.2% Intact in Edge Acres 15,483 14,122 1,361 8.8% 15,483 14,605 878 5.7% Non Intact in Edge Acres 223 166 57 25.6% 223 148 75 33.6%

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183 | Page B 4: Connectivity Impacts Farmton Current Plan Units Pre Post Change Percent FEGN (Totals) Acres 57,714 39,626 18,088 31.3% Priority 1 Acres 55,626 38,043 17,583 31.6% Priority 2 Acres 2,088 1,583 505 24.2% Priority 3 Acres 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% Priority 6 Acres 0 0 0 0.0% Landscape (Totals) Acres 58,705 40,310 18,395 31.3% Priority 1 Acres 55,495 37,958 17,537 31.6% Priority 2 Acres 0 0 0 0.0% Priority 3 Acres 2,108 1,598 510 24.2% Priority 4 Acres 1,102 754 348 31.6% Priority 5 Acres 0 0 0 0.0% TOTALS Acres 116,419 79,936 36,483 31.3% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 57,714 40,382 17,332 30.0% 57,714 48,592 9,122 15.8% Priority 1 Acres 55,626 38,722 16,904 30.4% 55,626 46,511 9,115 16.4% Priority 2 Acres 2,088 1,660 428 20.5% 2,088 2,081 7 0.3% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Landscape (Totals) Acres 58,705 41,062 17,643 30.1% 58,705 49,272 9,433 16.1% Priority 1 Acres 55,495 38,656 16,839 30.3% 55,495 46,397 9,098 16.4% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 2,108 1,676 432 20.5% 2,108 2,098 10 0.5% Priority 4 Acres 1,102 730 372 33.8% 1,102 777 325 29.5% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 116,419 81,444 34,975 30.0% 116,419 97,864 18,555 15.9%

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184 | Page Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent FEGN (Totals) Acres 57,714 46,584 11,130 19.3% 57,714 52,345 5,369 9.3% Priority 1 Acres 55,626 44,497 11,129 20.0% 55,626 50,257 5,369 9.7% Priority 2 Acres 2,088 2,087 1 0.0% 2,088 2,088 0 0.0% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Landscape (Totals) Acres 58,705 47,385 11,320 19.3% 58,705 53,332 5,373 9.2% Priority 1 Acres 55,495 44,386 11,109 20.0% 55,495 50,132 5,363 9.7% Priority 2 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 3 Acres 2,108 2,098 10 0.5% 2,108 2,108 0 0.0% Priority 4 Acres 1,102 901 201 18.2% 1,102 1,092 10 0.9% Priority 5 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 116,419 93,969 22,450 19.3% 116,419 105,677 10,742 9.2%

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185 | Page B 5 : Water Management Land Impacts Farmton Current Plan Units Pre Post Change Percent Functional Wetlands Acres 30,422 25,878 4,544 14.9% Priority 1 Acres 13,649 13,537 112 0.8% Priority 2 Acres 8,590 8,063 527 6.1% Priority 3 Acres 4,315 3,219 1,096 25.4% Priority 4 Acres 3,858 1,058 2,800 72.6% Priority 5 Acres 10 1 9 90.0% Priority 6 Acres 0 0 0 0.0% Aquifer Recharge Acres 58,607 40,211 18,396 31.4% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 1,408 1,041 367 26.1% Priority 3 Acres 12,773 7,419 5,354 41.9% Priority 4 Acres 18,413 11,390 7,023 38.1% Priority 5 Acres 14,010 11,386 2,624 18.7% Priority 6 Acres 12,003 8,975 3,028 25.2% Surface Wa ters Acres 58,570 40,176 18,394 31.4% Priority 1 Acres 0 0 0 0.0% Priority 2 Acres 325 325 0 0.0% Priority 3 Acres 0 0 0 0.0% Priority 4 Acres 3,406 3,100 306 9.0% Priority 5 Acres 1,469 1,235 234 15.9% Priority 6 Acres 23,650 13,631 10,019 42.4% Priority 7 Acres 29,720 21,885 7,835 26.4% Natural Floodplains Acres 40,728 31,382 9,346 22.9% Priority 1 Acres 13,531 13,361 170 1.3% Priority 2 Acres 10,552 9,868 684 6.5% Priority 3 Acres 6,974 5,200 1,774 25.4% Priority 4 Acres 9,653 2,948 6,705 69.5% Priority 5 Acres 18 5 13 72.2% Priority 6 Acres 0 0 0 0.0% TOTALS Acres 188,327 137,647 50,680 26.9%

