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Wetland avifauna use of littoral habitat prior to extreme habitat modification in Lake Tohopekaliga, Florida

University of Florida Institutional Repository

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WETLAND AVIFAUNA USAGE OF LITTO RAL HABITAT PRIOR TO EXTREME HABITAT MODIFICATION IN L AKE TOHOPEKALIGA, FLORIDA By JANELL MARIE BRUSH A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Janell Marie Brush

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This document is dedicated to my late gra ndmother, Alice Brush and to my family, all whom appreciate the value of a good education.

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ACKNOWLEDGMENTS I would first like to thank Duke Hamm ond, formerly of the Florida Fish and Wildlife Conservation Commission, who inspired and encouraged me to go to graduate school. I would like to thank my committee, Wiley Kitchens, Ken Meyer and Madan Oli, for their editorial comments support, encouragement and patience while I worked through the details of this projec t. I would especially like to thank my chief advisor, Dr. Wiley Kitchens, who provided me with inva luable knowledge of the field of wetland ecology and who has guided me and given me countless opportunities to grow and learn over the last six years of c onducting projects under his dire ction and leadership. A large thank you goes out to the project fiel d assistants. Without their expert bird identification skills, hard work, insight and atte ntion to detail, this project would not have been so successful. These people include Scott Berryman, Adam Cross, Brenda Calzada, Jamie Duberstein, John Davis, Samantha Musgrave, Vanessa Rumancik, John David Semones and Zach Welch. Special thanks go to Scott Berryman and Jamie Duberstein, who each dedicated two full year s to the Lake Tohopekaliga bi rd project and kept me on my feet. I would also like to thank the brave field crews, led by Melissa DeSa, who have continued the project post-enhancement despite hazardous working conditions and logistical nightmares. These people include Melinda Conners, Jami e Duberstein, Carolyn Enloe, Becky Hylton, Allison Pevler, Derek Piotrowicz, James Reyes, Jonathan Saunders, and Gina Zimmerman.

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5 I want to thank the Florida Fish and Wildlife Conservation Commission for funding this important long term project. I hope proj ects like the Lake Toho project will continue to be a priority as we continue to bri dge the gap between research and management. I am forever in debt to many graduate st udent colleagues, Sonia Canavelli, Jamie Duberstein, Julien Martin, Ann Marie Muen ch, Arpat Ozgul, Hardin Waddle and Zach Welch. Each one of these individuals provided invaluable knowledge and they brainstormed with me and assisted me with various phases of this project and analyses. A heartfelt thank you goes out to the Distance Sampling Development Team, without whom I would still be working on analyz ing the large amount of data this project produced. Thanks go to Steve Buckland, Len Thomas, Jon Bishop, and Tiago Marques. They not only taught me all there is to know about Distance sampling but became my support system. Their excitement for distan ce sampling and my project gave me the motivation I needed to finish. Last but definitely not least I would like to thank my family, Mary Ann Kalinay, Carl and Jan Brush, and Julie Brush, for their continued support as I brave new trails and adventures in the field of wetland ecology and al so in life. Lastly, I want to thank my Gainesville family, and local support syst em, Gina Zimmerman, James Reyes, Toho Bear, Shadow Bug, and the late Cosmo. If it was not for their continuing support, patience, unconditional love and understand ing, I would have never been able to complete this document.

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vi TABLE OF CONTENTS page ACKNOWLEDGMENTS...................................................................................................4 LIST OF TABLES.............................................................................................................ix LIST OF FIGURES...........................................................................................................xi ABSTRACT.....................................................................................................................xv i CHAPTER 1 INTRODUCTION........................................................................................................1 Florida Lakes Ecosystem..............................................................................................1 Lake Tohopekaliga.......................................................................................................5 Lake History and Management.............................................................................7 Previous Studies in Florida..................................................................................10 Lake Tohopekaliga Bird Study............................................................................13 Project Objectives................................................................................................14 2 STUDY AREA AND ANALYSIS METHODS........................................................17 Introduction.................................................................................................................17 Regional Scale Community Monitoring..............................................................18 Whole Lake Community Monitoring..................................................................20 Focal Species..............................................................................................................22 Distance Sampling Methods.......................................................................................26 Assumptions of Distance Sampling.....................................................................27 Parametric Models within DISTANCE...............................................................27 Clusters within DISTANCE................................................................................28 Data Truncation in Distance................................................................................28 Detection Covariates used within Distance.........................................................29 Density estimations.............................................................................................29 3 AVIAN DENSITIES AND VARIABLES IN STUDY AREAS...............................31 Survey Methods..........................................................................................................31 Analysis Methods.......................................................................................................34 Densities..............................................................................................................34

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vii Observer.......................................................................................................34 Vegetation Structure.....................................................................................35 Spatial Variations................................................................................................35 Temporal and Environmental Variations............................................................36 Results........................................................................................................................ .39 Spatial Variations................................................................................................39 Environmental and Temporal Variables..............................................................45 Discussion...................................................................................................................61 Spatial Variations................................................................................................61 Temporal and Environmental Variations............................................................65 4 AVIAN DENSITIES AND VARIABLES IN WHOLE LAKE SAMPLING...........71 Introduction.................................................................................................................71 Analysis Methods.......................................................................................................72 Densities..............................................................................................................72 Spatial Variations................................................................................................74 Temporal and Environmental Variations............................................................74 Results........................................................................................................................ .76 Spatial Variations................................................................................................77 Temporal and Environmental Variations............................................................81 Discussion...................................................................................................................95 Spatial Variations................................................................................................95 Temporal and Environmental Variations............................................................98 5 DISCUSSION OF STUDY AREA VS. WHOLE LAKE SAMPLING...................101 Introduction...............................................................................................................101 Caveats of Point Transect Distance Sampling..........................................................101 Caveats of Line Transect Distance Sampling...........................................................104 Spatial Variations of Point and Line Transects........................................................106 Conclusions from Study Area and Whole Lake Sampling.......................................109 American Coot...................................................................................................110 Anhinga.............................................................................................................111 Belted Kingfisher...............................................................................................113 Boat-tailed Grackle............................................................................................114 Cattle Egret........................................................................................................115 Common Moorhen.............................................................................................115 Florida Sandhill Crane.......................................................................................117 Glossy Ibis.........................................................................................................119 Great Blue Heron...............................................................................................121 Great Egret.........................................................................................................123 Green Heron......................................................................................................125 Least Bittern......................................................................................................127 Little Blue Heron...............................................................................................129 Limpkin.............................................................................................................130 Pied-billed Grebe...............................................................................................131

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viii Purple Gallinule.................................................................................................132 Ring-necked Duck.............................................................................................132 Red-winged Blackbird.......................................................................................134 Snowy Egret......................................................................................................135 Snail Kite...........................................................................................................137 Tricolored Heron...............................................................................................140 Summary and Future Analyses.................................................................................142 Future Analyses........................................................................................................143 6 AVIAN SPECIES RICHNESS WI THIN THE LITTORAL ZONE........................145 Analysis Methods.....................................................................................................145 Results.......................................................................................................................1 47 Study Area Sampling.........................................................................................147 Lake Wide Sampling.........................................................................................149 Discussion.................................................................................................................150 7 PROJECT SUMMARY............................................................................................154 APPENDIX A SAMPLE DATES FOR THE PREENHANCEMENT BIRD STUDY..................158 B AVIAN SPECIES LIST FROM STUDY AREA AND WHOLE LAKE SAMPLING..............................................................................................................160 C AVIAN FOCAL SPECIES ESTIMATED DENSITIES..........................................166 D DISTANCE ANALYSES MODEL PARAMETERS..............................................176 E GENERALIZED LINEAR MODELS.....................................................................179 F AVIAN SPECIES RICHNESS TABLES................................................................183 LIST OF REFERENCES.................................................................................................186 BIOGRAPHICAL SKETCH...........................................................................................196

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ix LIST OF TABLES Table page 3-1 Table of predictions for focal species for study area sampling................................38 3-2 Focal species with significant differe nces between density estimates for study areas 1 and 2.............................................................................................................40 3-3 Focal species with significant differe nces between density estimates for study areas 1 and 3.............................................................................................................42 3-4 Focal species with significant differe nces between density estimates for study areas 2 and 3.............................................................................................................44 3-5 Environmental and temporat variables th at influenced density estimates for focal species in study area sampling.................................................................................46 4-1 Predictions for line transect type used by each focal species...................................75 4-2. Table of predictions for whole lake sampling............................................................76 4-3 Focal species with significant differe nces between density estimates on inside vs. outside line transects...........................................................................................77 4-4 Focal species with significant differe nces between density estimates on inside vs. previously scra ped line transects........................................................................79 4-5 Focal species with significant differe nces between density estimates on outside vs. previously scra ped line transects........................................................................80 4-6 Environmental and temporatl variable th at influenced density estimates for focal species in whole lake sampling................................................................................82 A-1 Week number of sample and corresponding starting sampling day.......................158 A-2 Sample dates corresponding to whole lake surveys during the pre-enhancement avian community monitoring study........................................................................159 B-1 Species seen on the lake that were Flor ida designated species of special concern, and federally threatened or endangered..................................................................160 B-2 Species list from the study area point transect sampling.......................................161

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x B-3 Species list from the whole lake line transect surveys...........................................164 C-1 Estimated densities for study area (point transect) samples...................................167 C-2 Densities estimates and the correspondi ng standard error and variance for avian species by study area..............................................................................................172 C-3 Density estimates for focal species on line transect surveys. Sample date and species codes are used............................................................................................173 C-4 Density estimates by line tran sect type for focal species.......................................175 D-1 Analyses parameters for point tr ansect distance sampling for the most parsimonious model chosen model for each focal species.....................................177 D-2 Analyses parameters for line tran sect distance sampling for the most parsimonious model chosen model for each focal species.....................................178 E-1 Potential models for the study area anal yses which explain the response variable, density as a function of the predictor variables......................................................180 E-2 Potential models for the whole lake analyses which explain the response variable, density as a function of the predictor variables.......................................182 F-1 Species richness within the study areas by week of sample..................................184 F-2 Species richness for each m onthly whole lake sample..........................................185

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xi LIST OF FIGURES Figure page 1-1 Map of Lake Tohopekaliga and Florida Watershed...................................................6 1-2 Regulatory schedule on lake Toho (red lin e) and the actual stage levels on the lake during the pre-lake enhancement study..............................................................6 1-3 Historical stage data from the head water gauge station 61 on Lake Tohopekaliga...8 2-1 Study area locations on Lake Tohopekaliga.............................................................19 2-2 Study area setup indicating the point transect locations 1 – 32 within the planned treatment and control sites........................................................................................20 2-3 Map showing line transect locations within the littoral zone of Lake Tohopekaliga............................................................................................................21 2-4 The 1-4 ft. depth zones on Lake Tohopekaliga corresponding to the area of interest on the lake during the pre-lake enhancement studies..................................17 3-1 The bird blind setup for point transects on Lake Tohopekaliga...............................32 3-2 The value of differences in estima ted densities between study area 1 and study area 2 for focal bird species......................................................................................41 3-3 The value of differences in estima ted densities between study area 1 and study area 2 for focal species.............................................................................................42 3-4 The value of differences in estima ted densities between study area 1 and study area 3 for select bird species....................................................................................43 3-5 The value of differences in estimated densities (effect size ) between study area 1 and study area 3 for select bird species....................................................................43 3-6 The value of differences in estima ted densities between study area 2 and study area 3 for select bird species....................................................................................44 3-7 The value of differences in estima ted densities between study area 2 and study area 3 for select bird species....................................................................................45

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xii 3-8 Estimated densities for the great blue he ron within the lake littoral zone related to study area and lake stage......................................................................................47 3-9 Estimated densities for the common m oorhen within the lake littoral zone related to study area and lake stage..........................................................................48 3-10 Estimated densities for the limpkin within the lake littoral zone related to lake stage.......................................................................................................................... 49 3-11 Estimated densities for the glossy ibis within the lake littoral zone related to study area and lake stage..........................................................................................50 3-12 Estimated densities for the American coot during the winter season within the lake littoral zone related to study area and lake stage..............................................51 3-13 Estimated densities for the belted kingfisher during the summer and winter season within the lake littoral zone related to study ar ea and lake stage.................52 3-14 Estimated densities for the anhinga with in the lake littoral zone related to study area and season.........................................................................................................53 3-15 Estimated densities for the boat-tailed grackle within the lake littoral zone related to study area and season...............................................................................54 3-16 Estimated densities for the great egret w ithin the lake littoral zone related to season.......................................................................................................................55 3-17 Estimated densities for the ring-necked duck during the winter seasons within the lake littoral zone.................................................................................................56 3-18 Estimated densities for the least bitte rn during the breeding and summer seasons within the lake littoral zone......................................................................................57 3-19 Estimated densities for the snowy egret within the lake littoral zone related to study area and season...............................................................................................58 3-20 Estimated densities for the tricolored he ron within the lake littoral zone related to study area and season...........................................................................................59 3-21 Estimated densities for the snail kite with in the lake littoral zone related to lake stage.......................................................................................................................... 60 3-22 Estimated densities for the green heron within the lake littoral zone related to season.......................................................................................................................61 4-1 The value of differences in estimated densities between inside and outside line transect types............................................................................................................78

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xiii 4-2 The value of differences in estimated densities between inside and previously scraped line transect types.......................................................................................80 4-3 The value of differences in estimated densities between outside and previously scraped line transect types.......................................................................................81 4-4 Estimated densities for the anhinga duri ng the winter season w ithin the littoral zone..........................................................................................................................8 3 4-5 Estimated densities for the belted kingf isher during the winter season within the littoral zone...............................................................................................................84 4-6 Estimated densities for the ring-necked duck during the winter season within the littoral zone...............................................................................................................85 4-7 Estimated densities for the glossy ibis within the lake littoral zone related to season and lake stage................................................................................................86 4-8 Estimated densities for the tricolored he ron within the lake littoral zone related to season and lake stage...........................................................................................87 4-9 Estimated densities for the great egret w ithin the lake littoral zone related to season.......................................................................................................................88 4-10 Estimated densities for the little blue he ron within the lake littoral zone related to season...................................................................................................................89 4-11 Estimated densities for the snowy egret within the lake littoral zone related to season.......................................................................................................................90 4-12 Estimated densities for the Florida sandhi ll crane within the lake littoral zone related to season.......................................................................................................91 4-13 Estimated densities for the common m oorhen within the lake littoral zone related to season.......................................................................................................92 4-14 Estimated densities for the great blue he ron within the lake littoral zone related to season...................................................................................................................93 4-15 Estimated densities for the pied-billed gr ebe within the lake littoral zone related to season...................................................................................................................94 4-16 Estimated densities for the snail kite within the lake littoral zone related to season.......................................................................................................................95 5-1 Spatial relationship of point transect lo cations and line transect locations within study area 2.............................................................................................................109

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xiv 5-2 Spatial relationship of point transect lo cations and line transect locations within study area 1.............................................................................................................109 5-3 Estimated density for the anhinga within the study areas and along line transects during the winter season.........................................................................................112 5-4 Estimated density for the belted kingfi sher within the study areas and along line transects during the summer and winter seasons...................................................114 5-5 Estimated density for the common m oorhen within the study areas and along line transects during the pre-enhancement study...................................................117 5-6 Estimated density for the Florida Sandhill Crane within the study areas and along line transects during the pre enhancement study..........................................119 5-7 Estimated density for the glossy ib is within the study areas and along line transects during the pre-enhancement study..........................................................121 5-8 Estimated density for the great blue heron within the study areas and along line transects during the pre-enhancement study..........................................................123 5-9 Estimated density for the great egre t within the study areas and along line transects during the pre-enhancement study..........................................................125 5-10 Estimated density for the green he ron within the study areas and along line transects during the pre-enhancement study..........................................................127 5-11 Estimated density for the least bittern within the study areas and along line transects during the pre-enhancement study..........................................................128 5-12 Estimated density for the little blue heron within the study areas and along line transects during the pre-enhancement study..........................................................130 5-13 Estimated density for the ring-necked duck during the winter season within the study areas and along line transects.......................................................................133 5-14 Estimated density of red-winged blackbirds by study area....................................135 5-15 Estimated density for study area and w hole lake sampling for the snowy egret....137 5-16 Estimated density of snail kites for study area and whole lake sampling..............139 5-17 Estimated density by stage for the snail kite within the study areas and along line transects during the pre-enhancement study..........................................................140 5-18 Estimated density for the tricolored heron for study area and whole lake sampling.................................................................................................................142

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xv 6-1 Scatter plot of average air temperatur e vs. species richness estimate within the study areas..............................................................................................................148 6-2 Estimated species richness per week of sample.....................................................149 6-3 Estimated species richness per month of sample during th e initiation of the drawdown in the fall 2003......................................................................................150

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Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science WETLAND AVIFAUNA USAGE OF LITTO RAL HABITAT PRIOR TO EXTREME HABITAT MODIFICATION IN L AKE TOHOPEKALIGA, FLORIDA By Janell Marie Brush May 2006 Chair: Wiley M. Kitchens Major Department: Wildlife Ecology and Conservation Lake Tohopekaliga is the northernmost lake in the Kissimmee Chain of Lakes. The shallow lake is highly eutrophic in nature. This has caused “nuisance” vegetation to be excessively overgrown, encouraging organic sediment accumulation. The largest whole lake enhancement project ever attempted in the state of Florida was initiated on Lake Tohopekaliga during the winter 2003. The la ke levels were lowered and 7.3 million cubic meters (8 million cubic yards) of littoral shoreline habitat was removed. Little is known about how a project of this scale will impact the vegetation, herptofaunal, fish and avian communities which occupy these littoral habitats of the lake This study generates baseline data of the avian use patterns, a bundances, and richness with in the littoral zone for the two years before the enhancement project This is a long term project and the data collected prior to the lake enhancement will be used for future assessments post lake enhancement.

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xvii Distance sampling protocol which takes in to account detectability of the avian species was used to sample at the scale of the whole lake sampling (line transects) and study area sampling (point tran sects). Density estimates were generated for 21 focal species within the avian community within th e littoral zone. Gene ralized linear models were used to determine which environmenta l and temporal variables are driving the densities of the species. Spatial differences between the study area sampling as well as the whole lake sampling were determined and effective sampling methods were generated for each focal species. Season and lake stage were the variables which were driving the densities of many of the wetland dependent birds. When compari ng the results obtained from the two types of sampling, it was concluded that many bird species will move th roughout the littoral habitat in response to environm ental factors, especially lake stage. Avian use patterns within the littoral habitat were identified for each focal species. Estimates of species richness within the li ttoral zone were also obtained from the sampling. Species richness was negatively corr elated with average air temperature. Species richness also increased following a small scale drawdown and re-flooding event on the lake. The avian use of the littoral zone is dynamic and is dependent on the environmental, spatial and temporal pro cesses which are constantly changing. As research continues prior to the lake enhan cement, the long-term effects of the lake enhancement project can be assessed and pred ictions may be generated to determine the necessity of such large scale projects in the future.

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1 CHAPTER 1 INTRODUCTION Wetland dependent birds, which include bird s that use wetlands during some period during their life, whether as habitat for fora ging, nesting, roosting or for all three, have long been monitored in scientific studies beca use of their intrinsic conservation value and because they act as indicators of ecologi cal status (Furness and Greenwood 1993). Wetland birds integrate a variety of envir onmental factors which are difficult and expensive to measure individually (Furness and Greenwood 1993). As bioindicators, it is assumed that changes in the birds’ distri butions (habitat use patterns and abundances) will indicate the changes which have occurred in the independent variables which function as stressors (Kushlan 1993). Cairns (2000) states that the best way to resolve ambiguities about how water level manipula tions and managerial actions affect abundances of invertebrates and us e of habitat by birds is to test explicit hypotheses as an ecological experiment. This study is based on that premise and represents an attempt to provide critical measures of wetland use, a bundances and distributi on prior to the late 2003-2004 drawdown and scraping project on Lake Tohopekaliga, in central Florida. Florida Lakes Ecosystem The state of Florida has nearly 8,000 divers e natural lakes that range in size from 0.4 ha to over 180,000 ha (Shafer et al. 1986, Canfield, Jr. and Hoyer 1988). The majority of Florida lakes (80%) have surf ace areas that are less than 40 hectares (100 acres) in size. However, the largest lake, Lake Okeechobee, has a surface area greater than 183,000 hectares (450,000 acres), and is th e third largest freshwater lake located

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2 entirely within the United States (Brenner et al. 1990). These lakes generally have a large area:volume ratio due to the formation processes a nd the flat topography in the region (Brenner et al. 1990). Unlike the glacier-formed lakes of Northern United States, Florida lakes were chiefly formed by karst er osion, the collapse of the limestone bedrock substrate forming a solution lake, or by relict sea bottom depressions which filled in as the sea receded (McPherson and Halley 1996). The geology of the region combined with a subtropical climate with variable rainfall creates lim nology and hydrology unique to this region. Rains from summer thunderstorms and tropical systems in the late summer and autumn are highly variable. Due to the subtr opical climate, lake ev aporation is relatively constant from year to year (Brenner et al. 1990). Due to Florida’s topography, unevaporated water usually sinks rather than running off (Brenner et al. 1990). As a result, dry years are frequent and extreme and there is a 10% chance that rainfall will be 30% below normal in any year. What exists as “normal” is extreme variability, the condition limnologists call astatic, particularly with regard to depths and stages. In addition, shallow lakes of this nature t ypically have long stretches of undeveloped shoreline and expansive but lin ear littoral systems that are capable of supporting diverse aquatic vegetation types. It is the potential management of these littoral systems that provided the impetus for this study. This document will focus on the avian distribution, abundance and use of the littoral zone of one such lake, Lake Tohopekaliga (to be de scribed in a later section). In the context of this study, the littoral zone is defined as the eco tone between dry land and open water which spans into the maximu m depth at which plant growth occurs

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3 (Hoyer and Canfield 1994). These littoral zone s typically consist of heterogeneous patch mosaics that differ in their physio-chemical and biological properties from adjacent ecosystems (Pieczynska and Zalewski 1997) are characterized by high levels of biological diversity, but at the same time attr act human attention due to direct access to water resources and recreation. In add ition, these systems buffer ecological flows between terrestrial and aquatic ecosystems. They also have a possible role in the stability of the ecological systems that they de limit (Pieczynska and Zalewski 1997). In addition to being shallow biologically diverse systems, many Florida lakes are highly eutrophic in nature. Because lakes b ecome more eutrophic as they age, over time sediments nearest the bottom remain nutrient poor and the surface sediments are rich in organics (Likens 1972). In addition, shallow lakes of this type are less responsive to significant reductions in external nutrient load ing because the benthic-pelagic interactions tend to maintain high nutrient levels. For ex ample, nutrients are continually released from the bottom as a result of wind distur bance and tend to affect the entire water column. In addition to wind effects, nutrient releases or “internal loading” can result from gas bubble effects, high pH from intens e phytosynthesis, and from dissolved oxygen deficits at the sediment wate r interface (Cooke et al. 2005). In Florida this problem of internal loading is compounded by the accelerate d external loading associated with the urbanization of the state. With the rapid growth rate of human o ccupancy within the st ate of Florida came the need to control the natura l flow of water throughout the state. The first drainage canals were dug in the upper Kissimmee Rive r basin and between Lake Okeechobee and the Caloosahatchee River in the 1920’s. Lev ees were constructed around lakes to prevent

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4 flooding, and when they did not stand up to hurricane force conditions, flood control measures were initiated and the flow of water throughout the state was completely controlled by the 1960’s (McPherson and Halley 1996). Water level stabilization combines with nutrient loading and urban and agricultural runoff to lead to increasingly more eutrophic lakes. The eutrophic eff ects contribute to the proliferation and over abundance of undesirable vegeta tion in the littoral zone. Eutrophication in the Florida lakes cause s increased primary producer biomass, reduced water clarity, good growing condition for nuisance species, habitat degradation, and decreased lake volume (Cooke et al. 2005). The “nuisance” vegetation, such as cattails ( Typha spp.), pickerelweed ( Pontederia spp.), and the submersed hydrilla ( Hydrilla verticillata ), have become excessively overgrown in many Florida Lakes and controlling them has become a priority for managers. In order to combat littoral zone habitat degradation problems associated with lake eutrophication and the cumulative effects of an imposed stage regul ation schedule, the Florida Fish and Wildlife Conservation Commission (FFWCC), South Florida Water Management District (SFWMD), and Army Corps of Engineers (COE) have employed extreme drawdowns and occasionally mech anical removal of unwanted macrophytes (nuisance level pickerelweed, et c.) and associated organic sedi ment “muck” as well as aggressive herbicide applica tions in many Florida lakes in an attempt to manage these systems (HDR Engineering 1989, Moyer et al. 1995, SFWMD et al. 2004). Drawdowns have been used in lake management for many years to oxidize and consolidate flocculent sediments, to alter fish populations, and fo r aquatic weed control (Hoyer and Canfield 1997). The littoral system of Lake Tohopekaliga, located within the Kissimmee Chain of

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5 Lakes, and one of many eutrophic lakes in Florida, exhibits many of the over enrichment characteristics of other Florida lake s and is the focus of this study. Lake Tohopekaliga Lake Tohopekaliga (hereafter referred to as Lake Toho) is a shallow lake located in Osceola County, Florida (Figure 1-1). Its surface area covers 8,177 ha (20,204 acres) and has a mean depth of 2.13 meters (7 feet) at a maximum regulation stage of 55 feet NGVD. The lake has an expansive (2228 ha, 5507 acre) littoral zone of mixed emergents which comprises about 29% of the surface la ke area (ReMetrix, LLC 2003). Lake Toho drains a total area of about 340 square km (131 sq. miles) (HDR Engineering 1989) and is part of the Kissimmee watershed which covers approximately 3,000 square miles of south-central Florida (SFWMD et al. 2004). La ke Toho receives inflow from the Shingle Creek watershed; the East Lake Toho watershe d via Structure S-59; di rect precipitation; ground water seepage into the lake; 11 minor tributaries; and from unguaged flows (Fan and Lin 1984, HDR Engineering 1989). Lake Toho lies within the Osceola plain physiographic area. Th e lake is believed to have formed as a result of solution activ ity following the proce ss of geologic uplift. This process left behind a ridged, sand-coa ted limestone plain which was subject to solutioning, particularly in the lower areas be tween the ridges. Lake Toho resides in a basin composed of sands and silts underlai n by calcareous sands overlying limestone. Precipitation is its primary source of r echarge (Schiffer 1998). The lake, along with the other water bodies in the state of Florida, was drastically altered by the construction of the water control structur es and imposition of a regulatory schedule (Figure 1-2).

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6 Figure 1-1. Map of Lake Tohope kaliga and Florida Watershed. Figure 1-2. Regulatory schedul e on lake Toho (red line) and the actual stage levels on the lake during the pre-lake enhancement study.

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7 Lake History and Management The first major drainage and land re clamation project on Lake Toho was undertaken between 1882 – 1894. Disston’s Okeechobee Land C o. excavated a series of canals and ditches which linke d the upper Kissimmee basin’s principal lakes and cleaned and deepened the Kissimmee River (HDR E ngineering 1989). As early as the 1920’s 67 miles of canals had been dug throughout a 21,853 hectare (54,000 acr e) area to the east side of the lake around Shingle Creek and Boggy Creek basins (Blackman 1973). In the mid 1940’s the Army Corps of Engineers atte ntion had turned to developing means of flood control when two hurricanes caused extensive flooding in the Kissimmee area (HDR Engineering 1989). This project calle d for channelization of the Kissimmee River, rechannelization of some of the original uppe r basin canals, use of the upper basin lakes as storage/conservation areas, a nd the installation of a series of water control structures and levees. The astasis of lake water levels was replaced with the implementation of a water stage regulation schedule (Figure 1-2) By 1971 the project had been completed but not before the lake alterati ons as well as wastewater disc harge had drastically affected the water quality of the lake (Blake 1980, HDR Engineering 1989, Dierberg et al. 1988). Flooding and drying events in shallow lake systems are environmental disturbances which tend to maintain the spatial and tem poral heterogeneity and hence biodiversity (Pieczynska and Zalewski1997). In an attemp t to remediate the excessive growth of nuisance vegetation, the Florida Game and Freshwater Fish Co mmission (now FWC) implemented an extreme drawdown on Lake Toho in 1971 (SFWMD et al. 2004). The project was designed to consolidate bottom se diments and expand desirable aquatic plant communities by dewatering the lake to seasonal lows experienced historically by the lake (SFWMD et al. 2004). Lake Toho underwent scheduled drawdown events again in 1979,

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8 and 1987 to improve aquatic habitat for fisher ies (Figure 1-3). During the drawdown of 1987, mechanical removal of 172,024 cu meters (225,000 cu yards) of organic muck sediment was conducted in the littoral reaches of the southern area of the lake (FFWCC 2004). By the end of 1988 all direct and indi rect discharges to Lake Toho were ceased (HDR Engineering). Despite the disconti nuation of urban runoff, the removal of phosphorus from four sewage treatment plan ts, and the three extreme drawdowns, Lake Tohopekaliga, a nitrogen-limited lake, to pres ent date, has managed to remain eutrophic for over three decades (Dierberg et al. 1988). Lake Toho is currently collaboratively managed by Florida Fish and Wildlife Conservation Commission, South Florida Wa ter Management District, and The Army Corp of Engineers. The lake water levels are continuously managed for flood control and a schedule is followed throughout the year. However, flood control and navigation Figure 1-3. Historical stag e data from the headwater gauge station 61 on Lake Tohopekaliga. The years preceding the stabilized hydroperiod are seen, as well as the three scheduled drawdowns.

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9 represent concerns that often conflict with the desire to improve or maintain water quality. As in many other Florida lakes, “nuisance” vegetation, such as cattails ( Typha spp.), pickerelweed ( Pontederia spp.), and the submersed hydrilla ( Hydrilla verticillata ) become excessively overgrown, encouraging or ganic sediment “muck” accumulation. As a result of this accumulation there is an ove rall net decline in fish ery, habitat for some species, water quality, and recr eational access on the lake (M oyer et al. 1995, Cooke et al. 2005). In November 2003, the Florida Fish a nd Wildlife Conservation Commission initiated the Lake Tohopekaliga habitat en hancement project, which was the largest whole lake enhancement project ever attempted in the state of Florid a. The goal of the drawdown and muck removal project was to re-establish aquatic vegetation and improve lake habitat for sport fish, fish food organisms and wildlife. (FFWCC 2004). The lake level was lowered from 16.8 m (55.0 ft) to 14.9 m (49 ft) NGVD, and following the drawdown, an estimated 7.3 million cubic mete rs (8-million cubic yards), with 1,351 ha (3,339 acres) of shoreline habitat was remove d. This enhancement targeted the entire width of the littoral zone for removal, not only the organic berm. The main macrophyte community which was eliminated was the Pontederia cordata -dominated habitat throughout the lake. Twenty-nine in-lake spo il islands and many inland disposal islands were created from the scraped material ( FFWCC et al. 2004). On ce the water levels came back up to the normal stage regulation sc hedule, herbicide applications resumed as normal to keep the nuisance vegetation at bay. Although it has been documented that this type of management practice may be benefici al for some fish communities, (Dierberg et

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10 al. 1988, Moyer et al.1995, Allen et al. 2003), it is extremel y expensive and it has never been conducted at such a large s cale as the Lake Toho project. In addition to being expensive to remove unwanted vegetation there are also large uncertainties as to whether management will ha ve the predicted effects because of lack of clear understanding between results from sma ll-scale ecological experiments and large scale processes (Havens and Aumen 2000, Lindegarth and Chapman 2001). A comprehensive long term study was designed to capture the effects of a large scale habitat manipulation on the community assemb lages of vegetation, aquatic vertebrate, and avian communities which use or occupy th e littoral reaches of lake Toho. This aspect of the study being discussed here relate s to the avian community structure prior to lake enhancement activities. Previous Studies in Florida Many avian studies conducted within Florida, focus on birds in the marsh systems of south Florida, while few studies have exam ined the bird populati ons that use the lakes of Florida and how these populations may be affected by management actions (Hoyer and Canfield 1990). One study (Traut and Hostet ler 2003) examined avian use and behavior within Florida lake littoral zones in the Peace River Basin along developed vs. undeveloped shorelines. This study used count indexes along with behavior codes conducting surveys from a genoe to determine avian responses to shoreline developments. The authors concluded that wa terbird behavior is not associated with shoreline development (Traut and Hostetler 200 3). Studies relating to effects of habitat and environmental factors on avian community structure and abundan ces in the littoral habitats on Florida lakes are more common. A study conducted within the Winter Haven

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11 Chain of Lakes also used bird count data obtained from surveys i nvolving the use of a genoe (Huegel 1993) to determine habitat use within the littoral zo nes of the lakes. Wildlife surveys conducted on Orange Lake, in north central Florida, used point count data as well as sweep surveys (via air boat) to calculate dens ities (number of bird per unit area) of both individual species and al l species collectively within each habitat type (Sieving and Schaefer 1997). The resu lts were not quantita tive, however there seemed to be a correlation with increas ing bird densities with distance to the vegetation/water interface, with particular high numbers of bi rds associated with floating marsh habitat in close proximity to the shorel ine. Due to the cryptic species within the ciconiiformes (wading birds) group, these bird s were under-represented in the point count samples, and results from the airboat sw eep surveys were unreliable (Sieving and Schaefer 1997). Another study looked at factors influenc ing wintering waterfowl abundances in Lake Wales, Florida (Gasaway et al. 1977). This study used point index counts from set stations and determined correlations be tween species and aquatic vegetation ( Hydirlla ) present in the lake (Gasaway et al 1977). Plant commun ity use by wintering waterfowl was also the focus of another study c onducted on Lake Okeechobee (Johnson and Montalbano III 1984). Aerial censuses of ducks were conducted within the study areas to obtain count data used in the analyses. Also, on Lake Okeechobee, a study was conducted relating foraging habitat and sele ction among wading birds in relation to hydrology and vegetative cover (Smith et al 1995). Again, flight surveys were conducted to document the distribution and abundance of foraging wading birds on and adjacent to the lake. These flight surveys in cluded belt transects, margin transects, and

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12 count block surveys to obtain estimates of bird density. These results were used to produce bird density maps which were re lated to water levels and vegetation communities within the study area (Smith et al 1995). Raw counts of birds were used to produce population estimates compared with la ke stage. In addition to the studies designed to look at habitat preference of wetland birds, many studies have been conducted within the lake systems of Florida wh ich relate bird densities to water levels and management activities. A project examining the waterbird use of coastal impoundments and management implications in east-central Florida used count data to generate density estimates to relate with water depth (Breininger and Smith 1990) A project conduc ted by surveying the littoral zone of Lake Okeechobee by helicop ter determined wading bird abundance from count data related to water levels (David 1994). All of these studies employed a variety of different methods to obtain count indexes of the birds of interest; ho wever, none of these sampling methods take into account the detectability of the birds whic h were surveyed. The detectability of a species can be defined as the probability of detecting at le ast one individual of a given species in a particular sampling effort, given that individuals of that specie s are present in the area of interest during that sampling session (Boulinie r et al. 1998). Count index survey methods without taking into account de tectability tend to overestim ate densities and abundances for species that are obvious in behavior, large in stature, or often times are observed in large groups. Two studies that give an excelle nt account of the consequences of failure to adjust for detectability ar e Diefenbach et al. 2003 a nd Norvell et al. 2003. Making comparisons over time using index counts made at the same locations are compromised if

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13 habitat succession affects dete ctability, if observers change or during different seasons (Buckland 2004). Also, the resu lts tend to report highe r densities of birds associated with open areas or during specific seasons where the detectability of these birds is going to be higher. Without quantitative studi es in such systems it is hard to determine if the results are because birds actually use these areas more or is detectability a factor in the results. Even with all the information co llected within the littoral zone s of lakes in Florida, there is still little quantit ative information available on the relationship betw een wetland birds and environmental factors such as vegetation co ver or lake water leve ls. Other studies up to this date have not captured the effective density changes in various habitats. This study measures densities using a de parture from count indices. Lake Tohopekaliga Bird Study The Lake Toho bird study incorporates detect ability of bird species as a tool for the generation of density estimates. By us ing a sampling protocol that includes the detectability of the bird species I hope to generate density estimates in which obvious birds are not overestimated and cryptic bird s are not underrepresent ed. Also, by using this type of sampling, observer bias as well as bias associated with habitat type will be eliminated. The common assumption of e qual detectability of bird species when conducting bird point index counts has been fa lsified in many studi es that emphasize the importance of recognizing the heterogeneity in species detectability (Boulinier et al. 1998, Nichols et al. 1998, Nichol s et al. 2000, Rosenstock et al. 2002, Norvell et al. 2003, Buckland 2004). Detectability of bird sp ecies can depend on many things such as vegetation succession as seen by Bibby and Buckland (1987) and by observer differences as seen by Diefenbach et al. (2003). When conducting bird censuses one also must consider the time of year, time of day, a nd corresponding bird be haviors (cryptic or

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14 obvious) that can increase or decrease detecti on probability of the bird during that period of time (Marsden 1999). When conducting mixed species counts it is critical that species are looked at separately unless the detection of one is correlat ed with the presence of the other species (Buckland et al 2001). Distance sampling, an integrated approach which encompasses study design, data collection, and statistical analysis avoids many of the pitfalls of index counts and when applied pr operly, it provides direct estimates of bird density that are not confounded by detectability (Rosenstock et al. 2002). By using a distance sampling protocol combined with mu lti-scales of resolution, one can decipher what is going on within a system of interest (Marques and Buckland 2003). With the large amount of information available about habitat and feeding preference for individual bird species, one can get an idea of what bird community assemblages may occupy different patche s on the lake corresp onding to different environmental variables. Incorporating these known preferences with the results of this study will increase the information available to managers regarding the avian community response to lake enhancement ac tivities on Lake Tohopekaliga. Project Objectives The study presented here is part of a l ong term, large scale project evaluating the avifauna, aquatic vertebrate (Muench 2004) and vegetation (Welch 2004) community response to the 2004 Lake Toho enhancement. The long term project is designed to describe the avian abundance, distribution a nd use patterns prior to lake enhancement activities and again post lake enhancement. The research presented in this thesis examines the avian community structure prior to the 2004 drawdown and mechanical substrate removal. During the time period of this study, no management actions occurred on the lake system, with the exception of so me routine herbicide spraying of exotic

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15 vegetation species. Two different sampling t echniques were implemented to obtain bird densities and community structure data. A comparison which looks at results obtained from sampling at different scales between th e two methods will be addressed in following chapters. What will be presented here is the baseline data that will be used for comparisons made during the continuation of the study post lake enhancement and vegetative recovery. The specific ob jectives of this research include: Identify the environmental variables that are associated with densities of the abundant wetland dependent avian species within the littoral zone of lake Toho. Determine how these variable s influence avian abundance. Estimate bird species density within the l ittoral zone of lake Toho using two types of distance sampling. Determine spatia l variations on the lake. Determine responses to temporal and environmenta l variables includi ng lake stage, air temperature, season, year, etc. Compare the data collected using the tw o different distance sampling methods to determine which method best describes bird usage of the littoral zone, and outline advantages/disadvantages to each method of sampling. Determine species richness on the lake and determine what variables are influencing it. This remainder of this document is organized in the following way. Chapter two will describe how the whole lake (line transect s), and study area (point transects) were set up. Chapter two will also describe the fo cal avian species analyzed, detail distance sampling methods for the two types of sa mpling, list the assump tions of distance sampling, explain how distance sampling wo rks, and introduce general distance sampling methods used for both types of sa mpling. In Chapter 3 the sampling methods within the study areas will be outlined, analysis methods for the point transect data will be covered, and results and discussion for the study area analysis will be presented. In Chapter 4, the whole lake sampling methods, analysis, results and discussion will focus

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16 on the line transect sampling. Chapter 5 will be a discussion chapter comparing the two types of distance sampling results. It will discuss the preferred method for examining the variables of interest. This chapter will also discuss a dvantages and disadvantages of the two methods of sampling in this habitat and draw conclusions about each of the focal species and their usage within the littoral zone of the lake. Chapter 6 will discuss species richness within the littoral zone and envi ronmental variables influencing richness. Chapter 7 is a brief chapter discussing dete ctability and distance sampling and the future of the Lake Toho project.

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17 CHAPTER 2 STUDY AREA AND ANALYSIS METHODS Introduction This study used two different types of samp ling to gather baseline data that will permit monitoring of the effects of the Lake Toho enhancement project on the wetland dependent avian community. When looking at habitat selection for wading birds it is important to investigate across a continuum of temporal and spatial scales. (Strong et al. 1997). One type of sampling technique, line tr ansect sampling, was used to characterize the avian community structure and species specific responses before and after lake enhancement, by detecting changes or trends in distributions in randomly selected littoral reaches of the undeveloped shoreline of the lake with inferences applicable to the entire lake. The data obtained from the line transect sampling hereafter will be referred to as “Whole Lake Sampling”. The other method, which used point transect sampling, was designed to detect differences in avian community structure and species specific responses within specific study areas. Point tr ansects, which were replicated to provide inferences at the whole lake scale, utilized a treatment vs. control approach. The data obtained from the point transect sampling her eafter will be referred to as “Study Area Sampling”. In the chapters following, speci fic questions, methods, analysis, results and conclusions will be outlined separately for the two different sample methods, followed by a comparison of the two sets of results. Un less otherwise stated, the information in this chapter was applied to analysis methods that were the same for both types of sampling.

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18 No treatments were applied during the collecti on of the data presented in this document, which were gathered during the pre-enhancement phase, 2002 and 2003.. Regional Scale Community Monitoring Point transects were set up within the selected study ar eas to examine the bird distributions at a relatively fine scale. Three areas were sampled prior to lake enhancement in the same manner as they will be sampled once the lake enhancement has been completed to allow for comparisons of treatment effects within the study areas. This will be elaborated in the “Methods” s ection. The study areas were chosen based on similar types of shoreline with continuous types of littoral habita t (specifically dense Pontederia cordata (pickerelweed) and Typha (cattail)) (Figure 2-1) and were the target of the enhancement project. Each study area occupied 1600m (5,249 ft) of total shoreline length, divided equally into four treatment plots 400m (1,312 ft) in length. Two of these plots were randomly designated control plots and two of the plots were to be scraped following collection of the pre-enhancement data. Th e pre-enhancement vege tative habitat within the study areas was described in great de tail in Welch, 2004. Each study area had 32 possible point transect locations in varying microhabitats within the littoral zone. These points transects were arranged in the littoral habitat so that they were 100m away from the next closest sample location. Each of th e four treatment plots per area had 8 possible point transect locations within them (Figur e 2-2). These randomly sampled locations were in water depths up to 121.92 cm (48 in). The depth locations were based on the bathymetric maps provided by ReMetrix, but actual water levels were in constant fluctuation throughout the year. In this preenhancement study, no distinction as to future

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19 treatment status of the various study areas we re considered in the random assignments of point transect locations of any of the sampling events. Figure 2-1. Study area locatio ns on Lake Tohopekaliga.

