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Explaining and Monitoring Population Performance in Grizzly and American Black Bears University of Montana ScholarWorks at University of Montana Graduate Student Theses, Dissertations, & Professional Papers Graduate School 2017 EXPLAINING AND MONITORING POPULATION PERFORMANCE IN GRIZZLY AND AMERICAN BLACK BEARS Jeffrey Brian Stetz Follow this and additional works at: https://scholarworks.umt.edu/etd Let us know how access to this document benefits ou.y Recommended Citation Stetz, Jeffrey Brian, "EXPLAINING AND MONITORING POPULATION PERFORMANCE IN GRIZZLY AND AMERICAN BLACK BEARS" (2017). Graduate Student Theses, Dissertations, & Professional Papers. 10984. https://scholarworks.umt.edu/etd/10984 This Dissertation is brought to you for free and open access by the Graduate School at ScholarWorks at University of Montana. It has been accepted for inclusion in Graduate Student Theses, Dissertations, & Professional Papers by an authorized administrator of ScholarWorks at University of Montana. For more information, please contact [email protected]. EXPLAINING AND MONITORING POPULATION PERFORMANCE IN GRIZZLY AND AMERICAN BLACK BEARS By JEFFREY BRIAN STETZ B.Sc. Fish and Wildlife Management, Michigan State University, East Lansing, MI, USA, 1998 M.Sc. Wildlife Biology, University of Montana, Missoula, MT, USA, 2008 Dissertation presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Fish and Wildlife Biology The University of Montana Missoula, MT May 2017 Approved by: Scott Whittenburg, Dean of the Graduate School Graduate School Dr. Michael Mitchell, Chair Montana Cooperative Wildlife Research Unit Dr. Rich Harris Washington Department of Fish and Wildlife Dr. Mark Hebblewhite Wildlife Biology Program, W.A. Franke College of Forestry and Conservation Dr. Kevin McKelvey United States Forest Service Dr. L. Scott Mills Associate Vice President of Research for Global Change and Sustainability Katherine C. Kendall (ex-officio) United States Geological Survey i © COPYRIGHT By Jeffrey B. Stetz 2017 All Rights Reserved ii Stetz, Jeffrey, Ph.D., Fall 2016 Fish and Wildlife Biology Explaining and monitoring population performance in grizzly and American black bears. ABSTRACT Chairperson: Dr. Michael Mitchell Understanding how environmental factors influence wildlife populations is at the heart of ecology and management. Populations and their habitats are, however, inherently dynamic, which requires monitoring responses to changes in the environment. Beyond quantifying population dynamics, understanding why populations respond as they do may allow improved predictions within and across populations, ideally leading to better management. Grizzly bears (Ursus arctos) and American black bears (U. americanus) have been researched in North America for decades, providing excellent opportunities to explore ecological questions involving inter- and intraspecific competition and responses to spatial and temporal variation in resources. The wealth of data collected on these species may be used to answer ecological questions and obtain reliable information for monitoring and management in a rapidly changing world. Chapter 1: Why do grizzly and black bear densities vary in space and time? I used data from noninvasive genetic sampling of grizzly and black bears in northwestern Montana with spatially- explicit capture-recapture models to predict sex-specific density patterns for both species. In addition to intraspecific effects on density, I considered biotic and abiotic factors such as net primary productivity and habitat security. Chapter 2: Why do detection probabilities of grizzly bears at bear rubs vary within and across populations? Research has shown detection to vary by sex and season, but also across populations. I used data from two large noninvasive genetic sampling studies to explore a suite of biotic and abiotic factors that are plausibly related to bear rubbing behavior. After creating predicted density surfaces for both species, I competed models including effects of density, terrain characteristics, and sampling effort in mark-recapture models to evaluate support for my hypotheses. Chapter 3: Monitoring the performance of any wildlife population can be difficult, and the variety of research tools to do so can be overwhelming at times. To assist black bear managers across northeastern North America in identifying suitable tools, I assessed the tradeoffs of methods including traditional mark-recapture, spatially-explicit methods, and known fate models. For some methods, I also conducted simulations based on published data to provide insights into study design and expectations of model performance. iii ACKNOWLEDGEMENTS Principal funding for the grizzly and black bear data collected in Montana was provided by the United States Geological Survey and