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186 | Page Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 30,422 25,748 4,674 15.4% 30,422 28,121 2,301 7.6% Priority 1 Acres 13,649 13,537 112 0.8% 13,649 13,647 2 0.0% Priority 2 Acres 8,590 8,031 559 6.5% 8,590 8,476 114 1.3% Priority 3 Acres 4,315 2,809 1,506 34.9% 4,315 3,642 673 15.6% Priority 4 Acres 3,858 1,370 2,488 64.5% 3,858 2,353 1,505 39.0% Priority 5 Acres 10 1 9 90.0% 10 3 7 70.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Aquifer Recharge Acres 58,607 40,930 17,677 30.2% 58,607 49,173 9,434 16.1% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 1,408 974 434 30.8% 1,408 1,213 195 13.8% Priority 3 Acres 12,773 7,754 5,019 39.3% 12,773 10,975 1,798 14.1% Priority 4 Acres 18,413 12,202 6,211 33.7% 18,413 15,238 3,175 17.2% Priority 5 Acres 14,010 11,469 2,541 18.1% 14,010 12,069 1,941 13.9% Priority 6 Acres 12,003 8,531 3,472 28.9% 12,003 9,678 2,325 19.4% Surface Waters Acres 58,570 40,929 17,641 30.1% 58,570 49,138 9,432 16.1% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 325 325 0 0.0% 325 325 0 0.0% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 3,406 3,082 324 9.5% 3,406 3,132 274 8.0% Priority 5 Acres 1,469 1,062 407 27.7% 1,469 1,248 221 15.0% Priority 6 Acres 23,650 15,912 7,738 32.7% 23,650 18,805 4,845 20.5% Priority 7 Acres 29,720 20,548 9,172 30.9% 29,720 25,628 4,092 13.8% Natural Floodplains Acres 40,728 33,618 7,110 17.5% 40,728 35,752 4,976 12.2% Priority 1 Acres 13,531 13,360 171 1.3% 13,531 13,528 3 0.0% Priority 2 Acres 10,552 9,851 701 6.6% 10,552 10,345 207 2.0% Priority 3 Acres 6,974 6,762 212 3.0% 6,974 6,033 941 13.5% Priority 4 Acres 9,653 3,645 6,008 62.2% 9,653 5,843 3,810 39.5% Priority 5 Acres 18 0 18 100.0% 18 3 15 83.3% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 188,327 141,225 47,102 25.0% 188,327 162,184 26,143 13.9%

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187 | Page Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Functional Wetlands Acres 30,422 27,668 2,754 9.1% 30,422 29,356 1,066 3.5% Priority 1 Acres 13,649 13,647 2 0.0% 13,649 13,649 0 0.0% Priority 2 Acres 8,590 8,349 241 2.8% 8,590 8,559 31 0.4% Priority 3 Acres 4,315 3,543 772 17.9% 4,315 4,161 154 3.6% Priority 4 Acres 3,858 2,126 1,732 44.9% 3,858 2,984 874 22.7% Priority 5 Acres 10 3 7 70.0% 10 3 7 70.0% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% Aquifer Recharge Acres 58,607 47,284 11,323 19.3% 58,607 53,232 5,375 9.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 1,408 1,166 242 17.2% 1,408 1,316 92 6.5% Priority 3 Acres 12,773 10,475 2,298 18.0% 12,773 12,295 478 3.7% Priority 4 Acres 18,413 14,308 4,105 22.3% 18,413 16,998 1,415 7.7% Priority 5 Acres 14,010 11,770 2,240 16.0% 14,010 13,090 920 6.6% Priority 6 Acres 12,003 9,565 2,438 20.3% 12,003 9,533 2,470 20.6% Surface Waters Acres 58,570 47,251 11,319 19.3% 58,570 53,197 5,373 9.2% Priority 1 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 2 Acres 325 325 0 0.0% 325 325 0 0.0% Priority 3 Acres 0 0 0 0.0% 0 0 0 0.0% Priority 4 Acres 3,406 3,132 274 8.0% 3,406 3,146 260 7.6% Priority 5 Acres 1,469 1,247 222 15.1% 1,469 1,237 232 15.8% Priority 6 Acres 23,650 18,188 5,462 23.1% 23,650 21,026 2,624 11.1% Priority 7 Acres 29,720 24,359 5,361 18.0% 29,720 27,463 2,257 7.6% Natural Floodplains Acres 40,728 34,857 5,871 14.4% 40,728 37,831 2,897 7.1% Priority 1 Acres 13,531 13,528 3 0.0% 13,531 13,531 0 0.0% Priority 2 Acres 10,552 10,203 349 3.3% 10,552 10,501 51 0.5% Priority 3 Acres 6,974 5,798 1,176 16.9% 6,974 6,765 209 3.0% Priority 4 Acres 9,653 5,325 4,328 44.8% 9,653 7,031 2,622 27.2% Priority 5 Acres 18 3 15 83.3% 18 3 15 83.3% Priority 6 Acres 0 0 0 0.0% 0 0 0 0.0% TOTALS Acres 188,327 157,060 31,267 16.6% 188,327 173,616 14,711 7.8%

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188 | Page Urban Impacts C 1: Urban Patch Size Impacts Farmton Current Plan Units Pre Post Change Percent Number of Patches Number 367 287 80 21.8% Maximum Patch Size Acres 913 4,598 3,685 403.6% Average Pa tch Size Acres 7 69 62 941.1% Farmton Alternate #1 Farmton Alternate #2 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 367 283 84 22.9% 367 324 43 11.7% Maximum Patch Size Acres 913 6,821 5,908 647.1% 913 3,706 2,793 305.9% Average Patch Size Acres 7 68 61 925.5% 7 36 30 450.8% Farmton Alternate #3 Farmton Alternate #4 Units Pre Post Change Percent Pre Post Change Percent Number of Patches Number 367 311 56 15.3% 367 322 45 12.3% Maximum Patch Size Acres 913 4,183 3,270 358.2% 913 4,196 3,283 359.6% Average Patch Size Acres 7 44 37 562.5% 7 23 16 247.9% C 2: Urban Proximity Impacts Not Applicable. Since Restoration is located within the City of Edgewater, this analysis did not yield any results.