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20 Figure 2-2. Study area setup indicating the poi nt transect locations 1 – 32 within the planned treatment and control sites, re membering that sampling occurred prior to the treatments actually being implemented. Whole Lake Community Monitoring In order to look at the entire undevelope d shoreline of the lake, line transect samples were implemented in the southern tw o-thirds of the lake. Using digital ortho quarter quads (DOQQ) in the program Ar c Map 4.0 (ESRI 2005), a line was drawn parallel to the shoreline cove ring 27,600 meters. It was deci ded that the line transects should be 400 meters in length so that the obs ervers could see the w hole length of the line while sampling as to not violate the assump tions of distance sampling, and to limit the types of vegetation crossed while traversing a single line trans ect. There were 69

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21 possible such transects along this line and 26 of them were randomly chosen to be permanent line transects. Due to thick stretches of cattail that often impeded observations between the emergent and floating leaf vegetation, tran sects were randomly placed either shoreward or lakeward of the cattail. The habitats obser ved within the 1-4 foot depth zones of the littoral reaches of the lake were classified as either inside, outside or previously scraped areas (see lake history section) (Figure 2-3). Figure 2-3. Map showing line transect locatio ns within the littoral zone of Lake Tohopekaliga. Map indicates the types of transects. The principal vegetative communities occurring w ithin the inside littoral zone transects were mainly pickerelweed ( Pontederia cordata ), torpedo-grass ( Panicum repens ) and water-grass ( Luziola fluitans ). The transects located on the outside reaches of the littoral zone were composed of mainly submersed species such as coontail ( Ceratophyllum demersum ), hydrilla ( Hydrilla verticillata ), and emergent floating leaf species such as fragrant water-lily ( Nymphaea odorata ), spatterdock ( Nuphar polysepalum ), water lotus ( Nelumbo lutea ), banana-lily ( Nymphoides aquatica ) and the emergent Egyptian

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22 paspalidium ( Paspalidium geminatum ). The previously scraped sites (indicated in yellow in figure 2-3) have a steeper s horeline slope is due to prior restoration efforts (section of the lake which was scraped in 1987). This area is also target of aggressive herbicide applications for management of invasive vege tative species such as typha, alligator weed, and water hyacinth. As a result of the previ ous restoration efforts, this area has shorter less dense shoreward vegetation and less littoral zone (more open water) in general. In addition to these factors, this area also is subject to greater dist urbance by daily airboat tours. These characteristics create a habita t that appears different from both the inside and outside transects. Because of apparent differences in the habitat covered while conducting line transect sampling the three tr ansect types were developed and will be analyzed both separa tely and together. Focal Species This study focused on wetland-dependent spec ies, i.e., those that they use wetland habitats at some critical stage during thei r life cycle. These wetland dependent species constitute many different guilds. Analys es were conducted by species when enough observations were obtained to generate re liable estimates of density, determined by looking at the goodness of fit tests and the percen t coefficient of varia tion associated with the estimates. Some of these species were endangered, threatened or Species of Special Concern in the State of Florida (Table A1, Appendix A). Many of these wetland species are residents on the lake, are numerous, and could be analyzed at the species level. When possible, densities were estimated weekly (f or point transects) and monthly (for line transects). In cases where there were not enough observations within the week, detection probability was modeled globally to derive weekly density estimates. Within the lake littoral zone, density estimates for the follo wing species were obtai ned (in alphabetical

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23 order): (Specific life histor ies, including habitat prefer ence, seasonal movements, and foraging behavior, will be described in the following chapters.) American Coot. The American coot ( Fulica atra ), is a common and widespread waterbird that is hunted in many places. This swimming rail has an all black body and white beak. The American coot is a wint er non-breeding resident in Florida. It feeds on aquatic plants on the surface and underwater (Brisb in et al. 2002). Anhinga. The Anhinga ( Anhinga anhinga ), is a large dark waterbird with a long neck and tail and a pointed bill. Its p opulation is relatively stable although local extirpations have resulted fr om drainage and development of wetlands (Elphick et al. 2001). The anhinga is a y ear round Florida resident. They are found in various freshwater wetlands with open, shallow wate rs, but can also live in brackish and saltwater habitats in Florida. They mainly feed on fish they spear while swimming underwater (Frederick and Siegel-Causey 2000). Belted Kingfisher. The belted kingfisher ( Ceryle alcyon ) is a medium sized bird that is a common waterside resident in Florida during the non -breeding seasons. The belted kingfisher winters along the coast, streams and lakes. It uses a perch or hovers to look into clear water for prey ite ms and then dives to catch them. The population may be decreasing in many areas (Hamas 1994). Boat-tailed Grackle. Th e boat-tailed grackle ( Quiscalus major ) is a large, long tailed blackbird and a year round resident in Florida. In addition to being found in a variety of urban habitats on the coast, it is also found in freshwater and saline marshes. In the marsh system it eats inve rtebrates, as well as frogs (Post et al. 1996). It typically forages by turning over floating leaf aquatic vegetation or by sticking its bill into other vegetation looking for prey items. Cattle Egret. The cattle egret ( Bubulcus ibis ) is a medium sized white wading bird and is usually found in pastures and al ong roadsides, although it can be found in aquatic habitats. The cattle egret is a year round resident in Florida. It is an opportunistic forager and usually is seen following cattle or machinery catching insects that they stir up (Telfair 1994). Common Moorhen. The common moorhen ( Gallinula chloropus ) is the most widely distributed member in the rail family and a year round resident in Florida. The common moorhen is found in mars hes and ponds with tall emergent vegetation. It forages by picking food from emergent plants while walking or from the water surface while swimming. It of ten turns over floating leaf aquatic vegetation looking for snails. In many stat es across the country it is listed as a species of special concern due to decreas ing wetland habitat (Bannor and Kiviat 2002). Great Blue Heron. Th e great blue heron (Ardea herodias ) is the largest and most widespread heron in North America. It is a year round resident in Florida and is

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24 found near calm freshwater or seacoasts. It s diet consists of fish, invertebrates, amphibians, reptiles, birds, and small ma mmals. The great blue heron forages by walking slowly, and stabbing prey with a quick lunge of the bill (Butler 1992). Glossy Ibis. The glossy ibis ( Plegadis falcinellus ) is a dark, medium sized wading bird with a down-curved bill. It is a year round resident in Florida (Davis and Krither 2000). The glossy ibis probes mud to eat various aquatic prey. They also eat small vertebrates, and occasionally vege tation. Birds will travel long distances in response to water conditions that ma y hinder reproduction (E lphick et al. 2001). Great Egret. The great egret ( Ardea alba ) is a large white wa ding bird and second largest in North America. The species is a year round resident in Florida. It feeds in a variety of wetlands, including marshes, swamps, streams, rivers, ponds, lakes, tide flats, canals and flooded fields. It ea ts fish, invertebrates, amphibians, reptiles, birds and small mammals. The great eg ret captures prey by walking slowly, and stabbing prey with its bill (McCrimmon et al. 2001). Green Heron. The green heron ( Butorides virescens ) is a small wading bird and a year round resident bird in Florida. They forage in many wetland systems and eat small fish, invertebrates, small frogs, insects and other small mammals. They forage by standing still next to the wate rs edge and grab small fish with an explosive dart of the head and neck. It is one of the few birds that use bait to attract fish, it drops such things as bread crusts, insects, and twigs onto the water to lure prey. They are fairly common and wide spread although populations are hard to census (Davis and Kushlan 1994). Little Blue Heron. The little blue heron ( Egretta caerulea ) is a medium sized wading bird and a year round re sident in Florida. It breeds and forages in various wetland and estuarine habitats It feeds on small fish, aquatic invertebrates, and amphibians by foraging slow and methodicall y. The little blue heron is a Florida designated species of special concern. Habitat loss and human-caused changes in local water dynamics are the most serious threats to this species (Rodgers and Smith 1995). Least Bittern. The least bittern ( Ixobrychus exilis ) is a cryptic, tiny wading bird whose summer and year round range overlap in central Florida. It is found in freshwater or brackish marshes which ha ve tall emergent vegetation. The least bittern forages near reeds, sometimes next to rather deep water, or climbs on reed stalks, and strikes downward into water to get prey items such as small fish and insects. They nest in dense tall stands of vegetation, particularly cattail. Their conservation status is unknown because they are difficult to survey, however, loss of wetland habitat and the encroachment of exotic species of marsh vegetation may pose a threat to their numbers (Gibbs et al. 1990). Limpkin. The limpkin ( Aramus guarauna ) is a medium-sized wetland bird that resembles herons and ibises in general form, but the limpkin is generally considered to be more closely related to rails and cranes. Flor ida is the northern

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25 limit of the breeding range of the limpkin and it is a year round resident there. In Florida they are found in open freshwater marshes, swamp forests, and shores of lakes, rivers, and ponds. They choose areas with stable water levels to nest (Elphick et al. 2001). It feeds almost exclusively on a pple snails, which it extracts from their shells with its long bill. It forages by searching visually for snails in clear water, or by jabbin g or sweeping with bill. The limpkin is a Florida designated Species of Special Concern, and they declined about 95% from 1966 to1993 (Bryan 2002). Purple Gallinule. The purple gallinule ( Porphyrula martinica ) is a medium sized marsh bird, within the raillidae family, that breeds and lives in Florida year round. They are found in freshwater wetlands wh ich have dense floating leaf aquatic vegetation. The purple galli nule eats seeds, flowers, fruits, grains and some invertebrates (West and Hess 2002). The lo ss of suitable habitat is the greatest threat to this species. This is usually due to flooding or droughts, changes in water quality, erosion, pollution, pesticides and dikes (Elphick et al. 2001). Ring-necked Duck. The ring-necked duck ( Aythya collaris ) is the most common diving duck to be found on small ponds during migration. It is present in large numbers on Florida lakes dur ing the winter months (H ohman and Eberhardt 1998). The exotic plant Hydrilla (Hydrilla vertic illata) is a submerged plant favored as food by the ring-necked duck, but the pl ant soon dominates native vegetation, becoming extremely dense and reduces open water that the ducks need. As with other migratory wetland species, the decr ease in stopover habitat or wintering habitat may have negative consequen ces for these species (Elphick 2001). Red-winged Blackbird. The red-winged blackbird ( Agelaius phoeniceus ) is one of the most abundant songbirds in North America and is found in wetlands and agricultural lands year round in Florida. It feeds on insects, seeds and grain by probing in vegetation, looking on the gr ound, or around vegetation (Yasukawa and Searcy 1995). Florida Sandhill Crane. The Flor ida population of the sandhill crane ( Grus canadensis pratensis ) is a non-migratory species whose range spreads from Okeefenokee Swamp, GA south to the Flor ida Everglades. This sandhill crane species has been on the threatened speci es list since 1974 mostly due to its low productivity, habitat degrad ation through wetland drainage and development and direct human encroachment. The sandhill crane’s small clutch size, low recruitment rate, age at first breeding, and seasonal nesting result in a low reproductive potential. Thus, sandhill cranes have a limited abili ty to rebound from natural or human-induced catastrophes (Willia ms 1978). It inhabits a variety of freshwater wetlands and uplands, including agricultural tracts, but is typically restricted to open areas (Elphick et al. 2001). It feeds in open marshes or grain fields and eats mostly grains and seeds, however it also eats small insects, other invertebrates and small vertebrates. Th ey typically feed by pecking at the ground or probing the mud as they walk along (Tacha et al. 1992).

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26 Snowy Egret. The snowy egret ( Egretta thula ) is a medium sized white wading bird which is a year round Florida reside nt (Parsons and Master 2000). They occupy all types of wetlands and forage wh ile standing and wading in water. They primarily eat fish, but also amphibians, re ptiles, and aquatic i nvertebrates (Elphick et al. 2001). They are a Florida de signated Species of Special Concern. Snail Kite. The snail kite ( Rostrhamus sociabilis plumbeus ) is a Federally endangered raptor that inhab its flooded freshwater and sh allow lakes in peninsular Florida and Cuba (Sykes 1984, Sykes et al. 1995 ). The historical range of the snail kite covered over 4000 km2 (2480 mi2) in Fl orida, including the panhandle region (Sykes et al. 1995), but is now restricted mainly to the watersheds of the Everglades, Lake Okeechobee, Loxahatch ee Slough, the Kissimmee River, and the Upper St. Johns River. These habitats exhibit considerable variation in their physiographic and vegetative characteristic s, and include graminoid marshes (wet prairies, sloughs), cypress swamps, lake littoral shorelines, an d even some highly disturbed areas such as agricultural ditches or re tention ponds (Bennetts and Kitchens 1997). Three features that rema in constant in the variety of selected habitats are the presence of apple snails, areas of sparsely distributed emergent vegetation (Sykes 1983, 1987), and suitable ne sting substrates, all of which are critical to the nesting and foraging success of the snail ki te. Snail kites are dietary specialists, feeding almost exclusively on one species of aquatic apple snail, Pomacea paludosa (Sykes 1987, Sykes et al. 1995). Nearly continuous flooding of wetlands for >1 year is needed to sup port apple snail populations that, in turn sustain foraging by the snail kite (Syke s 1979, Beissinger 1988). Snail kites use two visual foraging methods, either flying 1.5-10m above the water surface or hunting from a perch (Sykes 1987) and both require open water or sparse vegetation. Tricolored Heron. Th e tricolored heron ( Egretta tricolor ) is a medium sized wading bird and a year round re sident in Florida (Fredrick 1997). They forage in water in wetland habitats and feed on a quatic invertebrates, fish, reptiles and amphibians. They are listed in Florida as a species of special concern. Distance Sampling Methods Distance-sampling methods (Buckland et al 2001), which account for variation in detectability in counts of animals from lines or points, were used for both the study area sampling (point transects) and whole lake sa mpling (line transects) The remainder of this chapter will give a brief description of distance sampling and highlight some of the methodologies used in conjunction with the program DISTANCE 5.0 (Thomas et al. 2005) to conduct this study and manage the data. These methods will include the

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27 parametric models used, methods for dealing with groups of birds, truncation distances, covariates examined within distance, and how density estimations were generated within DISTANCE 5.0 (Thomas et al. 2005) and presented. Assumptions of Distance Sampling The aim of distance sampling is to obtai n a “snapshot” estimate of animals’ presence around the survey line or point to calculate absolute dens ity (Buckland et al. 2001). When using distance sampling, caution is taken to avoid violation of three critical assumptions: (1) birds on the line or point are detected with certainty (2) birds are detected before evasive movement trigge red by the observer; and (3) distances are estimated or measured accura tely (Buckland et al. 2001). Distance sampling is based on the detection function g(x) for line transects or g(r) for point transects. This function is estimated from distance data and is used to compute probability of detection (p) for each species. The detection function compensates for the fact that detectability decreases with increasing distance from the observer. The pr obability of detecting a bird at any given perpendicular distance varies according to numerous factors, such as environmental conditions, differences among observers, and conspicuousness of the target species (Burnham et al. 1980). The program DISTANC E 5.0 (Thomas et al. 2005) is set up so that the resulting density estimates are not affected by those vari ations in detection probability (Buckland et al. 2001). Models of g(y) (the dete ction function) are robust to pooling if the data can be pooled over many factors which affect detection probability and still yield a reliable estimate of density (Buckland et al. 2001). Parametric Models within DISTANCE The true detection function g(y) is not known in DISTANCE. The program DISTANCE provides 4 parametric “key functions” for fitting the detection curve. When

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28 incorporating covariates into the multiple co variates distance sampling (MCDS) analysis engine in Distance, this number is reduced to two, the half-normal and hazard-rate key functions. The series expansions used to fit the detection function along with the key functions were cosine, simple polynomial, a nd hermite polynomial. Results from the model with the lowest Akaike’s Information Criterion (AIC) value were reported for each species or group. If the AIC values were with in two points of each other, I selected the simpler model with the fewer number of pa rameters with better fit and precision. Clusters within DISTANCE The number of individuals in the progra m distance were entered as clusters; a single individual was entered as a cluster of 1. This avoided the need to make and analyze individuals because many times birds o ccurred in clusters and their detectability was greater than that of a single bird. If a cluster of individuals was sighted, the observer counted the number of individua ls in the group and measured the distance to the center of the cluster. The analyses of clusters in the program DISTANCE were based on exact sizes. All clusters were analyzed using a re gression of the log of cluster size against the estimated detection function to estimate mean cluster size. However, in cases where alpha <0.15, the mean cluster size was used. Th is reduced the coefficient of variation and increased model fit during times of the year when there were few large clusters. This transformation reduced the influence of a few la rge clusters on the estimation of density. Data Truncation in Distance Truncations to the data were done in most cases because large distances contribute little to estimating the detection function bu t may lead to poor fit and high variance (Buckland et al. 2001). Truncations within th e data were made at the analysis phase rather than in the field. Large wadi ng birds often could be observed at 500 meters. As

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29 recommended by Buckland et al (2001), 5% of observations were truncated for line transects and 10% for point tran sects. The percentage is in creased for point transects due to the fact that more detections are made further away during point transect surveys. Truncation of the distance data deletes outli ers and facilitates m odel fitting. In some cases other truncation distances were used based on model fit. Detection Covariates used within Distance In conventional distance sampling (C DS) all analysis factors affecting detectability, except distance, are ignored (Buc kland et al 2001). In reality, many factors affect detectability. Stratification redu ces problems when modeling the detection function, meaning a different detection func tion is obtained in each stratum, although often times there are too few data for each st ratum. Adding covariates to the detection function is more parsimonious. Covariates ar e incorporated into the estimation of the detection probabilities via the scale parameter. In this formulation, they are assumed to affect the rate at which detectability decrea ses as a function of distance. (Marques and Buckland 2003). DISTANCE can model the e ffect of numerical covariates and can “share information” about dete ction function shape between c ovariate levels. Covariates effecting detectability were examined in the analyses and again AIC was used to determine if a model including a covariate was the best model. Specific covariates used in the study area and whole lake sampling will be described in the following chapters. Density estimations When using distance sampling methods, an accurate measure of the sampled area (in this case, littoral zone) is critical for density estimates. Within the littoral zone, this study focuses on the area corresponding to th e 1 – 4 foot depth zones as seen on the bathymetric maps provided by ReMetrix (ReM etrix, LLC 2003) (Figure 2-4). The area on

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30 the north end of the lake which corresponds to the developed s horeline of downtown Kissimmee and adjacent housing developments was taken out of th e calculation of the total acres of these depth zones. The area of the depth zones corresponding to the 1-4 ft depth zone in the undeveloped areas of th e lake were calculated within ArcMap 9.0 (ESRI 2005) by converting many shape files corr esponding to sections within the littoral zone into a value for area (hectares). The en tire littoral zone whic h I was interested was selected and the total area was calculated. The area of littoral zone within the depth zones was about 2,228 hectares (5,505 acres) of the total lake surface area. This also corresponds to the valu e of mixed emergent vegetativ e species reported by ReMetrix 2003. The areas covered by our point transect survey study sites were 256 hectares (633 acres) and covered 11.4% of the 1-4 foot depth zone of the lake. The area of the lake covered by our line transect su rveys was 312 hectares (771 ac res), which was 14% of the total area possible in the lit toral zone of the lake. Figure 2-4. The 1-4 ft. depth zones on La ke Tohopekaliga corresponding to the area of interest on the lake during the pre-lake enhancement studies are indicated in dark green. The red areas are the st udy area point transect locations.

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31 CHAPTER 3 AVIAN DENSITIES AND VARIABLES IN STUDY AREAS Introduction Point transect sampling was conducted w ithin study areas as discussed in the previous chapter, in order to look at future treatment effects. Th e data presented here were collected prior to any lake-enhancement treatments in the study areas. Therefore no comparisons within study areas will be made at this time. The specific project objectives addressed in this chapter are 1) to estimate densities for focal species within the lake littoral zone using point tran sect distance sampling, 2) to establish spatial variations among study area locations based on density es timates for focal species, and 3) to determine which environmental and temporal f actors were affecting the densities of focal species within the avian community Survey Methods Bird Blinds Point transect surveys were c onducted from a priori placed bird blinds. These moveable bird blinds pr ovided a good vantage point from which to conduct the point transect surv eys. Three bird blinds we re constructed from 1.5 inch diameter aluminum piping with a inch th ick plywood platform measuring 55 cm by 53 cm. The platform sits roughly 6 feet above the marsh surface. Once the observer reaches the blind, a camouflaged mesh was placed arou nd the top of the blind to provide some cover while conducting the su rvey (Figure 3-1).

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32 Figure 3-1. The bird blind setup for point transects on Lake Tohopekaliga. Ideally, each blind location allo wed effective detection of all birds within a radius of 50 meters, but this varied with distance at whic h 100% visibility could be achieved. In an open wetland habitat comprised of a matrix of plant species, wit hout upland tree species present, the visibility around the point transect location in theory could be infinite. However this does not equate to detectability. Sometimes visibility was less than 50 meters due to vegetation such as cattail, and other times the visibility was greater. Because of the differences in visibility at each sample location, each location was unlike the next as far as observers being able to de tect bird species. These differences were addressed in the analysis by using vegeta tion cover for each location as a covariate (meaning that it influenced the ability of the observer to detect a species). The blind locations were randomly selected for each sample occasion from a grid of 32 possible locations within each study area with a stipulation that no two sequential samples could be less than 200m apart. This avoided recounting birds in the same small area over the sample period. The blinds we re assembled and moved to the sampling location the day before the survey to minimi ze disturbance to the area immediately before

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33 the survey was conducted. Also, care was taken not to place the blinds to close to nesting birds (snail kites, Florida sandhill cranes, etc.) Observers and Sampling The point transect surveys were initiated in January 2002, and the study areas were vi sited every other week (6 mornings a month) for two years (Table A-1, Appendix A). If a sample was not conducted for some reason, then the effort in the analysis indicates this, meaning that the effort is reduced in the analysis stage. Before sunrise on the morning of th e sampling, observers drove airboats to their respective study areas and moor ed the boats far enough away from the blind to minimize disturbance. From there, they used poke-boats (similar to kayaks) or walked to get to the blind. If the area around the blind was disturbe d before the survey, the survey was started at least half an hour after the disturbance. Otherwise, surveys usually started within the first hours of light, with precise start time de pendent on the logistics of getting to each individual blind location. A ll three observers, located at the three different study areas, used 2-way radios to start the survey simultaneously. The observers surveyed the respective areas from the point location fo r 2 hours, turning north or south every 10 minutes and recording birds within a 180 degree viewing radius. During the sample, observers recorded indi vidual birds, those clustered by species in tight groups, distance from the blind, behavior of the bird (flying or stationary), vegetation within a 50 meter ra dius around the blind, and visibi lity in each quadrant (NE, NW, SE, SW) around the blind. Each observer used Bausch and Lomb 10 x 42 Elite binoculars. They also used a Bausch and Lomb Elite spotting scope with power of 20-60 mm focal length zoom with an objective diamet er of 70 mm to identify birds in thick vegetation or to identifying birds at greater distances. In order to accurately measure

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34 distances to each bird, each observer used a Bushnell Yardage Pro Scout Rangefinder, which measured distances in 2 meter increments up to 800 meters (2,624 ft). To aide in identification of rare or difficult species, obs ervers referred to the National Geographic’s Field Guide to Birds of North America (Dunn 1999). Analysis Methods Densities Densities were estimated with the pr ogram DISTANCE 5.0 (Thomas et al. 2005) using only stationary birds seen within the first hour of each sample. To reduce the chance of double-counting indivi duals, which would violate assumptions of distance sampling. Preliminary analysis indicated an hour was an effective duration for each sample. Species-level density estimates were obtained for the focal species discussed in Chapter 2. Covariates The covariates that were tested with each species analysis includd: study area, observer, season, vegeta tion structure, stage, and comb inations of the five. To investigate the potential effects of the various covariates, I adopted the stepwise approach outlined in Marques and Buckland 2003 to dete rmine the most parsimonious model. Observer. Using observer as a covariate led to problems in the analysis due to some observers having few detections for certa in species of intere st. Spanning the two year study, nine different observe rs were used on a bi-weekly basis. In order to look at observer effect on detectability, observers were placed into three observer detection groups based on bird identifica tion experience, length of tim e working on the project, and individual survey methodologi es each observer employed when dealing with recording multiple species bird surveys. This proved to be a good method as observer strata was a covariate in many of the models chosen.

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35 Vegetation Structure At each point location sa mpled, vegetation cover was recorded within a 50 meter radius of the bi rd blind. The vegetation data included 38 species. These species were placed into 4 vegetation classes based on height, cover, and associations with other species (Welch 2004). The four vegetation groups were associated with openness of the habitat and were indicative of water cover of (25% 100%). A cover estimate was obtained for each sample location every time it was sampled. Higher percentages indicate more open water associated with vegetation communities. For analyses in DISTANCE, th ese values were rounded and placed into 6 ‘vegetation-strata’ groups. Spatial Variations Overall density estimates of focal species were examined on a site specific basis (corresponding to three study areas), to examin e spatial effects on the lake. The true value of differences in densities referred to as effect size (ES) was computed to determine if there were study area specific differen ces for each species (Alisauska and Lindberg 2002). The effect size of the differences in estimated densities between two sites is calculated as the square root of the variances of the estimated densities minus twice the covariance. For this analys is, I assumed no covariance, wh ich means that I are assumed independence among study area locations. By making this assumption, I overestimated the confidence intervals, which led to a cons ervative size estimate. I assumed that if there was a significant difference in density es timates between sites, then the confidence interval would not overlap zero. If the conf idence interval overla pped zero, then there was no difference. These analyses identified species requiring analyses by specific study area, and those that could be analyzed at th e scale of the whole lake. Density estimates

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36 were generated by study area for those species that had a significant difference in density estimates between sites. Temporal and Environmental Variations Environmental variations due to temporal changes as defined by ‘avian season’ were used to describe temporal changes a ffecting focal species densities within the littoral zone of the lake. Pa tterns of bird movements can be attributed to water regimes and climatic factors (Weller 1999). Thes e movements include stopover patterns, nondirectional nomadic movements, and permanent residency. Using this example to describe bird movements, the data analysis was divided by seasons corresponding to such movements seen on Lake Toho. These seasons included breeding (B), summer (S) and winter (W). In this study, the breeding season was defined as March – June. The summer season was July – October. The wint er season was November – February. This is a general grouping used to look at seasona l effects on bird density estimates. In Florida, environmental conditions within ea ch season may be highly variable. Due to these possible differences between years, analysis was conducted by the following specific seasons: W02 = Jan ’02 – Feb ’02; B02 = Mar ’02 – Jun ’02; S02 = July ’02 – Oct ’02, W0203 = Nov ’02 – Feb ’03, B03 = Mar ’03 – Jun ’03, S03 = July ’03 – Oct ’03, W03 = Nov ’03 – Dec ’03. Bi-weekly density estimates for the focal species were analyzed to determine how season and any other environmental variables were causing shifts in avian densities on the lake. I tested predictor variables fo r density using the generalized linear model function in the program R (R 2004), were test ed. A Gaussian dist ribution was assumed and avian season was introduced into the mode l as a categorical variable, hence creating an ANCOVA analysis. The lin ear predictors for the density estimates included lake

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37 stage, water fluctuation, rate of water fluctuation, vegeta tion structure, average air temperature (described in the section to fo llow). A categorical predictor for stage and water movement was included in the model. In order to test which environmental variab les were affecting the densities of focal species on the lake, a priori predictions were generated ba sed on avian life history traits. Some focal species nest on the lake and many are Florida residents, factors that influenced predictions (Table 3-1). The speci es-specific predictors were tested with the program R (R 2004). To determine which environmental variables influenced bird densities on the lake and how they interacte d, interaction effects of the variables were examined in addition to additive effects. I predicted that season would be an importa nt variable for at migratory species and included it in the full predictor model for t hose species in the initial analysis. For resident species, other chosen environmenta l variables were tested in the model and season was added last. Once the full model of all the possible predictors was tested, the model was reduced using AIC (as well as looking at the predictors within each model and their significance) to choose the most parsimonious model, if one existed. Akaike’s information criterion (AIC), which is the f it of the model plus two times the number of parameters used in the model, was used to determine the most parsimonious model. The predictor with the lowest AIC value and >2 away from the next closest predictor was chosen. Lake Stage. Lake stages were obtained from the gage station located at S_61 spillway headwater on canal C-35 at lake Tohopekaliga. Hydrologic data were downloaded from the South Florida Water Management District DBHYDRO website

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38 ( http://www.sfwmd.gov/org/ema/dbhydro/ ). Lake stage is repor ted in FT NGVD 29 and was converted into meters for all analyses. Lake stage correspondi ng to days of point transect sampling was averaged for the each week of sample. Table 3-1. Table of predictions indicate focal species that ar e year round Florida residents as well as species which nest in the littoral zone of Lake Toho. Predictions indicating which environmenta l variables are driving the densities of each species are listed. These include Lake Stage (S), Average air temperature (T), vegetation structure (V ), rate of water fluctuation per day (R), water level fluctuation (F), and th e categorical variable, water movement (W). Species Common Name Scientific Name Nest on Lake FL Resident Predictions AMCO American Coot Fulica atra N N S,T,V,W ANHI Anhinga Anhinga anhinga N Y S,T,V,W BEKI Belted Kingfisher Ceryle alcyon N N S,T,V,W BTGR Boat-tailed Grackle Quiscalus major Y Y S,T,W CAEG Cattle Egret Bubulcus ibis N Y S,R COMO Common Moorhen Gallinula chloripus Y Y S,R,F,W GBHE Great Blue Heron Ardea herodias Y Y S,R,F,W GLIB Glossy Ibis Plegadis falcinellus N Y S,R,F,W GREG Great Egret Ardea alba N Y S,R,F,W GRHE Green Heron Butorides virescens Y Y S,V,R,W LBHE Little Blue Heron Egretta caerulea N Y S,R,F,W LEBI Least Bittern Ixobrychus exilis Y Y S,V,W LIMP Limpkin Aramus guarauna Y Y S,V,F,W PUGA Purple Gallinule Porphyrula martinica Y Y S,F,T,W RNDU Ring-necked Duck Aythya collaris N N S,T,V,W RWBL Red-winged Blackbird Agelaius phoeniceus Y Y S,T,V,W SACR Florida Sandhill Crane Grus canadensis pratensis Y Y S,T,W SNEG Snowy Egret Egretta thula N Y S,R,F,W SNKI Snail Kite Rostrhamus socialbilis plumbeus Y Y S,V,F,W TRHE Tricolored Heron Egretta tricolor N Y S,R,F,W Water Fluctuation and Rate Water fluctuations on the lake were examined in order to determine how water levels may be af fecting bird densities present on the lake. Using the stage data, a graph was produced to indicate changes associated with the releasing and re-flooding of water by manage ment schedules. The time period from the start to the end of a particular drop or rise in water level on the lake was recorded. Rate of water level fluctuation is the rate (cm/day) that the lake stage is increasing or

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39 decreasing over the period of time recorded. Water fluctuation was calculated by looking at water fluctuation during the sample plus the two days prior to the sample. The categorical variable called water movement is the letter ‘S’ repres enting stationary lake stage, ‘I’ for increasing lake stage, or ‘D’ for decreasing lake stage leve ls at that point in time. Vegetation Structure. The values for vegetation structure were obtained in the same manner as detailed in the Distance An alysis Methods section. Vegetation cover was averaged for the study area locations for the sample week. Average Air Temperature The values for average temperature were obtained from the NOAA National Climatic Data Center via their website ( http://www.ncdc.noaa. gov/oa/ncdc.html ). The data recorded at the weather station located at the Orlando In ternational Airport (MCO) were us ed in analyses. Average daily air temperature (dry bulb) was reported in degrees Fahrenheit a nd was converted to Celsius. Average daily temperature for the sample week was used in the analyses. Results There were 98 avian species identified within the study area s prior to lake enhancement activities (Table B-1, Appendix B) Density estimates (birds per hectare) for the focal species per week of sample, ar e listed in Table C-1 in Appendix C. The distance sampling analyses model parameters corresponding to thes e estimates can be found in Table D-1 in Appendix D. Spatial Variations Comparisons between the three study site s yielded significant differences for all species except the great egret, least bitt ern, purple gallinule, and ring-necked duck. These species will be the reference set for the pre-enhancement estimates when using the

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40 three study areas as replicates. The estimated densities by study area are listed in Table C-2 in Appendix C. The differences in de nsity estimates between study area 1 and study area 2 were significant for many species (Table 3-2) including the gr eat blue heron and green heron, which had signifi cantly greater densiti es within study area 2 (Figures 3-2 – 3-3). When comparing study area 1 with study area 3, the differences were significantly different for many species (Table 3-3), how ever, only two species, the limpkin and Florida sandhill crane, had greater density esti mates at study area 3 (Figures 3-4 – 3-5). Significant differences in species density es timates between study area 2 and study area 3 are listed in Table 3-4. The true values of the differences in densities between study areas 2 and 3 yielded the leas t number of species having sign ificant differences (Figure 36 – 3-7). Table 3-2. Focal species with significant differences betw een density estimates for study areas 1 and 2. Birds are listed under th e study area with th e greater density estimate. Study Area 1 Study Area 2 No Significant Difference American Coot Great Blue Heron Anhinga Boat-tailed Grackle Gree n Heron Belted Kingfisher Cattle Egret Great Egret Common Moorhen Least Bittern Glossy Ibis Limpkin Little Blue Heron Purple Gallinule Red-winged Blackbird Ring-necked Duck Snail Kite FL Sandhill Crane Tricolored Heron Snowy Egret

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41 Figure 3-2. The value of differences in es timated densities between study area 1 and study area 2 for focal bird species. Upper and lower 95% confidence intervals which do not cross 0 are indicated as significant (*). Anhinga Belted Kingfisher Cattle Egret Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Limpkin Sandhill Crane Snowy Egret Snail Kite Tricolored Heron Value of Difference in Density Estimates -0.4 -0.2 0.0 0.2 0.4 Focal Species * * * Study Area 1 Study Area 2

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42 Figure 3-3. The value of differences in es timated densities between study area 1 and study area 2 for focal species. U pper and lower 95% confidence intervals which do not cross 0 are i ndicated as significant ( ). Table 3-3. Bird species with significant di fferences between density estimates for study areas 1 and 3. Birds are listed under th e study area with th e greater density estimate. Study Area 1 Study Area 3 No Significant Difference American Coot Limpkin Anhinga Boat-tailed Grackle FL Sandhill Crane Cattle Egret Belted Kingfisher Great Blue Heron Common Moorhen Glossy Ibis Little Blue Heron Great Egret Snowy Egret Green Heron Snail Kite Least Bittern Purple Gallinule Ring-necked Duck Red-winged Blackbird American Coot Boat-tailed Grackle Common Moorhen Purple Gallinule Ring-necked Duck Red-winged Blackbird -5 0 5 10 15 20 25 30 Value of Difference in Density EstimatesFocal Species Study Area 1 Study Area 2 * *

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43 Figure 3-4. The value of differences in es timated densities between study area 1 and study area 3 for select bird species. Upper and lower 95% confidence intervals which do not cross 0 ar e indicated as significant ( ). Figure 3-5. The value of differences in es timated densities (effect size) between study area 1 and study area 3 for select bird species. Upper and lower 95% confidence intervals which do not cro ss 0 are indicated as significant ( ). Anhinga Belted Kingfisher Cattle Egret Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Limpkin Sandhill Crane Snowy Egret Snail Kite Tricolored Heron -1.0 -0.5 0.0 0.5 1.0 Value of Difference in Density EstimatesFocal Species Study Area 1 Study Area 3 * * * * American Coot Boat-tailed Grackle Common Moorhen Purple Gallinule Ring-necked Duck Red-winged Blackbird -10 -5 0 5 10 15 20 Value of Difference in Density EstimatesFocal Species Study Area 1 Study Area 3 **

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44 Table 3-4. Bird species with significant di fferences between density estimates for study areas 2 and 3. Birds are listed under th e study area with th e greater density estimate. Study Area 2 Study Area 3 No Significant Difference Belted Kingfisher Glossy Ibis American Coot Great Blue Heron Limpkin Anhinga Green Heron FL Sandhill Crane Boat-tailed Grackle Snowy Egret Red-winged Blackbird Cattle Egret Common Moorhen Great Egret Little Blue Heron Least Bittern Purple Gallinule Ring-necked Duck Snail Kite Tricolored Heron Figure 3-6. The value of differences in es timated densities between study area 2 and study area 3 for select bird species. Upper and lower 95% confidence intervals which do not cross 0 ar e indicated as significant ( ). Anhinga Belted Kingfisher Cattle Egret Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Limpkin Sandhill Crane Snowy Egret Snail Kite Tricolored Heron -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 Value of Difference in Density EstimatesFocal Species Study Area 2 Study Area 3 * * *

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45 Figure 3-7. The value of differences in es timated densities between study area 2 and study area 3 for select bird species. Upper and lower 95% confidence intervals which do not cross 0 ar e indicated as significant ( ). Environmental and Temporal Variables The results of the generaliz ed liner model can be found in Table E-1 in Appendix E. The most parsimonious model for density estimation of focal species appears in Table 3-5. Season was the only envir onmental variable associated w ith the densities of the four species that had no spatial vari ation between the study areas: th e great egret, least bittern, purple gallinule, and ring-necked duck. The model including the linear predictor, ‘stage’, explained the differences in density estimates for species that are common and year round residents on the lake, American Coot Boat-tailed Grackle Common Moorhen Purple Gallinule Ring-necked Duck Red-winged Blackbird -25 -20 -15 -10 -5 0 5 Value of Difference in Density EstimatesFocal Species Study Area 2 Study Area 3 *

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46 Table 3-5. Results of the generalized linea r model analysis and the most parsimonious model indicating which environmental or temporal variables influence density estimates for focal species. The four species which were spatially the same within the study areas is indicated with a ( ). Species Variable American Coot Season + Stage Anhinga Season Belted Kingfisher Season Stage Boat-tailed Grackle Season Cattle Egret None Common Moorhen Stage Glossy Ibis Stage Great Blue Heron Stage Great Egret Season Green Heron Season + Water Little Blue Heron None Least Bittern Season Limpkin Stage Purple Gallinule None Ring-necked Duck Season Red-winged Blackbird Season Florida Sandhill Crane None Snowy Egret Season Snail Kite Season Tricolored Heron Season including the common moorhen, great blue heron, glossy ibis and limpkin. The great blue heron was present during every sample on the lake, and the estimated densities have a positive correlation with stage at study areas 1 and 2 (Figure 3-8). The common moorhen density estimates are positively correl ated with stage at study area 1 (Figure 39). The limpkin densities are positively correlat ed with stage for all three sites combined until the lake stage is greater than 54.5 ft NGVD (Figure 3-10). At study area 1, the glossy ibis density estimates are positively co rrelated with lake st age until it reaches 54.5 ft NGVD (Figure 3-11). Densities of Ameri can coots are positively correlated with stage and winter season (p = 0.022825) (Figure 3-12) The interaction effect of season and stage explained the density estimates of the belted kingfisher as they were present on the lake only during late summer and early wi nter seasons (p=0.0026) (Figure 3-13).

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47 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 20 40 60 80 100 120 Study Area 1 Study Area 2 Study Area 3 Estimated Density (# birds/ lake littoral zone) Figure 3-8. Estimated densities for the great blue heron within the lake littoral zone related to study area and lake stage. The error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort-weighed stage estimates.

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48 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 500 1000 1500 2000 2500 3000 3500 Study Area 1 Study Area 2 Study Area 3 Lake Stage (ft NGVD)Estimated Density (# birds/ lake littoral zone) Figure 3-9. Estimated densities for the comm on moorhen within the lake littoral zone related to study area and lake stage. The error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort-weighed stage estimates.

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49 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 10 20 30 40 50 Density Estimates (# birds/ lake littoral zone)Lake Stage (ft NGVD) Figure 3-10. Estimated densities for the limpki n within the lake littoral zone related to lake stage. Bird numbers were too fe w to generate density estimates by site and stage. The error bars correspond to 95% confidence intervals. The mean value is the pooled estimated densit y derived from effort-weighed stage estimates.

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50 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 50 100 150 200 Study Area 1 Study Area 2 Study Area 3 Estimated Density (# birds/ lake littoral zone) Figure 3-11. Estimated densities for the glossy ibis within the lake littoral zone related to study area and lake stage. The erro r bars correspond to 95% confidence intervals. The mean value is the poole d estimated density derived from effortweighed stage estimates.

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51 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.0 52.5 Mean 0 200 400 600 800 1000 1200 1400 1600 1800 Study Area 1 Study Area 2 Study Area 3 Estimated Density (# birds/ lake littoral zone) Figure 3-12. Estimated densities for the Amer ican coot during the winter season within the lake littoral zone related to study area and lake stage. The error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort-weighed stage estimates.

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52 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.0 52.5 Mean 0 50 100 150 200 250 300 350 Study Area 1 Study Area 2 Study Area 3 Estimated Density (# birds/ lake littoral zone) Figure 3-13. Estimated densities for the belt ed kingfisher during the summer and winter season within the lake littoral zone rela ted to study area and lake stage. The error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived fro m effort-weighed stage estimates. The predictor variable season, alone, explained the variatio ns seen in the estimated densities of the anhinga, boat-tailed grackle, great egret, ring-necked duck, least bittern, red-winged blackbird, snowy egret, tr icolored heron and snail kite. The densities of anhinga increased duri ng the summer and winter seasons (p = 0.0460 and p = 0.0460 respectively) (Figure 3-14). Estimated densities, for the boattailed grackle, although fairly consistent throughout the year at study areas 2 and 3, increased during the breeding and summer seas ons at study area 1 (Figure 3-15). The estimated densities of the great egret within th e littoral zone of the lake were slightly lower during the breeding season, but consistent throughout the rest of the year (Figure 3-

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53 16). The ring-necked duck, a migratory speci es, had greater densities during the first winter sampling season 2002 (p = 0.0001) (Figur e 3-17). The least bittern was present on the lake during breeding and summer seasons and the density estimates were consistent throughout these seasons (Figure 3-18). Th e snowy egret and tricolored heron both showed dramatic increases in density es timated during the summer 2002 season leading into the winter 2002-2003 season on the lake (F igure 3-19 and Figure 3-20). The density estimates for the snail kite were explaine d by the breeding season on the lake. Although stage was not determined to be a predictor variable for kite densities, it appears to be positively correlated to snail kite density estim ated within the littoral zone of the lake. Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 100 200 300 400 500 Study Area 1 Study Area 2 Study Area 3 Density Estimates (# birds/ lake littoral zone) Figure 3-14. Estimated densities for the anhing a within the lake littoral zone related to study area and season. The error bars co rrespond to 95% confidence intervals.

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54 The estimated densities associated with breeding, summer and winter are estimated independent of year. Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 5000 10000 15000 20000 25000 30000 Study Area 1 Study Area 2 Study Area 3 Density Estimates (# birds/ lake littoral zone) Figure 3-15. Estimated densities for the boat-ta iled grackle within the lake littoral zone related to study area and season. The error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimat ed independent of year.

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55 Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 Density Estimates (# birds/ lake littoral zone) 0 5 10 15 20 25 Season of Sample Figure 3-16. Estimated densities for the great eg ret within the lake littoral zone related to season. The error bars correspond to 95% confidence intervals. The estimated densities associated with br eeding, summer and winter are estimated independent of year.

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56 Winter Winter 02 Winter 03 Winter 0203 0 50 100 150 200 250 300 350 Season of SampleDensity Estimates (# birds/ lake littoral zone) Figure 3-17. Estimated densities for the ring-necked duck during the winter seasons within the lake littoral zone. Bird nu mbers were too few to generate density estimates for study area by season. Th e error bars correspond to 95% confidence intervals. The estimated densities associated with winter are estimated independent of year.

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57 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 0 5 10 15 20 25 30 35 Density Estimates (# birds/ lake littoral zone) Figure 3-18. Estimated densities for the le ast bittern during the breeding and summer seasons within the lake littoral zone The error bars correspond to 95% confidence intervals. The estimated de nsities associated with breeding and summer are estimated independent of year.

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58 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 500 1000 1500 2000 2500 3000 Study Area 1 Study Area 2 Density Estimates (# birds/ lake littoral zone) Figure 3-19. Estimated densities for the snowy egret within the lake littoral zone related to study area and season. Bird numbers were too few to generate density estimates for study area 3 by season. The error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimat ed independent of year.

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59 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 Estimated Density (#birds/lake littoral zone) 0 20 40 60 80 100 120 140 Study Area 1 Study Area 2 Study Area 3 Figure 3-20. Estimated densities for the tric olored heron within the lake littoral zone related to study area and season. The error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimat ed independent of year.

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60 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 10 20 30 40 50 60 70 80 Estimated Density (# birds/ lake littoral zone)Lake Stage (ft NGVD) Figure 3-21. Estimated densities for the snail k ite within the lake littoral zone related to lake stage. Bird numbers were too few to generate density estimates by season and study area. The error bars co rrespond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighed stage estimates. The green heron densities are best explai ned by the additive effect of season and the categorical variable wate r movement. Density estimates for the green heron were greatest during breeding season 2003 when the water was stationary for a few weeks following a dramatic decrease in the lake leve l (Figure 3-21). A few species didn’t have any predictor variables that were significant: the cattle egret, lit tle blue heron, Florida sandhill crane, and purple gallinule.

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61 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 100 200 300 400 500 Density Estimates (# birds/ lake littoral zone) Figure 3-22. Estimated densities for the green heron within the lake littoral zone related to season. Bird numbers were too few to generate density estimates for study area by season. The error ba rs correspond to 95% conf idence intervals. The estimated densities associated with br eeding, summer and winter are estimated independent of year. Discussion Spatial Variations The littoral zone on Lake Toho is highly va riable in wave action, slope, shoreline use, and vegetation communities. The three study areas were desi gnated along different shorelines on the lake as replicates; thes e areas have similar slopes, an absence of physical differences, stream outflows and topogr aphy changes. These areas also covered the same distance of 1,600 m (a pprox 1 mile of shoreline). Their lakeward extent from the shoreline was delimited by the approximate maximum water depth to be mechanically

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62 scraped during a dry down and extended ju st beyond the deep water extent of the Pontederia community (Welch 2004). Based on our results we can conclude that there are differences between study areas, based on bird density estimates for each focal species. There are many spatial variations that influence densities of focal species between the three study areas. Avian species and their usage of different vegetation communities at different lake stages may explain some study area differe nces. Vegetation communities within the littoral zone are the same between study areas. However, the locations of these communities in relation to water depth varies among the study areas. For example, the deep water communities (water depths of 46 in – 62 in.) within study area one are composed of Hydrilla verticillata (hydrilla), Lymnobium spongia (frog’s bit), and Ceratophyllum (coontail) while the deep water hab itats of study area two and three lie within the Pontedaria cordata (pickerel weed), and Alternanthera philoxeroides (alligator weed) vegetation co mmunity, which also includes Typha (cattail) (Welch 2004). The greater proportion of submerse d aquatics found at study area one is the forage base for the higher densities of the American coots found there. The estimated densities of the endangered snail kite were greatest at study area one due to shallow less dense vegetation communities to forage expa nding lakeward to expa nsive stretches of Typha in which they nest. This study area is al so located just south of a large historical snail kite nesting and foraging area (near Brown’s point). The Pontedaria vegetative community is broader in study area 3 and dominated twice as many vegetation samples as in study ar ea one or two in the vegetative pre-lake enhancement study (Welch 2004). Red-winged blac kbirds prefer this type of habitat to

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63 forage and nest in smaller Typha clumps on the edges of this dense vegetation. The green heron usually was found in dense vegeta tion and nests in thick stretches of Typha during the breeding season at study area two. The shallo w littoral habitat along the grazed shorelines of study area one and th ree was dominated by the Luziola gluitans (watergrass) community and this community was proportionately greater at study area one in shallow water depths (Welch 2004). This vegetative commun ity may explain the densities of medium sized wading birds such as the little blue and tricolored heron. In addition to the study areas varying in proporti ons of vegetative communities, they also had spatial differences. The study areas are located along different sh orelines of the lake (Figure 2-1). Study area one is subject to high wave action given its location and the predominant wind direction. Study area two is located on a very sheltered shoreline. Study area three is located in a cove directly across from the C31 input canal from East Lake Tohopekaliga. We were not able to measure elevation differences between th e three study areas; however this may have been a factor influe ncing how long water st ayed in the littoral zone at different lake stages and seasons. Although vegetativ e and spatial characteristics influence avian communities present at the study areas, possibly more important is the characteristics of the littoral zone in relation to its surrounding features. The three study areas have major structur al differences at the upland boundary (land-inland water ecotne). In study area three, the one foot depth zone expands into an extensive ecotone that is flooded at different lake stages. This vegetated zone then becomes upland pasture land which meets th e trees which are about 500 – 800 meters (1,640 -2,625 ft) away. Study area one has th e same upland boundar y, except the trees

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64 are about 200 meters closer to the littoral zo ne than at study area 3. Many birds use this flooded ecotone for foraging and some use it for nesting. For example, birds, such as the Florida sandhill crane will nest and forage in this expansive ecotone bordering study area three because of the ideal shallow to dry fora ging habitat located there. Also, with the presence of pasture lands a nd cattle at both study area one and three, the densities of cattle egrets are greater there than at study area two. The glossy ibis, forages in smaller groups and prefers the expansive shallo w littoral zone to forage as well. In contrast, the littoral zone at study ar ea two extends into th e trees, without the presence of expansive pasture land, creating a swamp habitat at different times during the year, when the stage is high enough. In study ar ea two the distance to the tree line from the littoral zone is less than 100 meters (328 ft ). This unique characteristic of study area two attracted a few species different from than the other study areas. Some of the focal species that preferred study area two are bi rds that forage in wetlands near swamp habitats. The great blue he ron typically nests in trees near water (Bu tler 1992) and nesting activity was observed ne ar study area two. Another speci es that uses the trees is the belted kingfisher, which forages from either a perch or by hovering and diving for prey (Hamas 1994). The snowy egret may have been more common at study area two because of the cover of the tree line for prot ection against predators since they are white in color and are usually solitar y feeders. The differences in the upland edge habitat and other study area characteri stics influenced the densities of all but four focal species at each study area. This knowledge combined with the temporal and environmental variables that affect avian densities on the la ke will create the baseline data that will be used to compare densities following the lake enhancement.

