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Development and Assessment of a Wildlife Habitat Relationship Model for Terrestrial Vertebrates in the State of Maryland

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Development and Assessment of a Wildlife Habitat Relationship Model for Terrestrial Vertebrates in the State of Maryland DEVELOPMENT AND ASSESSMENT OF A WILDLIFE HABITAT RELATIONSHIP MODEL FOR TERRESTRIAL VERTEBRATES IN THE STATE OF MARYLAND by Robert John Northrop A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Wildlife Ecology Spring 2009 Copyright 2009 Robert John Northrop All Rights Reserved DEVELOPMENT AND ASSESSMENT OF A WILDLIFE HABITAT RELATIONSHIP MODEL FOR TERRESTRIAL VERTEBRATES IN THE STATE OF MARYLAND by Robert John Northrop Approved: __________________________________________________________ Jacob L. Bowman, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee Approved: __________________________________________________________ Douglas W. Tallamy, Ph.D. Chair of the Department of Entomology and Wildlife Ecology Approved: __________________________________________________________ Robin Morgan, Ph.D. Dean of the College of Agriculture and Natural Resources Approved: __________________________________________________________ Debra Hess Norris, M.S. Vice Provost for Graduate and Professional Education ACKNOWLEDGMENTS I thank Dr. Jacob Bowman for his patience and continuing support over the past several years. Thanks to Dr. Roland Roth who originally asked me to teach at the University of Delaware in 1989. The experience of teaching wildlife conservation and management at the University for 14 years has changed the way I approach my professional life as a forest ecologist. I also offer a big thank – you to all my students at the University I have learned more from you than you can imagine. I am grateful to the U.S. Forest Service, Dr. Mark Twery and Scott Thomasma, for funding the initial literature review and research, and for ongoing database support as we use this work to build a useful conservation tool for planners and natural resource managers in Maryland. I thank all of the men and women of the Maryland Department of Natural Resources who spend their lives working long hours for little money to protect the biological diversity and enhance natural legacy of that beautiful land. This is my parting gift to you. Finally, to Rebecca Northrop who never stops believing in me and JoAnn Hoffman who will be glad to have me back when this project is completed. Thank you very much. This work and the tool that will be developed from it are dedicated to the large old white oak tree that shared my yard and life during the 20 years that my family spent in Cecil County Maryland working to restore the Chesapeake Bay. It framed our lives, protected us during storms, and shaded us during the hot humid summers. iii TABLE OF CONTENTS LIST OF TABLES ......................................................................................................... v LIST OF FIGURES.......................................................................................................vi ABSTRACT .................................................................................................................vii INTRODUCTION…………………………………………………………………….9 STUDY AREAS………………………………………………………………..……13 METHODS…………………………………………………………………………...17 RESULTS…………………………………………………………………….………28 DISCUSSION…………………………………………………………………..….…34 MANAGEMENT IMPLICATIONS…………………………………………..……..39 LITERATURE CITED………………………………………………………….……41 REFERENCES USED TO POPULATE HABITAT MATRIX………………..……43 APPENDIX……………………………………………………………………….…59 iv LIST OF TABLES Table 3.1. Forest and non – forest data types used in the wildlife habitat relationship model ………………………………………………18 Table 3.2. Forest type classification and development stages used in the wildlife habitat relationship model………………………………19 Table 4.1. Summary of omission and commission errors for each of the seven study sites………………………………………………………..30 Table 4.2. Explanation of omission errors……………………..……...…....32 Table 4.3 Explanation of commission errors………………..……………..33 Appendix A Species predicted, observed and commission errors for each of the seven study sites…………………………………………………59 Appendix B Vertebrate species of Maryland considered within the Maryland Wildlife Habitat Relationship Model……………………………68 Appendix C Vertebrate species found within each county of Maryland ……..75 Appendix D Vertebrate species found within each of the physiographic provinces in Maryland…………………………………………...87 Appendix E Vertebrate species found within each of the 8 – digit Maryland watersheds…………………………………………………….....99 Appendix F Vertebrate species found within each U.S. Forest Service Northeast forest type and vegetative development stage…………………………………………………………….114 Appendix G Forest structure features associated with the habitat of each vertebrate species within the Maryland Wildlife Habitat Relationship Model ……………………………………..