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189 | Page Appendix C Farmton Suitability Analysis A: Identify lands suitable for agricultu r e. A 1: Identify the suitability for li v es t ock p r oduction. A 2: Identify the suitability for c r op p r oduction. A 3: Identify the suitability for timber p r oduction. B: Identify lands suitable for conse r v ation. B 1: Identify significant lands for biodi v ersit y . B 2: Identify significant lands for p r otecting water qualit y . B 3: Identify significant lands for p r otecting connectivit y . B 4: Identify suitable lands for permanent p r otection. C: Identify lands suitable for urban d e v elopment. C 1: Identify the suitability for r esidential use. C 2: Identify the suitability for comme r cial use. C 3: Identify the suitability for industrial use.

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190 | Page A: Agriculture Suitability Analysis A 1: Identify the suitability for li v estock p r oduction. (weighted at 40%) A 1.1: Identify the physical suitability for li v es t ock p r oduction. (weighted at 70%) A 1.1.1: Identify soil suitabilit y . (weighted at 50%) A 1.1.2: Identify existing li v es t ock p r oduction. (weighted at 10%) A 1.1.3: Identify existing land use and c o v e r . (weighte d at 40%) A 1.2: Identify the economic suitability for li v es t ock p r oduction (weighted at 30%) A 1.2.1: Identify suitable land v alue. (weighted at 20%) A 1.2.2: Identify p ro ximity t o major r oads. (weighted at 40%) A 1.2.3: Identify p ro ximity t o mar k ets. ( weighted at 40%) A 2: Identify the suitability for c r op p r oduction. (weighted at 20%) A 2.1: Identify the physical suitability for c r op p r oduction. (weighted at 70%) A 2.1.1: Identify soil suitabilit y . (weighted at 50%) A 2.1.2: Identify existing c r op p r oduction. (weighted at 10%) A 2.1.3: Identify existing land use and c o v e r . (weighted at 40%) A 2.2: Identify the economic suitability for c r op p r oduction (weighted at 30%) A 2.2.1: Identify suitable land v alue. (weighted at 20%) A 2.2.2: Identify p ro ximity t o major r oads. (weighted at 40%) A 2.2.3: Identify p ro ximity t o mar k ets. (weighted at 40%) A 3: Identify the suitability for timber p r oduction. (weighted at 40%) A 3.1: Identify the physical suitability for timber p r oduction. (weighted at 55%) A 3.1.1: Identify soil suitabilit y . (weighted at 50%) A 3.1.2: Identify existing timber p r oduction. (weighted at 10%) A 3.1.3: Identify existing land use and c o v e r . (weighted at 40%) A 3.2: Identify the economic suitability for timber p r oduction (weighted at 27%) A 3.2.1: Identify suitable land v alue. (weighted at 20%) A 3.2.2: Identify p ro ximity t o major r oads. (weighted at 40%) A 3.2.3: Identify p ro ximity t o mar k ets. (weighted at 40%) A 3.3: Identify existing and potential sustainable timber p r oduction. (weight ed at 18%)

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191 | Page A 1.1.1: Identify soils suitable for livestock production. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated based on three categories and then combined with a weighted sum function. Drainage Class (weighted at 33%) 9 = Well Drained and Moderately Well Drained 7 = Somewhat Poorly Drained 5 = Poorly Drained 1 = Excessively Drained and Very Poorly Drained Non Irrigation Capacity Class (weighted at 34%) 9 = Class 3 8 = Class 4 7 = Class 5 1 = Classes 8 6 Farmland Class (weighted at 33%) 9 = Not Prime Farmland 1 = Farmland of Unique Importance

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192 | Page A 1.1.2: Identify existing livestock production. (weighted at 10%) Data Used: CLC_v3_Poly (from Florida FWC) Existing livestock production was selected from the site clas sification and then giv en the following values 9 = 183313 (Improved Pasture) 9 = 183314 (Unimproved Pasture) 1 = All other classes

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193 | Page A 1.1.3: Identify existing land use. (weighted at 40%) Data Used: CLC_v3_Poly (from Florida FWC) Based on the site codes the existing land use was reclassified to the following values: 9 = Existing Agriculture 7 = Undeveloped Lands 6 = Wetlands and Marshes 3 = Rural Open Pine, Rural Open Land and Clear Cuts 1 = Developed Lands, Utilities, Transportation and Open Water

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194 | Page A 1.1: Identify the physical suitability for livestock production. (weighted at 70%) Data Used: A 1.1.1: Soil Suitability (weighted at 50%) A 1.1.2: Existing Livestock Production (weighted at 10%) A 1.1.3: Existing Land Use (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights .

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1 95 | Page A 1.2.1: Identify suitable land value. (weighted at 20%) Data Used: parcles_14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) A feature class was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function .

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196 | Page A 1.2.2: Identify proximity to roads (weighted at 40%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived from a zonal statistics function.

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197 | Page A 1.2.3: Identify proximity to markets. (weighted at 40%) Data Used: parcles_14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) Markets were defined as meat packaging plants as identified in the parcel data. The distances from the markets were rated based on the mean and standard deviation derived from a zonal statist ics function.

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198 | Page A 1.2: Identify the economic suitability for livestock production. (weighted at 30%) Data Used: A 1.2.1: Land Value Suitability (weighted at 20%) A 1.2.2: Road Proximity (weighted at 40%) A 1.2.3: Market Proximity (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights.

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199 | Page A 1: Identify the suitability for livestock production. (weighted at 40%) Data Used: A 1.1: Physical Suitability for Livestock Production (weig hted at 60%) A 1.2: Economic Suitability for Livestock Production (weighted at 40%) The weighted sum function was used to combine the two sub objectives at the above weights.