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65 The density estimates for four species, the l east bittern, great egre t, purple gallinule and ring-necked duck were not significan tly different among study areas. The ringnecked duck, which primarily feeds on the submersed Hydrilla is more associated with open water habitats around the e dge of the littoral zone that were equally distributed and positioned among three study areas. Species richness for the floating leaf aquatic vegetation communities, on which the purple ga llinule typically forages, was higher for this community than any other in the littora l zone on the lake with the exception of the grassy communities (Welch 2004). This is due to the ability of the floating leaf aquatic group to grow within a broad range of vegeta tive communities. Least bitterns forage and nest in monospecific strands of Typha The Typha vegetation community had the lowest species richness on the lake creating the habi tat preferred by the least bittern (Welch 2004). The large wading bird, the great egret, is opportunistic and will forage in almost any wetland vegetative community (McCrimmon et al. 2001). The great egret has a larger range than any other heron, which is re lated to the fact that it has access to a variety of deeper water habitats. These f our species will be important when comparing the lake before and after enhancement because their distribution within the littoral zone was the same within our study areas. The following section will address the environmental factors which are influencing the densities of thes e four key species. Temporal and Environmental Variations Lake Water Levels. Water can be used by birds for drinking, bathing, courtship, and escape from predators. Most importantly, water is an attractant for birds as a source of suitable foods (Weller 1999). Water depth and fluctuation can create different habitats suitable for many different avian species th roughout the year (Weller 1999). At

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66 extremely high lake stages, areas of the lake littoral zone may be one continuous pool and prey items may be harder to capture fo r some foraging birds (Kushlan 1981). The majority of wading birds require shallo w water (less than 25 cm for great egret and great blue heron and less than 15 cm for smaller herons) to forage successfully (Custer and Osborne 1978). On Lake Toho, due to floating vegetative mats, many avian species are able to forage the entire exte nt of the littoral zone by perching on floating mats in deeper water rather than being restricted to the waters edge. This is most likely the reason why lake stage was not influenci ng the densities of the medium sized wading birds, such as the tricolored heron, snowy eg ret, and little blue heron, all which forage from floating mats in addition to the shallows Densities for the large wading bird, the great blue heron, were positively correlated w ith lake stage. The reason the densities of the great blue heron were strongly associated with stage while those of the other large wading bird, the great egret were not is becau se the great egret leaves the lake during breeding season. Season, therefore, was the st rongest predictor for density of the great egret. However, densities of a medium sized wading bird, the lim pkin were negatively correlated with lake stage deeper than 54.5 ft NGVD. In the case of the limpkin, which feeds almost exclusively on aquatic apple snails ( Pomacea paludosa ), this trend may be due to the flooding of apple snail eggs duri ng late spring and early summer, which would decrease the food base for the limpkin within the littoral zone. The glossy ibis forages on the lake edge in the open shallow habitat a nd in general its density is constant except at study area one when more ar eas are inundated at lake stag es of 54 – 54.5 ft NGVD. The densities of the marsh birds, the co mmon moorhen and American coot, at study area one were positively correlated with lake stage. Study area one has an expansive

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67 littoral zone extending deeper than the study area sampling boundaries. At deeper stages, marsh birds would have increased access to all of these deep wa ter vegetated areas. Differences in elevation between study areas ma y cause them to flood at different rates. The densities of the belted kingfisher were also positively correlated with lake stage. Prey items may have been easier to obtai n in the shallow flooded habitats. Although lake stage did not play a critical role in the dens ities of many of the focal species, the new littoral habita t created by the enhancement may be more prone to effects of increased lake stage levels and wave acti on. The four key species that did not differ spatially prior to lake enhancement, the great egret, least bittern, purple gallinule and ring-necked duck, were not a ffected by lake stage. W ithout the dense stands of vegetation to shield the littora l habitat from wave action and without the floating mats of vegetation providing optimal fora ging locations within the litt oral zone at deeper lake stages, lake stage may be more of an in fluence on avian dens ities after the lake enhancement. Lake water level fluctuation and daily rate of change were not significant predictors for any of the focal species, although water m ovement as a categorical variable was for one species. Measuring these variables a nd their effects on different species is a challenge in avian research. Species react di fferently to water levels during the breeding season and these levels and rate of fluctuat ion different annually. Also, each species has different tolerances for water level fluc tuation and rates based on physiology, foraging methods, and prey availability. For example, our results indicated that during breeding season 2003, the green heron was influenced by water movement and had increased densities during a period of time when the wa ter was stable. Duri ng that particular

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68 breeding season, from late March into mid Apr il, water was decreasing at a rate of about 2 cm/day, overall decreasing about 50 cm (20 in), from 54.83 – 52.79 ft NGVD before the water level was stable again. As soon as the water level stabilized following this drastic decrease in water, the densities of green herons increased significantly. Looking at the breeding season 2002 during the same time period there were almost no green herons. During this breeding season, however the rate of water level fluctuation was never more than 1 cm/day, however the water never stabilized duri ng the whole breeding season. It continued to decrease. The opposite trend was seen for two othe r nesting species on the lake, although statistical differences were not significant. The snail kite, during th is same time period, breeding season 2002, was nesting and their dens ities were decreasing weekly with water level. However, in 2003, the densities for th e snail kite overall were lower than the 2002 season due to a quick drop in water level dur ing the nesting season. The same trends were seen with the Florida sandhill crane dens ities. During that time period in 2003 there were fewer Florida sandhill cranes in the la ke littoral zone. In 2002, the sandhill crane densities were greater. The Florida sandhill crane nested ex tensively within the littoral habitat in 2002. Their breeding season wa s extended from January – June due to favorable lake conditions for nesting. It is critical in analyses to look at multiple scales in order to determine environmental influences on avian densities. In general, large wading birds may be directly affected by water level fluctuations th at severely restrict their ability to feed successfully. Because of this, wetland birds, such as wading birds are often used as indicators of ecological changes within a wetland system (Furness and Greenwood 1993,

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69 Kushlan 1993, Dimalexis and Pyrovetsi 1997). The post-lake enhancement study, will determine how lake stage and water level fluc tuation influence densities of birds in the absence of vegetation within the littoral habitats. Vegetation Wetland birds are opportunistic. They will utilize a patch of good habitat and then move on to more productive patches. Wading birds will return to a previously used patch provided its profitability continues to be suffi cient (Kushlan 1981). A study conducted on Lake Okeechobee showed that when birds were presented with a choice of foraging habitats at moderate lake stages, all species c onsidered in the study tended to select patches of em ergent vegetation of moderate stature and species/structural diversity (Smith et. al 1 995). Vegetation such as Eleocharis -mix habitats, Rhynochospora -dominated and mixed-grass (primarly Panicum ), flats of Polygonum Nymphaea and sparse to moderate density cattail ( Typha spp.) were among the preferred mixtures of vegetation during different times of the year (Smith et al 1995). Bird diversity was linearly correlated with foliage height diversity and curvilinearly with total percent vegetation cover in a 1974 study conduc ted by Willson. The correlations with vegetation could not be measur ed within the scope of this study. A future manuscript combining the results of this study with th e results of the pre-enhancement vegetation study conducted within the same study areas (Welch 2004) will be generated for focal species. Season: Many wetland bird densities were de pendent on avian season defined as breeding, summer and winter. The two migr atory species, American coot and Ringnecked duck, were only present on the lake during the winter season. Their numbers at the scale of the lake system are much greater than what our density estimates indicate, as

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70 we sampled only within the littoral zone. Ma ny species leave the lake littoral system to nest elsewhere during breeding season. This is true for the belted kingfisher which is present on the lake during the summer and wi nter months but nests in bank habitats usually north of Florida. The density estimates for many of the wading birds decrease during the breeding season as well, when adults nest elsewhere in the state. This is true for the anhinga, great egret, snowy egret, a nd tricolored heron. Th e juvenile birds and non-breeding adults of these species rema in on the lake during breeding season. Conversely, the density estimates for birds th at nest on Lake Toho increase during this time of year. The small wading birds, the l east bittern and green heron, both nest in Typha in the lake littoral zone. The densities of these birds increase during the breeding season, and they also become more obvious in their behavior. Re d-winged blackbirds also nested within the dense vegetation with in the littoral zone, and densities increased during the breeding season. The snail kite a nd Florida sandhill cran e nested within the littoral habitats of the lake, however sandhill crane density estimates lacked correlates of density trends. Season as an environmental predictor for avian densities will not change after lake enhancement as long as avian species will still nest within the littoral zone of the lake and a new habitat within the littoral zone is not created for new nesting species

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71 CHAPTER 4 AVIAN DENSITIES AND VARIABLES IN WHOLE LAKE SAMPLING Introduction Lake wide community monitoring by line transect sampling was conducted within the littoral zone of Lake Toho in order to make comparisons with future treatment effects. The data presented here are from pre-enha ncement sampling and no treatment had been applied to the lake. The speci fic project objectives which will be examined within this chapter are 1) to generate density estimate s for focal species within the lake littoral habitat using line transect distance sampling 2) to determine if the design adequately sampled the entire littoral habitat by compar ing estimated densities of focal species by line transect type 3) to determine which environmental and temporal variables were affecting the densities of the focal species at a whole lake level within the littoral zone. The whole lake sampling was initiated Fe bruary 2002 as described in Chapter 2 (Table A-2, Appendix A). Conducting line trans ect sampling within the littoral zone of the lake required the use of an airboat to sa mple the 26 established 400m line transects. Surveys were conducted monthly during the two year pre-enhancement study. The only species not recorded in the line transect samples were the passerines, due to low detectability from a moving ai rboat, and American coots ( Fulica americana ) due to their vast numbers during some winter seasons. To avoid violating assumptions of distance sampling, two observers were used to sample the littoral zone communities. The sampling incorporated distance samp ling with the dependent double observer approach of Nichols et al. (2000). Two obs ervers conduct the sample from the same

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72 vantage point. One observer is the “primary” (independent) observer and the other is the “secondary” (dependent) observer. The tw o observers switch roles every survey to generate detection probabili ties for each observer. The only difference between the methodologies of Nichols et al. (2000) a nd our approach is that our primary and secondary observers never reversed roles. Im plications of using this method will be dealt with in Chapter 5. The observers counted birds from an air boat equipped with an intercom system The airboat traversed the line transect while the primary observer recorded, with a hand held tape recorder all birds observed and thei r perpendicular distance to the line transect. The secondary observer listened to the observa tions of the primary observer and recorded any additional birds into a separate recording device. A rangefinder was used to determine accurate perpendicular distances to the birds. This approach permited estimation of observer-specific detection probabilities for in corporation into the density estimation for each species. Analysis Methods Densities Density estimates for 16 different species were derived from the whole-lake linetransect sampling. The focal-species list from the whole-lake sampling differed from that generated from the study area sampling. Americ an coots, in addition to the passerines, the red-winged blackbird and boat-tailed gr ackle, were not sampled. The limpkin and cattle egret were also excluded for a lack of su fficient observations to estimate density. A new focal species, the pied-billed grebe, was more common on line transect samples than on point transect samples. Its life history is listed below.

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73 Pied-billed Grebe ( Podilymbus podiceps ). The pied-billed grebe is a common diving bird in North America and is a year round resident in Florida. The grebe breeds on seasonal or permanent ponds with dense stands of emergent vegetation. It also breeds near bays and sloughs. During the winter it uses most types of wetlands. It eats fish, crustaceans and aquatic insects and forages by diving underwater in either open water or among aquatic vegetation (Muller and Storer 1999). Densities were estimated using the program DISTANCE 5.0 (Thomas et al. 2005). In order to use the information gathered in ou r dual observer samples, a separate analysis was conducted to determine a new value for g(0), the probability that an object that is on the line is detected. One of the assumptions of distance sampling is that g(0) = 1. I adjusted g(0) by fitting the detection function for a single avian species recorded by the primary observer, within DISTANCE and an in terval was chosen from 0 to the distance in which the detection function was flat. In the program MARK (White and Burnham 1999), data for both primary and secondary obser vations within the distance selected was analyzed using the removal estimator on the primary/secondary dete ctions within that distance interval to ge t a g(0) and standard error (Buc kland et al. 2004). These values were put back into the program DISTANCE manually and analysis was conducted as normal using observations from the primary obs erver only. This method can be efficient depending on the truncation distance of the data when determining the flat shoulder of the detection function for each species (T homas and Laake pers. communication). The effort for the line transect sampli ng was calculated by taking the total line length of each transect multiplied by the number of times each line was sampled during the period of time being analyzed. Seasona l and monthly values differed and were selected as appropriate for each analysis.

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74 Covariates Covariates were transect type (i nside, outside, previously scraped), stage, and season. I selected the best model with the met hods of Marques and Buckland 2003. Spatial Variations In order to sample the entire width of th e littoral zone, line transect surveys were designed to run either ‘inside’ or ‘outside’ ha bitats of the littoral zone, covering the 1 – 4 foot depth zones on the lake, as described in Chapter 2. I assumed that vegetation composition would vary across transects with community type and water depth. The spatial analyses compared density estimates of focal species between the transect types to ensure that the extent of the habitats requi red for the presence of individual species was covered during a single sample occasion. This should be equivalent to the width of the littoral habitats sampled using the point tran sect sampling. In order to determine if variations exist between line transect types, the true value of differences in densities referred to as effect size (ES) was computed to determine if there were transect type specific differences for each focal species (Alisauskas and Lindberg 2002). This method of comparing densities was explained in Chap ter 3. Predictions of focal species use of lake transect habitat types (ins ide, outside, previously scraped) were generated based on life history characteristics (Table 4-1). Temporal and Environmental Variations Environmental variations due to season as described in Chapter 2, will be used to describe the temporal changes affecting fo cal-species density estimates for the wholelake sampling. Density estimates for focal species were obtained within DISTANCE by sample month (individua l survey) and season.

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75 Table 4-1. Predictions for line transect type used by each focal species. These include line transect types inside (I), outsid e (O), and previously scraped (P). Species Common Name Scientific Name Prediction ANHI Anhinga Anhinga anhinga O, P BEKI Belted Kingfisher Ceryle alcyon I, O, P COMO Common Moorhen Gallinula chloripus I, O, P GBHE Great Blue Heron Ardea herodias I, O, P GLIB Glossy Ibis Plegadis falcinellus I, P GREG Great Egret Ardea alba I, O, P GRHE Green Heron Butorides virescens O, P LBHE Little Blue Heron Egretta caerulea I, O, P LEBI Least Bittern Ixobrychus exilis O, P PBGR Pied-billed Grebe Podilymbus podiceps O, P PUGA Purple Gallinule Porphyrula martinica O, P RNDU Ring-necked Duck Aythya collaris O, P SACR Florida Sandhill Crane Grus canadensis pratensis I SNEG Snowy Egret Egretta thula I, O, P SNKI Snail Kite Rostrhamus socialbilis plumbeus O, P TRHE Tricolored Heron Egretta tricolor I, O, P Density estimates were obtained monthly for focal species within the littoral zone to determine which environmental variables we re affecting bird densities at the whole lake scale of sampling. The same analysis methodology used for th e study area analyses, was used for the whole lake sampling analyses, except that linear predictors for the density estimates included stage, air temperat ure, water fluctuation, rate of water level fluctuation, and the categorical variable wate r movement (described in chapter 3). The scale was month of sample rather than week of sample as in the study area analyses. Predictions for each focal species were the same as those in the study area analyses, with the exclusion of vegetation structure. A pred iction for the new focal species, the piedbilled grebe was added (Table 4-2). Season was introduced in the same manner it was in the study-area analyses, Chapter 3.

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76 Table 4-2. Table of predictions indicating which species nest on the lake and which are permanent Florida residents. Predictions indicate environmental variables that are driving the densities of each focal sp ecies. These include lake stage (S), average air temperature (T), rate of wa ter fluctuation per day , water level fluctuation (F), and the categorical variable, water movement (W). Species Common Name Scientific Name Nest on Lake FL Resident Predictions ANHI Anhinga Anhinga anhinga N Y S,T,W BEKI Belted Kingfisher Ceryle alcyon N N S,T,W COMO Common Moorhen Gallinula chloripus Y Y S,R,F,W GBHE Great Blue Heron Ardea herodias Y Y S,R,F,W GLIB Glossy Ibis Plegadis falcinellus N Y S,R,F,W GREG Great Egret Ardea alba N Y S,R,F,W GRHE Green Heron Butorides virescens Y Y S,R,W LBHE Little Blue Heron Egretta caerulea N Y S,R,F,W LEBI Least Bittern Ixobrychus exilis Y Y S,W PBGR Pied-billed Grebe Podilymbus podiceps Y Y S,R,F,W PUGA Purple Gallinule Porphyrula martinica Y Y S,F,T,W RNDU Ring-necked Duck Aythya collaris N N S,T,W SACR Florida Sandhill Crane Grus canadensis pratensis Y Y S,T,W SNEG Snowy Egret Egretta thula N Y S,R,F,W SNKI Snail Kite Rostrhamus socialbilis plumbeus Y Y S,F,W TRHE Tricolored Heron Egretta tricolor N Y S,R,F,W Results We recorded 49 avian species during the whole lake sampling (Table B-2, Appendix B). Sixteen were the focal species described in Chapters 2 and 3. The focal species were common enough to provide density estimates for each monthly sample, estimated as number of birds per hectar e (Table C-3, Appendix C). The distance sampling analyses model parameters correspond ing to the focal species density estimates, per hectare, can be found in Table D-2, Appe ndix D. Density estimates by month allow for the incorporation of environmental variable s. However, density estimates were then generated based on our environmental variable s to graphically display the trends and estimated densities in a way that makes them useful and comparable to the results from the study-area sampling.

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77 Spatial Variations Comparisons between the three types of lin e transects indicated that the estimated densities for focal species varied dependi ng on transect type. Many corresponded with the predictions. The estimated densities are listed in Table C-4, Appendix C. The preference for inside vs. outside tran sect type as indicated by the density estimates are listed in Table 4-3. Large wa ding birds, including the great blue heron, great egret and sandhill crane were more co mmon on the inside tr ansects. The sandhill crane was never seen on an outside line tr ansect during the samples. Three of the medium sized wading birds, the little blue heron, snowy egret and tr icolored heron, also were seen more often on an inside trans ects. The anhinga, common moorhen, and ringnecked duck were more common on out side transects (Figure 4-1). Table 4-3. Focal species with significant differences betwee n density estimates on inside vs. outside line transect s. Birds are listed unde r the line type having the greatest density estimate. Inside Outside No Significant Difference Great Blue Heron Anhinga Belted Kingfisher Great Egret Common Moorhen Glossy Ibis Little Blue Heron Ring-necked Duck Green Heron Sandhill Crane Least Bittern Snowy Egret Pied-billed Grebe Tricolored Heron Purple Gallinule Snail Kite

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78 Figure 4-1. The value of differences in esti mated densities between inside and outside line transect types. Upper and lower 95% confidence intervals which do not cross 0 are indicated as significant ( ). The preferences for inside vs. previously sc raped transect type are listed in Table 44. The purple gallinule, ring-necked duck and common moorhen a ll were seen more often on inside-line transects compared to prev iously scraped transect s (Figure 4-2). The density estimates for the belted kingfisher were greater on previously scraped line transects than inside-line transect types. Fi ve wading birds, the glo ssy ibis, great egret, little blue heron, tricolored heron and sandhill crane, also had greater numbers in the previously scraped transects compared to the inside transects. Focal Species Anhinga Belted Kingfisher Common Moorhen Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Pied-billed Grebe Purple Gallinule Ring-necked Duck Sandhill Crane Snowy Egret Snail Kite Tricolored Heron Value of Difference of Density Estimates -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 Inside Transects Outside Transects * * * *

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79 The focal species that preferred outside vs previously scraped transect types are listed in Table 4-5. Few focal species di ffered significantly between outside and. Previously-scraped transects. Little blue her ons were denser on the out side line transects. The anhinga, belted kingfisher, and comm on moorhen were counted on previously scraped transects in greater numbers th an the outside transects (Figure 4-3). The results indicate that our line-trans ect sampling effectively sampled a broad range of species encompassing many guilds and niches within the littoral habitat. Every focal species was dispersed across every type of transect, with the exception of the sandhill crane, which was never sampled on an outside transect. Focal species will be analyzed by combing across transect types for a single sample period. The following section will discuss the other environmental and temporal variations influencing focal species densities in the littoral zone of the lake. Table 4-4. Focal species with significant differences betwee n density estimates on inside vs. previously scraped lin e transects. Birds are listed under the line type having the greatest density estimate. Inside Previously Scraped No Significant Difference Common Moorhen Belted Kingfisher Anhinga Purple Gallinule Glossy Ibis Great Blue Heron Ring-necked Duck Great Egret Green Heron Little Blue Heron Least Bittern Sandhill Crane Pied-billed Grebe Tricolored Heron Snail Kite Snowy Egret

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80 Figure 4-2. The value of differe nces in estimated densities be tween inside and previously scraped line transect types. Upper a nd lower 95% confidence intervals that do not cross 0 are indica ted as significant ( ). Table 4-5. Focal species w ith significant differences between density estimates on outside vs. previously scraped line tran sects. Birds are listed under the line type having the greate st density estimate Outside Previously Scraped No Significant Difference Little Blue Heron Anhinga Great Blue Heron Belted Kingfisher Glossy Ibis Common Moorhen Great Egret Green Heron Least Bittern Pied-billed Grebe Purple Gallinule Sandhill Crane Snail Kite Snowy Egret Tricolored Heron Focal Species Anhinga Belted Kingfisher Common Moorhen Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Pied-billed Grebe Purple Gallinule Ring-necked Duck Sandhill Crane Snowy Egret Snail Kite Tricolored Heron -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 Value of Difference of Density Estimates Inside Transects Previously Scraped Transects * * * *

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81 Figure 4-3. The value of differences in estimated densities between outside and previously scraped line transect t ypes. Upper and lower 95% confidence intervals which do not cross 0 ar e indicated as significant ( ). Temporal and Environmental Variations The results of the generaliz ed linear model analyses can be found in Table E-2 in Appendix E. The density estimates for the fo cal species were explai ned as a function of two different predictor models : overall season (B, S, W); and season and year (B02, B03, S02, S03, W0203, W03). During the winter sa mple season 2003, the lake stage levels started to decline as the lake enhancement project began. The model chosen for many of the focal species reflects this rare occurrenc e of a dry localized event during the winter season. In order to determine results that accu rately depict these birds on the lake system Focal Species Anhinga Belted Kingfisher Common Moorhen Great Blue Heron Glossy Ibis Great Egret Green Heron Little Blue Heron Least Bittern Pied-billed Grebe Purple Gallinule Ring-necked Duck Sandhill Crane Snowy Egret Snail Kite Tricolored Heron -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 Value of Difference of Density Estimates Outside Transects Previously Scraped Transects * *

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82 seasonally, overall season was introduced into the model first and then year was added. The model that involves year was chosen as best only in cases where season alone was not a predictor for density. The most parsimonious model for density estimation for each focal species sampled on the line tran sects is listed in Table 4-6. The categorical predictor variable, seas on, explained the variation in monthly density estimates for 10 of the focal sp ecies. The model including winter season explained the densities of anhingas (p=0.0004) belted kingfishers (p = 0.0003), and ring necked ducks (p = 0.03) (Figures 4-4 – Figure 4-6). The density estimates for the glossy ibis and tricolored heron were greater during the winter (p =0.04 and p=0.04) at all lake stages except for one (Figure 4-7 – 4-8). S eason also was the predictor for the density estimates of the great egret, little blue he ron, and snowy egret, wh ich all show the same trend of greater density in the summer and winter and lower density during the breeding season (Figure 4-9 – 4-11). The density estimates for the sandhill crane were also influenced by season, but their numbers were greatest during the br eeding season (Figure 4-12). Table 4-6. The results of the generalized lin ear model analyses. The most parsimonious model is listed. The (+) symbol indi cates the additive effect of the two variables and the (*) indicates the intera ction effect of the two variables. Species Variable Anhinga Season Belted Kingfisher Season Common Moorhen Year Great Blue Heron Year Glossy Ibis Season Great Egret Season Green Heron None Little Blue Heron Season Least Bittern Season

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83 Table 4-6. Continued Species Variable Pied-billed Grebe Year Purple Gallinule None Ring-necked Duck Season Florida Sandhill Crane Season Snowy Egret Season Snail Kite Year Tricolored Heron Season Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 20 40 60 80 100 120 Estimated Density (# birds/littoral zone) Figure 4-4. Estimated densities for the a nhinga during the winter season within the littoral zone. The error bars correspo nd to 95% confidence intervals. The mean value is the pooled estimated dens ity derived from effort-weighted stage estimates.

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84 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 20 40 60 80 100 120 140 160 180 200 Estimated Density (# birds/littoral zone)Lake Stage (ft NGVD) Figure 4-5. Estimated densities for the belted kingfisher during the winter season within the littoral zone. The error bars corres pond to 95% confidence intervals. The mean value is the pooled estimated dens ity derived from effort-weighted stage estimates.

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85 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 200 400 600 800 1000 1200 Estimated Density (# birds/littoral zone) Figure 4-6. Estimated densities for the ringnecked duck during the winter season within the littoral zone. The error bars corres pond to 95% confidence intervals. The mean value is the pooled estimated dens ity derived from effort-weighted stage estimates.

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86 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean Estimated Density (#birds/lake littoral zone) 0 100 200 300 400 500 600 Breeding Season Summer Season Winter Season Figure 4-7. Estimated densities for the glossy ib is within the lake litt oral zone related to season and lake stage. The error bars correspond to 95% confidence intervals. The mean values are the pooled estimated densities derived from effortweighed stage estimates for each sample season.

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87 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 50 100 150 200 250 300 Breeding Season Summer Season Winter Season Estimated Density (#birds/lake littoral zone) Figure 4-8. Estimated densities for the tricol ored heron within the lake littoral zone related to season and lake stage. Th e error bars correspond to 95% confidence intervals. The mean values are the p ooled estimated densities derived from effort-weighed stage estimates for each sample season.

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88 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 20 40 60 80 100 120 140 Estimated Density (#birds/lake littoral zone) Figure 4-9. Estimated densities for the great egre t within the lake littoral zone related to season. The error bars correspond to the 95% confidence intervals. The estimated densities associated with br eeding, summer and winter are estimated independent of year.

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89 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 20 40 60 80 100 Estimated Density (#birds/lake littoral zone) Figure 4-10. Estimated densities for the little blue heron within the lake littoral zone related to season. The erro r bars correspond to the 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimated independent of year.

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90 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 50 100 150 200 250 Estimated Density (#birds/lake littoral zone) Figure 4-11. Estimated densities for the snowy egret within the lake littoral zone related to season. The error bars correspond to the 95% confidence intervals. The estimated densities associated with br eeding, summer and winter are estimated independent of year.

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91 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 10 20 30 40 Estimated Density (#birds/lake littoral zone) Figure 4-12. Estimated densities for the Flor ida sandhill crane with in the lake littoral zone related to season. The error bars correspond to the 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimated independent of year. The interaction of stage and winter seas on during the year 2003 was the predictor model for the common moorhen, great blue her on and pied-billed grebe. All three of these species had no temporal or environmenta l variables driving their densities until the drawdown event during the winter. All th ree focal species’ densities increased significantly during the winter 2003 season (Figures 4-13 – 4-15). All of the focal species except for the green heron, least b ittern, sandhill crane, and ring-necked duck showed higher densities during the winter of 2003. The densities of ring-necked ducks decreased in response to the dr awdown and the green heron, l east bittern, purple gallinule and sandhill crane numbers were unaffected duri ng that period of time. There were no

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92 predictor models for density fo r the green heron or purple gal linule as their densities were constant during the entire period of study. The de nsities of the last focal species, the snail kite, decreased during the summ er and winter 2003. Snail ki te densities were greatest during the breeding season 2002 and fluctuated during all other seasons (Figure 4-16). Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 500 1000 1500 2000 2500 3000 Estimated Density (# birds/littoral zone) Figure 4-13. Estimated densities for the comm on moorhen within the lake littoral zone related to season. The erro r bars correspond to the 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimated independent of year.

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93 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 Estimated Density (# birds/lake littoral zone) 0 20 40 60 80 100 120 140 160 Figure 4-14. Estimated densities for the grea t blue heron within the lake littoral zone related to season. The erro r bars correspond to the 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimated independent of year.

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94 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 20 40 60 80 100 Estimated Density (#birds/lake littoral zone) Figure 4-15. Estimated densities for the pied -billed grebe within the lake littoral zone related to season. The erro r bars correspond to the 95% confidence intervals. The estimated densities associated with breeding, summer and winter are estimated independent of year.

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95 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 20 40 60 80 100 120 140 Estimated Density (#birds/lake littoral zone) Figure 4-16. Estimated densities for the snail k ite within the lake littoral zone related to season. The error bars correspond to the 95% confidence intervals. The estimated densities associated with br eeding, summer and winter are estimated independent of year. Discussion Spatial Variations Wetland birds distribute themselves along an elevation gradient within the littoral zone according to how well they are adap ted to water (Mitsch and Gosselink 2000). Some species, such as the rails, live ac ross the whole range of wetlands, while other species, such as dabbling ducks, prefer th e marsh-water interface (Mitsch and Gosselink 2000). Habitat-selection responses are si multaneously functions of both hydrology and habitat structure (Smith et al. 1995). Within the littora l habitat of Lake Toho, line transect surveys covered the extent of th e littoral zone, including the water-marsh

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96 interface. The focal species present on Lake T oho used the all of the habitats within the littoral zone, although some sp ecies’ densities indicated a preference for a particular habitat type. Little blue heron densities were never hi gher on previously scraped transects than inside or outside transects. The sparsely-v egetated shoreline and steep slope were not conducive to the foraging needs of the little bl ue heron. The snail k ite, least bittern, and green heron, were detected equally on each of the transect types. The least bittern and green heron typically use tall stands of emergent vegetation. This preferred habitat type spans the area between both the inside and out side line transects and these species were observed from both sides of the littoral habi tat equally. The snail kite was usually observed while in flight and was seen from all transect types as it foraged for apple snails in different vegetation communities within the littoral zone. The Florida sandhill crane was only seen on inside and previously scraped line transects due to their extensive use of the pastureland and land-water ecotone, area s easily visible sampling an inside line transect. The ring-necked duck and purple ga llinule were found in outside habitats, however the densities were lower in previous ly scraped line transects than they were on inside line transects. Although the previously scraped habita ts include open water, the lack of floating leaf aquatic vegetation as well as other deep water submerged aquatic vegetation creates a habitat that is not suit able for large densities of these two focal species. The line transect sampling protocol included the three types of line transects within the littoral zone to take into account movement of species within the littoral zone during different times of the year and at different lake stage levels. The analyses did not

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97 measure seasonal effects on littoral habitat usage by individual bird species, but the sampling protocol assumed that one existe d. For example, the common moorhen is evenly distributed within the littoral habitat as indicated by our results. However, if our line transects were all arrange d in the inside littoral zone habitat, when lake stage decreased, our results would i ndicate that the densities of common moorhens decreased, when in fact they remained the same. By having a portion of line tr ansects at the marshlake interface, the common m oorhens are sampled on the outside transect during periods of lower lake stage. Transect line-type preferences for many of the focal species were inconclusive because the analyses used the pooled density estimates for each focal species by line type over the two years of sampling. A future an alysis can include us e of general littoral habitat (inside or outside) based on season, year and lake stage level. By combining the results of this study with the pre-enhancem ent vegetation study (Welch 2004), specific vegetation use by focal species can be determin ed. If habitat use were analyzed within seasons or at particular lake stages, one would find that many species move within the width of the littoral habitat as conditions vary. This indicat es the importance of the entire littoral habitat to wetland birds, not just th e deep or shallow water communities. Species often prefer the local hab itat around a wetland complex that provides various needs but also may act as a backup in event of cat astrophic change (Dob rowlski 1997). Wetland birds that forage the shoreline or shallows are highly mobile because foods are so closely linked to precise water depths; a centimeter can make major differences in invertebrate distribution (Weller 1999). The inclusion of a ll the line transect ty pes in the analyses

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98 covers the entire littora l habitat used by the focal species throughout the period of sample pre-enhancement. Temporal and Environmental Variations Wetland birds living in Florida, which has moderate temperature regimes and where water is generally availa ble all year round, are not for ced to migrate long distances to obtain resources and many are year round re sidents (Weller 1999). The challenge is to determine the correlates of lo calized bird movements within a system. The results of the whole lake sampling indicate that there were no good environmental predictors of these changes in density without including avian se ason. The unpredictability of resources available to avian species during a season lead s to the complexity of predicting densities of these species independent of year. For exam ple, densities of the endangered snail kite on the lake during the breeding season 2002 was significantly greater than the densities the same season the following year. The mont hly samples of the littoral zone were not frequent enough to determine the environmen tal variable that ma y have caused this decline in densities during the breeding season. The lo cal environmental conditions on the lake may have been different during the breeding season 2003 and may have negatively impacted the aquatic apple snail, the main prey item of the snail kite. Analyses conducted by season, without in cluding year, indicated no significant differences in density for the snail kite throughout the study. Lake stage, although not a si gnificant predictor alone, wh en acting within a season and year did explain some of the trends in densities of the focal species. The unusual occurrence of a localized drawdown event dur ing the winter season attracted many focal species to the littoral habitats of the lake. Ot her explanations were al so explored, such as unusually warm conditions in November and December 2003 compared to 2002. Cold

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99 temperatures cause small fish to become less active and to flee, burrow, and hide more readily when disturbed, which may render it more difficult for wading birds to secure prey during the cold seasons (Frederick and Loftus 1993). If it was unusually warm for this time of year, one would see similar tre nds as in the summer, when wading birds have the highest densities within the littoral zone This, however, was not the case. The period of time surrounding the sample (Winter 2003), sa w significantly lower temperatures than the normal (NOAA 2003). The trends in the density estimates are correlated with the drawdown event during this time of year. The winter 2003 sample season corresponded with the very beginning of the drawdown. Species that would benefit by prey items getting trapped due to rapid declines in lake stage all show increases in densities as more prey items became easily available within th e littoral zone. A lthough many focal species, especially wading birds, responded positively to the prey availability of the drawdown, others reacted negatively. The densities of many species, which use th e pastureland or the lake edge of the littoral zone, were not affected by the initia l drawdown. Densities of ring-necked ducks, sandhill cranes, green herons and purple gall inules were not immedi ately affected by the drawdown. Sandhill cranes, in the winter, fo rage opportunistically in pasture land and that area was unaffected by the lake level lo wering. Ring-necked ducks use the littoral zone as well as the lake habitat and their wi nter numbers were not significantly different than were the previous year. Green herons and purple gall inules associate with deep water vegetation and, during the sampling pe riod, winter 2003, there was still water in those habitats.

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100 Specific conclusions generated from both th e point and line transect sampling will be presented in the following discussion chapte r, which compares th e results obtained for each type of sampling.

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101 CHAPTER 5 DISCUSSION OF STUDY AREA VS. WHOLE LAKE SAMPLING Introduction Although resource use is ofte n investigated across a c ontinuum of temporal and spatial scales, the scale at which the investig ation is conducted will ha ve dramatic effects on the observed patterns and conclusions a bout the underlying processes (Wiens 1981, May 1993). Avian studies that have compared line and point transect sampling results have concluded that different types of sampling are more effective for different species (Buckland 2004). On Lake Toho, this may be true, for example, in cases where species are not restricted to one habita t type within the littoral zone, but rather move within the littoral zone based on environmen tal conditions such as lake st age. It is important to determine information desired from the result s of distance sampling before a survey is designed. In multi-species surveys it is difficult to devise simple field procedures that will give low bias across a wide range of species (Buckland 2004). The three assumptions of distance sampling are the same for point and line transect sampling, but there are many differences in information obta ined from each type of survey and how it can be interpreted. Caveats of Point Transect Distance Sampling Point transect sampling is useful for conducting multi-species surveys in difficult terrain where walking from one point to the next is problematic (CREEM 2004). There are many things that must be considered when looking at the results from the point transect distance sampling.

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102 The assumption that birds are detected be fore movement triggered by the observer is the first assumption we will address. The length of the point transect surveys (60 minutes) was sufficient enough for observers to r ecord all of the species that were present at the observation location from the start of the survey. In the littoral habitat, the distance which an observer could see gave them the advantage of recording species upwards of 800 meters from some point transect locations. Observers typically want to write down everything they see and the protocol must reflect this fact. For example, if the protocol states to igno re all birds greater than 300m, there will be a disproporti onately large number of observations around 300m. In the analyses phase, these observations at dist ances further away from the point contribute little to estimating the detec tion function, but may lead to poor fit and high variance, therefore it is critical that close distances are accurat ely recorded (CREEM 2004). Data truncation was done in the analysis phase to avoid these issues. One caveat of conducting such a long survey is that birds may m ove around and the chance of double counting an individual is greater with the length of the survey. Any movement of birds during the sample generates upward bias in density estim ates, even if the movement is independent of the observer (Buckland et al. 2001: 173). This problem may also be compounded with the fact that birds moving around ar e more likely to be detected closer to the point, so that detection distances tend to be too small, ge nerating further upward bias in density estimates. This problem was partially remedi ed by the exclusion of aerial birds in the analysis. The open littoral ha bitat makes it easier for obs ervers to keep track of individual species as they c ounted new ones that came into view. Unfortunately, due to

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103 the openness, there may have been some viol ations of another assumption of distance sampling. The assumption stating that birds on the line or point in distance sampling are detected with certainty was met during the po int transect sampling; however, some birds may have avoided the observer because of the vi sibility associated with the open habitat. The observer on a bird blind used a camouflage d material to better conceal their presence in the marsh. The bird blinds were 6 feet tall and, in a landscape with no trees. Despite the camouflage the bird blinds we re obvious to many avian species. The presence of an observer in th e blind may not have been as obvious to the birds as the actual structure. This was evident when observi ng flying birds. Some species, such as the belted kingfisher landed directly on the bird b lind. Wading birds in flight would be a few meters above the blind before they saw the observer and abruptly changed directions. Birds that were foraging from below the bird blind were often seen walking right towards the blind completely unaware of the obser vers’ presence. Other species would be foraging in the shallows and ignoring the bird blind. In general, the data indicated there was avoidance toward the observa tion station by most species. This led to poor fit of the detection function at zero distance for many species. Typically the opposite problem occurs in songbird studies in closed canopy upland habitats where many of the observations are directly over the obser vers’ head (at zero distance) (CREEM 2004). Havi ng point avoidance is a unique characteristic usually observed with distance sampling in open habita ts. Within the distance analysis this problem was dealt with by left truncating the da ta so that the fit of the detection function starts at some distance away from the point (depending on species), in which the species

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104 are detected with certainty yet are not avoiding the observe r. Left truncation is not advised unless there is good reason to believe that there is avoidan ce of the observer by a species, making certain other assumptions of distance sampling are not being violated (ex. movement away from location due to observe r). In the point transect data analyses data corresponding to many of the medium and large wading birds we re left truncated. Other avian species, particularly those that ar e cryptic in nature (least bittern) or that forage on top of the water surface (common mo orhen) would go directly underneath the bird observation blind and had suffici ent observations at zero distance. Another assumption of distance sampling is that distances are estimated or measured accurately. Measurement errors generate substantially more bias in density estimates than do errors of similar magnitude in line transect samp ling (Buckland et al. 2001:195). This is because the number of birds available for detection increases as one is moving away from the point. On line transect samples, the number of birds available for detection remains the same as one traverses th e line. Exact distance measurements were relatively easy to obtain in open habitat, esp ecially given the length of the samples. The same distance sampling assumptions apply to line transect sampling but new caveats are associated with the whole lake sampling protoc ol used in the pre-lake enhancement bird study. Caveats of Line Trans ect Distance Sampling The same three assumptions of distance sampling also apply to line transect sampling. One assumption is that birds need to be detected before evasive movement triggered by the observer. In line transect sampling, movement of birds independent of the observer is less problematic than for point transect sampling (Creem 2004). The opposite is true if an airboat is used to conduct line trans ect sampling. If the average

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105 speed of the bird is less than half the speed of the observer, bias is small (Buckland et al 2001). Airboat drivers took care to approach the line transect slowly, allowing observers time to scan the length of the transect looki ng for areas with many i ndividuals or obvious individuals on the line. As the airboat traversed the line tran sect, the airboat stayed ahead of the flushing birds, pushing them back toward the section already sampled. Line transect sampling is often used for species that are detected thr ough a flushing response, however not all bird species react the same way to the airboat appr oaching. All birds on the transect line must be detected, and if the transect is too long, or if there is a lot of vegetation on a particular transect, this assumption may be violated. The visibility of the 400 m long transect li ne was important to avoid violation of the assumptions of distance sampling. This was achieved by the use of PVC poles marking the beginning and end of the transect line. The line transects were permanent and were run monthly. A poten tial bias exists for the inside line transect types during times of the year when the lake stage was low. An airboat track on the inside line transect would remain from one sample occa sion to the next, with little vegetative recovery. In some instances th is trail would act as an attr actant, especially to larger wading birds, particularly the great blue he ron and the great egret. However, during times where the trail did not remain, these bi rds were still observed on the line transect, so overall bias may actually be small. The assumption that birds on the line are detected with certainty was remedied by conducting dual observer surveys. Some indi vidual transects had 16 different species comprising 33 clusters of birds, each requiring an associated distance. By having two observers, the secondary observer, in addi tion to looking for missed birds, obtained

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106 distances to birds on transects when the pr imary observer had a lot of observations to record. The challenge of seeing all birds along th e line transect is incr eased tenfold by the use of an airboat to conduct the sample. The primary observer keeps track of original locations of all of individuals flushed by th e airboat as the observers are traversing the transect at a speed to stay in front of the fl ushing birds. Distances to landmarks such as trees, vegetation patches, and shoreline featur es along the line transect were recorded and later distances to some birds were estima ted based on their relation to the landmarks. After a line transect was run, the observers would talk about any discrepancies with species or distances and, if necessary the crew would go b ack for a second look and to obtain exact distances. Despite the best effort s of the crew, often tim es exact distances of observed species were not obtained. There was evidence of “heaping” of data for some species. There were spikes in the detection function histogram for the whole lake data at distances which are common rounding numbers. For example, common distances of spikes in the data were seen at 25m, 50m, 75m, and 100m. This was remedied by manually selecting intervals used for the goodness of fit tests and hist ograms of distances. Anothe r caveat of our line transect methodology was that the line tran sects ran parallel to natura l structures such as the treeline, shoreline, and vegetation zones, wh ich also caused data to look heaped due to bird observations often occurri ng at distances associated with these natural structures. Spatial Variations of Point and Line Transects The results obtained by the point and line transect sampling are both useful and informative when they are compared, although they contain very different information overall. To allow for direct comparisons between sampling methods, results were displayed as avian density at th e scale of the lake littoral z one. In reality, the densities

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107 obtained from the study areas can really only be applied to the avian density within the study areas because of the scale of the sampli ng. Each monthly line transect sample covered 312 hectares (771 acres) of the li ttoral habitat (14% of the total emergent vegetation on the lake). The study area sa mpling covered 256 hectares (633 acres) (11.5% of the total emergent vegetation on th e lake) during a week of sampling within the study areas. If the entir e study area was sampled during a sample week, actually only a fraction of that area was sampled. For exam ple, during a sample week, if each observer had a visibility of 100m of littoral zone, then 63.5 total hectares (24%) of the 256 total possible hectares within the three study areas were actually sampled. A month (2 sampling weeks) of point transect sampling e ffectively covers about half of the entire study areas available to sample. The effort it takes to sample 18 point transect locations associated with the month of samples only c overs 3% of the entire emergent vegetation within the littoral habitats of the lake. Distance sampling can provide estimates of abundance over very large areas with only modest resources (Buckland 2004). This is true in situations where point or line transects are either systematically spaced or randomly placed within the entire area of interest (CREEM 2004). The whole lake line transect sampling effectively does this. However, the study area point transect samp ling design did not randomly sample within the entire littoral zone or cove r the littoral habitat evenly; ra ther efforts were concentrated within the three designated st udy area locations. The point transect data provides a good estimate of localized density at the three study areas and post-lake enhancement will be good for comparison at the treatment level. The line transect data provides a better overall picture of avian densities within the littoral habitat of the entire lake based on

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108 estimates generated from the whole lake sampling. Due to the scale of the lake enhancement project, all of the randomly placed line transects are located in areas where the vegetation will be scraped. The line transects can also be used to directly compare treatment effects at the scale of the whole lake. It was the overall goal of the avian monito ring project to genera te baseline data which can be used for comparison post enha ncement. This was achieved by generating densities for focal species at study area a nd whole lake sampling scales and then by relating these densities to vari ous spatial, temporal and en vironmental factors at each scale of resolution. In order to create baseline data abou t avian distributions, use patterns and abundances within the littoral zone of the lake, results from the two types of sampling must be compared. Environmental and tempor al variables which in fluence densities of focal species at one scale of resolution ma y have no effect when looking at the other scale. The spatial locations of point vs. line transects within the littoral zone will explain some of the results generated in the previous two chapters. The center of the point transect sample lo cations are organized in two lines running parallel to the shoreline within the littoral zone out to the four foot depth zone. The inside line transects correspond to the point tr ansect locations runni ng parallel closest to the shore (Figure 5-1). The outside line trans ects are situated in the 4-5 foot depth zone in the littoral zone, 100m lakewa rd of the outside point tran sect row of study area (Figure 5-2). Very different vegetative communities and associated water depths were sampled although the outside line transect location was only 100m away from the point transect locations. The vegetative community associated with the 4-5 foot depth zone included

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109 the tall emergent vegetation and divided the tw o types of samples. Due to the central location of this vegetation, observers on the out side line transect or in the study area were not always able to see to the other side during a sampling occasion. The inside study area point sampling locations were spatially correla ted with the inside lin e transect locations and spatially the potential of seeing the same species was equal. Figure 5-1. Spatial relationship of point transect locations (white) within study area two and permanent inside line transects (red) The depth zones are indicated in blue and start at the 0-1 foot depth zone (lightest blue). Figure 5-2. Spatial relationship of point transect locations (white) within study area one and permanent line transects (red) (two outside and one inside). The depth zones are indicated in blue and start at the 0-1 foot de pth zone (lightest blue). Conclusions from Study Area and Whole Lake Sampling In order to draw conclusions from the results obtained from the study area and whole lake sampling, each focal species needs to be examined differently. Some species

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110 were more easily sampled on line transect samp les. Species which are cryptic, yet flush in response to an airboat were more effec tively sampled on line tran sects. Variations exist for species that prefer a particular type of vegetation to forage in within the littoral zone. When environmental conditions and habitat are no longer conducive for feeding, these species move to a completely different location, rather than just moving within the littoral zone. Other species find a new locati on within the littoral habitat, but usually involving different vegetation community types. For example, the least bittern would flush from a moving airboat and observations we re frequent near the transect line. The same species, when sampling within the st udy areas was only seen when it jumped up and became obvious to the observer and of ten it was observed because it had moved closer to the bird blind (violating an assump tion of distance sampling). The least bittern, however may be influenced by environmental variables which only can be determined by conducting line transect samples. In the following section the results of the study area and whole lake sampling will be described and compared for each focal species (presented in alphabetical order) and overall re sults will be derived from the information generated from both study ar ea and whole lake sampling. American Coot The American Coot is a winter non-breeding resident in Florida. The results from the study area sampling indicated that densitie s for the American Coot were greatest at study area one. The additive effect of seas on and stage explained the variation seen in the densities of the species w ithin the study area locations. This focal species was not sampled at the whole lake sampling scale. Th e American coot is a highly mobile species that moves throughout the littoral habitat and it s overall density is positively correlated with lake stage level, although the species is pres ent throughout the wi nter season at all

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111 the study areas. The species will heavily use the deeper water habi tats of the littoral zone, the numbers were too many to count on li ne transect surveys, which is why they were not recorded. Anhinga The anhinga is a year round Florida resi dent which does not nest on Lake Toho. The results from the study area sampling indicated that densities for the anhinga were not different between the three study areas because the species uses deeper open water habitats to forage and was seen in the study areas perched and drying its feathers between foraging attempts. Study area sampling and line transect sampling indicated that densities for the anhinga were greatest duri ng the winter season. These densities were estimated to be greater in th e study areas during the first wi nter season and greater on the line transect samples the second winter season. The difference of mean densities for the anhinga for the winter season only differed by one bird between the sampling types. Many of the observations of this species were made while the bird was perched within the littoral zone over water. The anhinga doe s not perch over dry land. The increase in density is due to the anhinga moving lakeward in response to low la ke stages. Anhingas perched further away from shore had a highe r probability of being observed from the outside line transect during this period of time and were prob ably too far out to be seen from the study area poin t transect sampling. In conclusion, the Anhinga is most common on Lake Toho during the winter season. This mobile bird forages the littoral habitat in fairly open water and perches on structures within the littoral zone over wate r to dry its feathers. The densities of the anhinga are distributed evenly throughout the littoral habitats In cases of lower lake

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112 stages, the species will move lakeward out of the shallow water vegetation of the littoral zone to where the water levels are conduc ive for foraging and perching above deeper water. Density estimates for both methods of sampling can be used to compare with data collected post lake enhancement. I predict that the anhinga will not be aff ected by the lake enhancement project and the densities of the species on the lake will remain the same or increase. More open water will create more foraging habitat for th e anhinga. The number of perches within the littoral zone will remain th e same, but I don’t believe the de nsities of this species are dependent on number of perches. Environmen tal variables such as lake stage will still have the same effect on the species. Season of Sample Winter 0203Winter 03Winter Estimated Density (# birds/ 500 ha) 0 5 10 15 20 25 30 35 Study Area Sampling Whole Lake Sampling Figure 5-3. Estimated density for the anhi nga within the study areas and along line transects during the winter season. Es timated abundances associated with winter are estimated independent of year of sample. Densities were estimated as number of birds per 500 hectares.

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113 Belted Kingfisher The belted kingfisher is a common waters ide resident on Lake Toho during the non-breeding seasons. Like the anhinga the belted kingfisher is usually observed on a perch as it rests and forages w ithin the littoral habitat. The results of the study area sampling indicated that the belted kingfisher di d not prefer the littoral habitat associated with study area three, although it was found at a ll the study areas. The interaction effect of season and stage explained the densities seen within the study areas. Winter season was the only predictor variable which explai ned the density estimates from the whole lake sampling. The study area density estimates have a pos itive correlation with stage within the study areas and a negative correlation with st age within the whole lake sampling areas (Figure 5-4). This indicates that the belte d kingfisher moves to deep water vegetative habitat as stage decreases. The mean dens ities are similar between the two sampling scales. The belted kingfisher fo rages and perches over water. In conclusion, the belted kingfisher is most common during the summer and winter seasons. The species uses the entire width of the littoral habitat. The densities are correlated with water depth within the littora l zone and it moves to deep water habitats during periods of low lake stage. I predict that the densities of belted kingfishers will decrease post-lake enhancement. There will be more open wa ter habitat for the kingfisher to forage, however prey items may take more energy to ob tain due to the lack of vegetation within the littoral zone. Lake stage will still aff ect where the belted kingfisher is within the littoral zone as it hunts over water.