United States Forest Service via U.S. Congressional appropriations. Additional funding for black bear data was provided by the U.S. Geological Survey—Park Oriented Biological Science Program and the U.S. Forest Service. Montana Department of Fish, Wildlife, and Parks provided funding to analyze additional black bear samples. Specifically, I thank K. Kendall and Dr. J. Kershner with the USGS, and Dr. R. Mace with MTFWP for providing access to these valuable datasets. The following agencies provided additional data and invaluable logistical and in-kind support: Blackfeet Nation; Confederated Salish and Kootenai Tribes; Montana Department of Fish, Wildlife, and Parks; Montana Department of Natural Resources and Conservation; National Park Service; Northwest Connections; U.S. Bureau of Land Management; U.S. Fish and Wildlife Service; and the University of Montana. Funding for data and initial analyses in Canada was provided by Parks Canada, Western Transportation Institute, Woodcock Foundation, H.P. Kendall Foundation, Wilburforce Foundation, National Fish and Wildlife Foundation, Alberta Conservation Association, Calgary Foundation, and Mountain Equipment Cooperative. I thank Drs. M. Sawaya and A. Clevenger for access to these data. Funding for the analysis of population monitoring options for black bears in the northeast was provided by the member agencies of the Northeast Black Bear Technical Committee (NEBBTC) through the Wildlife Management Institute. I am grateful for the valuable guidance and constructive feedback on all stages of this work from J. McDonald and J. Hurst and thank all other members of the NEBBTC for their contributions: P. Rego, J. Vashon, H. Spiker, L. Conlee, K. Craig, C. Dyke, A. Timmins, K. Burguess, S. Spencer, M. de Almeida, M. Obbard, M. Ternent, R. Dibblee, S. Lefort, C. Brown, F. Hammond, J. Sajecki, and C. Carpenter. I thank K. Noyce and B. Scheick for sharing valuable data, S. Williamson of the Wildlife Management Institute for his help with contract management, and T. White for her administrative support throughout this project. This large undertaking was successful thanks to the hard work, insights, and patience of Drs. M. Sawaya, F. van Manen, and J. Clark, who have collectively and individually done tremendous things to advance my skills and knowledge and, more importantly, the conservation of bears around the globe. I am beyond grateful for the opportunity to work with them. The work presented here would not have been possible without the incalculable efforts invested by hundreds of field technicians and agency biologists over the course of many years. The amount of hard work, cooperation, and sharing I’ve witnessed during this time has been inspiring. This extends to a few special people who have worked so hard to develop the tools the rest of us rely on. I admire them for sharing the fruits of their labors, and for much needed guidance along the way. In particular, the analytical tools developed by Dr. M. Efford were integral to my work, as was his assistance with model development and guidance with these rapidly evolving methods. Genetic analyses were equally dependent on the efforts of Dr. D. Paetkau and the team at Wildlife Genetics International. I thank J. Braun and B. Deng for access to, and invaluable support using, the high-performance computing cluster at Montana Tech of the University of Montana. My analyses would have been impossible without each of them. I am also grateful to the dozens of private land owners who granted access for sampling efforts, shared knowledge of their lands, and provided support of conservation-based research. iv I thank my committee members for years of unending support and guidance through yet another of my unorthodox pursuits in academia. The opportunity to work with such a gifted and committed group has been an inspiration. Most of all I thank my advisor, Dr. Mike Mitchell. It would be impossible to relay everything he did to get me to this point, and equally impossible to express my gratitude for the lessons, insights, and skills he shared. Through everything, he lived up to his promise to change the way I see and ask questions about the world. It would be impossible to name everyone I am grateful to given the extent of the work, in both time and space, that I have been a part of and relied upon. Reflecting on what that list would look like is beyond humbling. I can only hope that those involved know how much I appreciate their contributions, support, and understanding. That being said, I have to give a special thanks to Robin Hamilton, Vanetta Burton, Tina Anderson, and the incomparable Jeanne Franz for years of help and guidance. We are all so fortunate to have such great people to help keep us out of trouble. I want to thank my family and friends for always
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