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200 | Page A 2.1.1: Identify soils suitable for crop production. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated based on three categories and then combined with a weighted sum function. Drainage Class (weighted at 33%) 9 = Well Drained 7 = Moderately Well Drained 5 = Somewhat Poorly Drained 3 = Poorly Drained 1 = Excessively Drained and Very Poorly Drained Non Irrigation Capacity Class (weighted at 33%) 9 = Class 3 7 = Class 4 1 = Classes 8 5 Farmland Class (weighted at 34%) 9 = Not Prime Farmland 1 = Farmland of Unique Importance

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201 | Page A 2.1.2: Identify existing crop production. (weighted at 10%) Data Used: CLC_v3_Poly (from Florida FWC) Existing crop production was selected from the site classification and then given the following values: 9 = 18331, 183311, 183312, 183342, 183343, 183352 (Row Crops/Specialty) 9 = 183321, 183324, 183341 (Orchards/Groves) 1 = All other classes

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202 | Page A 2.1.3: Identify existing land use. (weighted at 40%) Data Used: CLC_v3_Poly (from Florida FWC) Based on the site codes the existing land use was reclassified to the following values: 9 = Existing Agriculture 7 = Undeveloped Lands 5 = Wetlands and Marshes 3 = Rural Open Pine, Rural Open Land and Clear Cuts 1 = Developed Lands, Utilities, Transportation and Open Water

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203 | Page A 2.1: Identify the physical suitability for crop production. (weighted at 70%) Data Used: A 2.1.1: Soil Suitability (weighted at 50%) A 2.1.2: Existing Row Crop Production (weighted at 10%) A 2.1.3: Existing Land Use (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights.

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204 | Page A 2.2.1: Identify suitable land value. (weighted at 20%) Data Used: parcles_14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) A feature class was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function.

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205 | Page A 2.2.2: Identify proximity to roads (weighted at 40%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived from a zonal statistics function.

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206 | Page A 2.2.3: Identify proximity to markets. (weighted at 40%) Data Used: par_cit ylm_2011 (from FGDL.org) CLC_v3_Poly (from Florida FWC) Markets were defined as city limits as identified in the parcel data. The distances from the markets were rated based on the mean and standard deviation derived from a zonal statistics function.

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207 | Page A 2.2: Identify the economic suitability for crop production. (weighted at 30%) Data Used: A 2.2.1: Land Value Suitability (weighted at 20%) A 2.2.2: Road Proximity (weighted at 40%) A 2.2.3: Market Proximity (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights.

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208 | Page A 2: Identify the suitability for crop production. (weighted at 20%) Data Used: A 2.1: Physical Suitability (weighted at 60%) A 2.2: Economic Suitability (weighted at 40%) The weighted sum function was used to combine the two sub objectives at the above weights.

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209 | Page A 3.1.1: Identify soils suitable for timber production. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated bas ed on three categories and then combined with a weighted sum function. Drainage Class (weighted at 33%) 9 = Well Drained and Moderately Well Drained 7 = Somewhat Poorly Drained 5 = Poorly Drained 1 = Excessively Drained and Very Poorly Drained Non Irrigation Capacity Class (weighted at 33%) 9 = Class 3 8 = Class 4 7 = Class 5 1 = Classes 8 6 Farmland Class (weighted at 34%) 9 = Not Prime Farmland 1 = Farmland of Unique Importance

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210 | Page A 3.1.2: Identify existing timber production. (weighted at 10%) Da ta Used: CLC_v3_Poly (from Florida FWC) Existing timber production was selected from the site classification and then given the following values: 9 = 18333 (Tree Plantations) 9 = 183332 (Coniferous Plantations) 1 = All other classes

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211 | Page A 3.1.3: Identify existing land use. (weighted at 40%) Data Used: CLC_v3_Poly (from Florida FWC) Based on the site codes the existing land use was reclassified to the following values: 9 = Existing Agriculture 7 = Undeveloped Lands 5 = Rural Open Pine 3 = Wetland s, Marshes, Rural Open Land and Clear Cuts 1 = Developed Lands, Utilities, Transportation and Open Water

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212 | Page A 3.1: Identify the physical suitability for timber production. (weighted at 55%) Data Used: A 3.1.1: Soil Suitability (weighted at 50%) A 3.1.2: Existing Timber Production (weighted at 10%) A 3.1.3: Existing Land Use (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights.

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213 | Page A 3.2.1: Identify suitable land value. (weighted at 20%) Data Used: parcles_14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) A feature class was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function.

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214 | Page A 3.2.2: Identify proximity to roads (weighted at 40%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived fr om a zonal statistics function.

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215 | Page A 3.2.3: Identify proximity to markets. (weighted at 40%) Data Used: parcles_14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) Markets were defined as saw mills as identified in the parcel data. The distances from the markets were rated based on the mean and standard deviation derived from a zonal statistics function.

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216 | Page A 3.2: Identify the economic suitability for timber production. (weighted at 27%) Data Used: A 3.2.1: Land Value Suitability (weig hted at 20%) A 3.2.2: Road Proximity (weighted at 40%) A 3.2.3: Market Proximity (weighted at 40%) The weighted sum function was used to combine the three sub objectives at the above weights.

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217 | Page A 3.3: Identify existing and potential sustainable timber production. (weighted at 18%) Data Used: forstry_v4 (from FNAI.org) Sustainable forestry data was reclassified based on the priority levels as identified below: 9 = Priority Level 2 8 = Priority Level 3 6 = Priority Level 5 1 = Not a priority area

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218 | Page A 3: Identify the suitability for timber production (weighted at 40%) Data Used: A 3.1: Physical Suitability (weighted at 50%) A 3.2: Economic Suitability (weighted at 33.5%) A 3.3: Sustainable Timber Suitability (weighted at 16.5%) The weighted sum function was used to combine the three objectives at the above weights.