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114 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 20 40 60 80 100 Estimated Density (# birds/ 500 ha) Study Area Sampling Lake Wide Sampling Figure 5-4. Estimated density for the belted kingfisher within th e study areas and along line transects during the summer and winter seasons. Error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighted stage es timates. Densities were estimated as number of birds per 500 hectares. Boat-tailed Grackle The boat-tailed grackle is a year round resi dent in Florida and nests in the littoral habitat of Lake Toho. The results of the st udy area sampling indicate d that the greatest densities of boat-tailed grackles occurred at study area one, although the species was widespread throughout the entire littoral hab itat. The temporal variable, season, best explained the variations seen in the boat-taile d grackle densities. Densities were greatest during the breeding season during nesting. De nsities dropped slightly during the summer and even more during the winter. The boattailed grackle was the second most common

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115 passerine within the lake littoral zone. Passerines were not sampled on line transect surveys at the whole lake level due to their large numbers. The boat-tailed grackle will be affected by the lake enhancement during the breeding season. Significantly fewer birds, whic h nest in medium to tall thick emergent vegetation, will be able to nest in the remaining vegetation. I predict that the densities of the boat-tailed grackle will be significantly reduced overall and especially during the breeding season post-lake enhancement. Cattle Egret The cattle egret is a year round resident in Florida and forages chiefly in pastureland adjacent to the littoral zone habi tat. The cattle egret densities were not correlated with any environmental or temporal variables. The densit ies of the cattle egret were greatest at study area one where the numbe r of grazing cattle was also the greatest. Cattle egrets were not included in the line transe ct analyses. I predict that the densities of cattle egrets within the littoral habita t will be unchanged in the post enhancement sampling, given that cattle gra zed pastureland will still be adjacent littoral habitat. Common Moorhen The common moorhen is a year round resident that nests within the littoral habitat. The results of the study area sampling indicate that it is widespread but densities are highest within study area one. The line trans ect data indicate it is distributed evenly throughout the littoral zone and was seen equall y on all line transect t ypes. Stage was the only environmental variable which influen ced density within the study areas. The interaction of stage and year influenc ed densities on line transect sampling. There were twice as many common moor hens observed during line transect sampling than on point transect sampling. De nsity is positively co rrelated with stage

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116 within the study areas and positively correlated at low lake stage on the line transects (Figure 5-5). This indicates the common moor hens equally use the deeper and shallower water habitats within the littoral zone and ar e easily seen during both surveys. However, densities are positively correlated with lake st age within the study areas inside the littoral habitat. In conclusion, the common moorhen is di stributed evenly th roughout the littoral zone at all lake stages, with the exception of very low lake stages. It is mobile, and during periods of lower lake stage it will m ove lakeward into different vegetative communities. The littoral zone provides nesting substrate for the common moorhen. I predict that the densities of common moorhe ns within the littoral zone will decrease dramatically post enhancement. The mobility of the common moorhen will decrease as a result of the loss of various depth zones th roughout the littoral z one. Lake stage and weather conditions (ex. wind) will have a greater influence on the common moorhen within the littoral zone wit hout a barrier of vegetation to protect the bird from wave action and water level fluctuations. The co mmon moorhen is well ad apted to the littoral zone habitat and an open water habitat (even if shallow) is not conducive to the feeding and nesting requirements of this species.

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117 Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 100 200 300 400 500 600 Study Area Sampling Whole Lake Sampling Estimated Density (# birds/ 500 ha) Figure 5-5. Estimated density for the common moorhen within the study areas and along line transects during the pre-enhancem ent study. Error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighted stage es timates. Densities were estimated as number of birds per 500 hectares. Florida Sandhill Crane The Florida sandhill crane is a year round resident on Lake Toho and, it nests within the shallow littoral habitats. The an alyses of the study area samples indicated there were no variables describing changes in density estimates. The line transect samples indicated higher densities during the breeding season. These discrepancies are a result of the spatial scale of the two types of sampling. Flor ida sandhill cranes prefer to nest in Pontedaria cordata (pickerelweed), and Panicum hemitomon (maidencane) and avoid floating leaf aquatic and other deep water species. They also prefer to nest in water

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118 depths of 30 – 40 cm, and water depths may determine the nesting vegetative substrate from year to year (Dwyer 1990). The Florida sandhill crane was never observe d on an outside line transect because of the habitat and water depths associated with outside line transects. A pair of nesting cranes will not typically nest closer than 277 meters away from the next active nesting pair (Dwyer 1990). The number of potent ial cranes encountered during the breeding season is different for the two types of samp ling. In the area covered by the whole lake sampling, during breeding season, there are potentia l for four times the number of nesting sandhill cranes which may be encountered on a sample compared to the potential number within the study areas. However, when one lo oks at only the inside transect types then twice the number of nesting sa ndhill cranes can be seen from line transect surveys. The densities seen on the combined line transect types indicate fewer cranes because no cranes were observed on the outside line transect type s and few were observed on previously scraped line transe ct types (Figure 5-6). In conclusion, in order to determine dens ities of sandhill cranes using whole lake sampling, analyses must be conducted on inside line transect data a nd possibly previously scraped shorelines only. By doing this the e ffort can be adjusted and the densities will accurately reflect densities with in the littoral zone. The larger confidence intervals and variance associated with the point transect su rveys are due to encount er rate (explaings 71% of the variance) which indicates that the birds are spaced apart from each other. I predict that the densities of the sandhill cr anes post-lake enhancement will decrease, particularly during breeding season. The past ureland will still be used for foraging all

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119 year round, however the nesting habitat for the sandhill crane will be removed during the lake enhancement. Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 10 20 30 40 50 60 70 Studay Area Sampling Whole Lake Sampling EstimatedDensity (# birds/ 500 ha) Figure 5-6. Estimated density for the Florid a Sandhill Crane within the study areas and along line transects during the pre enha ncement study. Error bars correspond to 95% confidence intervals. The estimat ed densities associated with winter, breeding and summer are estimated inde pendent of year and is the pooled estimated density derived from effort we ighted year estimates. Densities were estimated as number of birds per 500 hectares Glossy Ibis The glossy ibis is a year round Florida re sident, but it does not breed on Lake Toho. The densities of the glossy ibis were equal at study areas one and th ree. Lake stage was the predictor variable which explained variations in dens ity estimates within the study area locations. The glossy ibis was distributed across inside and previously scraped line transects, although it had greater density estimates associated with the areas of the lake

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120 which were previously scraped. The winter season variable best explained the increased density on the whole lake samples. The glo ssy ibis probes mud to obtain various aquatic prey items, and its densities ar e higher within the littoral z one at lower lake stages as foraging areas become exposed. During low la ke stages, the glossy ibis did not move with the water, rather the higher densities we re observed on inside and previously scraped transects as the glossy ibis foraged in th e exposed muddy areas. Densities on the point and line transect sampling were the same, excep t for during the lowest lake stages (Figure 5-7). In conclusion, the densities of glossy ibis are fairly constant within the study areas and whole lake sampling. When lake stage levels are low, the littoral zone remains saturated and the glossy ibis is able to succe ssfully forage the marsh. The area which the glossy ibis usually forages is the wet eco tone between the litt oral habitat and the pastureland. At lower lake stag es the area available to them expands into the littoral zone and their densities increase. I predict that the densities of glossy ibis on the lake postlake enhancement will remain unchanged, however, at lower lake stages I predict that the densities will not increase. Post enhan cement, the foraging substrate will consist principally of sand spanning from the littora l habitat through the eco tone and into the pastureland. I predict that prey items will be fewer and harder to obtain in this foraging substrate.

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121 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 20 40 60 80 100 Study Area Sampling Lake Wide Sampling Estimated Abundance (# birds/ 500 ha) Figure 5-7. Estimated density for the glossy ibis within the study areas and along line transects during the pre-enhancement study. Error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighted stage estimates. Densities were estimated as number of birds per 500 hectares. Great Blue Heron The great blue is a year round resident on Lake Toho and sometimes nests in the trees surrounding the lake. The results from the point transect sampling within the study areas indicate that the great blue heron prefers study area tw o. Densities are higher on inside line transects than both the outside a nd previously scraped lin e transects. Lake stage was the indicator variable for density in study area sampling. The interaction of year and lake stage were the indicator variab les for density in the whole lake sampling.

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122 In the study areas, great blue heron density is positively correlated with lake stage. On line transect samples lake stage is only correlated with density at low lake stage (Figure 5-8). Great blue herons are mobile and will opportunistically forage the entire littoral habitat. Floating mats of vegetation provide access to deep water habitats for the great blue heron. The densitie s of great blue herons seen on line and point transects are greater at every lake stage, with the excepti on for extremely high lake stages. The higher lake stages occurred during the winter wh en prey items are ha rder to obtain. In conclusion, the densities of great blue herons within th e littoral zone are constant throughout the year. They use the entire li ttoral zone for foraging, but will move to deeper vegetation communities when the lake stag e is low. I predict that the densities of great blue herons will decrea se post-lake enhancement. The area that the great blue heron has access to prior to the drawdown is the entire width of the vegetative communities within the littoral zone. After the lake enhancement the great blue heron will be limited by the maximum water depth (28cm) at which they can effectively forage (Powell 1987). Decreasing area available to the great blue heron to forage and the removal of the habitat preference of many prey items will contribute to the decrease in density on the lake.

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123 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 5 10 15 20 25 30 35 Study Area Sampling Whole Lake Sampling Estimated Density (# birds/ 500 ha) Figure 5-8. Estimated density for the great bl ue heron within the study areas and along line transects during the pre-enhancem ent study. Error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighted stage es timates. Densities were estimated as number of birds per 500 hectares. Great Egret The great egret is a year round Florida resident that does not nest on Lake Toho. The results of the line and point transect sampling indicate that the great egret is widespread within the littoral zone. Its densities were not different between study areas or whole lake sampling. Both scales of reso lution showed fewer numbers of great egrets within the littoral zone during breeding season and the same densities through summer and winter. The same trends are seen for each season from both sampling types; however, the densities from the line transect sampling are at least twice as great as

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124 densities within the study area sampling (Fi gure 5-9). This may be explained by scale and given that great egrets are solitary when foraging and the chance of one being on a line transect sample is greater because of area covered. Densities were greater on previously scraped line transects than for the inside line transects. This may explain the low numbers in the study areas since they were located solely in inside littoral habitat. The two types of sampling yielded differe nt densities during the drawdown (winter 2003). Densities within the st udy areas decreased while dens ities on the line transects increased. In conclusion, great egrets are widespread throughout the littoral habitats. Sampling the great egret using whole lake samp ling accurately describes their densities. At level of the study area sampling, the densiti es of the great egre t are underestimated due to decreased encounter rates. At lower lake stages birds move out of the inside littoral zone and use the deep er water habitats. After the lake enhancement the great egret will be limited by the maximum water dept h (28cm) at which they can effectively forage (Powell 1987). Decrea sing area available to the great egrets to forage and the removal of the habitat preference of many prey will contribute to the decrease in density of the great egret on the lake.

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125 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 5 10 15 20 25 30 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-9. Estimated density for the great egret within the study areas and along line transects during the pre-enhancement study. Error bars correspond to 95% confidence intervals. The estimated densities associated with winter, breeding, and summer are estimated inde pendent of year and are the pooled estimated density derived from effort we ighted year estimates. Densities were estimated as number of bi rds per 500 hectares. Green Heron The green heron is a year round resident on Lake Toho. It breeds in tall emergent vegetation within the littoral zone. The densities of the gr een heron were greatest at study area two and distributed evenly across a ll line transect types. Season combined with lake stage as a categorical variable (inc reasing, decreasing, stat ionary), explained the density fluctuations seen in the study areas. There were no indicator variables to explain the density trends in the line transect sampling. Densities were significantly higher du ring the breeding season 2003. A prolific breeding season produced higher densities dur ing the 2003 summer and winter seasons. The increase in density occurred during a pe riod of time when the lake stage level was

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126 stable following a rapid decrease in stage over a short period of time. The green heron is a species which would hide from the oncoming ai rboat rather than flush. Because of this, green herons were rarely seen on line trans ect samples. Densities tended to decrease at lower levels of lake stage. The green he ron is associated with the tall emergent vegetation which is easily sampled from all line transect types while conducting a lake wide sample. During periods of low stage one would expect the green heron to remain in its deep water vegetative communities and not move out of the area. Without the data from the line transect surveys one cannot determine m ovement patterns of the green heron within the littoral zone. In conclusion, accurate green heron densities cannot be generated from whole lake sampling with an airboat. The data collected at the study areas indi cate a trend in season and can be used for comparison post-lake enhancement. I predict that post-lake enhancement densities of the green heron will decrease drastically with in the study areas. The tall emergent monospecific vegetation a ssociated with foraging and nesting for the green heron is not very re sistant to lake drawdowns. Any new growth of the Typha species will be aggressively managed with he rbicide. Wave acti on will also reduce the amount of tall emergent vegetation being re-established.

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127 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 20 40 60 80 100 120 Estimated Density (# birds/ 500 ha) Study Area Sampling Lake Wide Sampling Figure 5-10. Estimated density for the green heron within the st udy areas and along line transects during the pre-enhancement study. Error bars correspond to 95% confidence intervals. The estimated densities associated with winter, breeding, and summer are estimated inde pendent of year and are the pooled estimated density derived from effort we ighted year estimates Densities were estimated as number of bi rds per 500 hectares. Least Bittern The least bittern is a cryptic year round re sident that nests on Lake Toho. It nests and forages in monospecific tall emergent vege tation within the deep water communities. The least bittern is equally di stributed across all three study areas. It was never sampled from an inside line transect, and was obser ved only on outside and previously scraped transects. In both types of sampling, season was the indicator variable for density. Densities of the least bittern are higher on line transect sa mples compared to densities on point transect samples (Figure 5-11). This is partially due to the birds’ association with

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128 deep water vegetation communities and the locati ons of our outside line transect types. The least bittern flushed in response to the airboat on line transect surveys and was easy to detect. It usually forages and nests on the lakeward side of tall emergent monospecific patches of vegetation. During th e winter season, th e densities of leas t bitterns seen on line transect samples increased while they disappeared from th e point transect samples. This indicates that the species moves further lakeward in the littoral habitat after breeding and summer seasons. In conclusion, the whole lake sampling is better for sampling the least bittern within the littoral zone. Season is the only va riable which influences the densities of this species on the lake. I predict that post-lake enhancement densities of the least bittern will decrease drastically in the sa mples. As mentioned earlier, the tall emergent monospecific vegetation is not very resistant to lake drawdowns (Welch 2004). Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 5 10 15 20 25 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-11. Estimated density for the least bittern within the study areas and along line transects during the pre-enhancement study. Error bars correspond to 95% confidence intervals. The estimated densities associated with winter, breeding, and summer are estimated inde pendent of year and are the pooled estimated density derived from effort we ighted year estimates Densities were estimated as number of bi rds per 500 hectares.

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129 Little Blue Heron The little blue heron is a year round resi dent which does not breed on Lake Toho. Densities of the little blue heron were the greatest within study area one, but were distributed throughout all of the littoral zone vegetative communities. No environmental or temporal variables explaine d the densities in the point transect sampling, but season was an indicator variable for de nsity for whole lake sampling. With the exception of the winter season, de nsities of the little blue heron were slightly greater within the st udy areas than on line transect surveys (Figure 5-12). The little blue heron usually forages the shallows of the inside littoral zone habitat, but they also use floating mats to gain access to deep er water foraging. Acco rding to the results, even at deeper lake stages, the little blue heron stays close to the shoreline rather than foraging into deeper water vegetation communities. In conclusion, the little blue heron is not sensitive to ch anges in lake stage. The species uses the shallow vegetative communities for foraging more often than the deep water vegetation communities, although they are distributed throughout the littoral zone habitats. During period of low lake stage they do not move toward deep water vegetation communities, rather densities increase with in the same foraging locations they were located in when lake stage was higher. The l ittle blue heron will be an ideal species to examine following the lake enhancement within the study areas because it doesn’t move within the littoral habitat as much as other species. Post-lake enhancement I predict that the little blue heron densities will decrease dramatically. In the absence of emergent vegetation, they will only be able to forage the shoreline in water depths up to 19cm (Powell 1987). They forage in the sha llow water vegetation communities within the

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130 littoral zone, and with the absence of this ve getation they be forced to forage further upland into the ecotone a nd the pastureland areas. Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 10 20 30 40 50 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-12. Estimated density for the little blue heron within the st udy areas and along line transects during the pre-enhancem ent study. Error bars correspond to 95% confidence intervals. The estimated densities associated with winter, breeding, and summer are estimated inde pendent of year and are the pooled estimated density derived from effort we ighted year estimates Densities were estimated as number of bi rds per 500 hectares. Limpkin The limpkin is a focal species unique to Flor ida. It occasionally nests in willow or in the littoral habitats on Lake Toho. Densities of the limpkin on the lake are greatest near study area three, in Goblet ’s cove. Lake stage was the environmental indicator for density of the species. The observers on line transect sa mples never observed a limpkin.

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131 Goblet’s cove was not included in the line tran sect protocol. Densities of the limpkin are positively correlated with stage until lake stage exceeds 54.5 ft NGVD (Figure 3-10). In conclusion, the densities of the limpkin are heavily concentrated within Goblet’s cove. The densities of limpkins, in genera l increase as lake stage increases. The drawdown during the winter sampling season 20 03 had a negative effect on the density. In order to obtain accurate density estimates, analysis of only study area three should be conducted. I predict that the densities will decrease post lake enhancement with the drawdown, but will return back to the prior to lake enhancement densities. The limpkins heavily use the habitat directly across fr om study area three for nesting and foraging. This area will not be scraped during the enhancement and I predict that limpkins will increase their usage of this area. Pied-billed Grebe The pied-billed grebe is a y ear round resident in Flor ida. Although it is possible and probable that the species nests on the lake in thick emergent vegetation, only one nest was observed during two breeding seasons of sampling. The pied billed grebe was not observed frequently enough in study area samp ling to include it in the analyses, however it was more frequent on line transect sampli ng. The densities were constant throughout the study except during the drawdown in the wi nter season 2003. The densities of piedbilled grebes increased dramatically in response to the winter drawdown. Smaller fluctuations in lake stage di d not explain the density estimates of the pied-billed grebe. In conclusion, the pied-billed grebe is a good focal species for assessing the effects of the lake enhancement on the lakeward edge of the littoral zone. The results of the point transect surveys do not accurately repres ent the species within the littoral zone. I predict that the pied-billed greb e will be widespread in the littoral reaches of Lake Toho,

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132 after the lake enhancement. The species will forage in both open water as well as among aquatic vegetation. The presence of more open water will attract grea ter densities of the species to the entire r each of the littoral zone post-lake enhancement. Purple Gallinule The purple gallinule nests on Lake Toho and is a year round resident. The densities of the purple gallinule are the same at all three study areas. It was observed in greater densities on inside and outside line transects co mpared to previously scraped transects. There were no environmental or temporal va riables which explaine d the densities of purple gallinule in the littoral zone. In conclusion, the purple gall inule is an easy bird to survey and one of the few species which was evenly distributed throughout the littoral zone of the entire lake, with the exception of previously scraped shorelines The floating leaf aquatic communities in which they are closely associated occur over a wide range of water depths (20-180 cm, or 9-70 in (Welch 2004). The purple gallinule will be an ideal focal species to compare post-lake enhancement. The floating leaf aquatic communities are outside the area of the littoral zone which will be scraped, howe ver the extended period of time between drawdown and re-flood will have a negativ e effect on these vegetation communities (Welch 2004). I predict that the densities of the purple gallinule will decrease to the point of almost disappearing post-lake enhancement due to the decimation of the floating leaf communities. Even if some of these communities survive the lake enhancement, there will not be any vegetation connected to these communities decreasing accessibility. Ring-necked Duck The ring-necked duck is a winter migran t on Lake Toho. It uses the three study areas equally and was observed in higher dens ities on inside and out side line transects

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133 compared to previously scraped transects. Season was the only environmental variable which explained the variations in densities. The ring-neck duck forages on the lakeward edge of the littoral zone. The densities duri ng the winter seasons were consistent on both the line and point transect sampling, howev er there were about twice as many birds observed during whole lake sampling than within the study areas (Figure 5-13). In conclusion, the ring-necked duck is a good focal species for assessing enhancement impacts to determine any effects of wintering waterfowl usage of the littoral zone. It is best surveyed using line transect sampling, alt hough identifying waterfowl in flight from a moving airboat is challenging and many observa tions may get recorded as unknowns. The densities of ring-necked ducks did not increase or decrease during the drawdown during the winter 2003 season, as they are unaffected by changes in lake stage. I predict that this species w ill no longer use the littoral zone of Lake Toho as wintering grounds. This prediction is based solely on the fact that ring-necked ducks were never observed on any previously scraped littora l habitats within the littoral zone. Season of Sample WinterWinter 0203Winter 03 0 20 40 60 80 100 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-13. Estimated density for the ring-n ecked duck during the winter season within the study areas and along line transect s. Error bars correspond to 95%

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134 confidence intervals. The estimated densities associated with winter, are estimated independent of year and ar e the pooled estimated density derived from effort weighted year estimates Densities were estimated as number of birds per 500 hectares. Red-winged Blackbird The red-winged blackbird was the most co mmon passerine during the two years of sampling. This year round resident also nest ed within the littoral zone of Lake Toho. Sampling the red-winged blackbirds using dist ance sampling is challenging because they move extensively during the surv ey. Counts and distances were made to the best of the observers’ ability. I believe that these speci es were accurately sampled due to the fact that at least once during a sample, something would startle the floc k, and they would all take to flight allowing the observer to count additional i ndividuals. Study areas one and three had the greatest densities of red-winged blackbirds. They were not sampled during line transect sampling. Results from the st udy area sampling indicate that season was the only predictor variable for density. Overa ll densities were highly variable, but, in general, they were highest during the breed ing seasons and lowest during the winter seasons (Figure 5-14). In conclusion, densities of red-winged blackbirds by study area can be used to relate densities post-lake enhancement. Seas on is the only variable which can be used to generally predict densities. I predict that the densities of red-winged blackbirds will be reduced drastically post-lake enhancement. The littoral zone, without emergent vegetation for nesting and foraging, will onl y be inhabitable by few individuals.

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135 Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 03 Winter 0203 0 1000 2000 3000 4000 5000 6000 7000 Season of SampleDensity Estimates (# birds/ 256 ha) Study Area 1 Study Area 2 Study Area 3 Figure 5-14. Estimated density of red-wi nged blackbirds by study area. Error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter, are es timated independent of year and are the pooled estimated density derived from effort weighted year estimates Densities were estimated as number of birds per 256 hectares the total area of the study areas. Snowy Egret The snowy egret is a year round resident which does not breed on Lake Toho. The densities were highest at study areas one and two with study area three having few observations. The decreased observations with in Study area three cannot be adequately explained. An observer may have been too far away from the snowy egret to confidently determine if it was a snowy egret or if it was a juvenile little blue heron (white morph), due to the expansive shallow habitat and pa stureland adjacent to Study area three. At increasing distances it is hard er to distinguish these two sp ecies. Species recorded as unknown wading bird may have included many snowy egrets. The variable season best

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136 explained densities for both the study area a nd whole lake sampling as densities decrease during breeding season. Densities of snowy egrets, despite their absence within study area three, were greater using point transect sampling than on line transect sampling (Figure 5-15). Greatest densities of foraging snowy egrets are in the shallow to medi um water depths of the littoral zone. The species will forage in deeper water habitats on floating vegetation, but in general use the shallo w littoral habitats to forage for fish (Gawlik 2002). The winter 2003 drawdown had no e ffect on the densities. In conclusion, snowy egrets are best samp led using point transect sampling due to the spatial location that they forage within th e littoral zone. More investigation needs to be conducted to determine the reason why fe wer birds were observed within Study area three. If no conclusion can be reached th en post-lake enhancement comparisons must exclude this area. I predict that the sn owy egret densities wi ll decrease post-lake enhancement. Without vegetation to forage on the snowy egret will be limited by the maximum water depth which it can effectively forage (19 cm). (Powell 1987). This will drastically reduce the area within the littoral zone available for the bird to forage postlake enhancement.

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137 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 50 100 150 200 250 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-15. Estimated density for study ar ea and whole lake sampling for the snowy egret. Error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter, are estimated independent of year and are the pooled estimated density derived from effort weighted year estimates Densities we re estimated as number of birds per 500 hectares. Snail Kite The snail kite is an endangered raptor whic h nests within the littoral habitat of Lake Toho and is a year round reside nt. The densities of the sna il kite are highest in Study area one and were evenly distributed across line transect types. Spatially, the species was not evenly distributed throughout the littoral zone of the la ke. High densities of snail kites are clustered around a few historical snail kite nesting locations within the littoral habitat. Season was the best predictor variable for density within the study areas. The

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138 interaction effect of lake st age and season determined the densities on the line transect samples. The snail kite was usually obser ved while it was foraging, while in flight. Unfortunately, using distance sampling to estima te densities of flying birds is extremely difficult and not recommended. Fo rtunately, the snail kite will usually forage in the same area for a long length of time, allowing observers to measure distance to the center of the foraging area. Line transect sampling indica tes that the snail k ite will use the whole extent of the littoral zone. Densities were higher in th e study areas because each study area was located near favorable snail kite nest ing habitat (Figure 5-16) The line transect samples indicated that at higher lake stages the snail kite will forage closer to the inside littoral zone (Figure 5-17). In conclusion, the snail kite is distri buted unevenly throughout the lake littoral zone. Results obtained within the study areas may only apply to the scale of the study area since snail kites on the lake are concentrat ed there. The densities of snail kites per hectare obtained from the line transect sampli ng is a better whole lake representation of the number of snail kites within the littora l zone. Densities are higher during breeding season. They nest in the tall emergent vege tation within the littor al zone. Lake stage level influences where the snail kite will fora ge spatially within the littoral zone. The drawdown during the winter 2003 had a negative correlation with snai l kite densities. The most commonly suggested reasons that sn ail kites move are water levels and food (Beissinger 1998, Bennetts et al. 1994, Sykes et al. 1995). Low water levels are generally thought to impair food availability (Bennetts and Kitchens 1997). I predict that the densities of snail kites in the littoral zone of Lake T oho will decrease post enhancement

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139 due to the decrease in substrate required for th e recruitment of the aquatic apple snail, the main prey item of the snail kite. Sesaon of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 20 40 60 80 100 120 140 Study Area Sampling Lake WIde Sampling Estimated Density (# birds/ 500 ha) Figure 5-16. Estimated density of snail ki tes for study area and whole lake sampling. Error bars correspond to 95% confidence intervals. The estimated densities associated with breeding, summer and winter, are estimated independent of year and are the pooled estimated density derived from effort weighted year estimates Densities were estimated as number of birds per 500 hectares.

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140 Lake Stage (ft NGVD) 54.5 55.0 54.0 54.5 53.5 54.0 53.0 53.5 52.5 53.0 52.0 52.5 Mean 0 5 10 15 20 25 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-17. Estimated density by stage for the snail kite within th e study areas and along line transects during the pre-enhancem ent study. Error bars correspond to 95% confidence intervals. The mean value is the pooled estimated density derived from effort weighted stage es timates. Densities were estimated as number of birds per 500 hectares. Tricolored Heron The tricolored heron is a year round resi dent which does not nest on Lake Toho. The tricolored heron densities were highe st at Study area one and on inside and previously scraped line transect types. Th e temporal predictor, season, explained the densities of the tricolored he ron for both types of sampling. The tricolored heron densities by season were higher for the study area sampling than for the whole lake sampling (Figure 518). As with other medium sized wading birds, they prefer the shallow water dept hs and vegetation communities for foraging.

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141 Densities only sligh tly increased in res ponse to the drawdown dur ing the winter 2003. There were no environmental variables which explained the increase in densities during the summer of 2002. A previous study by Stro ng et al. 1997 discovered that tricolored herons were less sensitive to water level fluctuation in inland marsh and slough habitats than snowy egrets. Over short temporal scal es, tricolored herons may be better able to forage successfully at decreased prey densitie s and thus may not be as closely tied to changes in water levels (Strong et al. 1997). In conclusion, densities of the tricolored heron are better sampled within the study areas or only on inside and previously scrape d line transects. Dens ities during breeding season are low, but fluctuate the rest of the year, being highest duri ng the summer. Other environmental predictors do not describe the densities of tr icolored herons within the littoral zone. I predict that the tricolored heron densities will decrease post-lake enhancement. With the lack of vegetati on, the tricolored heron will be limited by the maximum water depth in which it can effectively forage (19 cm). (Powell 1987). This will drastically reduce the area within the litto ral zone available for the bird to forage post-lake enhancement. Lake stage and water fl uctuation do not affect this bird in inside littoral habitats, but in the absence of ve getation lake stage an d corresponding wind and wave action may negatively affect the densities of the tricolored heron.

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142 Season of Sample Breeding Breeding 02 Breeding 03 Summer Summer 02 Summer 03 Winter Winter 0203 Winter 03 0 50 100 150 200 250 300 350 Study Area Sampling Lake Wide Sampling Estimated Density (# birds/ 500 ha) Figure 5-18. Estimated density for the tricolored heron fo r study area and whole lake sampling. Error bars correspond to 95% c onfidence intervals. The estimated densities associated with breeding, summer and winter, are estimated independent of year and is the pooled estimated density derived from effort weighted year estimates Densities we re estimated as number of birds per 500 hectares. Summary and Future Analyses The avian sampling conducted from March 2002 through December 2003 provided detailed information about individual focal species distribution, use, and abundance within the littoral habitats on Lake Toho. Ta king into account dete ctability of the bird species as well as scale, we were able to ge nerate estimated. Usi ng two types of distance sampling which effectively covered the extent of the littoral zone on the lake enabled us to determine movement of species within th e littoral zone in response to environmental

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143 variables. The results obtained for the focal species will be directly comparable to results post-lake enhancement. Future Analyses There are many variables other than those examined in the focal species analysis which influence densities of birds in ma rsh habitats. The Lake Toho project was composed of three distinct parts, vegeta tion (Welch 2004), aquatic vertebrae (Muench 2004), and avian communities. The three studie s were concurrently conducted prior to the lake enhancement using the same scales of resolution as the avian project. In future analyses the three pre-lake enhancement proj ects will be integrated and new analyses will be generated to determine the complete picture of how the vegetation communities, aquatic vertebrae, and avian sp ecies are connected in the litto ral zone. The availability and density of prey items with in the littoral zone may have been influencing the densities of the focal species, posing an important questi on to address in future analyses, given the habitat has changed but the water will stay the same. A commonly cited reason for species to move within an environment is the availability of prey (Pyke 1984). A bird will leave a patch when the foraging costs equals the gain (Kohlmann and Risenhoover 1996). Prey availability and density are different things. Prey availability is a composite variable consisting of prey density and the vulnerability of a prey item to capture (Gawlik 2002). Th ese variables are partially dependent on the habitat. One study found that the vulnerability of fish to capture was negatively related to water depth, and the bird species did incur a foraging cost with increasing water depths (Gawlik 2002). The de nsities of avian speci es post enhancement may be indicative of changes in either the av ailability of prey ite ms or possibility the density of prey items within the littoral zone habitat.

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144 This concludes the analyses of the i ndividual focal species within the avian community on Lake Toho. The remainder of this document will discuss species richness within the littoral zone of the lake.

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145 CHAPTER 6 AVIAN SPECIES RICHNESS WITH IN THE LITTORAL ZONE Wetland systems are important from a cons ervation perspective. They not only provide diverse and dynamic habitats for multi-species which are influenced by the different patterns of water and vegetation regimes, attrac ting some group of species at any time (Weller 1999). These systems al so provide for a heterogeneous shore influencing lake wide biostability (Pieczyns ka and Zalewski 1997). Most bird species exhibit high adaptive ability in relation to breeding and feeding and because of this ecological plasticity, bird communities overlap in highly diverse areas such as littoral zones (Dobrowlski 1997). From the perspec tive of this study this system vegetation heterogeneity serves to increase bird sp ecies richness (Weller and Spatcher 1965). Expressing a measure of diversity has prove d to be a difficult challenge; however diversity measures have possibly been the most commonly used approach in ecological studies. It assumes that the relationship between diversity and disturba nces can be seen as a decrease in diversity as stress increases (M arques et al. 2005). The specific objectives of this chapter are 1) to determine species ric hness of avifauna within the littoral habitat for the study area and lake wide sampling 2) to determine which environmental and temporal variables are affecting species richness. Analysis Methods Information obtained from the study area and lake wide sampling was used to determine species richness on the lake. Species richness was estimated weekly for study area sampling and monthly for lake wide samp ling. For this analysis, the first winter

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146 2002 season (excluded from focal species analyses) will be included. The data obtained from the study area and lake wide sampling was presence-absence data. The winter 2002 data was excluded from earlier analyses due to the learning curve for distance sampling methods during the first season of sampling. The program SPECRICH2 was used with presence-absence data to estimate richness (Hines et al. 1999). The program uses a closed capture-recapture analysis: a model with heterogeneous capture probabilities. The program allows one to estimate the total number of species from species presence-absence data on multiple sample sites or occasions using model M(h) taken from the pr ogram CAPTURE (Hines et al 1999). This model M(h) allows each species to have a di fferent detection probability (the probability of detecting at least one indi vidual of the species in this case). The output includes an estimate for specie richness N(1), its corres ponding standard error SE N(1), and goodness of fit. Assumptions of this method are 1) clos ed population for species 2) independence of captures 3) capture probabi lities of individual species stay constant during sampling (Burnham and Overton 1979). This model is robust to deviations from these assumptions. To test any hypotheses about ch anges in species ric hness using data from counts of species, it must be assumed either that all species are detected (which is not true in most biological situations) or that detectability of the different species is the same or at least does not differ among groups (Boulinie r et al. 1998). For this study these assumptions were met. Temporal and Environmental Variations: Both temporal and environmental factors and their effect on sp ecies richness of the avian co mmunity were examined using

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147 the generalized linear mode l function in the program R (R 2004). A Gaussian distribution was assumed and avian season was introduced into the model as a categorical variable, hence creating an ANCOVA analysis. The linear predictors for the species ri chness estimates within the study areas included, lake stage, water fl uctuation, rate of water fluc tuation, vegetation structure, average air temperature, and the categorical variable water movement. These were the same linear predictors described in Chapter 3 that were used to predict density. The linear predictors of species richness on the lake wide sampling included lake stage, air temperature, water fluctuation, rate of water level fluctuation, and th e categorical variable water movement (described in Chapter 3). The scale was month of sample rather than week of sample as in the study area analyses. The linear predictors for species richne ss were introduced one by one into the model. Once the full model of all the possibl e predictors was tested, the model was then reduced using AIC (as well as looking at the predictors within each model and their significance) within the model to choose the mo st parsimonious model, if one existed. Akaike’s information criterion (AIC), which is the fit of the model plus two times the number of parameters used in the model, was used to determine the most parsimonious model. The predictor with the lowest AIC value and >2 away from the next closest predictor was chosen. Results Study Area Sampling There were 98 avian species observed duri ng the two years of sampling within the study areas (Table A-1, Appendix A). The esti mated values for species richness within the study areas ranged from 22 – 43 (Table F-1, Appendix F).

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148 The results of the generaliz ed linear model analyses for the study areas can be found in Table E-3, Appendix E The indi cator variable aver age air temperature explained the variation seen in the estimates of species rich ness within the study areas. There is a negative correlation between aver age air temperature and species richness (Figure 6-1). The outliers in the regressi on plot correspond to the lake drawdown of 2003. Although lake stage was not an indicato r variable for species richness, it is influencing richness during this short period of time. The gr aph of lake stage indicates that after the initial start of the drawdown, lake levels came back up for a brief period of time. It was during this period of increasing lake stage following a decline of almost two feet within a month that the speci es richness increased (Figure 6-2). Average Air Temperature 1012141618202224262830 Species Richness Estimate 20 25 30 35 40 45 50 Figure 6-1. Scatter plot of average air temperature vs. species richness estimate within the study areas. The straight regressi on line indicates a negative relationship between average air temperature and sp ecies richness in the study areas.

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149 Week of Sample 32343638404244 Estimate of Species Richness 0 10 20 30 40 50 60 Lake Stage (ft NGVD) 52.0 52.5 53.0 53.5 54.0 54.5 55.0 55.5 Summer Sample 03 Winter Sample 03 Lake Stage Figure 6-2. Estimated species richness per w eek of sample (see Table A-1 for sample week dates) during the in itiation of the drawdown in the fall 2003 (summer = oranges, winter = blue). The values fo r lake stage are indicated on the right yaxis. Lake Wide Sampling There were 49 avian species recorded duri ng the two years of whole lake sampling (Table A-2, Appendix A). The estimated valu es for species richness on the lake wide sampling ranged from 18 – 42 (Table F-2, Appendix F). The results of the generalized linear model analyses for the lake wide sampling can be found in Table E-4, Appendix E. There we re no environmental or temporal variables which explained the species richness for the lake wide sampling. The lake wide sampling corresponding to the drawdown in the fall 2003 is seen in Figure 6-3.

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150 Figure 6-3. Estimated species richness per m onth of sample during the initiation of the drawdown in the fall 2003. The values for lake stage are indicated on the right y-axis. Discussion Wetland bird diversity and community co mposition within a landscape may be strongly influenced by the diversity of we tland species present and by the pattern of wetness and dryness at a given time (Welle r 1999). Increased sp ecies richness with wetland size has been reported for diverse wa terbirds in lakes and smaller wetlands in Italy (Celada and Boglianai 1993) and Finl and (Lampolahti and Nuotio 1993). Wetlands which are kept at their wet or dry extr emes could be drastically changed over intermediate stages (Weller 1999). Larger wetland units were most important in providing habitat for species that occur in lower densities (Weller 1999). For management purposes, it is necessary to determine the minimal and optimal size of

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151 protected or constructed ecot ones, their shape and internal structure (Pieczynska and Zalewski 1997). The species richness analyses for the study and lake wide sampling cannot be compared. Typically species richness on the line transect survey s would be higher, assuming the habitats sampled were the same. This is due to how much area is covered on a lake wide sample. However, the numbe r of species sampled during line transect samples was less than in the study areas. The line transects samples focused on species which would be more conducive to survey from a moving airboat. This excluded all passerines which were observed on the point transect surveys as well as the American coot. Although the study area species richness included passer ines, it excluded those that are considered upland (not wetland dependent). With the exception of the passerines, species which were excluded from the lake wide sampling analysis were included in the estimation of species richness. The state of Florida is unique because it has a climate and habitat which enables many avian species to remain year round. Northern migratory waterfowl (ex. ringnecked duck, blue-winged teal), raptors (ex. northern harrier, sharp-shinned hawk) and occasionally shorebird species (ex. yellowlegs spp, least sandpiper) either use the littoral zone as stopover habitat en r oute to southern destinations, or stay throughout the winter season in the shallows of Lake Toho. With the influx of these migratory species during the winter, species richness is greater duri ng this time of year. Many of the wetland dependent passerines recorded during study area samples were short distance migratory birds. Short distant migrator y birds winter in southern United States and breed in

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152 Northern United States and Canada (ex. sw amp sparrow, marsh wren). These short distance migrants sometimes remain in the area year round. There are many things that influence species richness at smaller scales within the littoral habitat. Vegetation structure and wate r features are the only practical parameters to use to describe species richness because these are the images that humans recognize (Weller 1999). Different species of birds are attracted to different habitats within the littoral zone and their flood or drying events introduces ev en more diversity of species occupying the littoral habitat. Birds that pref er the deep water habitats include American coots, diving birds, pelicans, grebes, osprey s and bald eagles. Birds associated with floating leaf aquatic vegetation swimming birds such as the common moorhen, in addition to purple gallinule and passerines. Emergent vegetation is associated with the highest species richness, presumably because of its diverse food resources and structural opportunities of cover for different species a nd different functions during individual life cycles (Weller 1999). Dense stands of monos pecific vegetation wit hout interspersion of cover-water are less attractive to most species of birds (Kaminski and Prince 1984, Weller and Fredrickson 1974). Maintenance of a balanced cove r-water (ie., “hemimarsh”) is a management target used by w ildlife management agencies (Weller 1999). Ring-necked ducks and ruddy ducks also favor the protection from waves and wind that the emergent vegetation provides. They will ne st in the emergent vegetation but feed in the dense submerged vegetation often found in open areas with in the emergent vegetation (Weller 1999). Post enhancement, sandy bottom sparsely ve getated substrate will offer habitat for white and glossy ibis, and blue and green winged teal which specialize in feeding in

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153 shallow water, usually by feel or straining rather than sight (Weller 1999). Waders will forage in the shallow waters in search of fish, amphibians, reptiles, or large invertebrates. The numbers of shorebirds (i.e. killdeer, sandp ipers) will increase as they forage on sandy substrates.

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154 CHAPTER 7 PROJECT SUMMARY Bioindicators are a useful way of assessing the health of a syst em. Population level bioindicators are of particular concern to wetland managers because they relate directly to wetland values which are important to people (Kushlan 1992). The use of wetland bird species as bioindicators of wetland change would encourage the integration of wetland monitoring into wetland dependent species monitoring programs, the primary goal of which is the conservation and management of these populations (Kushlan 1992). Monitoring wetland dependent bird resource use patterns is important when making management decisions about a system of interest and predicting the effects those management actions will have on resident and migratory species. This long term study incorporated the detectab ility of the avian species as a tool to generate estimates of density a nd species richness. Detectabil ity of the avian species at a single location will be affected in studie s which make comparisons over time, with different observers and differe nt with stages of habita t succession (Buckland 2004, Bibby and Buckland 1987). Norvell et al. (2003) repor ted that detectabilities of birds recorded at point counts (without taking in to account detectability of th e bird species) varied three to five fold. They concluded that populati on trends based on point count data were not stable and reliable inferences could not be gene rated from them. Count data is also often used in estimates of species richness; however this assumes that the detectability of the bird species is the same for each sampling oc casion and location (Boulinier et al. 1998). The assumption of equal detectability acro ss species is genera lly false and unequal

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155 species detection probabilities can invalidate the results of a study (Boulinier et al. 1998). Statistical methods derived from capture-recaptu re approaches provide useful tools which take into account heterogeneous species dete ctability when estimating species richness (Burnham and Overton 1979). Beca use this study incorporated detectability as a tool for estimating density and richness of avian species within the littoral zone, inferences can be made in future studies. Multi-scale studies of this intensity which generate reliable quantitative comparative results are rare. However, inco rporating the detectab ility of the subject species into the study design is fairly straightforward and reli able estimates of density can be obtained with only modest resources (Buc kland et al. 2001). It was reported in Rosenstock et al. (2002) that 95% of publis hed studies used methods to obtain density and abundance without taking into account dete ctability of the species. Norvell et al. (2003) predict that this number is high because of the perception that alternative methods such as distance sampling (Buckland et al 2001), and double obser ver sampling (Nichols et al. 2000) are too complicated, time c onsuming, and expensive when point count indices will suffice. Even if only the distan ce to the bird is included in the density estimate (no covariates etc.) th e estimate of density will be a better than estimates which don’t consider detectability at all (Norvell et al. 2003, Buckland et al. 2001, Rosenstock et al. 2002). The drawdown and sediment removal project was initiated in late 2003 (sampling was ceased December 2003). Lake stage r eached a target of 14.8 m (48.5 ft) NGVD and heavy equipment removed 7.3 million cubic mete rs (8 million cubic yards) of littoral habitat, covering 1,351 ha (3,339 acres) of shor eline. As stated earlier, the scraped

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156 material was deposited in twenty-nine in -lake disposal islands and at many inland locations. The study area treatment locations were scra ped according to the planned protocol. Currently each of the three study areas has two control and two treatment blocks each measuring approximately 400 m by 200 m. Th e same distance sampling protocol is being used to sample the treatment effects post enhancement. The only difference is the addition of a fourth observer in order to sample the treatment vs. control locations simultaneously within a single study area. Th ree major hurricanes swept through the lake during the 2004 hurricane season following the lake enhancement project. The control blocks of study areas one and two, which are located outside the protection of Goblet’s Cove received substantial wave action associat ed with these storms. Potential hurricane effects to these two study areas will be examined along with the treatment effects, long term. All of the randomly located whole lake sampling line transects were scraped during the lake enhancement project. The protocol for the dual observer line transect sampling has been modified post lake enhancement. Two observers are still conducting the sample, however the two observers are inde pendent observers rather than dependent observers. This approach allows for estimation of observer-specific detection probabilities (Nichols et al. 2000). One challe nge with this new pr otocol is that the observers have to identify individual species along the line transect and then determine which observer actually saw the species. Anal ysis comparing data collected prior to the lake enhancement with data collected post enhancement will be conducted in the near future. Information generated from this st udy will inform managers of the impacts of

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157 large scale lake enhancement projects on th e wetland dependent avifauna species which use these habitats.

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158 APPENDIX A SAMPLE DATES FOR THE PREENHANCEMENT BIRD STUDY Table A-1. Week number of sample and co rresponding starting sampling day. Sampling weeks were three sample days long. Weeks 1-3 were deleted from the analysis due to inexperi ence with sampling methods. Week Sample Starting Week Sample Starting 1 1/23/02 23 2/11/03 2 2/5/02 24 2/25/03 3 2/19/02 25 3/12/03 4 3/12/02 26 3/25/03 5 3/16/02 27 4/17/03 6 4/2/02 28 4/24/03 7 4/16/02 29 5/6/03 8 5/14/02 30 5/20/03 9 5/29/02 31 6/14/03 10 6/4/02 32 7/10/03 11 7/9/02 33 7/27/03 12 7/28/02 34 8/14/03 13 8/13/02 35 8/25/03 14 8/27/02 36 9/9/03 15 9/10/02 37 9/24/03 16 9/24/02 38 10/7/03 17 10/8/02 39 10/22/03 18 10/22/02 40 11/4/03 19 11/5/02 41 11/18/03 20 11/19/02 42 12/2/03 21 12/16/02 43 12/16/03 22 1/28/03

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159 Table A-2. Sample dates corresponding to whole lake surv eys during the preenhancement avian community monito ring study. Each date had a line transect survey associated with it. The first survey was erased for the analysis. Week Date W2 03/15/02 W3 04/15/02 W4 05/15/02 W5 07/17/02 W6 08/30/02 W7 09/11/02 W8 11/20/02 W9 12/15/02 W10 01/18/03 W11 02/09/03 W12 03/14/03 W13 04/17/03 W14 05/09/03 W15 06/27/03 W16 07/29/03 W17 08/25/03 W18 09/24/03 W19 10/23/03 W20 11/20/03 W21 12/16/03

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160 APPENDIX B AVIAN SPECIES LIST FROM STUDY AR EA AND WHOLE LA KE SAMPLING Table B-1. Species seen on the lake that we re Florida designated species of special concern, and federally threatened or e ndangered. Those that are focal species are indicated ( ). Florida Designated Species of Special Concern Limpkin Aramus guarauna Little Blue Heron Egretta caerulea Tricolored Heron Egretta tricolor White Ibis Eudocimus albus Snowy Egret Egretta thula Roseate Spoonbill Ajaia ajaja Federally Threatened Species Bald Eagle Haliaeetus leucocephalus Florida Sandhill Crane Grus canadensis pratensis Crested Caracara Caracara plancus Least Tern Sterna antillarum American Kestrel Falco sparverius Federally Endangered Species Snail Kite Rostrhamus socialbilis plumbeus Wood Stork Mycteria americana

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161 Table B-2. Species list from the study area point transect sampling. Common Name Scientific Name American Bittern Botaurus lentiginosus American Coot Fulica atra American Crow Corvus brachyrhynchos American Kestrel Falco sparverius American Robin Turdus migratorius American White Pelican Pelecanus erythrorhynchos Anhinga Anhinga anhinga Bald Eagle Haliaeetus leucocephalus Barn Swallow Hirundo rustica Barred Owl Strix varia Belted Kingfisher Ceryle alcyon Black Skimmer Rynchops niger Black Vulture Coragyps atratus Black-bellied Plover Pluvialis squatarola Black-bellied Whistling Duck Dendrocygna autumnalis Black-crowned Night-Heron Nycticorax nycticorax Black-necked Stilt Himantopus mexicanus Blue Jay Cyanocitta cristata Blue-gray Gnatcatcher Polioptila caerulea Blue-winged Teal Anas Discors Boat-tailed Grackle Quiscalus major Bobolink Dolichonyx oryzivorus Carolina Wren Thryothorus ludovicianus Cattle Egret Bubulcus ibis Chimney Swift Chaetura pelagica Chipping Sparrow Spizella passerina Common Grackle Quiscalus quiscula Common Moorhen Gallinula chloripus Common Snipe Gallinago gallinago Common Yellowthroat Geothlypis trichas Cooper's Hawk Accipiter cooperii Crested Caracara Caracara plancus Double-crested Cormorant Phalacrocorax auritus Downy Woodpecker Picoides pubescens Eastern Kingbird Tyrannus tyrannus Eastern Meadowlark Sturnella magna Eastern Phoebe Sayornis phoebe European Starling Sturnus vulgaris Fish Crow Corvus ossifragus

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162 Table B-2. Continued Common Name Scientific Name Forster's Tern Sterna forsteri Fulvous Whistling Duck Dendrocygna bicolor Gadwall Anas strepera Glossy Ibis Plegadis falcinellus Gray Catbird Dumetella carolinensis Great Blue Heron Ardea herodias Great Egret Ardea alba Great Horned Owl Bubo virginianus Green Heron Butorides virescens Gull spp. Larus spp. Killdeer Charadrius vociferus King Rail Rallus elegans Least Bittern Ixobrychus exilis Least Sandpiper Calidris minutilla Least Tern Sterna antillarum Lesser Scaup Aythya affinis Limpkin Aramus guarauna Little Blue Heron Egretta caerulea Loggerhead Shrike Lanius ludovicianus Mallard Duck Anas platyrhynchos Marsh Wren Cistothorus palustris Mottled Duck Anas fulvigula Mourning Dove Zenaida macroura Northern Bobwhite Colinus virginianus Northern Cardinal Cardinalis cardinalis Northern Harrier Circus cyaneus Northern Mockingbird Mimus polyglottos Northern Parula Parula americana Osprey Pandion haliaetus Palm Warbler Dendroica palmarum Pied-billed Grebe Podilymbus podiceps Pileated Woodpecker Dryocopus pileatus Pine Warbler Dendroica pinus Prothonotary Warbler Protonotaria citrea Purple Gallinule Porphyrula martinica Red-bellied Woodpecker Melanerpes carolinus Red-shouldered Hawk Buteo lineatus Red-tailed Hawk Buteo jamaicensis

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163 Table B-2. Continued Common Name Scientific Name Red-winged Blackbird Agelaius phoeniceus Ring-necked Duck Aythya collaris Roseate Spoonbill Ajaia ajaja Ruby-crowned Kinglet Regulus calendula Florida Sandhill Crane Grus canadensis pratensis Savannah Sparrow Passerculus sandwichensis Semipalmated Plover Charadrius semipalmatus Sharp-shinned Hawk Accipiter striatus Snail Kite Rostrhamus socialbilis plumbeus Snow Goose Chen caerulescens Snowy Egret Egretta thula Solitary Sandpiper Tringa solitaria Song Sparrow Melospiza melodia Sora Porzana carolina Swamp Sparrow Melospiza georgiana Tern spp. Sterna spp. Thrush Spp. Catharus spp. Tree Swallow Tachycineta bicolor Tricolored Heron Egretta tricolor Tufted Titmouse Parus bicolor Turkey Vulture Cathartes aura Waterthrush spp. Seiurus spp. White eyed Vireo Vireo griseus White Ibis Eudocimus albus White-fronted Goose Anser albifrons Wild Turkey Meleagris gallopavo Wood Duck Aix sponsa Wood Stork Mycteria americana Yellow Warbler Dendroica petechia Yellowlegs spp. Tringa spp. Yellow-rumped Warbler Dendroica coronata

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164 Table B-3. Species list from the whol e lake line transect surveys. Common Name Scientific Name American Bittern Botaurus lentiginosus American White Pelican Pelecanus erythrorhynchos Anhinga Anhinga anhinga Bald Eagle Haliaeetus leucocephalus Belted Kingfisher Ceryle alcyon Black Vulture Coragyps atratus Black-crowned Night-Heron Nycticorax nycticorax Black-necked Stilt Himantopus mexicanus Blue-winged Teal Anas Discors Cattle Egret Bubulcus ibis Common Moorhen Gallinula chloripus Common Snipe Gallinago gallinago Crested Caracara Caracara plancus Double-crested Cormorant Phalacrocorax auritus Fish Crow Corvus ossifragus Florida Sandhill Crane Grus canadensis pratensis Forster's Tern Sterna forsteri Glossy Ibis Plegadis falcinellus Great Blue Heron Ardea herodias Great Egret Ardea alba Great Horned Owl Bubo virginianus Green Heron Butorides virescens Gull spp. Larus spp. Killdeer Charadrius vociferus Least Bittern Ixobrychus exilis Least Sandpiper Calidris minutilla Least Tern Sterna antillarum Lesser Scaup Aythya affinis Limpkin Aramus guarauna Little Blue Heron Egretta caerulea Mallard Duck Anas platyrhynchos Mottled Duck Anas fulvigula Osprey Pandion haliaetus Pied-billed Grebe Podilymbus podiceps Purple Gallinule Porphyrula martinica Red-shouldered Hawk Buteo lineatus Ring-necked Duck Aythya collaris

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165 Table B-3. Continued Common Name Species Name Roseate Spoonbill Ajaia ajaja Ruddy Duck Oxyura Jamaicensis Snail Kite Rostrhamus socialbilis plumbeus Snowy Egret Egretta thula Solitary Sandpiper Tringa solitaria Tern spp. Sterna spp. Turkey Vulture Cathartes aura White Ibis Eudocimus albus Wild Turkey Meleagris gallopavo Wood Duck Aix sponsa Wood Stork Mycteria americana Yellowlegs spp. Tringa spp.