……..127 Appendix H Non – forest structure features associated with the habitat of each vertebrate species within the Maryland Wildlife Habitat Relationship Model ……………………………….…….……..139 v LIST OF FIGURES Figure 2.1. Map showing location of Maryland within mid – Atlantic region and physiographic regions………………………………………14 Figure 2.2. Map showing location of Prettyboy Reservoir property within the Gunpowder watershed and Piedmont Plateau physiographic region……………………………………………………………16 Figure 3.1. Logic flow chart for the Maryland Wildlife Habitat Relationship Model…………………………………………………………...27 vi ABSTRACT Human population growth and development patterns have led to the accelerated loss of farmland and forest since the 1950s and has raised considerable concern over the loss of biodiversity and its impact on basic ecosystem functions that support ecological services needed by society for sustainability (EPA, 2004 and Conservation Fund, 2006). Traditional approaches to wildlife conservation have relied on a reactive species-by-species approach that is often prohibitively expensive, biased toward game or charismatic species and often ineffective (Pitelka 1981, Noss 1991). I have developed a rapid habitat assessment tool that uses an integrated series of databases that link forest composition, vegetative development stage, forest and non – forest structure, and non-forest habitat features with maps of known vertebrate distribution. The tool is intended to aid in the evaluation of habitat impacts associated with changes in land use and natural resource management within Maryland. I tested the habitat assessment tool using presence/absence data for 29 commonly occurring herpetofauna collected by the Maryland Department of Natural Resources over a two year period on seven sites within the Piedmont Plateau physiographic province. The initial run of the assessment tool correctly predicted the presence of 86% of the herpetofauna. The average omission error rate was 14%. The average commission error rate was 43%. I found a significant goodness of fit between 2 the observed and predicted herpetofauna at the 7 inventory sites (χ 0.05, 6df = 0.9, P>.975). vii The observed omission errors fell in three broad categories: field inventory error, forest types used by a species but not included in the Maryland Wildlife Habitat Relationship Model, and the use of closed-canopy forest by species thought to use only open canopy forest. Correcting for these forest type errors within the design of the Maryland Wildlife Habitat Relationship Model and the data entry errors reduced the overall omission error to 3%, improving the overall predictive rate to 61%, with reptiles at 44% and amphibians at 70%. With corrections the Maryland Wildlife Habitat Relationship Model accurately predicted the presence of 97% of the 29 field-inventoried species at each site. Low rates of omission errors (pre-assessment 14%, post-assessment 3%) suggest that the model is achieving improvements in accuracy over earlier wildlife habitat relationship models, a possible outcome of its narrow geographic focus and its focus on the use of local and regional habitat descriptions when available (Block et.al. 1994). Commission errors are likely to remain above acceptable rates for managers looking for a tool that can accurately provide site-specific vertebrate occupancy predictions in the commonly accepted range of 75 to 80% (Hurley 1986). viii INTRODUCTION The continuing loss of farmland and forest within the state of Maryland has raised considerable concern over the loss of biodiversity and its impact on basic ecosystem functions that support ecological services needed by society for sustainability (EPA, 2004 and Conservation Fund, 2006). Several state land use laws, including the Chesapeake Bay Critical Area Program (1984) and Forest Conservation Act (1991), now routinely require the collection and analysis of habitat data for inclusion in land use change decisions and forest and farm management planning. Yet, there is no effective and efficient mechanism available for using these data to assess the impacts of changes in habitat composition and structure at these levels of decision- making. Here I describe the development of a rapid wildlife habitat assessment tool, the Maryland Wildlife Habitat Relationship Model (MWHRM ). It uses vegetation composition and structural data commonly collected for land use and management decision making in Maryland to identify potential habitat capabilities across multiple species for use in Maryland. This work follows closely the work of Thomas (1979) in the Blue Mountains of Oregon, DeGraaf et. al. (1992) in New England, and Harvey (1994) in Pennsylvania. 9 Habitat provides the basis for most wildlife conservation activities (Morrison et.al., 1998). Understanding
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