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219 | Page A: Identify the suitability for agriculture production. Data Used: A 1: Livestock Suitability (weighted at 40%) A 2: Crop Suitability (weighted at 20%) A 3: Timber Suitability (weighted at 40%) The weighted sum function was used to combine the three goals at the above weights.

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220 | Page B: Conservation Suitability Analysis B 1: Identify significant lands for biodiversity. (if a 9, then 9, otherwise weighted at 25%) B 1.1: Identify lands with strategic habitats. (weighted at 30%) B 1.2: Identify lands with potential habitat richness. (weighted at 10%) B 1.3: Identify lands with rare species. (weighted at 30%) B 1.4: Identify lands with priority natural communities. (weighted at 30%) B 2: Identify significant lands for protecting water quality. (if a 9, then 9, weighted at 25 %) B 2.1: Identify significant lands for surface water quality. (combine using a max appr oach) B 2.1.1: Identify lands with functional wetlands. (weighted at 34%) B 2.1.2: Identify lands with significant surface waters. (weighted at 33%) B 2.1.3: Identify lands with natural floodplain functions. (weighted at 33%) B 2.2: Identify significant lands for ground water quality . (combine using a max approach) B 3: Identify significant lands for protecting connectivity. (weighted at 40%) B 3.1: Identify lands with priority for wild life corridors. (weighted at 75%) B 3.2: Identify lands significant for landscape integrity. (weighted at 25%) B 4: Identify lands suitable for perman ent conservation. (weighted at 1 0%) B 4.1: Identify lands in proximity to existing conservation lands. (weighted at 75%) B 4.2: Identify lands proposed for future conservati on. (weighted at 25%)

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221 | Page B 1.1: Identify lands with strategic habitats. (weighted at 30%) Data Used: SHCA_modified_for_FL_Forever_v4 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 2 8 = Priority Level 3 6 = Priority Level 5 1 = Not a priority area

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222 | Page B 1.2: Identify lands with potential habitat richness. (weighted at 10%) Data Used: phrich_clip3 (from FNAI.org) The data was reclassified based on the number of potential species. 9 = 7 or more species 8 = 5 6 species 7 = 3 4 species 6 = 1 2 species 1 = No species

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223 | Page B 1.3: Identify lands with rare species. (weighted at 30%) Data Used: Rare_Species_Habitat_Cons_Priorities_v4 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 3 8 = Priority Level 4 7 = Priority Level 5 6 = Priority Level 6 1 = Not a priority area

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224 | Page B 1.4: Identify lands with priority natural communities. (weighted at 30%) Data Used: natcom_clip3 (from FNAI.org ) CLC_v3_Poly (from Florida FWC) The natcom data was reclassified based on the priority levels. 9 = Priority Level 1 8 = Priority Level 2 The CLC data was reclassified based on the site codes. 7 = Natural Lands 6 = Semi Natural Lands, Timber Lands and Parks 1 = Developed Lands The two reclassified data sets were combined with a raster calculator.

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225 | Page B 1: Identify significant lands for biodiversity. (if a 9, then 9, otherwise weighted at 25%) Data Used: B 1.1: Strategic Habitats (weighted at 30%) B 1.2: Potential Habitat Richness (weighted at 10%) B 1.3: Rare Species Habitat (weighted at 30%) B 1.4: Natural Community Priorities (weighted at 30%) The weighted sum function was used to combine the four objectives at the above weights.

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226 | Page B 2.1.1: Identify lands with functional wetlands. (weighted at 34%) Data Used: Functional_Wetlands_v4 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 1 8 = Priority Level 2 7 = Priority Level 3 6 = Priority Level 4 5 = Priority Level 5 4 = Priority Level 6 1 = Not a priority area

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227 | Page B 2.1.2: Identify lands with significant surface waters. (weighted at 33%) Data Used: Significant_Surface_Waters_v4 (from FNAI) The data was reclassified based on the identified priorities. 9 = Priority Level 2 7 = Priority Level 4 6 = Priority Level 5 5 = Priority Level 6 4 = Priority Level 7 1 = Not a priority area

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228 | Page B 2.1.3: Identify lands with natural floodplain functions. (weighted at 33%) Data Used: Natural_Floodplain_v4 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 1 8 = Priority Level 2 7 = Priority Level 3 6 = Priority Level 4 5 = Priority Level 5 4 = Priority Level 6 1 = Not a priority area

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229 | Page B 2.1: Identify significant lands for surface water quality. (combined using a max approach) Data Used: B 2.1.1: Functional Wetland Priorities (weighted at 34%) B 2.1.2: Significant Surface Water Priorities (weighted at 33%) B 2.1.3: Natural Floodplai n Priorities (weighted at 33%) The weighted sum function was used to combine the three sub objectives at the above weights.

PAGE 231

230 | Page B 2.2: Identify significant lands for ground water quality. (combined using a max approach) Data Used: Aquifer_Recharge_v4 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 2 8 = Priority Level 3 7 = Priority Level 4 6 = Priority Level 5 5 = Priority Level 6 1 = Not a priority area

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231 | Page B 2: Identify signi ficant lands for protecting water quality. (if a 9, then 9, otherwise weighted at 25%) Data Used: B 2.1: Surface Water Suitability (combined using a max approach) B 2.2: Ground Water Suitability (combined using a max approach) The two objectives were comb ined using cell statistics where only the maximum values of any cell would be represented.