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APPENDIX C AVIAN FOCAL SPECIES ESTIMATED DENSITIES

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167 Table C-1. Estimated densities for study area (point transect) samples. Week number corresponds to week of sample (Table A-1) and focal species are indicated by species codes (Table 3-1). Upper and lower 95% confidence intervals are also listed. AMCO ANHI BEKI BTGR Week D LCL UCL D LCL UCL D LCL UCL D LCL UCL 1 21.68 7.36 63.88 0.05 0.02 0.12 0.04 0.01 0.17 2.03 1.16 3.55 2 19.87 4.70 83.94 0.01 0.00 0.10 0.08 0.03 0.27 11.14 3.74 33.23 3 17.56 3.99 77.20 0.01 0.00 0.06 0.08 0.03 0.20 2.94 1.28 6.75 4 25.73 8.14 81.34 0.01 0.00 0.05 0.08 0.02 0.24 7.70 3.92 15.13 5 8.10 2.51 26.16 0.01 0.00 0.05 0.02 0.00 0.14 4.28 2.68 6.81 6 0.89 0.24 3.27 0.00 0.00 0.00 0.02 0.00 0.14 2.66 1.17 6.08 7 0.08 0.01 0.53 0.00 0.00 0.00 0.02 0.00 0.14 1.53 1.04 2.24 8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.07 2.56 6.46 9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.03 0.77 5.39 10 0.00 0.00 0.00 0.01 0.00 0.06 0.00 0.00 0.00 2.26 1.09 4.68 11 0.00 0.00 0.00 0.03 0.00 0.20 0.00 0.00 0.00 2.03 0.84 4.93 12 0.04 0.01 0.26 0.04 0.02 0.12 0.00 0.00 0.00 1.32 0.49 3.58 13 0.00 0.00 0.00 0.01 0.00 0.06 0.00 0.00 0.00 2.87 0.55 14.96 14 0.04 0.01 0.26 0.01 0.00 0.10 0.04 0.01 0.29 1.50 0.30 7.55 15 0.00 0.00 0.00 0.04 0.02 0.11 0.02 0.00 0.14 2.38 0.67 8.47 16 0.00 0.00 0.00 0.05 0.02 0.14 0.02 0.00 0.14 2.45 0.90 6.72 17 0.00 0.00 0.00 0.01 0.00 0.10 0.15 0.08 0.28 2.53 1.09 5.87 18 0.00 0.00 0.00 0.02 0.01 0.07 0.06 0.01 0.27 1.25 0.62 2.55 19 1.16 0.29 4.68 0.06 0.03 0.14 0.11 0.05 0.22 3.15 0.77 12.95 20 0.66 0.10 4.48 0.01 0.00 0.06 0.06 0.02 0.19 0.65 0.23 1.79 21 2.78 1.04 7.41 0.02 0.01 0.06 0.13 0.06 0.26 5.36 2.36 12.16 22 5.64 1.62 19.69 0.06 0.02 0.15 0.03 0.01 0.12 1.16 0.57 2.34 23 4.21 1.33 13.27 0.07 0.03 0.21 0.11 0.04 0.28 0.70 0.33 1.47 24 9.33 1.69 51.57 0.02 0.00 0.08 0.14 0.07 0.25 1.35 0.42 4.33 25 10.81 2.12 55.02 0.00 0.00 0.00 0.19 0.12 0.30 4.89 3.13 7.64 26 3.48 0.92 13.10 0.00 0.00 0.00 0.04 0.01 0.17 3.06 1.91 4.92 27 0.27 0.07 1.10 0.00 0.00 0.00 0.00 0.00 0.00 2.72 1.79 4.13 28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.70 0.79 9.24 29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.31 2.58 15.45 30 0.08 0.01 0.53 0.00 0.00 0.00 0.00 0.00 0.00 6.66 2.80 15.82 31 0.12 0.02 0.86 0.01 0.00 0.03 0.00 0.00 0.00 4.57 2.29 9.13 32 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00 1.18 0.52 2.70 33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.50 0.12 2.02 34 0.12 0.02 0.79 0.00 0.00 0.00 0.00 0.00 0.00 0.98 0.44 2.19 35 0.12 0.02 0.79 0.01 0.00 0.05 0.02 0.00 0.14 2.33 0.79 6.92 36 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.01 0.29 1.54 0.49 4.84 37 0.00 0.00 0.00 0.01 0.00 0.05 0.06 0.01 0.27 2.45 0.89 6.74 38 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.03 0.20 8.90 3.20 24.79 39 1.12 0.25 5.10 0.00 0.00 0.00 0.17 0.09 0.32 1.61 0.98 2.65 40 5.90 1.46 23.93 0.01 0.00 0.09 0.06 0.01 0.28 2.10 0.72 6.14 41 0.16 0.02 1.01 0.02 0.01 0.08 0.05 0.02 0.15 2.98 1.19 7.46 42 2.89 0.51 16.35 0.00 0.00 0.00 0.06 0.02 0.19 1.47 0.47 4.63 43 6.32 1.22 32.61 0.06 0.02 0.19 0.09 0.03 0.28 1.24 0.27 5.74

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168 Table C-1. Continued. CAEG COMO GBHE GLIB Week D LCL UCL D LCL UCL D LCL UCL D LCL UCL 1 0.08 0.01 0.54 0.63 0.18 2.28 0.07 0.03 0.18 0.07 0.01 0.51 2 0.01 0.00 0.05 0.83 0.35 1.95 0.10 0.05 0.19 0.43 0.07 2.47 3 0.00 0.00 0.00 1.03 0.22 4.75 0.05 0.02 0.09 0.11 0.01 1.08 4 0.00 0.00 0.00 1.26 0.30 5.32 0.07 0.03 0.19 0.23 0.06 0.85 5 0.00 0.00 0.00 1.09 0.33 3.62 0.04 0.01 0.12 0.03 0.00 6.98 6 0.00 0.00 0.00 1.72 0.67 4.37 0.03 0.09 0.08 0.00 0.00 0.00 7 0.22 0.03 1.48 1.33 0.34 5.16 0.02 0.00 0.07 0.02 0.00 0.13 8 0.00 0.00 0.00 30.11 3.72 243.890.05 0.01 0.18 0.00 0.00 0.00 9 0.01 0.00 0.05 4.21 1.56 11.38 0.04 0.01 0.12 0.00 0.00 0.00 10 0.00 0.00 0.00 0.47 0.06 3.55 0.03 0.01 0.08 0.00 0.00 0.00 11 0.05 0.00 0.67 0.59 0.15 2.25 0.07 0.03 0.15 0.02 0.00 0.13 12 0.02 0.00 0.11 0.68 0.22 2.10 0.07 0.04 0.15 0.00 0.00 0.00 13 0.01 0.00 0.05 0.76 0.14 4.06 0.08 0.04 0.19 0.09 0.01 0.82 14 0.27 0.05 1.38 0.90 0.20 4.05 0.07 0.03 0.21 0.04 0.01 0.25 15 0.14 0.01 1.42 0.07 0.00 1.11 0.03 0.01 0.12 0.20 0.04 1.05 16 0.09 0.02 0.38 2.07 0.72 5.92 0.01 0.00 0.06 0.37 0.06 2.46 17 0.01 0.00 0.05 1.38 0.37 5.20 0.06 0.02 0.19 0.02 0.00 0.13 18 0.21 0.04 1.04 0.41 0.08 2.20 0.02 0.00 0.05 0.41 0.01 0.22 19 0.03 0.00 1.00 1.33 0.56 3.14 0.02 0.00 0.07 0.74 0.09 5.87 20 0.00 0.00 0.00 1.53 0.46 5.02 0.02 0.00 0.07 0.00 0.00 0.00 21 0.06 0.01 0.25 0.86 0.22 3.41 0.09 0.03 0.32 0.03 0.00 0.17 22 0.02 0.01 0.05 0.60 0.15 2.33 0.03 0.01 0.09 0.04 0.01 0.12 23 0.04 0.00 0.34 2.65 0.99 7.11 0.04 0.01 0.18 0.04 0.01 0.25 24 0.02 0.00 0.08 2.05 0.65 6.42 0.06 0.02 0.15 0.41 0.06 2.82 25 0.05 0.02 0.13 1.58 0.48 5.15 0.05 0.03 0.10 0.06 0.01 0.37 26 0.03 0.00 0.21 2.16 0.97 4.80 0.05 0.02 0.12 0.00 0.00 0.00 27 0.00 0.00 0.00 0.72 0.22 2.35 0.05 0.02 0.09 0.00 0.00 0.00 28 0.00 0.00 0.00 1.36 0.37 5.06 0.00 0.00 0.00 0.00 0.00 0.00 29 0.07 0.01 0.48 2.81 0.63 12.45 0.01 0.00 0.06 0.00 0.00 0.00 30 0.00 0.00 0.00 0.86 0.24 3.05 0.01 0.00 0.06 0.00 0.00 0.00 31 0.04 0.01 0.28 4.51 2.16 9.41 0.00 0.00 0.00 0.00 0.00 0.00 32 0.17 0.05 0.59 1.16 0.48 2.77 0.02 0.01 0.04 0.00 0.00 0.00 33 0.33 0.09 1.18 2.34 0.39 14.03 0.10 0.03 0.36 0.57 0.06 5.57 34 0.05 0.01 0.19 1.86 0.44 7.81 0.02 0.00 0.07 0.00 0.00 0.00 35 0.09 0.02 0.31 3.42 1.39 8.43 0.04 0.02 0.09 0.04 0.01 0.25 36 0.00 0.00 0.00 0.09 0.01 1.59 0.03 0.01 0.08 0.04 0.01 0.25 37 0.00 0.00 0.00 1.68 0.58 4.83 0.01 0.00 0.06 0.00 0.00 0.00 38 0.00 0.00 0.00 7.71 2.60 22.91 0.05 0.01 0.15 0.05 0.01 0.21 39 0.02 0.00 0.16 2.64 0.67 10.38 0.06 0.03 0.12 0.04 0.01 0.15 40 0.02 0.00 0.20 1.66 0.49 5.66 0.07 0.02 0.23 0.17 0.03 0.96 41 0.35 0.13 0.95 0.12 0.02 0.98 0.05 0.02 0.12 0.32 0.10 1.00 42 0.37 0.13 1.09 1.07 0.22 5.12 0.04 0.02 0.09 0.00 0.00 0.00 43 0.14 0.02 1.18 1.31 0.30 5.81 0.06 0.01 0.25 0.14 0.02 1.18

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169 Table C-1. Continued GREG GRHE LBHE LEBI Week D LCL UCL D LCL UCL D LCL UCL D LCL UCL 1 0.26 0.05 1.27 0.00 0.00 0.000.12 0.04 0.30 0.00 0.00 0.00 2 0.19 0.07 0.50 0.00 0.00 0.000.08 0.02 0.25 0.00 0.00 0.00 3 0.24 0.08 0.69 0.00 0.00 0.000.13 0.06 0.31 0.00 0.00 0.00 4 0.17 0.03 0.95 0.00 0.00 0.000.28 0.09 0.83 0.00 0.00 0.00 5 0.05 0.01 0.28 0.00 0.00 0.000.08 0.02 0.25 0.00 0.00 0.00 6 0.04 0.01 0.14 0.00 0.00 0.000.00 0.00 0.00 0.00 0.00 0.00 7 0.00 0.00 0.00 0.00 0.00 0.000.00 0.00 0.00 0.00 0.00 0.00 8 0.15 0.05 0.44 0.00 0.00 0.000.05 0.02 0.15 0.19 0.03 1.32 9 0.09 0.02 0.36 0.00 0.00 0.000.06 0.01 0.25 0.58 0.19 1.78 10 0.11 0.04 0.29 0.00 0.00 0.000.08 0.01 0.47 0.00 0.00 0.00 11 2.52 0.19 33.65 0.00 0.00 0.000.25 0.03 2.08 0.39 0.09 1.58 12 0.14 0.04 0.53 0.05 0.01 0.320.12 0.04 0.31 0.58 0.13 2.55 13 0.42 0.19 0.90 0.05 0.01 0.320.15 0.07 0.35 0.00 0.00 0.00 14 0.34 0.16 0.75 0.00 0.00 0.001.13 0.29 4.38 0.39 0.09 1.58 15 0.35 0.15 0.85 0.00 0.00 0.000.05 0.01 0.14 0.39 0.09 1.58 16 0.59 0.01 0.30 0.00 0.00 0.000.08 0.02 0.34 0.00 0.00 0.00 17 0.10 0.04 0.28 0.00 0.00 0.000.06 0.01 0.25 0.19 0.03 1.32 18 0.11 0.05 0.25 0.00 0.00 0.000.12 0.04 0.31 0.00 0.00 0.00 19 0.10 0.38 0.25 0.00 0.00 0.000.03 0.00 0.18 0.00 0.00 0.00 20 0.12 0.05 0.30 0.00 0.00 0.000.04 0.01 0.15 0.00 0.00 0.00 21 0.07 0.03 0.21 0.00 0.00 0.000.14 0.01 2.48 0.00 0.00 0.00 22 0.00 0.00 0.04 0.03 0.01 0.220.01 0.00 0.09 0.00 0.00 0.00 23 0.00 0.00 0.00 0.02 0.34 0.160.07 0.02 0.21 0.00 0.00 0.00 24 0.10 0.01 0.90 0.03 0.00 0.230.17 0.06 0.49 0.00 0.00 0.00 25 0.05 0.01 0.33 0.05 0.01 0.370.13 0.03 0.58 0.00 0.00 0.00 26 0.09 0.02 0.37 0.02 0.00 0.160.12 0.03 0.46 0.00 0.00 0.00 27 0.00 0.00 0.00 0.09 0.03 0.300.00 0.00 0.00 0.19 0.03 1.32 28 0.00 0.00 0.00 0.17 0.03 0.860.00 0.00 0.00 0.35 0.04 3.35 29 0.00 0.00 0.00 0.14 0.05 0.370.02 0.00 0.13 0.00 0.00 0.00 30 0.02 0.00 0.15 0.14 0.03 0.700.00 0.00 0.00 0.58 0.13 2.55 31 0.02 0.00 0.15 0.09 0.03 0.230.00 0.00 0.00 0.43 0.14 1.34 32 0.03 0.01 0.09 0.00 0.00 0.000.08 0.03 0.24 0.05 0.01 0.29 33 0.03 0.01 0.10 0.08 0.01 0.830.21 0.07 0.66 0.00 0.00 0.00 34 0.08 0.03 0.24 0.07 0.02 0.320.02 0.00 0.13 0.39 0.09 1.58 35 0.09 0.03 0.27 0.12 0.04 0.310.08 0.02 0.34 0.39 0.09 1.58 36 0.22 0.04 1.25 0.00 0.00 0.000.10 0.04 0.25 0.00 0.00 0.00 37 0.05 0.01 0.29 0.07 0.02 0.300.00 0.00 0.00 0.00 0.00 0.00 38 0.12 0.04 0.36 0.02 0.00 0.160.12 0.02 0.63 0.19 0.06 0.64 39 0.08 0.02 0.31 0.02 0.00 0.160.12 0.06 0.23 0.00 0.00 0.00 40 0.14 0.03 0.78 0.03 0.00 0.290.09 0.01 0.73 0.00 0.00 0.00 41 0.12 0.05 0.31 0.00 0.00 0.000.06 0.02 0.20 0.00 0.00 0.00 42 0.07 0.01 0.46 0.00 0.00 0.000.21 0.08 0.59 0.00 0.00 0.00 43 0.03 0.00 0.59 0.00 0.00 0.000.06 0.01 0.26 0.00 0.00 0.00

PAGE 187

170 Table C-1. Continued LIMP PUGA RNDU RWBL Week D LCL UCL D LCL UCL D LCL UCL D LCL UCL 1 0.01 0.00 0.09 0.48 0.07 3.362.66 0.78 9.07 17.19 6.65 44.47 2 0.01 0.00 0.09 0.00 0.00 0.001.56 0.54 4.50 3.04 0.89 10.40 3 0.00 0.00 0.00 0.00 0.00 0.0010.18 1.27 81.80 4.87 0.84 28.08 4 0.05 0.02 0.16 0.00 0.00 0.000.21 0.05 0.85 3.28 1.28 8.40 5 0.03 0.00 0.19 0.73 0.16 3.360.00 0.00 0.00 7.66 3.31 17.71 6 0.04 0.01 0.19 0.73 0.16 3.360.00 0.00 0.00 4.80 2.46 9.40 7 0.05 0.02 0.18 0.24 0.03 1.680.00 0.00 0.00 2.72 1.25 5.91 8 0.01 0.00 0.09 0.48 0.11 2.090.00 0.00 0.00 6.21 3.98 9.68 9 0.03 0.01 0.11 1.69 0.46 6.270.00 0.00 0.00 7.42 5.35 10.31 10 0.00 0.00 0.00 0.97 0.20 4.650.00 0.00 0.00 7.17 3.43 14.99 11 0.03 0.00 0.19 0.48 0.07 3.360.00 0.00 0.00 8.10 4.34 15.13 12 0.01 0.00 0.09 0.24 0.03 1.680.00 0.00 0.00 11.11 4.34 28.40 13 0.04 0.01 0.18 0.00 0.00 0.000.00 0.00 0.00 23.13 9.17 58.34 14 0.00 0.00 0.00 0.48 0.07 3.360.00 0.00 0.00 18.10 6.97 46.98 15 0.00 0.00 0.00 0.48 0.11 2.090.03 0.00 0.20 21.03 5.33 82.96 16 0.01 0.00 0.09 0.48 0.11 2.090.00 0.00 0.00 25.66 7.40 88.95 17 0.03 0.00 0.19 0.48 0.11 2.090.00 0.00 0.00 20.59 7.50 56.55 18 0.05 0.01 0.26 1.93 0.36 10.510.00 0.00 0.00 8.86 2.56 30.74 19 0.01 0.00 0.09 0.00 0.00 0.000.00 0.00 0.00 99.45 25.67 385.23 20 0.01 0.00 0.09 0.97 0.20 4.650.35 0.05 2.46 6.61 1.73 25.25 21 0.00 0.00 0.00 0.18 0.03 1.180.11 0.03 0.44 1.59 0.25 9.93 22 0.02 0.00 0.13 0.18 0.03 1.180.74 0.15 3.53 17.26 7.20 41.39 23 0.03 0.00 0.13 2.18 0.54 8.690.42 0.11 1.53 7.12 1.95 26.03 24 0.02 0.00 0.13 0.62 0.14 2.740.30 0.06 1.57 10.35 3.72 28.79 25 0.03 0.01 0.13 1.09 0.30 3.950.16 0.02 1.16 18.58 9.42 36.62 26 0.03 0.00 0.19 1.69 0.53 5.370.00 0.00 0.00 7.99 3.99 15.98 27 0.01 0.00 0.09 0.24 0.03 1.680.00 0.00 0.00 6.90 3.54 13.47 28 0.02 0.00 0.25 1.31 0.26 6.530.00 0.00 0.00 8.87 3.66 21.50 29 0.00 0.00 0.00 0.97 0.19 4.840.00 0.00 0.00 6.70 3.75 11.97 30 0.01 0.00 0.09 0.48 0.11 2.090.00 0.00 0.00 12.49 6.21 25.11 31 0.02 0.01 0.08 2.72 0.71 10.480.00 0.00 0.00 7.13 4.49 11.32 32 0.01 0.00 0.06 0.35 0.04 3.110.00 0.00 0.00 7.25 3.91 13.42 33 0.07 0.01 0.74 0.00 0.00 0.000.00 0.00 0.00 5.79 1.31 25.49 34 0.16 0.03 0.74 0.97 0.14 6.820.00 0.00 0.00 20.73 12.71 33.80 35 0.07 0.02 0.23 4.11 1.30 12.950.00 0.00 0.00 15.35 8.59 27.45 36 0.03 0.01 0.11 0.80 0.10 6.240.00 0.00 0.00 20.10 9.25 43.68 37 0.03 0.01 0.23 0.24 0.03 1.680.00 0.00 0.00 19.97 6.49 61.43 38 0.03 0.00 0.19 3.23 0.83 12.550.00 0.00 0.00 41.53 19.20 89.79 39 0.00 0.00 0.00 0.24 0.03 1.680.35 0.03 3.50 11.11 2.96 41.63 40 0.06 0.01 0.52 1.81 0.34 9.730.04 0.01 0.37 37.13 13.81 99.83 41 0.04 0.01 0.14 0.59 0.09 4.130.54 0.08 3.87 21.09 6.62 67.18 42 0.00 0.00 0.00 0.00 0.00 0.000.00 0.00 0.00 67.45 24.77 183.66 43 0.00 0.00 0.00 0.73 0.09 5.870.04 0.01 0.37 0.47 0.14 1.65

PAGE 188

171 Table C-1. Continued. SACR SNEG SNKI TRHE Week D LCL UCL D LCL UCL D LCL UCL D LCL UCL 1 0.02 0.00 0.11 0.00 0.00 0.000.05 0.01 0.240.15 0.06 0.39 2 0.39 0.14 1.07 0.03 0.00 0.220.18 0.08 0.410.12 0.04 0.41 3 0.10 0.04 0.21 0.06 0.01 0.300.10 0.04 0.270.05 0.01 0.34 4 0.04 0.01 0.14 0.00 0.00 0.000.14 0.06 0.320.11 0.03 0.43 5 0.04 0.01 0.14 0.11 0.02 0.750.09 0.03 0.230.07 0.01 0.51 6 0.07 0.03 0.18 0.00 0.00 0.000.27 0.11 0.690.02 0.00 0.17 7 0.08 0.03 0.21 0.04 0.01 0.280.21 0.08 0.570.00 0.00 0.00 8 0.08 0.03 0.25 0.06 0.01 0.430.16 0.07 0.370.02 0.00 0.17 9 0.54 0.13 2.25 0.00 0.00 0.000.12 0.05 0.310.07 0.02 0.34 10 0.10 0.03 0.31 0.02 0.00 0.110.16 0.07 0.350.02 0.00 0.17 11 0.22 0.06 0.81 0.11 0.02 0.750.07 0.02 0.230.14 0.02 0.91 12 0.11 0.03 0.45 0.02 0.00 0.110.03 0.01 0.140.52 0.15 1.83 13 0.06 0.02 0.22 0.51 0.18 1.440.02 0.00 0.120.42 0.15 1.15 14 0.10 0.03 0.32 1.14 0.33 3.850.03 0.01 0.142.40 0.73 7.96 15 0.11 0.03 0.46 0.11 0.02 0.550.02 0.00 0.120.25 0.08 0.76 16 0.01 0.00 0.14 0.39 0.12 1.270.02 0.00 0.120.10 0.04 0.23 17 0.10 0.03 0.35 0.06 0.01 0.280.07 0.03 0.170.22 0.08 0.65 18 0.04 0.01 0.14 0.05 0.01 0.220.03 0.01 0.140.22 0.11 0.44 19 0.03 0.01 0.12 0.00 0.00 0.000.03 0.01 0.240.20 0.08 0.49 20 0.07 0.02 0.21 0.03 0.00 0.220.00 0.00 0.000.17 0.08 0.37 21 0.03 0.01 0.14 0.13 0.04 0.450.01 0.00 0.080.11 0.06 0.21 22 0.08 0.03 0.19 0.02 0.01 0.090.04 0.01 0.120.06 0.02 0.16 23 0.07 0.02 0.23 0.05 0.02 0.140.07 0.02 0.220.02 0.00 0.17 24 0.08 0.03 0.20 0.10 0.04 0.260.24 0.08 0.730.20 0.09 0.45 25 0.02 0.00 0.11 0.04 0.00 0.250.10 0.04 0.250.06 0.01 0.23 26 0.00 0.00 0.00 0.00 0.00 0.000.14 0.06 0.340.00 0.00 0.00 27 0.08 0.03 0.22 0.00 0.00 0.000.07 0.02 0.230.00 0.00 0.00 28 0.04 0.01 0.27 0.00 0.00 0.000.09 0.02 0.500.09 0.01 0.89 29 0.13 0.05 0.29 0.00 0.00 0.000.12 0.05 0.280.00 0.00 0.00 30 0.09 0.03 0.23 0.00 0.00 0.000.10 0.05 0.230.05 0.01 0.34 31 0.03 0.01 0.12 0.00 0.00 0.000.08 0.03 0.210.06 0.01 0.23 32 0.07 0.03 0.16 0.05 0.02 0.190.02 0.01 0.060.09 0.05 0.17 33 0.07 0.01 0.35 0.57 0.15 2.170.01 0.00 0.310.44 0.13 1.49 34 0.06 0.01 0.71 0.05 0.01 0.220.07 0.02 0.220.20 0.09 0.45 35 0.03 0.01 0.17 0.13 0.03 0.470.05 0.02 0.150.14 0.05 0.38 36 0.10 0.02 0.59 0.00 0.00 0.000.02 0.00 0.120.07 0.02 0.32 37 0.06 0.01 0.22 0.00 0.00 0.000.03 0.01 0.240.05 0.01 0.20 38 1.10 0.25 4.93 0.02 0.00 0.110.10 0.02 0.450.40 0.18 0.87 39 0.30 0.05 1.72 0.02 0.00 0.110.02 0.00 0.120.20 0.07 0.53 40 0.06 0.01 0.30 0.02 0.00 0.200.00 0.00 0.000.22 0.07 0.75 41 0.07 0.03 0.16 0.06 0.02 0.210.00 0.00 0.000.18 0.09 0.38 42 0.13 0.04 0.42 0.05 0.01 0.210.00 0.00 0.000.10 0.03 0.32 43 0.03 0.01 0.22 0.21 0.03 1.790.00 0.00 0.000.19 0.08 0.43

PAGE 189

172 Table C-2. Densities estimates and the co rresponding standard e rror and variance for avian species by study area. Species ar e listed according to species code (Table 3-1). AMCO ANHI Area D SE VarianceArea D SE Variance 1 3.18 0.78290.6129 1 0.020.0053 0.0000 2 0.40 0.13590.0185 2 0.020.0045 0.0000 3 0.45 0.45670.2086 3 0.010.0034 0.0000 BEKI BTGR Area D SE VarianceArea D SE Variance 1 0.05 0.00950.0001 1 4.440.4682 0.2192 2 0.06 0.01050.0001 2 2.070.3251 0.1057 3 0.03 0.00640.0000 3 1.540.1781 0.0317 CAEG COMO Area D SE VarianceArea D SE Variance 1 0.19 0.05650.0032 1 2.980.3959 0.1567 2 0.03 0.00990.0001 2 1.410.2551 0.0651 3 0.02 0.01490.0002 3 0.350.2017 0.0407 GBHE GLIB Area D SE VarianceArea D SE Variance 1 0.04 0.00610.0000 1 0.130.0350 0.0012 2 0.07 0.00870.0001 2 0.010.0041 0.0000 3 0.03 0.00980.0001 3 0.080.0288 0.0008 GREG LBHE Area D SE VarianceArea D SE Variance 1 0.11 0.02220.0005 1 0.100.0170 0.0003 2 0.10 0.02030.0004 2 0.060.0121 0.0001 3 0.35 0.20170.0407 3 0.060.0097 0.0001 LEBI LIMP Area D SE VarianceArea D SE Variance 1 0.12 0.05660.0032 1 0.010.0041 0.0000 2 0.11 0.04490.0020 2 0.000.0014 0.0000 3 0.16 0.05770.0033 3 0.060.0122 0.0001 PUGA RNDU Area D SE VarianceArea D SE Variance 1 0.27 0.14170.0201 1 0.360.1491 0.0222 2 1.60 0.72030.5188 2 0.200.0906 0.0082 3 0.73 0.35360.1250 3 0.140.0926 0.0086 RWBL SACR Area D SE VarianceArea D SE Variance 1 27.51 5.029525.2959 1 0.070.0143 0.0002 2 7.75 1.45972.1307 2 0.040.0116 0.0001 3 23.62 3.779914.2876 3 0.200.0488 0.0024 SNEG SNKI Area D SE VarianceArea D SE Variance 1 0.17 0.05000.0025 1 0.100.0170 0.0003 2 0.08 0.02430.0006 2 0.060.0121 0.0001 3 0.02 0.00910.0001 3 0.060.0097 0.0001 TRHE Area D SE Variance 1 0.40 0.09360.0088 2 0.12 0.01890.0004 3 0.09 0.01710.0003

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173 Table C-3. Density estimates for focal species on line transect surveys. Sample date and species codes are used. Upper and lowe r 95% confidence intervals are listed. ANHI BEKI COMO GBHE Date D LCL UCL D LCL UCL D LCL UCL D LCL UCL 03/15/02 0.01 0.00 0.02 0.010.000.03 0.170.090.30 0.04 0.020.07 04/15/02 0.00 0.00 0.01 0.000.000.00 0.170.090.33 0.02 0.010.04 05/15/02 0.00 0.00 0.00 0.000.000.00 0.600.410.90 0.02 0.010.07 07/17/02 0.01 0.01 0.02 0.000.000.02 0.240.130.47 0.02 0.010.04 08/30/02 0.01 0.00 0.02 0.000.000.02 0.410.210.79 0.02 0.010.04 09/11/02 0.00 0.00 0.01 0.010.000.02 0.310.170.56 0.01 0.010.02 11/20/02 0.01 0.01 0.03 0.010.000.02 0.130.060.29 0.01 0.010.02 12/15/02 0.01 0.01 0.02 0.010.010.03 0.210.130.36 0.01 0.010.02 01/18/03 0.01 0.01 0.03 0.010.010.03 0.220.130.38 0.01 0.010.03 02/09/03 0.01 0.00 0.02 0.020.010.04 0.300.190.48 0.01 0.010.03 03/14/03 0.01 0.00 0.01 0.000.000.01 0.350.230.54 0.02 0.010.03 04/17/03 0.00 0.00 0.00 0.000.000.01 0.360.210.63 0.01 0.000.02 05/09/03 0.00 0.00 0.01 0.000.000.00 0.320.200.53 0.02 0.010.03 06/27/03 0.00 0.00 0.01 0.000.000.00 0.240.140.42 0.02 0.010.03 07/29/03 0.00 0.00 0.01 0.000.000.00 0.310.190.50 0.02 0.010.03 08/25/03 0.01 0.00 0.02 0.000.000.01 0.330.170.63 0.00 0.000.01 09/24/03 0.01 0.00 0.01 0.010.000.03 0.620.361.07 0.01 0.000.01 10/23/03 0.01 0.00 0.02 0.010.000.02 0.690.401.19 0.01 0.000.02 11/20/03 0.03 0.02 0.06 0.020.010.05 0.740.431.26 0.03 0.020.06 12/16/03 0.03 0.02 0.04 0.050.030.08 1.050.611.81 0.06 0.040.09 GLIB GREG GRHE LBHE Date D LCL UCL D LCL UCL D LCL UCL D LCL UCL 03/15/02 0.01 0.00 0.03 0.020.010.04 0.000.000.00 0.01 0.010.04 04/15/02 0.01 0.00 0.03 0.010.000.02 0.010.000.04 0.00 0.000.00 05/15/02 0.00 0.00 0.03 0.020.010.04 0.000.000.00 0.01 0.000.02 07/17/02 0.00 0.00 0.00 0.030.020.05 0.010.000.04 0.01 0.000.02 08/30/02 0.00 0.00 0.02 0.030.020.05 0.000.000.00 0.02 0.010.03 09/11/02 0.01 0.00 0.03 0.030.020.05 0.000.000.01 0.02 0.010.04 11/20/02 0.01 0.00 0.03 0.020.010.03 0.000.000.01 0.02 0.010.04 12/15/02 0.01 0.01 0.04 0.020.010.03 0.000.000.01 0.01 0.010.03 01/18/03 0.02 0.01 0.04 0.010.000.01 0.000.000.01 0.01 0.010.02 02/09/03 0.03 0.02 0.07 0.000.000.00 0.000.000.00 0.02 0.010.03 03/14/03 0.03 0.02 0.05 0.000.000.01 0.000.000.00 0.01 0.000.02 04/17/03 0.01 0.00 0.03 0.000.000.01 0.010.000.02 0.00 0.000.00 05/09/03 0.00 0.00 0.00 0.000.000.01 0.000.000.01 0.00 0.000.01 06/27/03 0.00 0.00 0.00 0.010.000.01 0.000.000.02 0.01 0.000.01 07/29/03 0.00 0.00 0.00 0.020.020.04 0.000.000.02 0.00 0.000.01 08/25/03 0.00 0.00 0.00 0.030.020.04 0.000.000.00 0.01 0.000.01 09/24/03 0.00 0.00 0.03 0.010.010.02 0.000.000.01 0.01 0.010.03 10/23/03 0.01 0.00 0.02 0.010.010.03 0.000.000.00 0.02 0.010.03 11/20/03 0.03 0.01 0.08 0.050.030.07 0.000.000.02 0.03 0.020.06 12/16/03 0.13 0.07 0.26 0.030.020.05 0.010.000.03 0.02 0.010.04

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174 Table C-3. Continued. LEBI PBGR PUGA RNDU Date D LCL UCL D LCL UCL D LCL UCL D LCL UCL 03/15/02 0.000.00 0.00 0.000.000.00 0.020.000.09 0.23 0.120.46 04/15/02 0.030.01 0.11 0.000.000.01 0.010.000.05 0.02 0.010.07 05/15/02 0.050.01 0.25 0.000.000.00 0.010.000.08 0.00 0.000.00 07/17/02 0.010.00 0.07 0.000.000.00 0.050.010.22 0.00 0.000.00 08/30/02 0.010.00 0.07 0.000.000.00 0.010.000.05 0.00 0.000.00 09/11/02 0.000.00 0.00 0.000.000.00 0.000.000.00 0.00 0.000.00 11/20/02 0.000.00 0.00 0.000.000.00 0.020.010.05 0.08 0.030.23 12/15/02 0.000.00 0.00 0.000.000.01 0.030.010.08 0.05 0.020.13 01/18/03 0.000.00 0.00 0.000.000.01 0.010.000.04 0.10 0.040.26 02/09/03 0.000.00 0.00 0.000.000.01 0.010.000.03 0.11 0.050.25 03/14/03 0.010.00 0.05 0.010.000.03 0.020.010.06 0.03 0.010.08 04/17/03 0.020.00 0.09 0.000.000.00 0.030.010.09 0.02 0.000.07 05/09/03 0.030.01 0.13 0.000.000.00 0.010.000.04 0.02 0.010.09 06/27/03 0.020.01 0.08 0.000.000.00 0.000.000.00 0.01 0.000.03 07/29/03 0.050.01 0.21 0.000.000.01 0.020.010.07 0.00 0.000.00 08/25/03 0.010.00 0.05 0.000.000.01 0.030.010.13 0.00 0.000.00 09/24/03 0.000.00 0.00 0.000.000.01 0.010.000.05 0.03 0.010.08 10/23/03 0.000.00 0.00 0.000.000.01 0.020.000.07 0.01 0.000.03 11/20/03 0.000.00 0.00 0.020.010.06 0.010.000.06 0.08 0.020.28 12/16/03 0.000.00 0.00 0.000.000.03 0.060.020.22 0.07 0.020.22 SACR SNEG SNKI TRHE Date D LCL UCL D LCL UCL D LCL UCL D LCL UCL 03/15/02 0.010.00 0.03 0.000.000.04 0.010.000.03 0.04 0.010.11 04/15/02 0.010.00 0.02 0.000.000.00 0.040.010.10 0.02 0.010.04 05/15/02 0.000.00 0.02 0.000.000.00 0.020.010.09 0.00 0.000.00 07/17/02 0.000.00 0.01 0.010.000.03 0.000.000.00 0.06 0.030.11 08/30/02 0.000.00 0.00 0.040.020.10 0.000.000.02 0.07 0.040.11 09/11/02 0.000.00 0.00 0.050.030.09 0.000.000.01 0.07 0.040.13 11/20/02 0.000.00 0.00 0.010.000.02 0.000.000.00 0.03 0.020.05 12/15/02 0.000.00 0.00 0.040.020.06 0.000.000.02 0.03 0.020.05 01/18/03 0.000.00 0.01 0.030.010.05 0.010.000.02 0.01 0.010.03 02/09/03 0.000.00 0.01 0.020.010.04 0.010.000.04 0.03 0.020.05 03/14/03 0.000.00 0.01 0.010.000.03 0.000.000.00 0.03 0.010.06 04/17/03 0.000.00 0.01 0.020.010.07 0.000.000.00 0.01 0.010.02 05/09/03 0.000.00 0.03 0.000.000.00 0.000.000.01 0.01 0.000.03 06/27/03 0.010.00 0.03 0.000.000.02 0.000.000.00 0.02 0.010.03 07/29/03 0.000.00 0.00 0.030.020.06 0.000.000.00 0.03 0.020.05 08/25/03 0.000.00 0.00 0.030.010.06 0.000.000.00 0.03 0.020.05 09/24/03 0.000.00 0.01 0.000.000.02 0.000.000.00 0.02 0.010.03 10/23/03 0.000.00 0.00 0.010.010.03 0.000.000.00 0.02 0.010.04 11/20/03 0.000.00 0.00 0.040.020.10 0.000.000.00 0.05 0.020.09 12/16/03 0.010.00 0.02 0.070.040.13 0.000.000.00 0.07 0.040.10

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175 Table C-4. Density estimates by line transect type for focal speci es. The corresponding standard error and variance associat ed with the density are listed. ANHI BEKI Type D SE VarianceType D SE Variance I 0.004 0.0010.000I 0.0050.001 0.000 O 0.014 0.0020.000O 0.0050.002 0.000 P 0.011 0.0020.000P 0.0130.002 0.000 COMO GBHE Type D SE VarianceType D SE Variance I 0.176 0.0380.001I 0.0220.003 0.000 O 0.557 0.0700.005O 0.0140.002 0.000 P 0.374 0.0480.002P 0.0160.003 0.000 GLIB GREG Type D SE VarianceType D SE Variance I 0.014 0.0040.000I 0.0230.003 0.000 O 0.007 0.0020.000O 0.0100.002 0.000 P 0.023 0.0070.000P 0.0170.002 0.000 GRHE LBHE Type D SE VarianceType D SE Variance I 0.003 0.0010.000I 0.0210.003 0.000 O 0.002 0.0010.000O 0.0030.001 0.000 P 0.004 0.0010.000P 0.0120.002 0.000 LEBI PBGR Type D SE VarianceType D SE Variance I 0.000 0.6490.421I 0.0010.000 0.000 O 0.017 0.0060.000O 0.0020.001 0.000 P 0.007 0.0040.000P 0.0040.002 0.000 PUGA RNDU Type D SE VarianceType D SE Variance I 0.012 0.0060.000I 0.0520.029 0.001 O 0.034 0.0110.000O 0.2730.089 0.008 P 0.008 0.0030.000P 0.0000.000 0.000 SACR SNEG Type D SE VarianceType D SE Variance I 0.004 0.0020.000I 0.0290.005 0.000 O 0.000 0.0000.000O 0.0120.003 0.000 P 0.003 0.0010.000P 0.0200.115 0.013 SNKI TRHE Type D SE VarianceType D SE Variance I 0.001 0.0010.000I 0.0430.006 0.000 O 0.006 0.0030.000O 0.0160.003 0.000 P 0.007 0.0030.000P 0.0330.004 0.000

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APPENDIX D DISTANCE ANALYSES MODEL PARAMETERS

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177 Table D-1. Analyses parameters for point transect distance sampling for the most parsimonious model chosen model for each focal species. The variables are explained in Chapter 2 and Chapter 3. Species Key Function Adjustment # p Truncation Left Truncation Covariates Detection Function Detection Prob GOF LBHE Halfnormal Cosine 3 200 20 ObsCode Pooled 0.46 0.236 BTGR Halfnormal Cosine 7 140 0 ObsCode Pooled 0.27 0.001 GBHE Hazardrate Cosine 4 150 50 ObsCode Pooled 0.61 0.897 TRHE Halfnormal Cosine 3 10% 0 ObsCode Pooled 0.28 0.182 GLIB Halfnormal Cosine 3 10% 20 ObsCode Pooled 0.33 0.303 AMCO Hazardrate Cosine 8 10% 24 Season Pooled 0.23 0.000 RNDU Halfnormal Cosine 3 10% 50 ObsCode Pooled 0.23 0.165 BEKI Halfnormal Cosine 3 10% 14 Site Pooled 0.42 0.612 COMO Hazardrate Cosine 8 10% 0 Season Stratified 0.19 0.115 GREG Halfnormal Cosine 3 250 50 ObsCode Stratified 0.49 0.001 GRHE Halfnormal Cosine 3 10% 0 ObsCode Pooled 0.42 0.270 LEBI Halfnormal Cosine 3 10% 0 Site Pooled 0.15 0.196 LIMP Halfnormal Cosine 3 10% 0 ObsCode Pooled 0.38 0.496 PUGA Hazardrate Cosine 2 100 0 None Pooled 0.15 0.005 RWBL Hazardrate Cosine 2 10% 0 None Pooled 0.14 0.000 SACR Hazardrate Cosine 6 10% 0 Site/ObsCode Stratified 0.45 0.001 SNEG Hazardrate Cosine 3 10% 0 ObsCode Pooled 0.25 0.378 SNKI Hazardrate Cosine 4 200 20 Site Global 0.51 0.456 AHNI Halfnormal Cosine 6 10% 0 Vegetation Pooled 0.44 0.007 CAEG Hazardrate Cosine 2 10% 0 None Pooled 0.51 0.864

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178 Table D-2. Analyses parameters for line transect distance sampling for the most parsimonious model chosen model for each focal species. The variable (T) indicates truncation (LT) is left tr uncation. Truncation distances are in meters. The value for g(0) and its asso ciated standard error (SE) is the new estimated probability of detection fo r the dual observer survey. The other variables are explained in Chapter 2 and Chapter 4. Species Key Function AdjustmentT LT Covariatesg(0) SE ANHI Hazard-rate Cosine 5% 0 None 0.8451 0.0304 BEKI Half-normal Cosi ne 1500 None 0.9000 0.0548 COMO Half-normal Cosine 5% 0 None 0.9145 0.0712 GBHE Hazard-rate Cosine 5% 10 None 0.9010 0.0312 GLIB Hazard-rate Cosine 1400 None 0.6153 0.0450 GREG Hazard-rate Cosine 5% 0 None 0.8484 0.0255 GRHE Half-normal Cosine 0 0 None 0.7273 0.1343 LBHE Hazard-rate Cosine 1750 None 0.8793 0.0257 LEBI Half-normal Cosine 50 0 Stratum 0.8667 0.0878 PBGR Half-normal Cosine 0 0 None 0.5714 0.0000 PUGA Half-normal Cosine 0 0 None 0.6383 0.0701 RNDU Half-normal Cosine 5% 0 Stratum 0.8761 0.0179 SACR Half-normal Cosine 0 0 None 1.0000 0.0000 SNEG Half-normal Cosine 5% 0 None 0.9007 0.0110 SNKI Half-normal Cosine 1500 Season 0.8499 0.0798 TRHE Hazard-rate Cosine 1210 None 0.9064 0.0223

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APPENDIX E GENERALIZED LINEAR MODELS