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232 | Page B 3.1: Identify lands with priority for wild life corridors. (weighted at 75%) Data Used: grnway_clip3 (from FNAI.org) The data was reclassified based on the identified priorities. 9 = Priority Level 1 8 = Priority Level 2 1 = Not a priority area

PAGE 234

233 | Page B 3.2: Identify lands that are significant for landscape integrity. (weighted at 25%) Data Used: lsinteg_clip3 (from FNAI.org) The data was reclassified based on the identified level of integrity. The higher the level the higher the identified integrity class. 9 = Level 9 8 = Level 8 7 = Level 7 5 = Level 5 4 = Level 4 3 = Level 3 1 = Not a priority area

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234 | Page B 3: Identify significant lands for protecting connectivity. (weighted at 40%) Data Used: B 3.1: Corridor Priorities (weighted at 75%) B 3.2: Landscape Integrity Priorities (weighted at 25%) The weighted sum function was used to combine the two objectives at the above weights.

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235 | Page B 4.1: Identify lands in proximity to existing conservation. (weighted at 75%) Data Used: flma_201412 (from FNAI.org) CLC_v3_Poly (from Florida FWC) mitigation_banks (from Florida DEP) The distance from the mitigation banks and existing conservatio n and the land uses were reclassified into the following: 9 = 0 1/2 miles 9 = Natural and Semi Natural Lands 7 = 1/2 1 miles 5 = Timber Lands 5 = 1 2 miles 3 = Parks 1 = More than 2 miles 1= Developed Lands The combine function was then use d and the combinations were ranked as follows: X = (Distance/Land Use) 9 = (9/9) 5 = (9/3) (5/5) (7/3) 8 = (7/9) 4 = (5/3) 7 = (9/5) (5/9) 3 = (9/1) (1/9) (7/1) 6 = (7/5) 1 = (1/5) (5/1)

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236 | Page B 4.2: Identify lands proposed for future conservation (weighted at 25%) Data Used: FFBOT_201408 (from FNAI.org) Proposed conservation areas became a 9 and all other land became a 1.

PAGE 238

237 | Page B 4: Identify lands suitable for permanent conservation. (we ighted at 10%) Data Used: B 4.1: Proximity to Existing Conservation (weighted at 75%) B 4.2: Proposed Conservation Lands (weighted at 25%). The weighted sum function was used to combine the two objectives at the above weights.

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238 | Page B: Identify the suitability for conservation. Data Used: B 1: Significant Lands for Biodiversity (if a 9, then 9, otherwise weighted at 25%) B 2: Significant Lands for Water Quality (if a 9, then 9, otherwise weighted at 25%) B 3: Significant Lands for Conn ectivity (weighted at 40%) B 4: Significant Lands for Protection (weighted at 10%) A conditional statement was used in raster calculator to state that if B 1 or B 2 were a 9 then they would remain a 9. Otherwise the four goals would be weighted as indicate d above.

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239 | Page C: Urban Suitability Analysis C 1: Identify the suitability for residential use. (weighted at 50%) C 1.1: Identify the physical suitability for residential use. (weighted at 60%) C 1.1.1: Identify soil suitability. (weighted at 50%) C 1.1.2: Identify flood zone areas. (weighted at 50%) C 1.2: Identify the economic suitability for residential use. (weighted at 40%) C 1.2.1: Identify suitable land value. (weighted at 10%) C 1.2.2: Identify proximity to roads. (weighted at 20%) C 1.2.3: Identify proximity to existing commercial use. (weighted at 20%) C 1.2.4: Identify proximity to schools and hospitals. (weighted at 20%) C 1.2.5: Identify proximity to recreation areas. (weighted at 15%) C 1.2.6: Identify proximity to existing wat er service areas. (weighted at 15%) C 2: Identify the suitability for commercial use. (weighted at 25%) C 2.1: Identify the physical suitability for commercial use. (weighted at 60%) C 2.1.1: Identify soil suitability. (weighted at 50%) C 2.1.2: Identify flood zone areas. (weighted at 50%) C 2.2: Identify the economic suitability for commercial use. (weighted at 40%) C 2.2.1: Identify suitable land value. (weighted at 20%) C 2.2.2: Identify proximity to roads. (weighted at 25%) C 2.2.3: Identify proximity to existing commercial use. (weighted at 20%) C 2.2.4: Identify proximity to existing residential use. (weighted at 10%) C 2.2.5: Identify proximity to existing water service areas. (weighted at 25%) C 3: Identify the suitability for industrial use. (weigh ted at 25%) C 3.1: Identify the physical suitability for industrial use. (weighted at 60%) C 3.1.1: Identify soil suitability. (weighted at 50%) C 3.1.2: Identify flood zone areas. (weighted at 50%) C 3.2: Identify the economic suitability for industrial use. (weighted at 40%) C 3.2.1: Identify suitable land value. (weighted at 10%) C 3.2.2: Identify proximity to roads. (weighted at 30%) C 3.2.3: Identify proximity to rail. (weighted at 20%) C 3.2.4: Identify proximity to existing industrial use. (weighted at 10%) C 3.2.5: Identify proximity to existing residential use. (weighted at 10%) C 3.2.6: Identify proximity to existing water service areas. (weighted at 20%)

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240 | Page C 1.1.1: Identify soils suitable for residential development. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated based on two categories and then combined with a weighted sum function. Drainage Class (weighted at 50%) 9 = Excessively Drained 8 = Well Drained 7 = Moderately Well Drained 5 = Somewhat Poorly Drained 3 = Poorly Drained 1 = Very Poorly Drained ENGLRSDCD (weighted at 50%) 9 = Not Limited 7 = Somewhat Limited 1 = Very Limited and Not Rated

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241 | Page C 1.1.2: Identify flood zone areas. (weighted at 50%) Data Used: dfirm_fldhaz_mar14 (from FGDL.org) The flood zone data was reclassified based on the floodplain class to the following values: 9 = Outside the Floodplain 5 = 500 Year Floodplain 1 = 100 Year Floodplain

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242 | Page C 1.1: Identify the physical suitability for residential use. (weighted at 60%) Data Used: C 1.1.1: Soil Suitability (weighted at 50%) C 1.1.2: Flood zones (weighted at 50%) The weighted sum function was used to combine the two sub objectives at the above weights.

PAGE 244

243 | Page C 1.2.1: Identify suitable land value for res idential development. (weighted at 10%) Data Used: parcels_2014 (from FGDL.org) CLC_v3_Poly (from Florida FWC) A feature class was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function.

PAGE 245

244 | Page C 1.2.2: Identify proximity to roads. (weighted at 20%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mea n and standard deviation derived from a zonal statistics function.

PAGE 246

245 | Page C 1.2.3: Identify proximity to existing commercial areas (weighted at 20%) Data Used: CLC_v3_Poly (from Florida FWC) The distance from commercial areas were ranked based on the mean and standard deviation derived from a zonal statistics function.

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246 | Page C 1.2.4: Identify proximity to schools and hospitals. (weighted at 20%) Data Used: gc_schools_may12 (from FGDL.org) gc_hospitals_feb13 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from schools and hospitals were ranked based on the mean and standard deviation derived from a zonal statistics function. The weighted sum function was used to combine the two data sets at the following weights: Schools (weighted at 60%) Hospitals (weighted at 40%)

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247 | Page C 1.2.5: Identify proximity to recreation areas (weighted at 15%) Data Used: gc_parksbnd_aug14 (from FGDL.org) existing_trails_jul12 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distan ce from the parks and trails data was ranked based on the mean and standard deviation derived from a zonal statistics function.

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248 | Page C 1.2.6: Identify proximity to existing water infrastructure. (weighted at 15%) Data Used: pwsab (from SJRWMD) CLC_v3_Poly (from Florida FWC) The distance from the existing water service areas was ranked based on the mean and standard deviation derived from a zonal statistics function.

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249 | Page C 1.2: Identify the economic suitability for residential development. (weighted at 40%) Data Used: C 1.2.1: Land Value Suitability (weighted at 10%) C 1.2.2: Proximity to Roads (weighted at20%) C 1.2.3: Proximity to Existing Commercial (weighted at 20%) C 1.2.4 : Proximity to Schools and Hospitals (weighted at 20%) C 1.2.5: Proximity to Recreation (weighted at 15%) C 1.2.6: Proximity to Existing Water Service Areas (weighted at 15%) The weighted sum function was used to combine the six sub objectives at the above weights.

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250 | Page C 1: Identify the suitability for residential development. (weighted at 50%) Data Used: C 1.1: Physical Suitability (weighted at 60%) C 1.2: Economic Suitability (weighted at 40%) The weighted sum function was used to combine the two o bjectives at the above weights.

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251 | Page C 2.1.1: Identify soils suitable for commercial development. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated based on two categories and then combined with a weighted sum function. Drainage Class (weighted at 50%) 9 = Excessively Drained 8 = Well Drained 7 = Moderately Well Drained 5 = Somewhat Poorly Drained 3 = Poorly Drained 1 = Very Poorly Drained ENGLRSDCD (weighted at 50%) 9 = Not Limited 7 = Somewhat Limited 1 = Very Limited and Not Rated

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25 2 | Page C 2.1.2: Identify flood zone areas. (weighted at 50%) Data Used: dfirm_fldhaz_mar14 (from FGDL.org) The flood zone data was reclassified based on the floodplain class to the following values: 9 = Outside the Floodplain 5 = 500 Year Floodplain 1 = 100 Year Floodplain

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253 | Page C 2.1: Identify the physical suitability for commercial use. (weighted at 60%) Data Used: C 2.1.1: Soil Suitability (weighted at 50%) C 2.1.2: Flood zones (weighted at 50%) The weighted sum function was used to combine the two sub objectives at the above weights.

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254 | Page C 2.2.1: Identify suitable land value for commercial development. (weighted at 20%) Data Used: parcels_2014 (from FGDL.org) CLC_v3_Poly (from Florida FWC) A feature c lass was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function.

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255 | Page C 2.2.2: Identify proximity to roads. (weighted at 25%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived from a zonal statistics function.

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256 | Page C 2.2.3: Identify proximity to existing com mercial areas (weighted at 20%) Data Used: CLC_v3_Poly (from Florida FWC) The distance from commercial areas were ranked based on the mean and standard deviation derived from a zonal statistics function.

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257 | Page C 2.2.4: Identify proximity to existing residential use. (weighted at 10%) Data Used: CLC_v3_Poly (from Florida FWC) The distance from residential areas were ranked based on the mean and standard deviation derived from a zonal statistics function.

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258 | Page C 2.2.5: Identify proximity to existing water infrastructure. (weighted at 25%) Data Used: pwsab (from SJRWMD) CLC_v3_Poly (from Florida FWC) The distance from the existing water service areas was ranked based on the mean and standard deviation derived fr om a zonal statistics function.