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180 Table E-1. Potential models for the study area analyses which explain the response variable, density as a function of the predictor variables Stage (St), Water level fluctuation (F), rate of water le vel fluctuation per day R, average air temperature (T), vegetation structure (V ), Season (Se), Year (Y), Water level (W). AMCO AIC AIC #p ANHI AIC AIC #p BEKI AIC AIC #p Se 10.30 278.07 3 St 14.22 -208.32 2 Se 6.16 -23.16 3 Se + St 0.00 267.77 4 T 9.79 -212.75 2 Se + St 6.89 -22.43 4 Se St 1.19 268.96 6 V 15.00 -207.05 2 Se St 0.00 -29.32 6 Se + T 12.10 279.87 4 Se 0.00 -222.54 3 Se + T 7.68 -21.64 4 Se T 11.59 279.36 6 Se + St 2.39 -220.15 4 Se T 11.32 -18.00 6 Se + V 12.23 280.00 4 Se St 5.77 -216.77 6 Se + V 8.03 -21.29 4 Se V 11.82 279.59 6 W 17.41 -205.13 3 Se V 12.03 -17.29 6 W 18.72 286.49 3 St W 18.37 -204.17 6 St W 14.97 -14.35 6 BTGR AIC AIC #p CAEG AIC AIC #p COMO AIC AIC #p St 3.00 197.88 3 St 5.07 -69.30 2 St 0.00 253.15 2 T 2.74 197.62 4 R 2.72 -71.65 2 R 4.31 257.46 2 Se 0.31 195.19 6 Se 3.84 -70.53 3 F 3.80 256.95 2 Se + St 0.00 194.88 2 Se + St 3.03 -71.34 4 Se 8.12 261.27 3 Se St 3.83 198.71 2 Se St 2.69 -71.68 6 W 6.21 259.36 3 W 3.54 198.73 3 Se + R 0.80 -73.57 4 St W 2.58 255.73 St W 5.37 200.56 6 Se R 0.00 -74.37 6 GBHE AIC AIC #p GLIB AIC AIC #p GREG AIC AIC #p St 0.00 -188.53 2 St 0.16 -27.43 2 St 2.26 -56.11 2 R 4.17 -184.36 2 R 5.17 -22.42 2 F 6.56 -51.81 2 F 4.75 -183.78 2 F 4.41 -23.18 2 R 5.19 -53.18 2 Se 2.63 -185.90 3 Se 0.61 -26.98 3 Se 0.00 -58.37 3 W 5.52 -183.01 3 Se + St 0.00 -27.59 4 Se + St 0.08 -58.29 4 Se St 1.48 -26.11 6 Se St 3.60 -54.77 6 W 6.21 -21.22 3 W 7.14 -51.23 3 GRHE AIC AIC #p LBHE AIC AIC #p LEBI AIC AIC #p St 34.17 -140.35 2 St 0.47 -24.17 2 St 4.55 -16.42 2 R 33.26 -141.26 2 R 1.18 -23.46 2 W 7.97 -13.00 3 V 34.26 -140.26 2 F 1.15 -23.49 2 V 6.14 -14.83 2 Se 31.57 -142.95 3 Se 0.00 -24.64 3 Se 0.00 -20.97 3 Y 5.72 -168.80 7 W 2.59 -22.05 Y + W 0.00 -174.52 8 W 26.84 -147.68 3 LIMP AIC AIC #p PUGA AIC AIC #p RNDU AIC AIC #p St 0.00 -181.53 2 St 1.82 99.63 2 Se 23.25 162.99 3 F 2.03 -179.50 2 T 0.75 98.56 2 Se + St 24.43 164.17 4 V 2.01 -179.52 2 F 0.00 97.81 2 Se St 27.21 166.95 6 Se 2.22 -179.31 3 Se 2.30 100.11 3 Se + T 24.87 164.61 4 W 2.89 -178.64 3 W 21.21 119.02 3 Se T 26.93 166.67 6 Se + V 24.74 164.48 4 Se V 27.76 167.50 6 W 28.51 168.25 3 Y 0.00 139.74 7

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181 Table E-1. Continued. RWBL AIC AIC #p SACR AIC #p SNEG AIC #p St 7.47 333.98 2 St 0.00 -94.24 2 St 5.22 -9.31 2 T 8.91 335.42 2 T 0.35 -93.89 2 F 4.58 -9.95 2 V 3.76 330.27 2 Se 0.72 -93.52 3 R 3.72 -10.81 2 Se 5.22 331.73 3 W 2.06 -92.18 3 Se 0.00 -14.53 3 W 9.28 335.79 3 W 5.67 -8.86 3 Y 0.00 326.51 7 SNKI AIC AIC #p TRHE AIC AIC #p St 19.31 -104.36 2 St 4.60 40.32 2 F 19.84 -103.83 2 F 4.98 40.70 2 V 10.90 -112.77 2 R 4.98 40.70 2 Se 6.00 -117.67 3 Se 0.00 35.72 3 Y 0.00 -123.67 7 W 6.67 42.39 3 W 21.21 -102.46 3 St W 19.41 -104.26 8

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182 Table E-2. Potential models for the whole lake analyses which explain the response variable, density as a function of the predictor variables Stage (St), Water level fluctuation (F), rate of water le vel fluctuation per day R, average air temperature (T), vegetation structure (V ), Season (Se), Year (Y), Water level (W). ANHI AIC AIC #p BEKI AIC AIC #p COMO AIC AIC #p St 13.81 -130.17 2 St 45.41 -128.03 2 St 12.42 1.09 2 T 22.74 -121.24 2 T 42.34 -131.10 2 R 12.41 1.08 2 Se 0.00 -143.98 3 W 45.72 -127.72 2 F 11.67 0.34 2 W 22.95 -121.03 2 Y 32.21 -141.23 7 W 12.75 1.42 2 Y 23.89 -167.87 7 Ss St 0.00 -173.44 6 Y 0.00 -11.33 7 Se + St 29.71 -143.73 4 Y St -4.93 -16.26 12 Y + St -5.71 -17.04 8 GBHE AIC AIC #p GLIB AIC AIC #p GREG AIC AIC #p St 34.23 -104.27 2 St 2.66 -86.55 2 St 4.94 -113.40 2 R 30.23 -108.27 2 R 2.31 -86.90 2 F 5.70 -112.64 2 F 33.84 -104.66 2 F 2.56 -86.65 2 R 5.80 -112.54 2 Se 32.12 -106.38 3 W 4.62 -84.59 2 Y 16.04 -134.38 7 Y Str -7.00 -145.50 12 Y 3.23 -92.44 7 Se 0.00 -118.34 3 Y 0.00 -138.50 7 Se 0.00 -89.21 3 Se + St 1.98 -116.36 4 Se + St 0.25 -89.46 4 GRHE AIC AIC #p LBHE AIC AIC #p LEBI AIC AIC #p St 1.02 -168.88 2 St 10.84 -131.06 2 St 2.97 -103.82 2 R 0.00 -169.90 2 R 10.62 -131.28 2 W 5.19 -101.60 2 F 2.78 -167.12 2 F 11.65 -130.25 2 Y 4.92 -101.87 7 Se 5.10 -164.80 3 Se 0.00 -141.90 3 Se 0.00 -106.79 3 Y 7.05 -162.85 7 Y -1.32 -143.22 7 PUGA AIC AIC #p RNDU AIC AIC #p SACR AIC AIC #p St 1.04 -105.85 2 St 8.97 -52.37 2 St 6.11 -178.87 2 T 0.00 -106.89 2 T 4.15 -57.19 2 T 10.05 -174.93 2 F 1.00 -105.89 2 W 8.40 -52.94 2 W 9.29 -175.69 2 Se 2.04 -104.85 3 Se 3.73 -57.61 3 Se 0.00 -184.98 3 Y 4.98 -101.91 7 Y 5.78 -55.56 7 Y 4.07 -180.91 7 Se + Str 0.00 -61.34 4 SNEG AIC AIC #p SNKI AIC AIC #p TRHE AIC AIC #p St 6.52 -95.32 2 St 18.50 -126.08 2 St 3.97 -94.15 2 F 5.77 -96.07 2 F 19.44 -125.14 2 F 4.74 -93.38 2 R 6.47 -95.37 2 Se 18.27 -126.31 3 R 4.66 -93.46 2 Y -6.48 -108.32 7 Y 0.00 -144.58 7 W 4.98 -93.14 2 Se 0.00 -101.84 3 W 18.67 -125.91 2 Se 0.00 -98.12 3 Y 20.48 -118.60 7 Se + St 1.99 -96.13 4 Se St -0.82 -98.94 6

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APPENDIX F AVIAN SPECIES RICHNESS TABLES

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184 Table F-1. Species richness within the study areas by week of sample. N(1) is the estimated species richness with it’s corresponding standard error SE, X^2, degrees of freedom and probability. Week N(1) SE N(1) X^2 df Prob 1 37 4.059 12.500 2 0.002 2 45 4.830 3.875 2 0.144 3 39 3.501 3.524 2 0.172 4 27 2.396 6.167 2 0.046 5 35 4.286 0.111 2 0.946 6 38 5.239 0.789 2 0.673 7 29 4.082 6.500 2 0.038 8 26 2.623 5.200 2 0.074 9 31 3.576 6.125 2 0.047 10 29 4.089 8.000 2 0.018 11 25 2.660 1.500 2 0.472 12 28 3.339 2.714 2 0.257 13 32 3.461 0.059 2 0.971 14 34 4.588 4.133 2 0.127 15 31 3.940 1.412 2 0.494 16 22 2.470 2.889 2 0.236 17 31 3.136 0.375 2 0.829 18 30 2.843 1.733 2 0.420 19 34 3.933 2.294 2 0.318 20 30 2.137 1.412 2 0.494 21 33 2.741 1.400 3 0.706 22 40 4.055 1.836 3 0.607 23 43 4.047 2.375 2 0.305 24 40 4.372 6.429 2 0.040 25 36 3.216 6.636 2 0.036 26 33 3.460 0.118 2 0.943 27 39 4.129 4.261 2 0.119 28 29 3.354 0.600 1 0.439 29 32 4.640 1.186 2 0.395 30 23 2.734 3.455 2 0.179 31 31 4.507 6.667 3 0.083 32 27 3.002 4.116 3 0.249 33 22 2.290 1.286 1 0.257 34 25 2.835 0.200 2 0.905 35 35 4.506 4.875 2 0.087 36 31 4.421 0.824 2 0.663 37 33 4.413 0.471 2 0.790 38 37 3.213 1.130 2 0.568 39 46 5.208 7.900 2 0.019 40 36 3.122 7.769 1 0.005 41 40 4.305 25.814 3 0.000 42 33 3.225 0.600 2 0.741 43 33 2.739 0.200 1 0.655

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185 Table F-2. Species richness for each monthly whole lake sample. Species richness is listed as N(1) and it’s corresponding sta ndard error, chi-squared, degrees of freedom and probability. Week N(1) SE N(1) X^2 df Prob 1 36 4.031 5.100 2 0.078 2 42 5.289 1.750 2 0.417 3 28 3.817 0.778 2 0.678 4 22 4.016 7.538 2 0.023 5 26 3.476 2.077 2 0.354 6 32 5.064 0.875 2 0.646 7 25 3.587 3.875 2 0.144 8 29 3.365 2.167 2 0.339 9 38 4.250 3.364 2 0.186 10 31 3.288 2.000 2 0.368 11 28 2.627 2.714 2 0.257 12 33 4.068 0.875 2 0.646 13 30 4.841 8.375 2 0.015 14 21 3.353 5.286 2 0.071 15 25 4.228 1.733 2 0.420 16 33 5.076 6.533 2 0.038 17 18 2.840 1.400 2 0.497 18 34 4.710 5.333 2 0.070 19 33 3.810 2.111 2 0.348 20 28 3.037 10.111 2 0.006 21 40 4.976 10.211 2 0.006

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194 South Florida Water Management District (SFWMD), Florida Fish and Wildlife Conservation Commission (FFWCC), Flor ida Department of Environmental Protection (DEP), Florida Department of Agriculture and Consumer Services, U.S. Army Corps of Engineers (COE), U.S. Fish and Wildlife Service (FWS), and U.S. Environmental Protection Agency. 2004. Proposed Scope for the Kissimmee Chain of Lakes Long-Term Management Plan (Draft). Project charter and management goals 3/1/04. Strong, A.M., G.T. Bancroft, and S.D. Je well. 1997. Hydrologi cal constraints on tricolored heron and snowy egret resource use. The Condor 99:894-905. Sykes, P.W., Jr. 1979. Status of the Everglade kite in Florida, 1968-1978. Wilson Bull 91:495-511. Sykes, P.W., Jr. 1983. Snail kite use of th e freshwater marshes of South Florida. Florida Field Nat. 11:73-88. Sykes, P.W., Jr. 1984. The range of the snai l kite and its history in Florida. Bulletin of the Florida State Museum of Biological Science 29: 211-264. Sykes, P.W., Jr. 1987. The feeding habits of the snail kite in Florida, USA. Col. Waterbirds 10:84-92. Sykes, P.W., Jr., J.A. Rodgers Jr ., R.E. Bennetts. 1995. Snail kite (Rostrahamus sociabilis ). In The Birds of North America (A. Poole and F. Gill, eds). The Academy of Natural Sciences, Philadelphia, and The American Ornithologists’ Union, Washington D.C. No 171. 32pp. Tacha, T. C., S. A. Nesbitt, and P. A. Vohs. 1992. Sandhill Crane ( Grus canadensis ). In The Birds of North America, No. 31 (A. Poole, P. Stettenheim, and F. Gill, Eds.). Philadelphia: The Academy of Natural Sc iences; Washington, DC: The American Ornithologists' Union. Telfair, R. C. II. 1994. Cattle Egret ( Bubulcus ibis ). In The Birds of North America, No. 113 (A. Poole, and F. Gill, eds.). The Academy of Natural Sciences, Philadelphia, PA, and The American Ornithol ogists' Union, Washington, D.C. Thomas, L., Laake, J.L., Strindberg, S., Mar ques, F.F.C., Buckland, S.T., Borchers, D.L., Anderson, D.R., Burnham, K.P., Hedley, S.L., Pollard, J.H., Bishop, J.R.B. and Marques, T.A. 2005. Distance 5.0. Release “5.0”. Research Unit for Wildlife Population Assessment, Univer sity of St. Andrews, UK. http://www.ruwpa.stand.ac.uk/distance/ Last accessed March 2006. Traut, A.H. and M.E. Hostetler. 2003. Ur ban lakes and waterbirds: effects of development on avian behavior. Waterbirds 26(3): 290-302.

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195 Welch, Z. C. 2004. Littoral vegetation of Lake Tohopekaliga: community descriptions prior to a large-scale fisheries habita t-enhancement project. M.S. Thesis. University of Florida, Gainesville, Florida, USA. Weller, M.W. 1995. Use of two waterbird gui lds as evaluation tools for the Kissimmee River restoration. Restoration Ecology 3(3):211-224. Weller, M.W. 1999. Wetland Birds: Habitat Resources and Conservation Implications. Cambridge University Press. Cambridge, United Kingdom. Weller M.W., and L.H. Fredrickson. 1974. Avian ecology of a managed glacial marsh. Living Bird 12:269-91. Weller M.W., and C.S. Spatcher. 1965. Role of habitat in the distribution and abundance of marsh birds. Special Report No. 43. Iowa State University of Science and Technology, Ames, IA. West, R. L., and G. K. Hess. 2002. Purple Gallinule ( Porphyrula martinica ). In The Birds of North America, No. 626 (A. Poole and F. Gill, eds.). The Birds of North America, Inc., Philadelphia, PA. White, G.C., and K. P. Burnham. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study 46 Supplement, 120-138. http://www.warnercnr.colostate.edu/~gwhite/mark/mark.htm Last accessed March 2006. Wiens, J.A. 1981. Scale problems in avian censusing. Studies of Avian Biology 6:513521. Williams, L.E. Jr. 1978. Florida sandhill cran e. Pp. 36-37 in M.W.Kale, ed. Rare and Endangered Biota of Florida: Vol. 2, Birds. Univ. of Florida Presses, Gainesville, FL. Willson, M.F. 1974. Avian community organization and habitat structure. Ecology 55:1017-1029. Yasukawa, K., and W. A. Sear cy. 1995. Red-winged Blackbird ( Agelaius phoeniceus ). In The Birds of North America, No. 184 (A. P oole and F. Gill, eds.). The Academy of Natural Sciences, Philadel phia, PA, and The American Ornithologists' Union, Washington, D.C.

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196 BIOGRAPHICAL SKETCH Janell Marie Brush was born in Grand Island, Nebraska, on April 3, 1976. Grand Island, Nebraska, is known as the “City of Ki ndness” as well as th e city on the Platte River. Living near the Plat te River provided unique opportu nities for Janell to explore nature in one of the best places in the worl d to experience prairie wildlife, especially during spring migration when thousands of sa ndhill cranes arrived. At peak migration, half a million cranes are packed into a 60 mile stretch along the Platte River. The call of the sandhill crane still reminds Janell of her homeland and good times camping and fishing near the Platte River. After Janell graduated from high school in 1994, she was off to Northwest Missouri State University to seek a degree in the biol ogical sciences. Following two years of study she decided to return to Nebraska to attend th e University of Nebras ka at Lincoln. While she was in school she had the unique opport unity to attend classes at Cedar Point Biological Station in Western Nebraska. Th e abundance and variet y of plants, animals and ecosystems make Cedar Point a great resear ch and learning environment. This is where Janell decided that she wanted to fo cus on the wildlife aspect of the Biological Sciences. In December 1998 she graduated with her B.S. in biological sciences from the University of Nebraska. Soon she was off to learn as much as she could about wildlife biology. In May 1999 Janell was fortunate enough to have Rodney Siegel of the Institute of Bird Populations hire her to work on a avian nest searching project in the Sierra Nevada

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197 mountains. Through this experience Janell kne w she was in the right line of work and in 2000 made her move to work on the Endange red Snail Kite Project in the Florida Everglades. She was never afraid of hard work and it was a good thing because these jobs led to many opportunities which allowe d Janell to be challenged and learn. She fortunately had acquired and/or inherited some of her father’s engineering skills and was thus able to solve countless problems and de sign numerous projects and contraptions while working as a technician at the Coop Unit. It was th e job with the Coop Unit that eventually lead to her becoming a graduate research assistant in the Department of Wildlife Ecology and Conservation at the University of Florida. In April, 2006, because writing her thesis was not enough to keep her busy, she decided to plan her wedding to once again pr ove that she works better under pressure. She married James Albert Reyes on April 2, 200 6 and they are continuing the journey of life together.


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Permanent Link: http://ufdc.ufl.edu/UFE0014260/00001

Material Information

Title: Wetland avifauna use of littoral habitat prior to extreme habitat modification in Lake Tohopekaliga, Florida
Physical Description: xvii, 197 p. ; ill.
Language: English
Creator: Brush, Janell Marie ( Dissertant )
Kitchens, Wiley M. ( Thesis advisor )
Meyer, Ken ( Reviewer )
Oli, Madan ( Reviewer )
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2006
Copyright Date: 2006

Subjects

Subjects / Keywords: local   ( local )
Dissertations, Academic -- UF -- Wildlife Ecology and Conservation   ( local )

Notes

Abstract: Lake Tohopekaliga is the northernmost lake in the Kissimmee Chain of Lakes. The shallow lake is highly eutrophic in nature. This has caused "nuisance" vegetation to be excessively overgrown, encouraging organic sediment accumulation. The largest whole lake enhancement project ever attempted in the state of Florida was initiated on Lake Tohopekaliga during the winter 2003. The lake levels were lowered and 7.3 million cubic meters (8 million cubic yards) of littoral shoreline habitat was removed. Little is known about how a project of this scale will impact the vegetation, herptofaunal, fish and avian communities which occupy these littoral habitats of the lake. This study generates baseline data of the avian use patterns, abundances, and richness within the littoral zone for the two years before the enhancement project. This is a long term project and the data collected prior to the lake enhancement will be used for future assessments post lake enhancement. Distance sampling protocol which takes into account detectability of the avian species was used to sample at the scale of the whole lake sampling (line transects) and study area sampling (point transects). Density estimates were generated for 21 focal species within the avian community within the littoral zone. Generalized linear models were used to determine which environmental and temporal variables are driving the densities of the species. Spatial differences between the study area sampling as well as the whole lake sampling were determined and effective sampling methods were generated for each focal species. Season and lake stage were the variables which were driving the densities of many of the wetland dependent birds. When comparing the results obtained from the two types of sampling, it was concluded that many bird species will move throughout the littoral habitat in response to environmental factors, especially lake stage. Avian use patterns within the littoral habitat were identified for each focal species. Estimates of species richness within the littoral zone were also obtained from the sampling. Species richness was negatively correlated with average air temperature. Species richness also increased following a small scale drawdown and re-flooding event on the lake. The avian use of the littoral zone is dynamic and is dependent on the environmental, spatial and temporal processes which are constantly changing. As research continues prior to the lake enhancement, the long-term effects of the lake enhancement project can be assessed and predictions may be generated to determine the necessity of such large scale projects in the future.
Subject: avian, distance, littoral, management, Lake Tohopekaliga
General Note: Title from title page of source document.
General Note: Document formatted into pages; contains 214 pages.
General Note: Includes vita.
Thesis: Thesis (M.S.)--University of Florida, 2006.
Bibliography: Includes bibliographical references.
General Note: Text (Electronic thesis) in PDF format.

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0014260:00001

Permanent Link: http://ufdc.ufl.edu/UFE0014260/00001

Material Information

Title: Wetland avifauna use of littoral habitat prior to extreme habitat modification in Lake Tohopekaliga, Florida
Physical Description: xvii, 197 p. ; ill.
Language: English
Creator: Brush, Janell Marie ( Dissertant )
Kitchens, Wiley M. ( Thesis advisor )
Meyer, Ken ( Reviewer )
Oli, Madan ( Reviewer )
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2006
Copyright Date: 2006

Subjects

Subjects / Keywords: local   ( local )
Dissertations, Academic -- UF -- Wildlife Ecology and Conservation   ( local )

Notes

Abstract: Lake Tohopekaliga is the northernmost lake in the Kissimmee Chain of Lakes. The shallow lake is highly eutrophic in nature. This has caused "nuisance" vegetation to be excessively overgrown, encouraging organic sediment accumulation. The largest whole lake enhancement project ever attempted in the state of Florida was initiated on Lake Tohopekaliga during the winter 2003. The lake levels were lowered and 7.3 million cubic meters (8 million cubic yards) of littoral shoreline habitat was removed. Little is known about how a project of this scale will impact the vegetation, herptofaunal, fish and avian communities which occupy these littoral habitats of the lake. This study generates baseline data of the avian use patterns, abundances, and richness within the littoral zone for the two years before the enhancement project. This is a long term project and the data collected prior to the lake enhancement will be used for future assessments post lake enhancement. Distance sampling protocol which takes into account detectability of the avian species was used to sample at the scale of the whole lake sampling (line transects) and study area sampling (point transects). Density estimates were generated for 21 focal species within the avian community within the littoral zone. Generalized linear models were used to determine which environmental and temporal variables are driving the densities of the species. Spatial differences between the study area sampling as well as the whole lake sampling were determined and effective sampling methods were generated for each focal species. Season and lake stage were the variables which were driving the densities of many of the wetland dependent birds. When comparing the results obtained from the two types of sampling, it was concluded that many bird species will move throughout the littoral habitat in response to environmental factors, especially lake stage. Avian use patterns within the littoral habitat were identified for each focal species. Estimates of species richness within the littoral zone were also obtained from the sampling. Species richness was negatively correlated with average air temperature. Species richness also increased following a small scale drawdown and re-flooding event on the lake. The avian use of the littoral zone is dynamic and is dependent on the environmental, spatial and temporal processes which are constantly changing. As research continues prior to the lake enhancement, the long-term effects of the lake enhancement project can be assessed and predictions may be generated to determine the necessity of such large scale projects in the future.
Subject: avian, distance, littoral, management, Lake Tohopekaliga
General Note: Title from title page of source document.
General Note: Document formatted into pages; contains 214 pages.
General Note: Includes vita.
Thesis: Thesis (M.S.)--University of Florida, 2006.
Bibliography: Includes bibliographical references.
General Note: Text (Electronic thesis) in PDF format.

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0014260:00001


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WETLAND AVIFAUNA USAGE OF LITTORAL HABITAT PRIOR TO EXTREME
HABITAT MODIFICATION IN LAKE TOHOPEKALIGA, FLORIDA















By

JANELL MARIE BRUSH


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2006

































Copyright 2006

by

Janell Marie Brush

































This document is dedicated to my late grandmother, Alice Brush and to my family, all
whom appreciate the value of a good education.















ACKNOWLEDGMENTS

I would first like to thank Duke Hammond, formerly of the Florida Fish and

Wildlife Conservation Commission, who inspired and encouraged me to go to graduate

school. I would like to thank my committee, Wiley Kitchens, Ken Meyer and Madan Oli,

for their editorial comments, support, encouragement and patience while I worked

through the details of this project. I would especially like to thank my chief advisor, Dr.

Wiley Kitchens, who provided me with invaluable knowledge of the field of wetland

ecology and who has guided me and given me countless opportunities to grow and learn

over the last six years of conducting projects under his direction and leadership.

A large thank you goes out to the project field assistants. Without their expert bird

identification skills, hard work, insight and attention to detail, this project would not have

been so successful. These people include Scott Berryman, Adam Cross, Brenda Calzada,

Jamie Duberstein, John Davis, Samantha Musgrave, Vanessa Rumancik, John David

Semones and Zach Welch. Special thanks go to Scott Berryman and Jamie Duberstein,

who each dedicated two full years to the Lake Tohopekaliga bird project and kept me on

my feet. I would also like to thank the brave field crews, led by Melissa DeSa, who have

continued the project post-enhancement despite hazardous working conditions and

logistical nightmares. These people include Melinda Conners, Jamie Duberstein, Carolyn

Enloe, Becky Hylton, Allison Pevler, Derek Piotrowicz, James Reyes, Jonathan

Saunders, and Gina Zimmerman.









I want to thank the Florida Fish and Wildlife Conservation Commission for funding

this important long term project. I hope projects like the Lake Toho project will continue

to be a priority as we continue to bridge the gap between research and management.

I am forever in debt to many graduate student colleagues, Sonia Canavelli, Jamie

Duberstein, Julien Martin, Ann Marie Muench, Arpat Ozgul, Hardin Waddle and Zach

Welch. Each one of these individuals provided invaluable knowledge and they

brainstormed with me and assisted me with various phases of this project and analyses.

A heartfelt thank you goes out to the Distance Sampling Development Team,

without whom I would still be working on analyzing the large amount of data this project

produced. Thanks go to Steve Buckland, Len Thomas, Jon Bishop, and Tiago Marques.

They not only taught me all there is to know about Distance sampling but became my

support system. Their excitement for distance sampling and my project gave me the

motivation I needed to finish.

Last but definitely not least I would like to thank my family, Mary Ann Kalinay,

Carl and Jan Brush, and Julie Brush, for their continued support as I brave new trails and

adventures in the field of wetland ecology and also in life. Lastly, I want to thank my

Gainesville family, and local support system, Gina Zimmerman, James Reyes, Toho

Bear, Shadow Bug, and the late Cosmo. If it was not for their continuing support,

patience, unconditional love and understanding, I would have never been able to

complete this document.
















TABLE OF CONTENTS

page

A C K N O W L E D G M E N T S ........................................................................ .....................4

LIST OF TABLES ....................................................... ............ ....... ....... ix

LIST OF FIGURES ......... ......................... ...... ........ ............ xi

ABSTRACT ........ .............. ............. ...... ...................... xvi

CHAPTER

1 IN TR OD U CTION ............................................... .. ......................... ..

Florida Lakes Ecosystem ........................................................... ..............
Lake Tohopekaliga ................................... .... .. .. ......... ...... ......5
Lake H history and M anagem ent ........................................ ........................ 7
Previous Studies in Florida .............. ........................................ ............... 10
Lake Tohopekaliga Bird Study.......... .......................... ..................... 13
P roje ct O bjectiv e s ................... ................................................ .................. .... 14

2 STUDY AREA AND ANALYSIS METHODS ................................................17

In tro d u ctio n ................ ..... ....... .......... ...... ................. ................ 17
Regional Scale Community M onitoring................................... ............... 18
Whole Lake Community Monitoring ......................... ..................20
F ocal Species ...................................................... ................. 22
D instance Sam pling M ethods ........................ .. ........... ..................... ............... 26
Assumptions of Distance Sampling............................ .... ...............27
Parametric Models within DISTANCE........................................................27
Clusters within DISTANCE .....................................................28
D ata Truncation in D istance.......... ................. ........................... .... ......... 28
D election Covariates used within Distance .............................. ....................29
D en sity estim ation s .............................. ........................ .. ........ .... ............29

3 AVIAN DENSITIES AND VARIABLES IN STUDY AREAS ............................31

Survey M ethods ................................................................................... ... 3 1
A naly sis M methods ................. .................................. ................ ............. 34
D en sites ........................................... ........................... 34









O b serve er. ...................................................................................................... 34
V egetation Structure......................................................... ................35
Spatial Variations ..................... .... .......... ...... ............ .............. 35
Temporal and Environm ental Variations ................................. ................ 36
R results ..........................................................................................39
Spatial Variations ......................... ................................. 39
Environm ental and Temporal Variables........................................................ 45
D isc u ssio n ............................................................................................................. 6 1
Spatial Variations ..................... .... .......... ...... ............ .............. 61
Temporal and Environm ental Variations ................................. ................ 65

4 AVIAN DENSITIES AND VARIABLES IN WHOLE LAKE SAMPLING ...........71

In tro d u ctio n ........................................................................................................... 7 1
A naly sis M methods ................. .................................. ................ ............. 72
D en sites ................................................................... 72
Spatial Variations ..................... .... .......... ...... ............ .............. 74
Temporal and Environm ental Variations ................................. ................ 74
R e su lts .................. ................. .....................................................................................7 6
Spatial Variations ..................... .... .......... ...... ............ .............. 77
Temporal and Environm ental Variations .................................... ............... 81
D isc u ssio n .................................... ...................................................9 5
Spatial Variations ..................... .... .......... ...... ............ .............. 95
Temporal and Environm ental Variations ................................. ................ 98

5 DISCUSSION OF STUDY AREA VS. WHOLE LAKE SAMPLING.................. 101

In tro d u ctio n ........................ ...... ..... .......... ...................................................... 10 1
Caveats of Point Transect Distance Sampling................................ 101
Caveats of Line Transect Distance Sampling....................................................104
Spatial Variations of Point and Line Transects ............ ..................................106
Conclusions from Study Area and Whole Lake Sampling ............. ............... 109
American Coot................................... .................. ................ 110
Anhinga .............. ................ ...... ...............111
B elted K in g fish er........ ................................................................... .... 1 13
Boat-tailed Grackle....... ....... ............... ............ ................114
Cattle Egret ............ ...... ...... ....................................... 115
Common Moorhen ............ .......... ............................. 115
Florida Sandhill Crane .......... .... ................ ............... 117
Glossy Ibis ................ .... ......... ..................119
G great B lu e H eron ............................................................................ ....... 12 1
Great Egret................ .... ......... .................. 123
G re e n H e ro n ................................................................................................ 12 5
L east B ittern ....................................................... 12 7
Little Blue Heron ................ ...... .......... ......... 129
L im p k in ............................................................................................................. 1 3 0
Pied-billed G rebe.................................................... 131









P u rp le G allinu le ............ .... .. .............................................. .................... 132
Ring-necked Duck .................. .......................... .... .. .. .............. .. 132
R ed-w inged Blackbird ......................................................... .............. 134
S n o w y E g ret ................................................................................................ 1 3 5
Snail K ite ........................................................................................... ....... 137
Tricolored Heron ....... ...................................... .......... 140
Summary and Future Analyses.............. .............. .. ................... ....... ............... 142
Future Analyses ........................................................................... ... ......... ................... 143

6 AVIAN SPECIES RICHNESS WITHIN THE LITTORAL ZONE........................145

A n aly sis M eth o d s ........................................................................... ................ .. 14 5
R e su lts ...................... .. ............. .. ......................................................1 4 7
Stu dy A rea Sam pling ............................................ ....................................... 14 7
Lake W ide Sam pling ............................ ............................................. 149
Discussion ...................................................150

7 PROJECT SUMMARY......................................................... 154

APPENDIX

A SAMPLE DATES FOR THE PRE-ENHANCEMENT BIRD STUDY ..................158

B AVIAN SPECIES LIST FROM STUDY AREA AND WHOLE LAKE
SA M P L IN G ...................................... .............................. ................ 160

C AVIAN FOCAL SPECIES ESTIMATED DENSITIES ..........................................166

D DISTANCE ANALYSES MODEL PARAMETERS.............................................176

E GENERALIZED LINEAR MODELS ........................................ ............... 179

F AVIAN SPECIES RICHNESS TABLES ..................................... .................183

LIST OF REFEREN CES ........................................................... .. ............... 186

BIOGRAPHICAL SKETCH ............................................................. ............... 196
















LIST OF TABLES


Table pge

3-1 Table of predictions for focal species for study area sampling .............................38

3-2 Focal species with significant differences between density estimates for study
areas 1 and 2 ..................................... ............................... ........... 40

3-3 Focal species with significant differences between density estimates for study
are a s 1 a n d 3 ....................................................... ................ 4 2

3-4 Focal species with significant differences between density estimates for study
are a s 2 a n d 3 ....................................................... ................ 4 4

3-5 Environmental and temporat variables that influenced density estimates for focal
species in study area sam pling ........................................... .......................... 46

4-1 Predictions for line transect type used by each focal species...............................75

4-2. Table of predictions for whole lake sampling ..................................................76

4-3 Focal species with significant differences between density estimates on inside
vs. outside line transects...................................... ......... ........ ... .. ........ 77

4-4 Focal species with significant differences between density estimates on inside
vs. previously scraped line transects. ............................................ ............... 79

4-5 Focal species with significant differences between density estimates on outside
vs. previously scraped line transects. ............................................ ............... 80

4-6 Environmental and temporatl variable that influenced density estimates for focal
species in w hole lake sam pling. ......................................................................... 82

A-i Week number of sample and corresponding starting sampling day.....................158

A-2 Sample dates corresponding to whole lake surveys during the pre-enhancement
avian community monitoring study ............................ ........ ............. .................. 159

B-l Species seen on the lake that were Florida designated species of special concern,
and federally threatened or endangered....................................... ............... 160

B-2 Species list from the study area point transect sampling. ......................................161









B-3 Species list from the whole lake line transect surveys........................................164

C-1 Estimated densities for study area (point transect) samples................................167

C-2 Densities estimates and the corresponding standard error and variance for avian
species by study area. ...................... ...... ................ ................ .... ........ 172

C-3 Density estimates for focal species on line transect surveys. Sample date and
species codes are used .................. ................................ .. .. .. ............ 173

C-4 Density estimates by line transect type for focal species....................................175

D-1 Analyses parameters for point transect distance sampling for the most
parsimonious model chosen model for each focal species.............................. 177

D-2 Analyses parameters for line transect distance sampling for the most
parsimonious model chosen model for each focal species.............................. 178

E-l Potential models for the study area analyses which explain the response variable,
density as a function of the predictor variables................... ...................................180

E-2 Potential models for the whole lake analyses which explain the response
variable, density as a function of the predictor variables ............... .................182

F-l Species richness within the study areas by week of sample.. ..............................184

F-2 Species richness for each monthly whole lake sample. ........................................185















LIST OF FIGURES


Figure page

1-1 Map of Lake Tohopekaliga and Florida Watershed............... ..... ........... ....6

1-2 Regulatory schedule on lake Toho (red line) and the actual stage levels on the
lake during the pre-lake enhancement study. ..................................................... 6

1-3 Historical stage data from the headwater gauge station 61 on Lake Tohopekaliga...8

2-1 Study area locations on Lake Tohopekaliga.................................. ...... ............ ...19

2-2 Study area setup indicating the point transect locations 1 32 within the planned
treatm ent and control sites............................................... ............................. 20

2-3 Map showing line transect locations within the littoral zone of Lake
Tohopekaliga. ............... .. ....... ................................ ... ......... 21

2-4 The 1-4 ft. depth zones on Lake Tohopekaliga corresponding to the area of
interest on the lake during the pre-lake enhancement studies............... ...............17

3-1 The bird blind setup for point transects on Lake Tohopekaliga .............. ..............32

3-2 The value of differences in estimated densities between study area 1 and study
area 2 for focal bird species........................................................... ............... 41

3-3 The value of differences in estimated densities between study area 1 and study
area 2 for focal species. ............................... ................ ................. ............. 42

3-4 The value of differences in estimated densities between study area 1 and study
area 3 for select bird species. ............................................................................. 43

3-5 The value of differences in estimated densities (effect size) between study area 1
and study area 3 for select bird species. ......................................... ...............43

3-6 The value of differences in estimated densities between study area 2 and study
area 3 for select bird species. ............................................................................. 44

3-7 The value of differences in estimated densities between study area 2 and study
area 3 for select bird species. ............................................................................. 45









3-8 Estimated densities for the great blue heron within the lake littoral zone related
to study area and lake stage .............................................. ............................ 47

3-9 Estimated densities for the common moorhen within the lake littoral zone
related to study area and lake stage ........................................ ...................... 48

3-10 Estimated densities for the limpkin within the lake littoral zone related to lake
sta g e ............................................................................ .4 9

3-11 Estimated densities for the glossy ibis within the lake littoral zone related to
study area and lake stage. ............................................... ............................... 50

3-12 Estimated densities for the American coot during the winter season within the
lake littoral zone related to study area and lake stage. ..................... ...............51

3-13 Estimated densities for the belted kingfisher during the summer and winter
season within the lake littoral zone related to study area and lake stage. ................52

3-14 Estimated densities for the anhinga within the lake littoral zone related to study
area an d season n ......................................................................................... 5 3

3-15 Estimated densities for the boat-tailed grackle within the lake littoral zone
related to study area and season. ........................................ ......................... 54

3-16 Estimated densities for the great egret within the lake littoral zone related to
se a so n ............................................................................ 5 5

3-17 Estimated densities for the ring-necked duck during the winter seasons within
the lake littoral zone. ............................ ..... ... .. ...... ...............56

3-18 Estimated densities for the least bittern during the breeding and summer seasons
w within the lake littoral zone. ............................................. ............................. 57

3-19 Estimated densities for the snowy egret within the lake littoral zone related to
study area and season. ............................ ...... ............................ .... ...... ...... 58

3-20 Estimated densities for the tricolored heron within the lake littoral zone related
to study area and season ............................................ .........................................59

3-21 Estimated densities for the snail kite within the lake littoral zone related to lake
sta g e ...................................... ..................................... ................ 6 0

3-22 Estimated densities for the green heron within the lake littoral zone related to
season .............................................................................. 6 1

4-1 The value of differences in estimated densities between inside and outside line
tran sect types. ...................................................... ................. 78










4-2 The value of differences in estimated densities between inside and previously
scraped line transect types......................................................... .............. 80

4-3 The value of differences in estimated densities between outside and previously
scraped line transect types .......................................................................... .. ..... 8 1

4-4 Estimated densities for the anhinga during the winter season within the littoral
z o n e ............................................................................. 8 3

4-5 Estimated densities for the belted kingfisher during the winter season within the
litto ra l z o n e ................................................................................................ ..... 8 4

4-6 Estimated densities for the ring-necked duck during the winter season within the
litto ra l z o n e ................................................................................................ ..... 8 5

4-7 Estimated densities for the glossy ibis within the lake littoral zone related to
season and lake stage..................................... ......... ........ 86

4-8 Estimated densities for the tricolored heron within the lake littoral zone related
to season and lake stage. ...................... .. .... ..................................... 87

4-9 Estimated densities for the great egret within the lake littoral zone related to
season .............................................................................. 88

4-10 Estimated densities for the little blue heron within the lake littoral zone related
to season ............................................................................89

4-11 Estimated densities for the snowy egret within the lake littoral zone related to
season .............................................................................. 90

4-12 Estimated densities for the Florida sandhill crane within the lake littoral zone
related to season. ......................................................................91

4-13 Estimated densities for the common moorhen within the lake littoral zone
related to season. ......................................................................92

4-14 Estimated densities for the great blue heron within the lake littoral zone related
to season ............................................................................93

4-15 Estimated densities for the pied-billed grebe within the lake littoral zone related
to season ............................................................................94

4-16 Estimated densities for the snail kite within the lake littoral zone related to
season .............................................................................. 9 5

5-1 Spatial relationship of point transect locations and line transect locations within
study area 2.......................................................................................... ........ 109









5-2 Spatial relationship of point transect locations and line transect locations within
stu dy area 1 ............................................. ........ ................. 109

5-3 Estimated density for the anhinga within the study areas and along line transects
during the w inter season ...................................................................................... 112

5-4 Estimated density for the belted kingfisher within the study areas and along line
transects during the summer and winter seasons. .........................114

5-5 Estimated density for the common moorhen within the study areas and along
line transects during the pre-enhancement study. ..................................................117

5-6 Estimated density for the Florida Sandhill Crane within the study areas and
along line transects during the pre enhancement study............... ... ...............119

5-7 Estimated density for the glossy ibis within the study areas and along line
transects during the pre-enhancement study. ................................. ............... 121

5-8 Estimated density for the great blue heron within the study areas and along line
transects during the pre-enhancement study. ................................. ............... 123

5-9 Estimated density for the great egret within the study areas and along line
transects during the pre-enhancement study. ................................. ............... 125

5-10 Estimated density for the green heron within the study areas and along line
transects during the pre-enhancement study ............................... ............... 127

5-11 Estimated density for the least bittern within the study areas and along line
transects during the pre-enhancement study ............................... ............... 128

5-12 Estimated density for the little blue heron within the study areas and along line
transects during the pre-enhancement study ............................... ............... 130

5-13 Estimated density for the ring-necked duck during the winter season within the
study areas and along line transects ............................................ ............... 133

5-14 Estimated density of red-winged blackbirds by study area...............................135

5-15 Estimated density for study area and whole lake sampling for the snowy egret....137

5-16 Estimated density of snail kites for study area and whole lake sampling..............139

5-17 Estimated density by stage for the snail kite within the study areas and along line
transects during the pre-enhancement study .................................. ............... 140

5-18 Estimated density for the tricolored heron for study area and whole lake
sam p lin g ...........................................................................14 2









6-1 Scatter plot of average air temperature vs. species richness estimate within the
study areas .......... .... ..... ............................... ...................................... 148

6-2 Estimated species richness per week of sample...............................................149

6-3 Estimated species richness per month of sample during the initiation of the
draw dow n in the fall 2003 ......................................................................... ... ... 150
















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

WETLAND AVIFAUNA USAGE OF LITTORAL HABITAT PRIOR TO EXTREME
HABITAT MODIFICATION IN LAKE TOHOPEKALIGA, FLORIDA

By

Janell Marie Brush

May 2006

Chair: Wiley M. Kitchens
Major Department: Wildlife Ecology and Conservation

Lake Tohopekaliga is the northernmost lake in the Kissimmee Chain of Lakes. The

shallow lake is highly eutrophic in nature. This has caused "nuisance" vegetation to be

excessively overgrown, encouraging organic sediment accumulation. The largest whole

lake enhancement project ever attempted in the state of Florida was initiated on Lake

Tohopekaliga during the winter 2003. The lake levels were lowered and 7.3 million

cubic meters (8 million cubic yards) of littoral shoreline habitat was removed. Little is

known about how a project of this scale will impact the vegetation, herptofaunal, fish and

avian communities which occupy these littoral habitats of the lake. This study generates

baseline data of the avian use patterns, abundances, and richness within the littoral zone

for the two years before the enhancement project. This is a long term project and the data

collected prior to the lake enhancement will be used for future assessments post lake

enhancement.









Distance sampling protocol which takes into account detectability of the avian

species was used to sample at the scale of the whole lake sampling (line transects) and

study area sampling (point transects). Density estimates were generated for 21 focal

species within the avian community within the littoral zone. Generalized linear models

were used to determine which environmental and temporal variables are driving the

densities of the species. Spatial differences between the study area sampling as well as

the whole lake sampling were determined and effective sampling methods were

generated for each focal species.

Season and lake stage were the variables which were driving the densities of many

of the wetland dependent birds. When comparing the results obtained from the two types

of sampling, it was concluded that many bird species will move throughout the littoral

habitat in response to environmental factors, especially lake stage. Avian use patterns

within the littoral habitat were identified for each focal species.

Estimates of species richness within the littoral zone were also obtained from the

sampling. Species richness was negatively correlated with average air temperature.

Species richness also increased following a small scale drawdown and re-flooding event

on the lake. The avian use of the littoral zone is dynamic and is dependent on the

environmental, spatial and temporal processes which are constantly changing. As

research continues prior to the lake enhancement, the long-term effects of the lake

enhancement project can be assessed and predictions may be generated to determine the

necessity of such large scale projects in the future.














CHAPTER 1
INTRODUCTION

Wetland dependent birds, which include birds that use wetlands during some period

during their life, whether as habitat for foraging, nesting, roosting or for all three, have

long been monitored in scientific studies because of their intrinsic conservation value and

because they act as indicators of ecological status (Furness and Greenwood 1993).

Wetland birds integrate a variety of environmental factors which are difficult and

expensive to measure individually (Furness and Greenwood 1993). As bioindicators, it is

assumed that changes in the birds' distributions (habitat use patterns and abundances)

will indicate the changes which have occurred in the independent variables which

function as stressors (Kushlan 1993). Cairns (2000) states that the best way to resolve

ambiguities about how water level manipulations and managerial actions affect

abundances of invertebrates and use of habitat by birds is to test explicit hypotheses as an

ecological experiment. This study is based on that premise and represents an attempt to

provide critical measures of wetland use, abundances and distribution prior to the late

2003-2004 drawdown and scraping project on Lake Tohopekaliga, in central Florida.

Florida Lakes Ecosystem

The state of Florida has nearly 8,000 diverse natural lakes that range in size from

0.4 ha to over 180,000 ha (Shafer et al. 1986, Canfield, Jr. and Hoyer 1988). The

majority of Florida lakes (80%) have surface areas that are less than 40 hectares (100

acres) in size. However, the largest lake, Lake Okeechobee, has a surface area greater

than 183,000 hectares (450,000 acres), and is the third largest freshwater lake located









entirely within the United States (Brenner et al. 1990). These lakes generally have a

large area:volume ratio due to the formation processes and the flat topography in the

region (Brenner et al. 1990). Unlike the glacier-formed lakes of Northern United States,

Florida lakes were chiefly formed by karst erosion, the collapse of the limestone bedrock

substrate forming a solution lake, or by relict sea bottom depressions which filled in as

the sea receded (McPherson and Halley 1996). The geology of the region combined with

a subtropical climate with variable rainfall creates limnology and hydrology unique to

this region.

Rains from summer thunderstorms and tropical systems in the late summer and

autumn are highly variable. Due to the subtropical climate, lake evaporation is relatively

constant from year to year (Brenner et al. 1990). Due to Florida's topography,

unevaporated water usually sinks rather than running off (Brenner et al. 1990). As a

result, dry years are frequent and extreme and there is a 10% chance that rainfall will be

30% below normal in any year. What exists as "normal" is extreme variability, the

condition limnologists call astatic, particularly with regard to depths and stages. In

addition, shallow lakes of this nature typically have long stretches of undeveloped

shoreline and expansive but linear littoral systems that are capable of supporting diverse

aquatic vegetation types.

It is the potential management of these littoral systems that provided the impetus

for this study. This document will focus on the avian distribution, abundance and use of

the littoral zone of one such lake, Lake Tohopekaliga (to be described in a later section).

In the context of this study, the littoral zone is defined as the ecotone between dry land

and open water which spans into the maximum depth at which plant growth occurs









(Hoyer and Canfield 1994). These littoral zones typically consist of heterogeneous patch

mosaics that differ in their physio-chemical and biological properties from adjacent

ecosystems (Pieczynska and Zalewski 1997), are characterized by high levels of

biological diversity, but at the same time attract human attention due to direct access to

water resources and recreation. In addition, these systems buffer ecological flows

between terrestrial and aquatic ecosystems. They also have a possible role in the stability

of the ecological systems that they delimit (Pieczynska and Zalewski 1997).

In addition to being shallow biologically diverse systems, many Florida lakes are

highly eutrophic in nature. Because lakes become more eutrophic as they age, over time

sediments nearest the bottom remain nutrient poor and the surface sediments are rich in

organic (Likens 1972). In addition, shallow lakes of this type are less responsive to

significant reductions in external nutrient loading because the benthic-pelagic interactions

tend to maintain high nutrient levels. For example, nutrients are continually released

from the bottom as a result of wind disturbance and tend to affect the entire water

column. In addition to wind effects, nutrient releases or "internal loading" can result

from gas bubble effects, high pH from intense phytosynthesis, and from dissolved oxygen

deficits at the sediment water interface (Cooke et al. 2005). In Florida this problem of

internal loading is compounded by the accelerated external loading associated with the

urbanization of the state.

With the rapid growth rate of human occupancy within the state of Florida came

the need to control the natural flow of water throughout the state. The first drainage

canals were dug in the upper Kissimmee River basin and between Lake Okeechobee and

the Caloosahatchee River in the 1920's. Levees were constructed around lakes to prevent









flooding, and when they did not stand up to hurricane force conditions, flood control

measures were initiated and the flow of water throughout the state was completely

controlled by the 1960's (McPherson and Halley 1996). Water level stabilization

combines with nutrient loading and urban and agricultural runoff to lead to increasingly

more eutrophic lakes. The eutrophic effects contribute to the proliferation and over

abundance of undesirable vegetation in the littoral zone.