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259 | Page C 2.2: Identify the economic suitability for commercial development. (weighted at 40%) Data Used: C 2.2.1: Land Value Suitability (weighted at 20%) C 2.2.2: Proximity to Roads (weighted at25%) C 2.2.3: Proximity to Existing Commercial (weighted at 20%) C 2.2.4: Proximity to Existing Residential (weighted at 10%) C 2.2.5: Proximity to Existing Water Service Areas (weighted at 25%) The weighted sum function was used to combine the five sub objectives at th e above weights.

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260 | Page C 2: Identify the suitability for commercial development. (weighted at 25%) Data Used: C 2.1: Physical Suitability (weighted at 60%) C 2.2: Economic Suitability (weighted at 40%) The weighted sum function was used to combine th e two objectives at the above weights.

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261 | Page C 3.1.1: Identify soils suitable for industrial development. (weighted at 50%) Data Used: nrcs_soils_jun_12 (from FGDL.org) The soils were rated based on two categories and then combined with a weighted sum function. Drainage Class (weighted at 50%) 9 = Excessively Drained 8 = Well Drained 7 = Moderately Well Drained 5 = Somewhat Poorly Drained 3 = Poorly Drained 1 = Very Poorly Drained ENGLRSDCD (weighted at 50%) 9 = Not Limited 7 = Somewhat Lim ited 1 = Very Limited and Not Rated

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262 | Page C 3.1.2: Identify flood zone areas. (weighted at 50%) Data Used: dfirm_fldhaz_mar14 (from FGDL.org) The flood zone data was reclassified based on the floodplain class to the following values: 9 = Outside the Floodplain 5 = 500 Year Floodplain 1 = 100 Year Floodplain

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263 | Page C 3.1: Identify the physical suitability for industrial use. (weighted at 60%) Data Used: C 3.1.1: Soil Suitability (weighted at 50%) C 3.1.2: Flood zones (weighted at 50%) The weighted sum function was used to combine the two sub objectives at the above weights.

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264 | Page C 3.2.1: Identify suitable land value for industrial development. (weighted at 10%) Data Used: parcels_2014 (from FGDL.org) CLC_v3_Poly (from Florida FWC ) A feature class was created to calculate value per acre of land based off of the just value class. The land value was rated based on the mean and standard deviation derived from a zonal statistics function.

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265 | Page C 3.2.2: Identify proximity to roads. (weighted at 30%) Data Used: majrds_oct14 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived from a zonal statistics function.

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266 | Page C 3.2.3: Identify proximity to rail. (weighted at 20%) Data Used: rails_transtat_2014 (from FGDL.org) CLC_v3_Poly (from Florida FWC) The distance from roads was ranked based on the mean and standard deviation derived from a zonal statistics function.

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267 | Page C 3.2.4: Identify proximity to existing industrial use. (weighted at 10%) Data Used: CLC_v3_Poly (from Florida FWC) The distance from industrial areas were ranked based on the mean and standard deviation derived from a zonal statistics function .

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268 | Page C 3.2.5: Identify proximity to existing residential use. (weighted at 10%) Data Used: CLC_v3_Poly (from Florida FWC) The distance from residential areas were ranked based on the mean and standard deviation derived from a zonal statistics function.

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269 | Page C 3.2.6: Identify proximity to existing water infrastructure. (weighted at 20%) Data Used: pwsab (from SJRWMD) CLC_v3_Poly (from Florida FWC) The distance from the existing water service areas was ranked based on the mean and standard deviation derived from a zonal statistics function.

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270 | Page C 3.2: Identify the economic suitability for industrial development. (weighted at 40%) Data Used: C 3.2.1: Land Value Suitability (weighted at 10%) C 3.2.2: Proximity to Roads (wei ghted at30%) C 3.2.3: Proximity to Rail (weighted at 20%) C 3.2.4: Proximity to Existing Industrial (weighted at 10%) C 3.2.5: Proximity to Existing Residential (weighted at 10%) C 3.2.6: Proximity to Existing Water Service Areas (weighted at 20%) The weighted sum function was used to combine the six sub objectives at the above weights.

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271 | Page C 3: Identify the suitability for industrial development. (weighted at 25%) Data Used: C 1.1: Physical Suitability (weighted at 60%) C 1.2: Economic Suitabil ity (weighted at 40%) The weighted sum function was used to combine the two objectives at the above weights.

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272 | Page C: Identify the suitability for urban development. Data Used: C 1: Residential Suitability (weighted at 50%) C 2: Commercials Suitability (weighted at 25%) C 3: Industrial Suitability (weighted at 25%) The weighted sum function was used to combine the three goals at the above weights.

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273 | Page Farmton Land use Conflict Grid Data Used: A: Agriculture Suitability B: Conservation Suitability C: Urban Suitability The three suitability rasters had all existing conservation lands, developed lands and open waters removed for the conflict analysis. The data sets were then converted from a 1 9 scale to a 1 3 scale. Finally t he data was combined into one grid.

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274 | Page

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275 | Page Appendix D : Farmton Alternate Plans Farmton Alternate Plan #1 Farmton Alternate Plan #2 Farmton Alternate Plan #3 Farmton Alternate Plan #4

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276 | Page Farmton Current Plan

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277 | Page Farmton Alternate Plan #1

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278 | Page Farmton Alternate Plan #2

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279 | Page Farmton Alternate Plan #3

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280 | Page Farmton Alternate Plan #4

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