Eutrophication in the Florida lakes causes increased primary producer biomass,

reduced water clarity, good growing condition for nuisance species, habitat degradation,

and decreased lake volume (Cooke et al. 2005). The "nuisance" vegetation, such as

cattails (Typha spp.), pickerelweed (Pontederia spp.), and the submersed hydrilla

(Hydrilla verticillata), have become excessively overgrown in many Florida Lakes and

controlling them has become a priority for managers.

In order to combat littoral zone habitat degradation problems associated with lake

eutrophication and the cumulative effects of an imposed stage regulation schedule, the

Florida Fish and Wildlife Conservation Commission (FFWCC), South Florida Water

Management District (SFWMD), and Army Corps of Engineers (COE) have employed

extreme drawdowns and occasionally mechanical removal of unwanted macrophytes

(nuisance level pickerelweed, etc.) and associated organic sediment "muck" as well as

aggressive herbicide applications in many Florida lakes in an attempt to manage these

systems (HDR Engineering 1989, Moyer et al. 1995, SFWMD et al. 2004). Drawdowns

have been used in lake management for many years to oxidize and consolidate flocculent

sediments, to alter fish populations, and for aquatic weed control (Hoyer and Canfield

1997). The littoral system of Lake Tohopekaliga, located within the Kissimmee Chain of









Lakes, and one of many eutrophic lakes in Florida, exhibits many of the over enrichment

characteristics of other Florida lakes and is the focus of this study.

Lake Tohopekaliga

Lake Tohopekaliga (hereafter referred to as Lake Toho) is a shallow lake located in

Osceola County, Florida (Figure 1-1). Its surface area covers 8,177 ha (20,204 acres) and

has a mean depth of 2.13 meters (7 feet) at a maximum regulation stage of 55 feet

NGVD. The lake has an expansive (2228 ha, 5507 acre) littoral zone of mixed emergents

which comprises about 29% of the surface lake area (ReMetrix, LLC 2003). Lake Toho

drains a total area of about 340 square km. (131 sq. miles) (HDR Engineering 1989) and

is part of the Kissimmee watershed which covers approximately 3,000 square miles of

south-central Florida (SFWMD et al. 2004). Lake Toho receives inflow from the Shingle

Creek watershed; the East Lake Toho watershed via Structure S-59; direct precipitation;

ground water seepage into the lake; 11 minor tributaries; and from unguaged flows (Fan

and Lin 1984, HDR Engineering 1989).

Lake Toho lies within the Osceola plain physiographic area. The lake is believed

to have formed as a result of solution activity following the process of geologic uplift.

This process left behind a ridged, sand-coated limestone plain which was subject to

solutioning, particularly in the lower areas between the ridges. Lake Toho resides in a

basin composed of sands and silts underlain by calcareous sands overlying limestone.

Precipitation is its primary source of recharge (Schiffer 1998). The lake, along

with the other water bodies in the state of Florida, was drastically altered by the

construction of the water control structures and imposition of a regulatory schedule

(Figure 1-2).











Lake Tohopekaliga


N
+E FLORIDA





Osceola County


Lake Kissimmee ,


Like Oke.I.J-r
Lake Okeep,:,:,.,ee


Big Cypress National Preser-I -


Everglades National Park -


Figure 1-1. Map of Lake Tohopekaliga and Florida Watershed.

58
2002 2003
57
,. --


a 5 m U




Figure 1-2. Regulatory schedule on lake Toho (red line) and the actual stage levels on
the lake during the pre-lake enhancement study.









Lake History and Management

The first major drainage and land reclamation project on Lake Toho was

undertaken between 1882 1894. Disston's Okeechobee Land Co. excavated a series of

canals and ditches which linked the upper Kissimmee basin's principal lakes and cleaned

and deepened the Kissimmee River (HDR Engineering 1989). As early as the 1920's 67

miles of canals had been dug throughout a 21,853 hectare (54,000 acre) area to the east

side of the lake around Shingle Creek and Boggy Creek basins (Blackman 1973). In the

mid 1940's the Army Corps of Engineers attention had turned to developing means of

flood control when two hurricanes caused extensive flooding in the Kissimmee area

(HDR Engineering 1989). This project called for channelization of the Kissimmee River,

rechannelization of some of the original upper basin canals, use of the upper basin lakes

as storage/conservation areas, and the installation of a series of water control structures

and levees. The astasis of lake water levels was replaced with the implementation of a

water stage regulation schedule (Figure 1-2). By 1971 the project had been completed

but not before the lake alterations as well as wastewater discharge had drastically affected

the water quality of the lake (Blake 1980, HDR Engineering 1989, Dierberg et al. 1988).

Flooding and drying events in shallow lake systems are environmental disturbances

which tend to maintain the spatial and temporal heterogeneity and hence biodiversity

(Pieczynska and Zalewskil997). In an attempt to remediate the excessive growth of

nuisance vegetation, the Florida Game and Freshwater Fish Commission (now FWC)

implemented an extreme drawdown on Lake Toho in 1971 (SFWMD et al. 2004). The

project was designed to consolidate bottom sediments and expand desirable aquatic plant

communities by dewatering the lake to seasonal lows experienced historically by the lake

(SFWMD et al. 2004). Lake Toho underwent scheduled drawdown events again in 1979,









and 1987 to improve aquatic habitat for fisheries (Figure 1-3). During the drawdown of

1987, mechanical removal of 172,024 cu meters (225,000 cu yards) of organic muck

sediment was conducted in the littoral reaches of the southern area of the lake (FFWCC

2004). By the end of 1988 all direct and indirect discharges to Lake Toho were ceased

(HDR Engineering). Despite the discontinuation of urban runoff, the removal of

phosphorus from four sewage treatment plants, and the three extreme drawdowns, Lake

Tohopekaliga, a nitrogen-limited lake, to present date, has managed to remain eutrophic

for over three decades (Dierberg et al. 1988).

Lake Toho is currently collaboratively managed by Florida Fish and Wildlife

Conservation Commission, South Florida Water Management District, and The Army

Corp of Engineers. The lake water levels are continuously managed for flood control and

a schedule is followed throughout the year. However, flood control and navigation


1971 1979 1987





56-










V M [ 5 I ( C 0 U B l f4 0 5



Figure 1-3. Historical stage data from the headwater gauge station 61 on Lake
Tohopekaliga. The years preceding the stabilized hydroperiod are seen, as
well as the three scheduled drawdowns.









represent concerns that often conflict with the desire to improve or maintain water

quality. As in many other Florida lakes, "nuisance" vegetation, such as cattails (Typha

spp.), pickerelweed (Pontederia spp.), and the submersed hydrilla (Hydrilla verticillata)

become excessively overgrown, encouraging organic sediment "muck" accumulation. As

a result of this accumulation there is an overall net decline in fishery, habitat for some

species, water quality, and recreational access on the lake (Moyer et al. 1995, Cooke et al.

2005).

In November 2003, the Florida Fish and Wildlife Conservation Commission

initiated the Lake Tohopekaliga habitat enhancement project, which was the largest

whole lake enhancement project ever attempted in the state of Florida. The goal of the

drawdown and muck removal project was to re-establish aquatic vegetation and improve

lake habitat for sport fish, fish food organisms and wildlife. (FFWCC 2004). The lake

level was lowered from 16.8 m (55.0 ft) to 14.9 m (49 ft) NGVD, and following the

drawdown, an estimated 7.3 million cubic meters (8-million cubic yards), with 1,351 ha

(3,339 acres) of shoreline habitat was removed. This enhancement targeted the entire

width of the littoral zone for removal, not only the organic berm. The main macrophyte

community which was eliminated was the Pontederia cordata-dominated habitat

throughout the lake. Twenty-nine in-lake spoil islands and many inland disposal islands

were created from the scraped material (FFWCC et al. 2004). Once the water levels

came back up to the normal stage regulation schedule, herbicide applications resumed as

normal to keep the nuisance vegetation at bay. Although it has been documented that this

type of management practice may be beneficial for some fish communities, (Dierberg et









al. 1988, Moyer et al.1995, Allen et al. 2003), it is extremely expensive and it has never

been conducted at such a large scale as the Lake Toho project.

In addition to being expensive to remove unwanted vegetation there are also large

uncertainties as to whether management will have the predicted effects because of lack of

clear understanding between results from small-scale ecological experiments and large

scale processes (Havens and Aumen 2000, Lindegarth and Chapman 2001). A

comprehensive long term study was designed to capture the effects of a large scale

habitat manipulation on the community assemblages of vegetation, aquatic vertebrate,

and avian communities which use or occupy the littoral reaches of lake Toho. This

aspect of the study being discussed here relates to the avian community structure prior to

lake enhancement activities.

Previous Studies in Florida

Many avian studies conducted within Florida, focus on birds in the marsh systems

of south Florida, while few studies have examined the bird populations that use the lakes

of Florida and how these populations may be affected by management actions (Hoyer and

Canfield 1990). One study (Traut and Hostetler 2003) examined avian use and behavior

within Florida lake littoral zones in the Peace River Basin along developed vs.

undeveloped shorelines. This study used count indexes along with behavior codes

conducting surveys from a genoe to determine avian responses to shoreline

developments. The authors concluded that waterbird behavior is not associated with

shoreline development (Traut and Hostetler 2003). Studies relating to effects of habitat

and environmental factors on avian community structure and abundances in the littoral

habitats on Florida lakes are more common. A study conducted within the Winter Haven









Chain of Lakes also used bird count data obtained from surveys involving the use of a

genoe (Huegel 1993) to determine habitat use within the littoral zones of the lakes.

Wildlife surveys conducted on Orange Lake, in north central Florida, used point

count data as well as sweep surveys (via airboat) to calculate densities (number of bird

per unit area) of both individual species and all species collectively within each habitat

type (Sieving and Schaefer 1997). The results were not quantitative, however there

seemed to be a correlation with increasing bird densities with distance to the

vegetation/water interface, with particular high numbers of birds associated with floating

marsh habitat in close proximity to the shoreline. Due to the cryptic species within the

ciconiiformes (wading birds) group, these birds were under-represented in the point count

samples, and results from the airboat sweep surveys were unreliable (Sieving and

Schaefer 1997).

Another study looked at factors influencing wintering waterfowl abundances in

Lake Wales, Florida (Gasaway et al. 1977). This study used point index counts from set

stations and determined correlations between species and aquatic vegetation (Hydirlla)

present in the lake (Gasaway et al 1977). Plant community use by wintering waterfowl

was also the focus of another study conducted on Lake Okeechobee (Johnson and

Montalbano III 1984). Aerial censuses of ducks were conducted within the study areas to

obtain count data used in the analyses. Also, on Lake Okeechobee, a study was

conducted relating foraging habitat and selection among wading birds in relation to

hydrology and vegetative cover (Smith et al. 1995). Again, flight surveys were

conducted to document the distribution and abundance of foraging wading birds on and

adjacent to the lake. These flight surveys included belt transects, margin transects, and









count block surveys to obtain estimates of bird density. These results were used to

produce bird density maps which were related to water levels and vegetation

communities within the study area (Smith et al. 1995). Raw counts of birds were used to

produce population estimates compared with lake stage. In addition to the studies

designed to look at habitat preference of wetland birds, many studies have been

conducted within the lake systems of Florida which relate bird densities to water levels

and management activities.

A project examining the waterbird use of coastal impoundments and management

implications in east-central Florida used count data to generate density estimates to relate

with water depth (Breininger and Smith 1990). A project conducted by surveying the

littoral zone of Lake Okeechobee by helicopter determined wading bird abundance from

count data related to water levels (David 1994).

All of these studies employed a variety of different methods to obtain count indexes

of the birds of interest; however, none of these sampling methods take into account the

detectability of the birds which were surveyed. The detectability of a species can be

defined as the probability of detecting at least one individual of a given species in a

particular sampling effort, given that individuals of that species are present in the area of

interest during that sampling session (Boulinier et al. 1998). Count index survey methods

without taking into account detectability tend to overestimate densities and abundances

for species that are obvious in behavior, large in stature, or often times are observed in

large groups. Two studies that give an excellent account of the consequences of failure to

adjust for detectability are Diefenbach et al. 2003 and Norvell et al. 2003. Making

comparisons over time using index counts made at the same locations are compromised if









habitat succession affects detectability, if observers change, or during different seasons

(Buckland 2004). Also, the results tend to report higher densities of birds associated with

open areas or during specific seasons where the detectability of these birds is going to be

higher. Without quantitative studies in such systems it is hard to determine if the results

are because birds actually use these areas more or is detectability a factor in the results.

Even with all the information collected within the littoral zones of lakes in Florida, there

is still little quantitative information available on the relationship between wetland birds

and environmental factors such as vegetation cover or lake water levels. Other studies up

to this date have not captured the effective density changes in various habitats. This

study measures densities using a departure from count indices.

Lake Tohopekaliga Bird Study

The Lake Toho bird study incorporates detectability of bird species as a tool for the

generation of density estimates. By using a sampling protocol that includes the

detectability of the bird species I hope to generate density estimates in which obvious

birds are not overestimated and cryptic birds are not underrepresented. Also, by using

this type of sampling, observer bias as well as bias associated with habitat type will be

eliminated. The common assumption of equal detectability of bird species when

conducting bird point index counts has been falsified in many studies that emphasize the

importance of recognizing the heterogeneity in species detectability (Boulinier et al.

1998, Nichols et al. 1998, Nichols et al. 2000, Rosenstock et al. 2002, Norvell et al.

2003, Buckland 2004). Detectability of bird species can depend on many things such as

vegetation succession as seen by Bibby and Buckland (1987) and by observer differences

as seen by Diefenbach et al. (2003). When conducting bird censuses one also must

consider the time of year, time of day, and corresponding bird behaviors (cryptic or









obvious) that can increase or decrease detection probability of the bird during that period

of time (Marsden 1999). When conducting mixed species counts it is critical that species

are looked at separately unless the detection of one is correlated with the presence of the

other species (Buckland et al. 2001). Distance sampling, an integrated approach which

encompasses study design, data collection, and statistical analysis avoids many of the

pitfalls of index counts and when applied properly, it provides direct estimates of bird

density that are not confounded by detectability (Rosenstock et al. 2002). By using a

distance sampling protocol combined with multi-scales of resolution, one can decipher

what is going on within a system of interest (Marques and Buckland 2003).

With the large amount of information available about habitat and feeding

preference for individual bird species, one can get an idea of what bird community

assemblages may occupy different patches on the lake corresponding to different

environmental variables. Incorporating these known preferences with the results of this

study will increase the information available to managers regarding the avian community

response to lake enhancement activities on Lake Tohopekaliga.

Project Objectives

The study presented here is part of a long term, large scale project evaluating the

avifauna, aquatic vertebrate (Muench 2004) and vegetation (Welch 2004) community

response to the 2004 Lake Toho enhancement. The long term project is designed to

describe the avian abundance, distribution and use patterns prior to lake enhancement

activities and again post lake enhancement. The research presented in this thesis

examines the avian community structure prior to the 2004 drawdown and mechanical

substrate removal. During the time period of this study, no management actions occurred

on the lake system, with the exception of some routine herbicide spraying of exotic









vegetation species. Two different sampling techniques were implemented to obtain bird

densities and community structure data. A comparison which looks at results obtained

from sampling at different scales between the two methods will be addressed in following

chapters. What will be presented here is the baseline data that will be used for

comparisons made during the continuation of the study post lake enhancement and

vegetative recovery. The specific objectives of this research include:

* Identify the environmental variables that are associated with densities of the
abundant wetland dependent avian species within the littoral zone of lake Toho.

* Determine how these variables influence avian abundance.

* Estimate bird species density within the littoral zone of lake Toho using two types
of distance sampling. Determine spatial variations on the lake. Determine
responses to temporal and environmental variables including lake stage, air
temperature, season, year, etc.

* Compare the data collected using the two different distance sampling methods to
determine which method best describes bird usage of the littoral zone, and outline
advantages/disadvantages to each method of sampling.

* Determine species richness on the lake and determine what variables are
influencing it.

This remainder of this document is organized in the following way. Chapter two

will describe how the whole lake (line transects), and study area (point transects) were set

up. Chapter two will also describe the focal avian species analyzed, detail distance

sampling methods for the two types of sampling, list the assumptions of distance

sampling, explain how distance sampling works, and introduce general distance

sampling methods used for both types of sampling. In Chapter 3 the sampling methods

within the study areas will be outlined, analysis methods for the point transect data will

be covered, and results and discussion for the study area analysis will be presented. In

Chapter 4, the whole lake sampling methods, analysis, results and discussion will focus









on the line transect sampling. Chapter 5 will be a discussion chapter comparing the two

types of distance sampling results. It will discuss the preferred method for examining the

variables of interest. This chapter will also discuss advantages and disadvantages of the

two methods of sampling in this habitat and draw conclusions about each of the focal

species and their usage within the littoral zone of the lake. Chapter 6 will discuss species

richness within the littoral zone and environmental variables influencing richness.

Chapter 7 is a brief chapter discussing detectability and distance sampling and the future

of the Lake Toho project.














CHAPTER 2
STUDY AREA AND ANALYSIS METHODS

Introduction

This study used two different types of sampling to gather baseline data that will

permit monitoring of the effects of the Lake Toho enhancement project on the wetland

dependent avian community. When looking at habitat selection for wading birds it is

important to investigate across a continuum of temporal and spatial scales. (Strong et al.

1997). One type of sampling technique, line transect sampling, was used to characterize

the avian community structure and species specific responses before and after lake

enhancement, by detecting changes or trends in distributions in randomly selected littoral

reaches of the undeveloped shoreline of the lake with inferences applicable to the entire

lake. The data obtained from the line transect sampling hereafter will be referred to as

"Whole Lake Sampling". The other method, which used point transect sampling, was

designed to detect differences in avian community structure and species specific

responses within specific study areas. Point transects, which were replicated to provide

inferences at the whole lake scale, utilized a treatment vs. control approach. The data

obtained from the point transect sampling hereafter will be referred to as "Study Area

Sampling". In the chapters following, specific questions, methods, analysis, results and

conclusions will be outlined separately for the two different sample methods, followed by

a comparison of the two sets of results. Unless otherwise stated, the information in this

chapter was applied to analysis methods that were the same for both types of sampling.









No treatments were applied during the collection of the data presented in this document,

which were gathered during the pre-enhancement phase, 2002 and 2003..

Regional Scale Community Monitoring

Point transects were set up within the selected study areas to examine the bird

distributions at a relatively fine scale. Three areas were sampled prior to lake

enhancement in the same manner as they will be sampled once the lake enhancement has

been completed to allow for comparisons of treatment effects within the study areas.

This will be elaborated in the "Methods" section. The study areas were chosen based on

similar types of shoreline with continuous types of littoral habitat (specifically dense

Pontederia cordata pickerelweedd) and Typha (cattail)) (Figure 2-1) and were the target

of the enhancement project.

Each study area occupied 1600m (5,249 ft) of total shoreline length, divided

equally into four treatment plots 400m (1,312 ft) in length. Two of these plots were

randomly designated control plots and two of the plots were to be scraped following

collection of the pre-enhancement data. The pre-enhancement vegetative habitat within

the study areas was described in great detail in Welch, 2004. Each study area had 32

possible point transect locations in varying microhabitats within the littoral zone. These

points transects were arranged in the littoral habitat so that they were 100m away from

the next closest sample location. Each of the four treatment plots per area had 8 possible

point transect locations within them (Figure 2-2). These randomly sampled locations

were in water depths up to 121.92 cm (48 in). The depth locations were based on the

bathymetric maps provided by ReMetrix, but actual water levels were in constant

fluctuation throughout the year. In this pre-enhancement study, no distinction as to future









treatment status of the various study areas were considered in the random assignments of

point transect locations of any of the sampling events.


Figure 2-1. Study area locations on Lake Tohopekaliga.





































Figure 2-2. Study area setup indicating the point transect locations 1 32 within the
planned treatment and control sites, remembering that sampling occurred prior
to the treatments actually being implemented.

Whole Lake Community Monitoring

In order to look at the entire undeveloped shoreline of the lake, line transect

samples were implemented in the southern two-thirds of the lake. Using digital ortho

quarter quads (DOQQ) in the program Arc Map 4.0 (ESRI 2005), a line was drawn

parallel to the shoreline covering 27,600 meters. It was decided that the line transects

should be 400 meters in length so that the observers could see the whole length of the line

while sampling as to not violate the assumptions of distance sampling, and to limit the

types of vegetation crossed while traversing a single line transect. There were 69









possible such transects along this line and 26 of them were randomly chosen to be

permanent line transects.

Due to thick stretches of cattail that often impeded observations between the

emergent and floating leaf vegetation, transects were randomly placed either shoreward

or lakeward of the cattail. The habitats observed within the 1-4 foot depth zones of the

littoral reaches of the lake were classified as either inside, outside or previously scraped

areas (see lake history section) (Figure 2-3).

















Figure 2-3. Map showing line transect locations within the littoral zone of Lake
Tohopekaliga. Map indicates the types of transects.

The principal vegetative communities occurring within the inside littoral zone transects

were mainly pickerelweed (Pontederia cordata), torpedo-grass (Panicum repens) and

water-grass (Luziolafluitans). The transects located on the outside reaches of the littoral

zone were composed of mainly submersed species such as coontail (Ceratophyllum

demersum), hydrilla (Hydrilla verticillata), and emergent floating leaf species such as

fragrant water-lily (Nymphaea odorata), spatterdock (Nuphar polysepalum), water lotus

(Nelumbo lutea), banana-lily (Nymphoides aquatic) and the emergent Egyptian









paspalidium (Paspalidium geminatum). The previously scraped sites (indicated in yellow

in figure 2-3) have a steeper shoreline slope is due to prior restoration efforts (section of

the lake which was scraped in 1987). This area is also target of aggressive herbicide

applications for management of invasive vegetative species such as typha, alligator weed,

and water hyacinth. As a result of the previous restoration efforts, this area has shorter

less dense shoreward vegetation and less littoral zone (more open water) in general. In

addition to these factors, this area also is subject to greater disturbance by daily airboat

tours. These characteristics create a habitat that appears different from both the inside

and outside transects. Because of apparent differences in the habitat covered while

conducting line transect sampling the three transect types were developed and will be

analyzed both separately and together.

Focal Species

This study focused on wetland-dependent species, i.e., those that they use wetland

habitats at some critical stage during their life cycle. These wetland dependent species

constitute many different guilds. Analyses were conducted by species when enough

observations were obtained to generate reliable estimates of density, determined by

looking at the goodness of fit tests and the percent coefficient of variation associated with

the estimates. Some of these species were endangered, threatened or Species of Special

Concern in the State of Florida (Table A-i, Appendix A). Many of these wetland species

are residents on the lake, are numerous, and could be analyzed at the species level. When

possible, densities were estimated weekly (for point transects) and monthly (for line

transects). In cases where there were not enough observations within the week, detection

probability was modeled globally to derive weekly density estimates. Within the lake

littoral zone, density estimates for the following species were obtained (in alphabetical









order): (Specific life histories, including habitat preference, seasonal movements, and

foraging behavior, will be described in the following chapters.)

* American Coot. The American coot (Fulica atra), is a common and widespread
waterbird that is hunted in many places. This swimming rail has an all black body
and white beak. The American coot is a winter non-breeding resident in Florida. It
feeds on aquatic plants on the surface and underwater (Brisbin et al. 2002).

* Anhinga. The Anhinga (Anhinga anhinga), is a large dark waterbird with a long
neck and tail and a pointed bill. Its population is relatively stable although local
extirpations have resulted from drainage and development of wetlands (Elphick et
al. 2001). The anhinga is a year round Florida resident. They are found in various
freshwater wetlands with open, shallow waters, but can also live in brackish and
saltwater habitats in Florida. They mainly feed on fish they spear while swimming
underwater (Frederick and Siegel-Causey 2000).

* Belted Kingfisher. The belted kingfisher (Ceryle alcyon) is a medium sized bird
that is a common waterside resident in Florida during the non-breeding seasons.
The belted kingfisher winters along the coast, streams and lakes. It uses a perch or
hovers to look into clear water for prey items and then dives to catch them. The
population may be decreasing in many areas (Hamas 1994).

* Boat-tailed Grackle. The boat-tailed grackle (Quiscalus major) is a large, long
tailed blackbird and a year round resident in Florida. In addition to being found in
a variety of urban habitats on the coast, it is also found in freshwater and saline
marshes. In the marsh system it eats invertebrates, as well as frogs (Post et al.
1996). It typically forages by turning over floating leaf aquatic vegetation or by
sticking its bill into other vegetation looking for prey items.

* Cattle Egret. The cattle egret (Bubulcus ibis) is a medium sized white wading bird
and is usually found in pastures and along roadsides, although it can be found in
aquatic habitats. The cattle egret is a year round resident in Florida. It is an
opportunistic forager and usually is seen following cattle or machinery catching
insects that they stir up (Telfair 1994).

* Common Moorhen. The common moorhen (Gallinula chloropus) is the most
widely distributed member in the rail family and a year round resident in Florida.
The common moorhen is found in marshes and ponds with tall emergent
vegetation. It forages by picking food from emergent plants while walking or from
the water surface while swimming. It often turns over floating leaf aquatic
vegetation looking for snails. In many states across the country it is listed as a
species of special concern due to decreasing wetland habitat (Bannor and Kiviat
2002).

* Great Blue Heron. The great blue heron (Ardea herodias) is the largest and most
widespread heron in North America. It is a year round resident in Florida and is









found near calm freshwater or seacoasts. Its diet consists of fish, invertebrates,
amphibians, reptiles, birds, and small mammals. The great blue heron forages by
walking slowly, and stabbing prey with a quick lunge of the bill (Butler 1992).

* Glossy Ibis. The glossy ibis (Plegadisfalcinellus) is a dark, medium sized wading
bird with a down-curved bill. It is a year round resident in Florida (Davis and
Krither 2000). The glossy ibis probes mud to eat various aquatic prey. They also
eat small vertebrates, and occasionally vegetation. Birds will travel long distances
in response to water conditions that may hinder reproduction (Elphick et al. 2001).

* Great Egret. The great egret (Ardea alba) is a large white wading bird and second
largest in North America. The species is a year round resident in Florida. It feeds
in a variety of wetlands, including marshes, swamps, streams, rivers, ponds, lakes,
tide flats, canals and flooded fields. It eats fish, invertebrates, amphibians, reptiles,
birds and small mammals. The great egret captures prey by walking slowly, and
stabbing prey with its bill (McCrimmon et al. 2001).

* Green Heron. The green heron (Butorides virescens) is a small wading bird and a
year round resident bird in Florida. They forage in many wetland systems and eat
small fish, invertebrates, small frogs, insects and other small mammals. They
forage by standing still next to the waters edge and grab small fish with an
explosive dart of the head and neck. It is one of the few birds that use bait to attract
fish, it drops such things as bread crusts, insects, and twigs onto the water to lure
prey. They are fairly common and widespread although populations are hard to
census (Davis and Kushlan 1994).

* Little Blue Heron. The little blue heron (Egretta caerulea) is a medium sized
wading bird and a year round resident in Florida. It breeds and forages in various
wetland and estuarine habitats. It feeds on small fish, aquatic invertebrates, and
amphibians by foraging slow and methodically. The little blue heron is a Florida
designated species of special concern. Habitat loss and human-caused changes in
local water dynamics are the most serious threats to this species (Rodgers and
Smith 1995).

* Least Bittern. The least bittern (Ixobrychus exilis) is a cryptic, tiny wading bird
whose summer and year round range overlap in central Florida. It is found in
freshwater or brackish marshes which have tall emergent vegetation. The least
bittern forages near reeds, sometimes next to rather deep water, or climbs on reed
stalks, and strikes downward into water to get prey items such as small fish and
insects. They nest in dense tall stands of vegetation, particularly cattail. Their
conservation status is unknown because they are difficult to survey, however, loss
of wetland habitat and the encroachment of exotic species of marsh vegetation may
pose a threat to their numbers (Gibbs et al. 1990).

* Limpkin. The limpkin (Aramus guarauna) is a medium-sized wetland bird that
resembles herons and ibises in general form, but the limpkin is generally
considered to be more closely related to rails and cranes. Florida is the northern









limit of the breeding range of the limpkin and it is a year round resident there. In
Florida they are found in open freshwater marshes, swamp forests, and shores of
lakes, rivers, and ponds. They choose areas with stable water levels to nest
(Elphick et al. 2001). It feeds almost exclusively on apple snails, which it extracts
from their shells with its long bill. It forages by searching visually for snails in
clear water, or by jabbing or sweeping with bill. The limpkin is a Florida
designated Species of Special Concern, and they declined about 95% from 1966
to1993 (Bryan 2002).

* Purple Gallinule. The purple gallinule (Porphyrula martinica) is a medium sized
marsh bird, within the raillidae family, that breeds and lives in Florida year round.
They are found in freshwater wetlands which have dense floating leaf aquatic
vegetation. The purple gallinule eats seeds, flowers, fruits, grains and some
invertebrates (West and Hess 2002). The loss of suitable habitat is the greatest
threat to this species. This is usually due to flooding or droughts, changes in water
quality, erosion, pollution, pesticides, and dikes (Elphick et al. 2001).

* Ring-necked Duck. The ring-necked duck (Aythya collaris) is the most common
diving duck to be found on small ponds during migration. It is present in large
numbers on Florida lakes during the winter months (Hohman and Eberhardt 1998).
The exotic plant Hydrilla (Hydrilla verticillata) is a submerged plant favored as
food by the ring-necked duck, but the plant soon dominates native vegetation,
becoming extremely dense and reduces open water that the ducks need. As with
other migratory wetland species, the decrease in stopover habitat or wintering
habitat may have negative consequences for these species (Elphick 2001).

* Red-winged Blackbird. The red-winged blackbird (Agelaiusphoeniceus) is one of
the most abundant songbirds in North America and is found in wetlands and
agricultural lands year round in Florida. It feeds on insects, seeds and grain by
probing in vegetation, looking on the ground, or around vegetation (Yasukawa and
Searcy 1995).

* Florida Sandhill Crane. The Florida population of the sandhill crane (Grus
canadensispratensis) is a non-migratory species whose range spreads from
Okeefenokee Swamp, GA south to the Florida Everglades. This sandhill crane
species has been on the threatened species list since 1974 mostly due to its low
productivity, habitat degradation through wetland drainage and development and
direct human encroachment. The sandhill crane's small clutch size, low
recruitment rate, age at first breeding, and seasonal nesting result in a low
reproductive potential. Thus, sandhill cranes have a limited ability to rebound from
natural or human-induced catastrophes (Williams 1978). It inhabits a variety of
freshwater wetlands and uplands, including agricultural tracts, but is typically
restricted to open areas (Elphick et al. 2001). It feeds in open marshes or grain
fields and eats mostly grains and seeds, however it also eats small insects, other
invertebrates and small vertebrates. They typically feed by pecking at the ground
or probing the mud as they walk along (Tacha et al. 1992).









* Snowy Egret. The snowy egret (Egretta thula) is a medium sized white wading
bird which is a year round Florida resident (Parsons and Master 2000). They
occupy all types of wetlands and forage while standing and wading in water. They
primarily eat fish, but also amphibians, reptiles, and aquatic invertebrates (Elphick
et al. 2001). They are a Florida designated Species of Special Concern.

* Snail Kite. The snail kite (Rostrhamus sociabilisplumbeus) is a Federally
endangered raptor that inhabits flooded freshwater and shallow lakes in peninsular
Florida and Cuba (Sykes 1984, Sykes et al. 1995). The historical range of the snail
kite covered over 4000 km2 (2480 mi2) in Florida, including the panhandle region
(Sykes et al. 1995), but is now restricted mainly to the watersheds of the
Everglades, Lake Okeechobee, Loxahatchee Slough, the Kissimmee River, and the
Upper St. Johns River. These habitats exhibit considerable variation in their
physiographic and vegetative characteristics, and include graminoid marshes (wet
prairies, sloughs), cypress swamps, lake littoral shorelines, and even some highly
disturbed areas such as agricultural ditches or retention ponds (Bennetts and
Kitchens 1997). Three features that remain constant in the variety of selected
habitats are the presence of apple snails, areas of sparsely distributed emergent
vegetation (Sykes 1983, 1987), and suitable nesting substrates, all of which are
critical to the nesting and foraging success of the snail kite. Snail kites are dietary
specialists, feeding almost exclusively on one species of aquatic apple snail,
Pomacea paludosa (Sykes 1987, Sykes et al. 1995). Nearly continuous flooding of
wetlands for >1 year is needed to support apple snail populations that, in turn
sustain foraging by the snail kite (Sykes 1979, Beissinger 1988). Snail kites use
two visual foraging methods, either flying 1.5-10m above the water surface or
hunting from a perch (Sykes 1987) and both require open water or sparse
vegetation.

* Tricolored Heron. The tricolored heron (Egretta tricolor) is a medium sized
wading bird and a year round resident in Florida (Fredrick 1997). They forage in
water in wetland habitats and feed on aquatic invertebrates, fish, reptiles and
amphibians. They are listed in Florida as a species of special concern.

Distance Sampling Methods

Distance-sampling methods (Buckland et al. 2001), which account for variation in

detectability in counts of animals from lines or points, were used for both the study area

sampling (point transects) and whole lake sampling (line transects). The remainder of

this chapter will give a brief description of distance sampling and highlight some of the

methodologies used in conjunction with the program DISTANCE 5.0 (Thomas et al.

2005) to conduct this study and manage the data. These methods will include the









parametric models used, methods for dealing with groups of birds, truncation distances,

covariates examined within distance, and how density estimations were generated within

DISTANCE 5.0 (Thomas et al. 2005) and presented.

Assumptions of Distance Sampling

The aim of distance sampling is to obtain a "snapshot" estimate of animals'

presence around the survey line or point to calculate absolute density (Buckland et al.

2001). When using distance sampling, caution is taken to avoid violation of three

critical assumptions: (1) birds on the line or point are detected with certainty (2) birds are

detected before evasive movement triggered by the observer; and (3) distances are

estimated or measured accurately (Buckland et al. 2001). Distance sampling is based on

the detection function g(x) for line transects or g(r) for point transects. This function is

estimated from distance data and is used to compute probability of detection (p) for each

species. The detection function compensates for the fact that detectability decreases with

increasing distance from the observer. The probability of detecting a bird at any given

perpendicular distance varies according to numerous factors, such as environmental

conditions, differences among observers, and conspicuousness of the target species

(Burnham et al. 1980). The program DISTANCE 5.0 (Thomas et al. 2005) is set up so

that the resulting density estimates are not affected by those variations in detection

probability (Buckland et al. 2001). Models of g(y) (the detection function) are robust to

pooling if the data can be pooled over many factors which affect detection probability

and still yield a reliable estimate of density (Buckland et al. 2001).

Parametric Models within DISTANCE

The true detection function g(y) is not known in DISTANCE. The program

DISTANCE provides 4 parametric "key functions" for fitting the detection curve. When









incorporating covariates into the multiple covariates distance sampling (MCDS) analysis

engine in Distance, this number is reduced to two, the half-normal and hazard-rate key

functions. The series expansions used to fit the detection function along with the key

functions were cosine, simple polynomial, and hermite polynomial. Results from the

model with the lowest Akaike's Information Criterion (AIC) value were reported for each

species or group. If the AIC values were within two points of each other, I selected the

simpler model with the fewer number of parameters with better fit and precision.

Clusters within DISTANCE

The number of individuals in the program distance were entered as clusters; a

single individual was entered as a cluster of 1. This avoided the need to make and

analyze individuals because many times birds occurred in clusters and their detectability

was greater than that of a single bird. If a cluster of individuals was sighted, the observer

counted the number of individuals in the group and measured the distance to the center of

the cluster. The analyses of clusters in the program DISTANCE were based on exact

sizes. All clusters were analyzed using a regression of the log of cluster size against the

estimated detection function to estimate mean cluster size. However, in cases where

alpha <0.15, the mean cluster size was used. This reduced the coefficient of variation and

increased model fit during times of the year when there were few large clusters. This

transformation reduced the influence of a few large clusters on the estimation of density.

Data Truncation in Distance

Truncations to the data were done in most cases because large distances contribute

little to estimating the detection function but may lead to poor fit and high variance

(Buckland et al. 2001). Truncations within the data were made at the analysis phase

rather than in the field. Large wading birds often could be observed at > 500 meters. As









recommended by Buckland et al (2001), 5% of observations were truncated for line

transects and 10% for point transects. The percentage is increased for point transects due

to the fact that more detections are made further away during point transect surveys.

Truncation of the distance data deletes outliers and facilitates model fitting. In some

cases other truncation distances were used based on model fit.

Detection Covariates used within Distance

In conventional distance sampling (CDS) all analysis factors affecting

detectability, except distance, are ignored (Buckland et al 2001). In reality, many factors

affect detectability. Stratification reduces problems when modeling the detection

function, meaning a different detection function is obtained in each stratum, although

often times there are too few data for each stratum. Adding covariates to the detection

function is more parsimonious. Covariates are incorporated into the estimation of the

detection probabilities via the scale parameter. In this formulation, they are assumed to

affect the rate at which detectability decreases as a function of distance. (Marques and

Buckland 2003). DISTANCE can model the effect of numerical covariates and can

"share information" about detection function shape between covariate levels. Covariates

effecting detectability were examined in the analyses and again AIC was used to

determine if a model including a covariate was the best model. Specific covariates used

in the study area and whole lake sampling will be described in the following chapters.

Density estimations

When using distance sampling methods, an accurate measure of the sampled area

(in this case, littoral zone) is critical for density estimates. Within the littoral zone, this

study focuses on the area corresponding to the 1 4 foot depth zones as seen on the

bathymetric maps provided by ReMetrix (ReMetrix, LLC 2003) (Figure 2-4). The area on








the north end of the lake which corresponds to the developed shoreline of downtown
Kissimmee and adjacent housing developments was taken out of the calculation of the
total acres of these depth zones. The area of the depth zones corresponding to the 1-4 ft
depth zone in the undeveloped areas of the lake were calculated within ArcMap 9.0
(ESRI 2005) by converting many shape files corresponding to sections within the littoral
zone into a value for area (hectares). The entire littoral zone which I was interested was
selected and the total area was calculated. The area of littoral zone within the depth
zones was about 2,228 hectares (5,505 acres) of the total lake surface area. This also
corresponds to the value of mixed emergent vegetative species reported by ReMetrix
2003. The areas covered by our point transect survey study sites were 256 hectares (633
acres) and covered 11.4% of the 1-4 foot depth zone of the lake. The area of the lake
covered by our line transect surveys was 312 hectares (771 acres), which was 14% of the
total area possible in the littoral zone of the lake.



,..*,





/, ^





Figure 2-4. The 1-4 ft. depth zones on Lake Tohopekaliga corresponding to the area of
interest on the lake during the pre-lake enhancement studies are indicated in
dark green. The red areas are the study area point transect locations.














CHAPTER 3
AVIAN DENSITIES AND VARIABLES IN STUDY AREAS

Introduction
Point transect sampling was conducted within study areas as discussed in the

previous chapter, in order to look at future treatment effects. The data presented here

were collected prior to any lake-enhancement treatments in the study areas. Therefore no

comparisons within study areas will be made at this time. The specific project objectives

addressed in this chapter are 1) to estimate densities for focal species within the lake

littoral zone using point transect distance sampling, 2) to establish spatial variations

among study area locations based on density estimates for focal species, and 3) to

determine which environmental and temporal factors were affecting the densities of focal

species within the avian community .

Survey Methods

Bird Blinds. Point transect surveys were conducted from a priori placed bird

blinds. These moveable bird blinds provided a good vantage point from which to

conduct the point transect surveys. Three bird blinds were constructed from 1.5 inch

diameter aluminum piping with a 12 inch thick plywood platform measuring 55 cm by 53

cm. The platform sits roughly 6 feet above the marsh surface. Once the observer reaches

the blind, a camouflaged mesh was placed around the top of the blind to provide some

cover while conducting the survey (Figure 3-1).


























Figure 3-1. The bird blind setup for point transects on Lake Tohopekaliga.

Ideally, each blind location allowed effective detection of all birds within a radius of 50

meters, but this varied with distance at which 100% visibility could be achieved. In an

open wetland habitat comprised of a matrix of plant species, without upland tree species

present, the visibility around the point transect location in theory could be infinite.

However this does not equate to detectability. Sometimes visibility was less than 50

meters due to vegetation such as cattail, and other times the visibility was greater.

Because of the differences in visibility at each sample location, each location was unlike

the next as far as observers being able to detect bird species. These differences were

addressed in the analysis by using vegetation cover for each location as a covariate

(meaning that it influenced the ability of the observer to detect a species).

The blind locations were randomly selected for each sample occasion from a grid

of 32 possible locations within each study area with a stipulation that no two sequential

samples could be less than 200m apart. This avoided recounting birds in the same small

area over the sample period. The blinds were assembled and moved to the sampling

location the day before the survey to minimize disturbance to the area immediately before









the survey was conducted. Also, care was taken not to place the blinds to close to nesting

birds (snail kites, Florida sandhill cranes, etc.)

Observers and Sampling. The point transect surveys were initiated in January

2002, and the study areas were visited every other week (6 mornings a month) for two

years (Table A-i, Appendix A). If a sample was not conducted for some reason, then the

effort in the analysis indicates this, meaning that the effort is reduced in the analysis

stage. Before sunrise on the morning of the sampling, observers drove airboats to their

respective study areas and moored the boats far enough away from the blind to minimize

disturbance. From there, they used poke-boats (similar to kayaks) or walked to get to the

blind. If the area around the blind was disturbed before the survey, the survey was started

at least half an hour after the disturbance. Otherwise, surveys usually started within the

first hours of light, with precise start time dependent on the logistics of getting to each

individual blind location. All three observers, located at the three different study areas,

used 2-way radios to start the survey simultaneously. The observers surveyed the

respective areas from the point location for 2 hours, turning north or south every 10

minutes and recording birds within a 180 degree viewing radius.

During the sample, observers recorded individual birds, those clustered by species

in tight groups, distance from the blind, behavior of the bird (flying or stationary),

vegetation within a 50 meter radius around the blind, and visibility in each quadrant (NE,

NW, SE, SW) around the blind. Each observer used Bausch and Lomb 10 x 42 Elite

binoculars. They also used a Bausch and Lomb Elite spotting scope with power of 20-60

mm focal length zoom with an objective diameter of 70 mm to identify birds in thick

vegetation or to identifying birds at greater distances. In order to accurately measure









distances to each bird, each observer used a Bushnell Yardage Pro Scout Rangefinder,

which measured distances in 2 meter increments up to 800 meters (2,624 ft). To aide in

identification of rare or difficult species, observers referred to the National Geographic's

Field Guide to Birds of North America (Dunn 1999).

Analysis Methods

Densities

Densities were estimated with the program DISTANCE 5.0 (Thomas et al. 2005)

using only stationary birds seen within the first hour of each sample. To reduce the

chance of double-counting individuals, which would violate assumptions of distance

sampling. Preliminary analysis indicated an hour was an effective duration for each

sample. Species-level density estimates were obtained for the focal species discussed in

Chapter 2.

Covariates. The covariates that were tested with each species analysis included:

study area, observer, season, vegetation structure, stage, and combinations of the five. To

investigate the potential effects of the various covariates, I adopted the stepwise approach

outlined in Marques and Buckland 2003 to determine the most parsimonious model.

Observer. Using observer as a covariate led to problems in the analysis due to

some observers having few detections for certain species of interest. Spanning the two

year study, nine different observers were used on a bi-weekly basis. In order to look at

observer effect on detectability, observers were placed into three observer detection

groups based on bird identification experience, length of time working on the project, and

individual survey methodologies each observer employed when dealing with recording

multiple species bird surveys. This proved to be a good method as observer strata was a

covariate in many of the models chosen.









Vegetation Structure. At each point location sampled, vegetation cover was

recorded within a 50 meter radius of the bird blind. The vegetation data included 38

species. These species were placed into 4 vegetation classes based on height, cover, and

associations with other species (Welch 2004). The four vegetation groups were

associated with openness of the habitat and were indicative of water cover of (25% -

100%). A cover estimate was obtained for each sample location every time it was

sampled. Higher percentages indicate more open water associated with vegetation

communities. For analyses in DISTANCE, these values were rounded and placed into 6

'vegetation-strata' groups.

Spatial Variations

Overall density estimates of focal species were examined on a site specific basis

(corresponding to three study areas), to examine spatial effects on the lake. The true

value of differences in densities referred to as effect size (ES) was computed to determine

if there were study area specific differences for each species (Alisauska and Lindberg

2002). The effect size of the differences in estimated densities between two sites is

calculated as the square root of the variances of the estimated densities minus twice the

covariance. For this analysis, I assumed no covariance, which means that I are assumed

independence among study area locations. By making this assumption, I overestimated

the confidence intervals, which led to a conservative size estimate. I assumed that if

there was a significant difference in density estimates between sites, then the confidence

interval would not overlap zero. If the confidence interval overlapped zero, then there

was no difference. These analyses identified species requiring analyses by specific study

area, and those that could be analyzed at the scale of the whole lake. Density estimates









were generated by study area for those species that had a significant difference in density

estimates between sites.

Temporal and Environmental Variations

Environmental variations due to temporal changes as defined by 'avian season'

were used to describe temporal changes affecting focal species densities within the

littoral zone of the lake. Patterns of bird movements can be attributed to water regimes

and climatic factors (Weller 1999). These movements include stopover patterns, non-

directional nomadic movements, and permanent residency. Using this example to

describe bird movements, the data analysis was divided by seasons corresponding to such

movements seen on Lake Toho. These seasons included breeding (B), summer (S) and

winter (W). In this study, the breeding season was defined as March June. The

summer season was July October. The winter season was November February. This

is a general grouping used to look at seasonal effects on bird density estimates. In

Florida, environmental conditions within each season may be highly variable. Due to

these possible differences between years, analysis was conducted by the following

specific seasons: W02 = Jan '02 Feb '02; B02 = Mar '02 Jun '02; S02 = July '02 -

Oct '02, W0203 = Nov '02 Feb '03, B03 = Mar '03 Jun '03, S03 = July '03 Oct

'03, W03 = Nov '03 Dec '03.

Bi-weekly density estimates for the focal species were analyzed to determine how

season and any other environmental variables were causing shifts in avian densities on

the lake. I tested predictor variables for density using the generalized linear model

function in the program R (R 2004), were tested. A Gaussian distribution was assumed

and avian season was introduced into the model as a categorical variable, hence creating

an ANCOVA analysis. The linear predictors for the density estimates included lake









stage, water fluctuation, rate of water fluctuation, vegetation structure, average air

temperature (described in the section to follow). A categorical predictor for stage and

water movement was included in the model.

In order to test which environmental variables were affecting the densities of focal

species on the lake, apriori predictions were generated based on avian life history traits.

Some focal species nest on the lake and many are Florida residents, factors that

influenced predictions (Table 3-1). The species-specific predictors were tested with the

program R (R 2004). To determine which environmental variables influenced bird

densities on the lake and how they interacted, interaction effects of the variables were

examined in addition to additive effects.

I predicted that season would be an important variable for at migratory species and

included it in the full predictor model for those species in the initial analysis. For

resident species, other chosen environmental variables were tested in the model and

season was added last. Once the full model of all the possible predictors was tested, the

model was reduced using AIC (as well as looking at the predictors within each model and

their significance) to choose the most parsimonious model, if one existed. Akaike's

information criterion (AIC), which is the fit of the model plus two times the number of

parameters used in the model, was used to determine the most parsimonious model. The

predictor with the lowest AIC value and >2 away from the next closest predictor was

chosen.

Lake Stage. Lake stages were obtained from the gage station located at S_61

spillway headwater on canal C-35 at lake Tohopekaliga. Hydrologic data were

downloaded from the South Florida Water Management District DBHYDRO website










(http://www.sfwmd.gov/org/ema/dbhydro/). Lake stage is reported in FT NGVD 29 and

was converted into meters for all analyses. Lake stage corresponding to days of point

transect sampling was averaged for the each week of sample.

Table 3-1. Table of predictions indicate focal species that are year round Florida
residents as well as species which nest in the littoral zone of Lake Toho.
Predictions indicating which environmental variables are driving the densities
of each species are listed. These include Lake Stage (S), Average air
temperature (T), vegetation structure (V), rate of water fluctuation per day
(R), water level fluctuation (F), and the categorical variable, water movement
(W).


C'l nioii Nanic
American Coot
Anhinga
Belted Kingfisher
Boat-tailed Grackle
Cattle Egret
Common Moorhen
Great Blue Heron
Glossy Ibis
Great Egret
Green Heron
Little Blue Heron
Least Bittern
Limpkin
Purple Gallinule
Ring-necked Duck
Red-winged Blackbird
Florida Sandhill Crane
Snowy Egret
Snail Kite
Tricolored Heron


Scientific Namni
Fulica atra
Anhinga anhinga
Ceryle alcyon
Quiscalus major
Bubulcus ibis
Gallinula chloripus
Ardea herodias
Plegadis falcinellus
Ardea alba
Butorides virescens
Egretta caerulea
Ixobrychus exilis
Aramus guarauna
Porphyrula martinica
Aythya collaris
Agelaius phoeniceus
Grus canadensis pratensis
Egretta thula
Rostrhamus socialbilis plumbeus
Egretta tricolor


Water Fluctuation and Rate. Water fluctuations on the lake were examined in

order to determine how water levels may be affecting bird densities present on the lake.

Using the stage data, a graph was produced to indicate changes associated with the

releasing and re-flooding of water by management schedules. The time period from the

start to the end of a particular drop or rise in water level on the lake was recorded. Rate

of water level fluctuation is the rate (cm/day) that the lake stage is increasing or


Ncil on
L.ik
N


Species
AMCO
ANHI
BEKI
BTGR
CAEG
COMO
GBHE
GLIB
GREG
GRHE
LBHE
LEBI
LIMP
PUGA
RNDU
RWBL
SACR
SNEG
SNKI
TRHE


FL
Rcsidcnii
N
Y
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
Y
Y
Y
Y
Y


PredictionI
S,T,V,W
S,T,V,W
S,T,V,W
S,T,W
S,R
S,R,F,W
S,R,F,W
S,R,F,W
S,R,F,W
S,V,R,W
S,R,F,W
S,V,W
S,V,F,W
S,F,T,W
S,T,V,W
S,T,V,W
S,T,W
S,R,F,W
S,V,F,W
S,R,F,W









decreasing over the period of time recorded. Water fluctuation was calculated by looking

at water fluctuation during the sample plus the two days prior to the sample. The

categorical variable called water movement is the letter 'S' representing stationary lake

stage, 'I' for increasing lake stage, or 'D' for decreasing lake stage levels at that point in

time.

Vegetation Structure. The values for vegetation structure were obtained in the

same manner as detailed in the Distance Analysis Methods section. Vegetation cover

was averaged for the study area locations for the sample week.

Average Air Temperature. The values for average temperature were obtained

from the NOAA National Climatic Data Center via their website

(http://www.ncdc.noaa.gov/oa/ncdc.html). The data recorded at the weather station

located at the Orlando International Airport (MCO) were used in analyses. Average daily

air temperature (dry bulb) was reported in degrees Fahrenheit and was converted to

Celsius. Average daily temperature for the sample week was used in the analyses.

Results

There were 98 avian species identified within the study areas prior to lake

enhancement activities (Table B-l, Appendix B). Density estimates (birds per hectare)

for the focal species per week of sample, are listed in Table C-l in Appendix C. The

distance sampling analyses model parameters corresponding to these estimates can be

found in Table D-l in Appendix D.

Spatial Variations

Comparisons between the three study sites yielded significant differences for all

species except the great egret, least bittern, purple gallinule, and ring-necked duck.

These species will be the reference set for the pre-enhancement estimates when using the










three study areas as replicates. The estimated densities by study area are listed in Table

C-2 in Appendix C. The differences in density estimates between study area 1 and study

area 2 were significant for many species (Table 3-2) including the great blue heron and

green heron, which had significantly greater densities within study area 2 (Figures 3-2 -

3-3). When comparing study area 1 with study area 3, the differences were significantly

different for many species (Table 3-3), however, only two species, the limpkin and

Florida sandhill crane, had greater density estimates at study area 3 (Figures 3-4 3-5).

Significant differences in species density estimates between study area 2 and study area 3

are listed in Table 3-4. The true values of the differences in densities between study

areas 2 and 3 yielded the least number of species having significant differences (Figure 3-

6- 3-7).

Table 3-2. Focal species with significant differences between density estimates for study
areas 1 and 2. Birds are listed under the study area with the greater density
estimate.

Study Area 1 Study Area 2 No Significant Difference
Great Blue
American Coot Heron Anhinga
Boat-tailed Grackle Green Heron Belted Kingfisher
Cattle Egret Great Egret
Common Moorhen Least Bittern
Glossy Ibis Limpkin
Little Blue Heron Purple Gallinule
Red-winged Blackbird Ring-necked Duck
Snail Kite FL Sandhill Crane
Tricolored Heron Snowy Earet







41







S0.4 -
TO
E
U)
>, 0.2 I










-0.4
a)

Study Area 2
I 1










T- U) E
ic i i i i i i i i i iW i





S- 0. 0



Focal Species
Figure 3-2. The value of differences in estimated densities between study area 1 and
study area 2 for focal bird species. Upper and lower 95% confidence
intervals which do not cross 0 are indicated as significant (*).
< D"^ D s- 'C-
a ,^s
I
CDaII
Foa pce
Fgr3-02.Tevleodifrneinetmtddniesbtensuyaa1ad
std ra2frfclbr pce.Upradlwr9%cniec
inevl hc ontcos0ar niae ssgiiat()









































Focal Species
Figure 3-3. The value of differences in estimated densities between study area 1 and
study area 2 for focal species. Upper and lower 95% confidence intervals
which do not cross 0 are indicated as significant (*).

Table 3-3. Bird species with significant differences between density estimates for study
areas 1 and 3. Birds are listed under the study area with the greater density
estimate.


Study Area 1
American Coot
Boat-tailed Grackle
Belted Kingfisher
Common Moorhen
Little Blue Heron
Snowy Egret
Snail Kite


Study Area 3
Limpkin
FL Sandhill Crane


No Significant Difference
Anhinga
Cattle Egret
Great Blue Heron
Glossy Ibis
Great Egret
Green Heron
Least Bittern
Purple Gallinule
Ring-necked Duck
Red-winQed Blackbird


Study Area 1














Study Area 2


















1.0

Ul)
E
2
Uo
S0.5



S0.0




-0.5



-1.0


ro ~ ~ ~ ~ l *c 00C C 0j ~ 0C


lM 0l) 3 o I
0 IIB *I W -

u 0
2' U' .
CD (I 'I 0
C, ,


Focal Species
Figure 3-4. The value of differences in estimated densities between study area 1 and
study area 3 for select bird species. Upper and lower 95% confidence
intervals which do not cross 0 are indicated as significant (*).


20


S15


10
C

.c 5





-5
J -5


Study Area 1














Study Area 3



M 0

EE E


Co-


Focal Species
Figure 3-5. The value of differences in estimated densities (effect size) between study
area 1 and study area 3 for select bird species. Upper and lower 95%
confidence intervals which do not cross 0 are indicated as significant (*).







44


Table 3-4. Bird species with significant differences between density estimates for study
areas 2 and 3. Birds are listed under the study area with the greater density
estimate.
Study Area 2 Study Area 3 No Significant Difference
Belted Kingfisher Glossy Ibis American Coot
Great Blue Heron Limpkin Anhinga
Green Heron FL Sandhill Crane Boat-tailed Grackle
Snowy Egret Red-winged Blackbird Cattle Egret
Common Moorhen Great Egret
Little Blue Heron
Least Bittern
Purple Gallinule
Ring-necked Duck
Snail Kite
Tricolored Heron


I 0.4 Study Area 2

N 0.2




_ -0.2 -




" -0.6 -
t-

2 -0.6


O-0.8
> Study Area 3

-1.0


D) 0
a o)

C O
0 (


- IIa
0 0

0(9 -_
_j


Focal Species
Figure 3-6. The value of differences in estimated densities between study area 2 and
study area 3 for select bird species. Upper and lower 95% confidence
intervals which do not cross 0 are indicated as significant (*).












5


uJ
E 0
C
S-5



-10
C:
V -10


0
c,

D
M-
o

= -20


-25


Focal Species
Figure 3-7. The value of differences in estimated densities between study area 2 and
study area 3 for select bird species. Upper and lower 95% confidence
intervals which do not cross 0 are indicated as significant (*).

Environmental and Temporal Variables

The results of the generalized liner model can be found in Table E-1 in Appendix

E. The most parsimonious model for density estimation of focal species appears in Table

3-5. Season was the only environmental variable associated with the densities of the four

species that had no spatial variation between the study areas: the great egret, least bittern,

purple gallinule, and ring-necked duck. The model including the linear predictor, 'stage',

explained the differences in density estimates for species that are common and year round

residents on the lake,


Study Area 2













Study Area 3


Study Area 3










Table 3-5. Results of the generalized linear model analysis and the most parsimonious
model indicating which environmental or temporal variables influence density
estimates for focal species. The four species which were spatially the same
within the study areas is indicated with a (*).
Species Variable
American Coot Season + Stage
Anhinga Season
Belted Kingfisher Season Stage
Boat-tailed Grackle Season
Cattle Egret None
Common Moorhen Stage
Glossy Ibis Stage
Great Blue Heron Stage
Great Egret* Season
Green Heron Season + Water
Little Blue Heron None
Least Bittern* Season
Limpkin Stage
Purple Gallinule* None
Ring-necked Duck* Season
Red-winged Blackbird Season
Florida Sandhill Crane None
Snowy Egret Season
Snail Kite Season
Tricolored Heron Season

including the common moorhen, great blue heron, glossy ibis and limpkin. The great

blue heron was present during every sample on the lake, and the estimated densities have

a positive correlation with stage at study areas 1 and 2 (Figure 3-8). The common

moorhen density estimates are positively correlated with stage at study area 1 (Figure 3-

9). The limpkin densities are positively correlated with stage for all three sites combined

until the lake stage is greater than 54.5 ft NGVD (Figure 3-10). At study area 1, the

glossy ibis density estimates are positively correlated with lake stage until it reaches 54.5

ft NGVD (Figure 3-11). Densities of American coots are positively correlated with stage

and winter season (p = 0.022825) (Figure 3-12). The interaction effect of season and

stage explained the density estimates of the belted kingfisher as they were present on the

lake only during late summer and early winter seasons (p=0.0026) (Figure 3-13).







47





-D 120
C
o
N StudyArea 1
100 Study Area 2
2 A Study Area 3

0 80


60-


40
40 -
C
-o 20


n 0
LI.


o io O iO o iN
I I I I I I
Lq O Lq O Lq O
LO LO LO LO LO LO



Lake Stage (ft NGVD)
Figure 3-8. Estimated densities for the great blue heron within the lake littoral zone
related to study area and lake stage. The error bars correspond to 95%
confidence intervals. The mean value is the pooled estimated density derived
from effort-weighed stage estimates.







48





I 3500
o
N U Study Area 1
3000 Study Area 2
SA Study Area 3
0 2500

2000

E 1500

I 1000 -
C

500 -


LU 0-0


O Lf o L o L-
LO1 CO CO N CU
LO LO LO LO LO LO

U)o U ci CM Ci
't O CO MO N ON
LO LO LO LO LO LO


Lake Stage (ft NGVD)

Figure 3-9. Estimated densities for the common moorhen within the lake littoral zone
related to study area and lake stage. The error bars correspond to 95%
confidence intervals. The mean value is the pooled estimated density derived
from effort-weighed stage estimates.







49





50
C
o
N

3 40


CU
30


S20






I I I I I
10 o-







O LO o 10 o 10 c

L r c\.i


Lake Stage (ft NGVD)
Figure 3-10. Estimated densities for the limpkin within the lake littoral zone related to
lake stage. Bird numbers were too few to generate density estimates by site
and stage. The error bars correspond to 95% confidence intervals. The mean
value is the pooled estimated density derived from effort-weighed stage
estimates.












200



150 -



100 -



50 -



0-


Lake Stage (ft NGVD)
Figure 3-11. Estimated densities for the glossy ibis within the lake littoral zone related to
study area and lake stage. The error bars correspond to 95% confidence
intervals. The mean value is the pooled estimated density derived from effort-
weighed stage estimates.


* Study Area 1
* Study Area 2
A Study Area 3







51





1800
c U Study Area 1
o 1600 -
N 1600 Study Area 2
1400 Study Area 3
1400 -

o 1200

1000

.l 800 -

Z' 600 -

C) 400 -I
"o


0 0


o L0 0 L0 L C
LO LO LO LO LOa

CO CO ON
LO LO LO LO LO

Lake Stage (ft NGVD)
Figure 3-12. Estimated densities for the American coot during the winter season within
the lake littoral zone related to study area and lake stage. The error bars
correspond to 95% confidence intervals. The mean value is the pooled
estimated density derived from effort-weighed stage estimates.
lill10101








estimated density derived from effort-weighed stage estimates.







52





S350
C
o 3 Study Area 1
N 300
300 Study Area 2
o A Study Area 3
S250

200

150-

C 100 I
D
0 50-
Cu
Ei


o Lq o Lq Lq r
I I I I I 2

't CO CO ON
LO LO LO LO LO

Lake Stage (ft NGVD)
Figure 3-13. Estimated densities for the belted kingfisher during the summer and winter
season within the lake littoral zone related to study area and lake stage. The
error bars correspond to 95% confidence intervals. The mean value is the
pooled estimated density derived from effort-weighed stage estimates.

The predictor variable season, alone, explained the variations seen in the estimated

densities of the anhinga, boat-tailed grackle, great egret, ring-necked duck, least bittern,

red-winged blackbird, snowy egret, tricolored heron and snail kite.

The densities of anhinga increased during the summer and winter seasons (p =

0.0460 and p = 0.0460 respectively) (Figure 3-14). Estimated densities, for the boat-

tailed grackle, although fairly consistent throughout the year at study areas 2 and 3,

increased during the breeding and summer seasons at study area 1 (Figure 3-15). The

estimated densities of the great egret within the littoral zone of the lake were slightly

lower during the breeding season, but consistent throughout the rest of the year (Figure 3-







53


16). The ring-necked duck, a migratory species, had greater densities during the first

winter sampling season 2002 (p = 0.0001) (Figure 3-17). The least bittern was present on

the lake during breeding and summer seasons and the density estimates were consistent

throughout these seasons (Figure 3-18). The snowy egret and tricolored heron both

showed dramatic increases in density estimated during the summer 2002 season leading

into the winter 2002-2003 season on the lake (Figure 3-19 and Figure 3-20). The density

estimates for the snail kite were explained by the breeding season on the lake. Although

stage was not determined to be a predictor variable for kite densities, it appears to be

positively correlated to snail kite density estimated within the littoral zone of the lake.



i 500
0
o
N U Study Area 1
FU 0 Study Area 2
2 400 A Study Area 3


S300



200

E
.E 100


c 0
i I iI i I i i

0) C CO C CO CO CO
O O 0 0 0 0
) 0 E N
^ r r E a) ( 0
o o E E .E
m 1 C/ ) E E -
m m 09) ) <

Season of Sample
Figure 3-14. Estimated densities for the anhinga within the lake littoral zone related to
study area and season. The error bars correspond to 95% confidence intervals.







54


The estimated densities associated with breeding, summer and winter are
estimated independent of year.



30000
C
No Study Area 1
25000 0 Study Area 2
0 A Study Area 3

c 20000


15000


E 10000 -





0 I I I I I I I I
5000 i



C C CO C CO O CO
c ) E i Co
c : E E a o
SU o ) E E -

m m c9) 9 )


Season of Sample
Figure 3-15. Estimated densities for the boat-tailed grackle within the lake littoral zone
related to study area and season. The error bars correspond to 95%
confidence intervals. The estimated densities associated with breeding,
summer and winter are estimated independent of year.













25

C
N
E 20 -
2o

(0

-7 15



10 1


( T


(D
LI.I
C)


C O O 0 0 0 0
0) 0) E C%4
T rn -- ^ 1- 1- o u0
m 0 E E

m m E E


Season of Sample
Figure 3-16. Estimated densities for the great egret within the lake littoral zone related to
season. The error bars correspond to 95% confidence intervals. The
estimated densities associated with breeding, summer and winter are estimated
independent of year.







56





350
o
0
N
300


S250


200


S 150
Cu
E


S100- I
S 50


00
SCM CO CO
o o o






Season of Sample
Figure 3-17. Estimated densities for the ring-necked duck during the winter seasons
within the lake littoral zone. Bird numbers were too few to generate density
estimates for study area by season. The error bars correspond to 95%
confidence intervals. The estimated densities associated with winter are
estimated independent of year.







57





35
C
N
S30 -
30

25
D 25 -


S20 -







5u-
n

S15 -





10
5 1 1






( D E E
Cm E E
1 m m E)



Season of Sample
Figure 3-18. Estimated densities for the least bittern during the breeding and summer
seasons within the lake littoral zone. The error bars correspond to 95%
confidence intervals. The estimated densities associated with breeding and
summer are estimated independent of year.






58




3000

o U Study Area 1
N 2500 Study Area 2


a3 2000

1500



E
S500





,0 0 ) E o
o g E E r
r a, a, 0") E E ._
E E
m m a) a)

Season of Sample
Figure 3-19. Estimated densities for the snowy egret within the lake littoral zone related
to study area and season. Bird numbers were too few to generate density
estimates for study area 3 by season. The error bars correspond to 95%
confidence intervals. The estimated densities associated with breeding,
summer and winter are estimated independent of year.







59





140

c U Study Area 1
o 120 Study Area 2
-" A Study Area 3
0 100

U 80

S60-

S40
C
o 20-
0-



C C O CO CO CO





Season of Sample
Figure 3-20. Estimated densities for the tricolored heron within the lake littoral zone
related to study area and season. The error bars correspond to 95%
confidence intervals. The estimated densities associated with breeding,
summer and winter are estimated independent of year.







60





0 80
0
N
S70 -
0
60 -
CU
50

40

30 -


CL
U 20

E
0 10


o Lo o Lq o L -

LO L LO LO LO L 0
I I I I 10 102

LO LO LO LO LO LO

Lake Stage (ft NGVD)
Figure 3-21. Estimated densities for the snail kite within the lake littoral zone related to
lake stage. Bird numbers were too few to generate density estimates by
season and study area. The error bars correspond to 95% confidence intervals.
The mean value is the pooled estimated density derived from effort weighed
stage estimates.


The green heron densities are best explained by the additive effect of season and

the categorical variable water movement. Density estimates for the green heron were

greatest during breeding season 2003 when the water was stationary for a few weeks

following a dramatic decrease in the lake level (Figure 3-21). A few species didn't have

any predictor variables that were significant: the cattle egret, little blue heron, Florida

sandhill crane, and purple gallinule.







61




500
0
N
| 400


300





E 100

C


Q

0) CM CO CN CIO cCO CIO
C: 0 0 0 0 0 0
S3 3 -
)E ai) 0**
m r E E-

m m ca) a)
Season of Sample
Figure 3-22. Estimated densities for the green heron within the lake littoral zone related
to season. Bird numbers were too few to generate density estimates for study
area by season. The error bars correspond to 95% confidence intervals. The
estimated densities associated with breeding, summer and winter are estimated
independent of year.

Discussion

Spatial Variations

The littoral zone on Lake Toho is highly variable in wave action, slope, shoreline

use, and vegetation communities. The three study areas were designated along different

shorelines on the lake as replicates; these areas have similar slopes, an absence of

physical differences, stream outflows and topography changes. These areas also covered

the same distance of 1,600 m (approx 1 mile of shoreline). Their lakeward extent from

the shoreline was delimited by the approximate maximum water depth to be mechanically









scraped during a dry down and extended just beyond the deep water extent of the

Pontederia community (Welch 2004). Based on our results we can conclude that there

are differences between study areas, based on bird density estimates for each focal

species. There are many spatial variations that influence densities of focal species

between the three study areas.

Avian species and their usage of different vegetation communities at different lake

stages may explain some study area differences. Vegetation communities within the

littoral zone are the same between study areas. However, the locations of these

communities in relation to water depth varies among the study areas. For example, the

deep water communities (water depths of 46 in 62 in.) within study area one are

composed ofHydrilla verticillata (hydrilla), Lymnobium spongia (frog's bit), and

Ceratophyllum (coontail) while the deep water habitats of study area two and three lie

within the Pontedaria cordata (pickerel weed), and Alternantheraphiloxeroides

(alligator weed) vegetation community, which also includes Typha (cattail) (Welch

2004). The greater proportion of submersed aquatics found at study area one is the

forage base for the higher densities of the American coots found there. The estimated

densities of the endangered snail kite were greatest at study area one due to shallow less

dense vegetation communities to forage expanding lakeward to expansive stretches of

Typha in which they nest. This study area is also located just south of a large historical

snail kite nesting and foraging area (near Brown's point).

The Pontedaria vegetative community is broader in study area 3 and dominated

twice as many vegetation samples as in study area one or two in the vegetative pre-lake

enhancement study (Welch 2004). Red-winged blackbirds prefer this type of habitat to









forage and nest in smaller Typha clumps on the edges of this dense vegetation. The

green heron usually was found in dense vegetation and nests in thick stretches of Typha

during the breeding season at study area two. The shallow littoral habitat along the

grazed shorelines of study area one and three was dominated by the Luziola gluitans

(watergrass) community and this community was proportionately greater at study area

one in shallow water depths (Welch 2004). This vegetative community may explain the

densities of medium sized wading birds such as the little blue and tricolored heron. In

addition to the study areas varying in proportions of vegetative communities, they also

had spatial differences.

The study areas are located along different shorelines of the lake (Figure 2-1).

Study area one is subject to high wave action given its location and the predominant wind

direction. Study area two is located on a very sheltered shoreline. Study area three is

located in a cove directly across from the C-31 input canal from East Lake Tohopekaliga.

We were not able to measure elevation differences between the three study areas;

however this may have been a factor influencing how long water stayed in the littoral

zone at different lake stages and seasons. Although vegetative and spatial characteristics

influence avian communities present at the study areas, possibly more important is the

characteristics of the littoral zone in relation to its surrounding features.

The three study areas have major structural differences at the upland boundary

(land-inland water ecotne). In study area three, the one foot depth zone expands into an

extensive ecotone that is flooded at different lake stages. This vegetated zone then

becomes upland pasture land which meets the trees which are about 500 800 meters

(1,640 -2,625 ft) away. Study area one has the same upland boundary, except the trees









are about 200 meters closer to the littoral zone than at study area 3. Many birds use this

flooded ecotone for foraging and some use it for nesting. For example, birds, such as the

Florida sandhill crane will nest and forage in this expansive ecotone bordering study area

three because of the ideal shallow to dry foraging habitat located there. Also, with the

presence of pasture lands and cattle at both study area one and three, the densities of

cattle egrets are greater there than at study area two. The glossy ibis, forages in smaller

groups and prefers the expansive shallow littoral zone to forage as well.

In contrast, the littoral zone at study area two extends into the trees, without the

presence of expansive pasture land, creating a swamp habitat at different times during the

year, when the stage is high enough. In study area two the distance to the tree line from

the littoral zone is less than 100 meters (328 ft). This unique characteristic of study area

two attracted a few species different from than the other study areas. Some of the focal

species that preferred study area two are birds that forage in wetlands near swamp

habitats. The great blue heron typically nests in trees near water (Butler 1992) and

nesting activity was observed near study area two. Another species that uses the trees is

the belted kingfisher, which forages from either a perch or by hovering and diving for

prey (Hamas 1994). The snowy egret may have been more common at study area two

because of the cover of the tree line for protection against predators since they are white

in color and are usually solitary feeders. The differences in the upland edge habitat and

other study area characteristics influenced the densities of all but four focal species at

each study area. This knowledge combined with the temporal and environmental

variables that affect avian densities on the lake will create the baseline data that will be

used to compare densities following the lake enhancement.









The density estimates for four species, the least bittern, great egret, purple gallinule

and ring-necked duck were not significantly different among study areas. The ring-

necked duck, which primarily feeds on the submersed Hydrilla is more associated with

open water habitats around the edge of the littoral zone that were equally distributed and

positioned among three study areas. Species richness for the floating leaf aquatic

vegetation communities, on which the purple gallinule typically forages, was higher for

this community than any other in the littoral zone on the lake with the exception of the

grassy communities (Welch 2004). This is due to the ability of the floating leaf aquatic

group to grow within a broad range of vegetative communities. Least bitterns forage and

nest in monospecific strands of Typha. The Typha vegetation community had the lowest

species richness on the lake creating the habitat preferred by the least bittern (Welch

2004). The large wading bird, the great egret, is opportunistic and will forage in almost

any wetland vegetative community (McCrimmon et al. 2001). The great egret has a

larger range than any other heron, which is related to the fact that it has access to a

variety of deeper water habitats. These four species will be important when comparing

the lake before and after enhancement because their distribution within the littoral zone

was the same within our study areas. The following section will address the

environmental factors which are influencing the densities of these four key species.

Temporal and Environmental Variations

Lake Water Levels. Water can be used by birds for drinking, bathing, courtship,

and escape from predators. Most importantly, water is an attractant for birds as a source

of suitable foods (Weller 1999). Water depth and fluctuation can create different habitats

suitable for many different avian species throughout the year (Weller 1999). At









extremely high lake stages, areas of the lake littoral zone may be one continuous pool and

prey items may be harder to capture for some foraging birds (Kushlan 1981).

The majority of wading birds require shallow water (less than 25 cm for great egret

and great blue heron and less than 15 cm for smaller herons) to forage successfully

(Custer and Osborne 1978). On Lake Toho, due to floating vegetative mats, many avian

species are able to forage the entire extent of the littoral zone by perching on floating

mats in deeper water rather than being restricted to the waters edge. This is most likely

the reason why lake stage was not influencing the densities of the medium sized wading

birds, such as the tricolored heron, snowy egret, and little blue heron, all which forage

from floating mats in addition to the shallows. Densities for the large wading bird, the

great blue heron, were positively correlated with lake stage. The reason the densities of

the great blue heron were strongly associated with stage while those of the other large

wading bird, the great egret were not is because the great egret leaves the lake during

breeding season. Season, therefore, was the strongest predictor for density of the great

egret. However, densities of a medium sized wading bird, the limpkin were negatively

correlated with lake stage deeper than 54.5 ft NGVD. In the case of the limpkin, which

feeds almost exclusively on aquatic apple snails (Pomaceapaludosa), this trend may be

due to the flooding of apple snail eggs during late spring and early summer, which would

decrease the food base for the limpkin within the littoral zone. The glossy ibis forages

on the lake edge in the open shallow habitat and in general its density is constant except

at study area one when more areas are inundated at lake stages of 54 54.5 ft NGVD.

The densities of the marsh birds, the common moorhen and American coot, at study

area one were positively correlated with lake stage. Study area one has an expansive









littoral zone extending deeper than the study area sampling boundaries. At deeper stages,

marsh birds would have increased access to all of these deep water vegetated areas.

Differences in elevation between study areas may cause them to flood at different rates.

The densities of the belted kingfisher were also positively correlated with lake stage.

Prey items may have been easier to obtain in the shallow flooded habitats.

Although lake stage did not play a critical role in the densities of many of the focal

species, the new littoral habitat created by the enhancement may be more prone to effects

of increased lake stage levels and wave action. The four key species that did not differ

spatially prior to lake enhancement, the great egret, least bittern, purple gallinule and

ring-necked duck, were not affected by lake stage. Without the dense stands of

vegetation to shield the littoral habitat from wave action and without the floating mats of

vegetation providing optimal foraging locations within the littoral zone at deeper lake

stages, lake stage may be more of an influence on avian densities after the lake

enhancement.

Lake water level fluctuation and daily rate of change were not significant predictors

for any of the focal species, although water movement as a categorical variable was for

one species. Measuring these variables and their effects on different species is a

challenge in avian research. Species react differently to water levels during the breeding

season and these levels and rate of fluctuation different annually. Also, each species has

different tolerances for water level fluctuation and rates based on physiology, foraging

methods, and prey availability. For example, our results indicated that during breeding

season 2003, the green heron was influenced by water movement and had increased

densities during a period of time when the water was stable. During that particular









breeding season, from late March into mid April, water was decreasing at a rate of about

2 cm/day, overall decreasing about 50 cm (20 in), from 54.83 52.79 ft NGVD before

the water level was stable again. As soon as the water level stabilized following this

drastic decrease in water, the densities of green herons increased significantly. Looking

at the breeding season 2002 during the same time period there were almost no green

herons. During this breeding season, however the rate of water level fluctuation was

never more than 1 cm/day, however the water never stabilized during the whole breeding

season. It continued to decrease.

The opposite trend was seen for two other nesting species on the lake, although

statistical differences were not significant. The snail kite, during this same time period,

breeding season 2002, was nesting and their densities were decreasing weekly with water

level. However, in 2003, the densities for the snail kite overall were lower than the 2002

season due to a quick drop in water level during the nesting season. The same trends

were seen with the Florida sandhill crane densities. During that time period in 2003 there

were fewer Florida sandhill cranes in the lake littoral zone. In 2002, the sandhill crane

densities were greater. The Florida sandhill crane nested extensively within the littoral

habitat in 2002. Their breeding season was extended from January June due to

favorable lake conditions for nesting.

It is critical in analyses to look at multiple scales in order to determine

environmental influences on avian densities. In general, large wading birds may be

directly affected by water level fluctuations that severely restrict their ability to feed

successfully. Because of this, wetland birds, such as wading birds are often used as

indicators of ecological changes within a wetland system (Furness and Greenwood 1993,









Kushlan 1993, Dimalexis and Pyrovetsi 1997). The post-lake enhancement study, will

determine how lake stage and water level fluctuation influence densities of birds in the

absence of vegetation within the littoral habitats.

Vegetation. Wetland birds are opportunistic. They will utilize a patch of good

habitat and then move on to more productive patches. Wading birds will return to a

previously used patch provided its profitability continues to be sufficient (Kushlan 1981).

A study conducted on Lake Okeechobee showed that when birds were presented with a

choice of foraging habitats at moderate lake stages, all species considered in the study

tended to select patches of emergent vegetation of moderate stature and species/structural

diversity (Smith et. al 1995). Vegetation such as Eleocharis-mix habitats,

Rhynochospora-dominated and mixed-grass primarilyy Panicum), flats ofPolygonum,

Nymphaea and sparse to moderate density cattail (Typha spp.) were among the preferred

mixtures of vegetation during different times of the year (Smith et al 1995). Bird

diversity was linearly correlated with foliage height diversity and curvilinearly with total

percent vegetation cover in a 1974 study conducted by Willson. The correlations with

vegetation could not be measured within the scope of this study. A future manuscript

combining the results of this study with the results of the pre-enhancement vegetation

study conducted within the same study areas (Welch 2004) will be generated for focal

species.

Season: Many wetland bird densities were dependent on avian season defined as

breeding, summer and winter. The two migratory species, American coot and Ring-

necked duck, were only present on the lake during the winter season. Their numbers at

the scale of the lake system are much greater than what our density estimates indicate, as









we sampled only within the littoral zone. Many species leave the lake littoral system to

nest elsewhere during breeding season. This is true for the belted kingfisher which is

present on the lake during the summer and winter months but nests in bank habitats

usually north of Florida. The density estimates for many of the wading birds decrease

during the breeding season as well, when adults nest elsewhere in the state. This is true

for the anhinga, great egret, snowy egret, and tricolored heron. The juvenile birds and

non-breeding adults of these species remain on the lake during breeding season.

Conversely, the density estimates for birds that nest on Lake Toho increase during this

time of year. The small wading birds, the least bittern and green heron, both nest in

Typha in the lake littoral zone. The densities of these birds increase during the breeding

season, and they also become more obvious in their behavior. Red-winged blackbirds

also nested within the dense vegetation within the littoral zone, and densities increased

during the breeding season. The snail kite and Florida sandhill crane nested within the

littoral habitats of the lake, however sandhill crane density estimates lacked correlates of

density trends. Season as an environmental predictor for avian densities will not change

after lake enhancement as long as avian species will still nest within the littoral zone of

the lake and a new habitat within the littoral zone is not created for new nesting species














CHAPTER 4
AVIAN DENSITIES AND VARIABLES IN WHOLE LAKE SAMPLING

Introduction

Lake wide community monitoring by line transect sampling was conducted within

the littoral zone of Lake Toho in order to make comparisons with future treatment effects.

The data presented here are from pre-enhancement sampling and no treatment had been

applied to the lake. The specific project objectives which will be examined within this

chapter are 1) to generate density estimates for focal species within the lake littoral

habitat using line transect distance sampling 2) to determine if the design adequately

sampled the entire littoral habitat by comparing estimated densities of focal species by

line transect type 3) to determine which environmental and temporal variables were

affecting the densities of the focal species at a whole lake level within the littoral zone.

The whole lake sampling was initiated February 2002 as described in Chapter 2

(Table A-2, Appendix A). Conducting line transect sampling within the littoral zone of

the lake required the use of an airboat to sample the 26 established 400m line transects.

Surveys were conducted monthly during the two year pre-enhancement study. The only

species not recorded in the line transect samples were the passerines, due to low

detectability from a moving airboat, and American coots (Fulica americana) due to their

vast numbers during some winter seasons. To avoid violating assumptions of distance

sampling, two observers were used to sample the littoral zone communities.

The sampling incorporated distance sampling with the dependent double observer

approach of Nichols et al. (2000). Two observers conduct the sample from the same









vantage point. One observer is the "primary" (independent) observer and the other is the

"secondary" (dependent) observer. The two observers switch roles every survey to

generate detection probabilities for each observer. The only difference between the

methodologies of Nichols et al. (2000) and our approach is that our primary and

secondary observers never reversed roles. Implications of using this method will be dealt

with in Chapter 5.

The observers counted birds from an airboat equipped with an intercom system

The airboat traversed the line transect while the primary observer recorded, with a hand

held tape recorder all birds observed and their perpendicular distance to the line transect.

The secondary observer listened to the observations of the primary observer and recorded

any additional birds into a separate recording device. A rangefinder was used to

determine accurate perpendicular distances to the birds. This approach permitted

estimation of observer-specific detection probabilities for incorporation into the density

estimation for each species.

Analysis Methods

Densities

Density estimates for 16 different species were derived from the whole-lake line-

transect sampling. The focal-species list from the whole-lake sampling differed from that

generated from the study area sampling. American coots, in addition to the passerines,

the red-winged blackbird and boat-tailed grackle, were not sampled. The limpkin and

cattle egret were also excluded for a lack of sufficient observations to estimate density. A

new focal species, the pied-billed grebe, was more common on line transect samples than

on point transect samples. Its life history is listed below.









* Pied-billed Grebe (Podilymbuspodiceps). The pied-billed grebe is a common
diving bird in North America and is a year round resident in Florida. The grebe
breeds on seasonal or permanent ponds with dense stands of emergent vegetation.
It also breeds near bays and sloughs. During the winter, it uses most types of
wetlands. It eats fish, crustaceans and aquatic insects and forages by diving
underwater in either open water or among aquatic vegetation (Muller and Storer
1999).

Densities were estimated using the program DISTANCE 5.0 (Thomas et al. 2005).

In order to use the information gathered in our dual observer samples, a separate analysis

was conducted to determine a new value for g(0), the probability that an object that is on

the line is detected. One of the assumptions of distance sampling is that g(0) = 1. I

adjusted g(0) by fitting the detection function for a single avian species recorded by the

primary observer, within DISTANCE and an interval was chosen from 0 to the distance

in which the detection function was flat. In the program MARK (White and Bumham

1999), data for both primary and secondary observations within the distance selected was

analyzed using the removal estimator on the primary/secondary detections within that

distance interval to get a g(0) and standard error (Buckland et al. 2004). These values

were put back into the program DISTANCE manually and analysis was conducted as

normal using observations from the primary observer only. This method can be efficient

depending on the truncation distance of the data when determining the flat shoulder of the

detection function for each species (Thomas and Laake pers. communication).

The effort for the line transect sampling was calculated by taking the total line

length of each transect multiplied by the number of times each line was sampled during

the period of time being analyzed. Seasonal and monthly values differed and were

selected as appropriate for each analysis.









Covariates. Covariates were transect type (inside, outside, previously scraped),

stage, and season. I selected the best model with the methods of Marques and Buckland

2003.

Spatial Variations

In order to sample the entire width of the littoral zone, line transect surveys were

designed to run either 'inside' or 'outside' habitats of the littoral zone, covering the 1 4

foot depth zones on the lake, as described in Chapter 2. I assumed that vegetation

composition would vary across transects with community type and water depth. The

spatial analyses compared density estimates of focal species between the transect types to

ensure that the extent of the habitats required for the presence of individual species was

covered during a single sample occasion. This should be equivalent to the width of the

littoral habitats sampled using the point transect sampling. In order to determine if

variations exist between line transect types, the true value of differences in densities

referred to as effect size (ES) was computed to determine if there were transect type

specific differences for each focal species (Alisauskas and Lindberg 2002). This method

of comparing densities was explained in Chapter 3. Predictions of focal species use of

lake transect habitat types (inside, outside, previously scraped) were generated based on

life history characteristics (Table 4-1).

Temporal and Environmental Variations

Environmental variations due to season as described in Chapter 2, will be used to

describe the temporal changes affecting focal-species density estimates for the whole-

lake sampling. Density estimates for focal species were obtained within DISTANCE by

sample month (individual survey) and season.










Table 4-1. Predictions for line transect type used by each focal species. These include
line transect types inside (I), outside (0), and previously scraped (P).


Species
ANHI
BEKI
COMO
GBHE
GLIB
GREG
GRHE
LBHE
LEBI
PBGR
PUGA
RNDU
SACR
SNEG
SNKI
TRHE


Common Name
Anhinga
Belted Kingfisher
Common Moorhen
Great Blue Heron
Glossy Ibis
Great Egret
Green Heron
Little Blue Heron
Least Bittern
Pied-billed Grebe
Purple Gallinule
Ring-necked Duck
Florida Sandhill Crane
Snowy Egret
Snail Kite
Tricolored Heron


Density estimates were obtained monthly for focal species within the littoral zone

to determine which environmental variables were affecting bird densities at the whole

lake scale of sampling. The same analysis methodology used for the study area analyses,

was used for the whole lake sampling analyses, except that linear predictors for the

density estimates included stage, air temperature, water fluctuation, rate of water level

fluctuation, and the categorical variable water movement (described in chapter 3). The

scale was month of sample rather than week of sample as in the study area analyses.

Predictions for each focal species were the same as those in the study area analyses, with

the exclusion of vegetation structure. A prediction for the new focal species, the pied-

billed grebe was added (Table 4-2). Season was introduced in the same manner it was in

the study-area analyses, Chapter 3.


Scientific Name
Anhinga anhinga
Ceryle alcyon
Gallinula chloripus
Ardea herodias
Plegadis falcinellus
Ardea alba
Butorides virescens
Egretta caerulea
Ixobrychus exilis
Podilymbus podiceps
Porphyrula martinica
Aythya collaris
Grus canadensis pratensis
Egretta thula
Rostrhamus socialbilis plumbeus
Ekretta tricolor


Prediction
O,P
I, O, P
I, O, P
I, O, P
I, P
I, O, P
O,P
I, O, P
O,P
O,P
O,P
O,P
I
I, O, P
O,P
I, O, P










Table 4-2. Table of predictions indicating which species nest on the lake and which are
permanent Florida residents. Predictions indicate environmental variables that
are driving the densities of each focal species. These include lake stage (S),
average air temperature (T), rate of water fluctuation per day 9, water level
fluctuation (F), and the categorical variable, water movement (W).


Common Name
Anhinga
Belted Kingfisher
Common Moorhen
Great Blue Heron
Glossy Ibis
Great Egret
Green Heron
Little Blue Heron
Least Bittern
Pied-billed Grebe
Purple Gallinule
Ring-necked Duck
Florida Sandhill Crane
Snowy Egret
Snail Kite
Tricolored Heron


Scientific Name
Anhinga anhinga
Ceryle alcyon
Gallinula chloripus
Ardea herodias
Plegadis falcinellus
Ardea alba
Butorides virescens
Egretta caerulea
Ixobrychus exilis
Podilymbus podiceps
Porphyrula martinica
Aythya collaris
Grus canadensis pratensis
Egretta thula
Rostrhamus socialbilis plumbeus
Egretta tricolor


Results

We recorded 49 avian species during the whole lake sampling (Table B-2,

Appendix B). Sixteen were the focal species described in Chapters 2 and 3. The focal

species were common enough to provide density estimates for each monthly sample,

estimated as number of birds per hectare (Table C-3, Appendix C). The distance

sampling analyses model parameters corresponding to the focal species density estimates,

per hectare, can be found in Table D-2, Appendix D. Density estimates by month allow

for the incorporation of environmental variables. However, density estimates were then

generated based on our environmental variables to graphically display the trends and

estimated densities in a way that makes them useful and comparable to the results from


the study-area sampling.


Species
ANHI
BEKI
COMO
GBHE
GLIB
GREG
GRHE
LBHE
LEBI
PBGR
PUGA
RNDU
SACR
SNEG
SNKI
TRHE


Nest
on
Lake
N
N
Y
Y
N
N
Y
N
Y
Y
Y
N
Y


FL
Resident
Y
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
Y
Y
Y
Y


Predictions
S,T,W
S,T,W
S,R,F,W
S,R,F,W
S,R,F,W
S,R,F,W
S,R,W
S,R,F,W
S,W
S,R,F,W
S,F,T,W
S,T,W
S,T,W
S,R,F,W
S,F,W
S,R,F,W










Spatial Variations

Comparisons between the three types of line transects indicated that the estimated

densities for focal species varied depending on transect type. Many corresponded with

the predictions. The estimated densities are listed in Table C-4, Appendix C.

The preference for inside vs. outside transect type as indicated by the density

estimates are listed in Table 4-3. Large wading birds, including the great blue heron,

great egret and sandhill crane were more common on the inside transects. The sandhill

crane was never seen on an outside line transect during the samples. Three of the

medium sized wading birds, the little blue heron, snowy egret and tricolored heron, also

were seen more often on an inside transects. The anhinga, common moorhen, and ring-

necked duck were more common on outside transects (Figure 4-1).

Table 4-3. Focal species with significant differences between density estimates on inside
vs. outside line transects. Birds are listed under the line type having the
greatest density estimate.
Inside Outside No Significant Difference
Great Blue Heron Anhinga Belted Kingfisher
Great Egret Common Moorhen Glossy Ibis
Little Blue Heron Ring-necked Duck Green Heron
Sandhill Crane Least Bittern
Snowy Egret Pied-billed Grebe
Tricolored Heron Purple Gallinule
Snail Kite







78




0.1
Inside Transects *
0. *e
E 0.0 -

2Outside Transects
-0.1
CD

5 -0.2 -

o
S-0.3

5
S-0.4 -




0 C) ci, -i i
-- Em M




Figure 4-1. The value of differences in estimated densities between inside and outside
cross 0 are indicated as significant (*). 0
often on inside-line transects compared to previously scraped transects (Figure 4-2). The
EI ) U)





Focal Species
Figure 4-1. The value of differences in estimated densities between inside and outside
line transect types. Upper and lower 95% confidence intervals which do not
cross 0 are indicated as significant (*).


The preferences for inside vs. previously scraped transect type are listed in Table 4-

4. The purple gallinule, ring-necked duck and common moorhen all were seen more

often on inside-line transects compared to previously scraped transects (Figure 4-2). The

density estimates for the belted kingfisher were greater on previously scraped line

transects than inside-line transect types. Five wading birds, the glossy ibis, great egret,

little blue heron, tricolored heron and sandhill crane, also had greater numbers in the

previously scraped transects compared to the inside transects.









The focal species that preferred outside vs. previously scraped transect types are

listed in Table 4-5. Few focal species differed significantly between outside and.

Previously-scraped transects. Little blue herons were denser on the outside line transects.

The anhinga, belted kingfisher, and common moorhen were counted on previously

scraped transects in greater numbers than the outside transects (Figure 4-3).

The results indicate that our line-transect sampling effectively sampled a broad

range of species encompassing many guilds and niches within the littoral habitat. Every

focal species was dispersed across every type of transect, with the exception of the

sandhill crane, which was never sampled on an outside transect. Focal species will be

analyzed by combing across transect types for a single sample period. The following

section will discuss the other environmental and temporal variations influencing focal

species densities in the littoral zone of the lake.

Table 4-4. Focal species with significant differences between density estimates on inside
vs. previously scraped line transects. Birds are listed under the line type
having the greatest density estimate.
Inside Previously Scraped No Significant Difference
Common Moorhen Belted Kingfisher Anhinga
Purple Gallinule Glossy Ibis Great Blue Heron
Ring-necked Duck Great Egret Green Heron
Little Blue Heron Least Bittern
Sandhill Crane Pied-billed Grebe
Tricolored Heron Snail Kite
Snowy Egret














0.5


0.4


S0.3


0 .
4-
0

0 0.0
o



)
.4-
D
o -0.1


> -0.2


-U
0)
.c L

<


c1,
m


g g
2
Sg


E -c
E a
o(I
0
0


C: C: C: (1 ( e CL O
LU 02
-0ci 0 M 0
U II^ *

U, ~ ci) U

-c6) U U)
O~cu~n, -j
(3C~e m 0o


0) -
LU -
UU
r
03
(C)
UI)


Focal Species
Figure 4-2. The value of differences in estimated densities between inside and previously
scraped line transect types. Upper and lower 95% confidence intervals that
do not cross 0 are indicated as significant (*).

Table 4-5. Focal species with significant differences between density estimates on
outside vs. previously scraped line transects. Birds are listed under the line
type having the greatest density estimate


Outside
Little Blue Heron


Previously Scraped
Anhinga
Belted Kingfisher
Common Moorhen


No Significant Difference
Great Blue Heron
Glossy Ibis
Great Egret
Green Heron
Least Bittern
Pied-billed Grebe
Purple Gallinule
Sandhill Crane
Snail Kite
Snowy Egret
Tricolored Heron


Inside Transects


Previously Scraped Transects


Previously Scraped Transects












0.3

I 0.2
E
Yl)
w
0.1

o nn


-0.1

O -0.2

S-0.3
Previously Scraped Transects
-0.4








Focal Species
Figure 4-3. The value of differences in estimated densities between outside and
previously scraped line transect types. Upper and lower 95% confidence
intervals which do not cross 0 are indicated as significant (*).
a o o -0 >, Qo -












Temporal and Environmental Variations

The results of the generalized linear model analyses can be found in Table E-2 in

Appendix E. The density estimates for the focal species were explained as a function of

two different predictor models: overall season (B, S, W); and season and year (B02, B03,

S02, S03, W0203, W03). During the winter sample season 2003, the lake stage levels

started to decline as the lake enhancement project began. The model chosen for many of

the focal species reflects this rare occurrence of a dry localized event during the winter

season. In order to determine results that accurately depict these birds on the lake system
season. In order to determine results that accurately depict these birds on the lake system


Outside Transects



-*-









seasonally, overall season was introduced into the model first and then year was added.

The model that involves year was chosen as best only in cases where season alone was

not a predictor for density. The most parsimonious model for density estimation for each

focal species sampled on the line transects is listed in Table 4-6.

The categorical predictor variable, season, explained the variation in monthly

density estimates for 10 of the focal species. The model including winter season

explained the densities of anhingas (p=0.0004), belted kingfishers (p = 0.0003), and ring

necked ducks (p = 0.03) (Figures 4-4 Figure 4-6). The density estimates for the glossy

ibis and tricolored heron were greater during the winter (p=0.04 and p=0.04) at all lake

stages except for one (Figure 4-7 4-8). Season also was the predictor for the density

estimates of the great egret, little blue heron, and snowy egret, which all show the same

trend of greater density in the summer and winter and lower density during the breeding

season (Figure 4-9 4-11). The density estimates for the sandhill crane were also

influenced by season, but their numbers were greatest during the breeding season (Figure

4-12).

Table 4-6. The results of the generalized linear model analyses. The most parsimonious
model is listed. The (+) symbol indicates the additive effect of the two
variables and the (*) indicates the interaction effect of the two variables.
Species Variable
Anhinga Season
Belted Kingfisher Season
Common Moorhen Year
Great Blue Heron Year
Glossy Ibis Season
Great Egret Season
Green Heron None
Little Blue Heron Season
Least Bittern Season









Table 4-6. Continued
S
P
P
R
F
S
S
T



120
a,
N 100




60 -

S40 -
0)
Q 40 -

E
I 20
LuJ


species Variable
ied-billed Grebe Year
urple Gallinule None
ing-necked Duck Season
lorida Sandhill Crane Season
nowy Egret Season
nail Kite Year
ricolored Heron Season


Lake Stage (ft NGVD)
Figure 4-4. Estimated densities for the anhinga during the winter season within the
littoral zone. The error bars correspond to 95% confidence intervals. The
mean value is the pooled estimated density derived from effort-weighted stage
estimates.


T