EXPLORING GENERALITIES IN THE DRIVERS OF DIVERSITY PATTERNS IN FRAGMENTED LANDSCAPES: MULTI-CONTINENTAL MODEL CROSS- COMPARISONS USING BUTTERFLIES By NATALIE S ROBINSON B.S., University of California, Berkeley, 2003 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirement for the degree of Doctor of Philosophy Department of Ecology and Evolutionary Biology 2014 This thesis entitled: Exploring Generalities in the Drivers of Diversity Patterns in Fragmented Landscapes: Multi- continental Model Cross-Comparisons Using Butterflies written by Natalie Suzanne Robinson has been approved for the Department of Ecology and Evolutionary Biology _______________________________________ (Dr. M. Deane Bowers, Committee Co-chair) _______________________________________ (Dr. Robert Guralnick, Committee Co-chair) _______________________________________ (Dr. Kendi Davies) _______________________________________ (Dr. Brett Melbourne) _______________________________________ (Dr. Cesar Nufio) _______________________________________ (Dr. Stefan Leyk) Date_______________ The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. Robinson, Natalie S. (Ph.D., Ecology and Evolutionary Biology) Exploring Generalities in the Drivers of Diversity Patterns in Fragmented Landscapes: Multi- continental Model Cross-Comparisons Using Butterflies Thesis directed by Professors M. Deane Bowers and Robert Guralnick ABSTRACT Landscape modification is leaving an irrevocable scar on the planet, most notably through habitat fragmentation. Fragmented landscapes are often unable to support communities that once inhabited them, leading to unprecedented rates of global biodiversity loss. As a result, substantial research effort focuses on investigating the drivers of species’ responses to habitat fragmentation, usually for one or a few species at select locations. This dissertation expands upon previous research in order to broaden understanding of the determinants of diversity patterns in fragmented landscapes. I modeled variation in among fragment butterfly diversity for entire communities, using both environmental attributes and species traits as predictors. I then compared models across three, widely separated fragmented landscapes. I found that patch area and water availability had consistent influences on butterfly diversity patterns; these factors may warrant inclusion into management policies for fragmented landscapes worldwide. Other predictors, e.g., butterfly wing length, had variable influences on diversity patterns, although results revealed similarities between certain study areas. For example, habitat heterogeneity influenced diversity patterns similarly in two study areas, possibly due to similarities in ecological and/or climatic characteristics (e.g., drought-prone summers). Furthermore, species traits played important, albeit inconsistent, roles in driving butterfly diversity patterns; this iii pattern also potentially driven by among location ecological and/or climatic conditions. In all, this integrative data reuse analysis demonstrated patterns that may provide crucial information for better understanding wide-spread species responses to habitat fragmentation. The final component of this dissertation was an exploration of questions that arose from the data reuse strategy employed: how different are models constructed from datasets obtained via disparate levels of survey effort, and what implications does this have for data reuse analyses. I constructed a new model using data collected via 2/3 of the full sampling effort for one dataset. The model was almost identical to that constructed from the full dataset, and the use of this ‘reduced sampling effort’ dataset would thus have had negligible impact on previous results. This work provides insight into the sensitivity of downstream analyses to variation in survey methods, and substantiates the validity of analyses reusing datasets collected by different researchers. iv ACKNOWLEDGEMENTS I am not sure how I can put to words all of my appreciation for the myriad people whose support and understanding have helped me through this crazy journey. This is a long list, which starts with my major advisors, Deane Bowers and Rob Guralnick. Together you have given me zillions of hours of your time, through countless meetings, edits, and talks. You have been my cheerleaders, my mentors, my inspiration, and my friends. You have shaped both my dissertation research, and my ability to ask deeper questions, perform more focused investigations, and communicate more effectively than I ever thought possible. You took a naïve girl from a sheltered world and made her into a scientist, and all of my past and future successes are owed to you. Deane and Rob, I can never thank you enough for your intellectual stimulation, enthusiasm, tenacity, and encouragement. I would also like to sincerely thank my other committee members, Kendi Davies, Stefan Leyk, Brett Melbourne, and Cesar Nufio, whose insights and feedback through the years have shaped my PhD into something truly unique and exciting. Finally, I feel lucky to have been accepted into a department of such amazing, supportive faculty and staff as are found in EEB. Special thanks to Jeff Mitton for encouraging me to explore my options and pursue my dreams, Yan Linhart for sharing his infectious love of science and seeing me through early days of my studies, and Mike Grant for your encouragement and intellectual support. My ability to complete this PhD hinged upon help and support from a few key people. To my collaborators, Martin Konvicka, Tomas Kadlec, and Matt Williams, your willingness to share your hard-earned data and work with me to develop new ideas are at the heart of making this integrative study possible. I am forever grateful for having had the opportunity to work with other like-minded scientists who believe in the importance of sharing data, and who were willing v to do whatever I needed in order to help me complete these analyses. Special thanks also to several people who helped me gather and synthesize additional information for this project through the years, Laura Tietz, Annie Frazier, Jan Koenig, and Monica Rother. To my the friends, both biological and non-biological, you’ve seen me through so many years, supported me and understood what I was trying to do, expanded my ways of thinking, and accompanied me on countless adventures. In particular, to the girls, Susan Whitehead, Loren Sackett, Kallin Tea, Se Jin Song, Mary Kay Herzenach, and Katherine McClure, our girls nights were a sustaining force during these many years in the Master’s and PhD programs, and I love you all for your commitment to our friendships. To my other biological friends, Carolina Quintero, Ty Tuff, Evan Lampert, Amanda Williams, Niffer Wilkening, and so many more; your support and feedback have aided in this project in ways that you could not even know, thank you for every minute of it. I also wish to acknowledge the Bowers and Guralnick labs, past and present, including Caitlin Kelly, Megan Blanchard, Toby Hammer, Adrian Carper, Peri Mason, Collin Schwantes, Carolina Quintero, Mary Jamieson, Katie Wolfson, Brian Stucky, Gaurav Vaidya, Leisl and Peter Erb, Nate Kleist, Aiden Beers, and Aly Seeberger, thank-you for the stimulating conversation and amazing feedback throughout this process. And finally, to my non- biological friends, I would have gone crazy if you had not been there to remind me that there is more to life than just school. Special thanks to Amber Freeman and Cris Sturgis, my oldest and dearest friends whose support has been unbelievable. Thank-you also, and especially, to Jeremy Lauffenburger, Phil Sonnenfeld, Truman Bradley, Taylor Chase, and Anna Jablonski for the late night Catan games, amazing hut trips, incredible raft trips, and other inspiring adventures. Finally, I am unendingly grateful to my family, without whom I never would have had the strength to upend my life, start with a clean slate, and make a new and brighter future for vi myself. To Jessica Robinson, you have been at times my sounding board, and at others my ear, and I appreciate your love and support over all of these years. To my Mom, Susan Robinson, you provided me with the one thing that has made every success in my life possible, a belief that I can do anything that I set my mind to. You taught me early to be strong, independent, tenacious, and confident in my ability to achieve any goal, no matter how challenging. I can never repay you, or express enough gratitude for you to understand that you are the foundation of everything that I am, and that I couldn’t be more proud to be your daughter. To my Dad, Bruce Robinson, you are my rock, my hero. I have always known that you believed in me, that your support for me could never be shaken, and that your love for me is completely unconditional. I walk with a higher step, a brighter smile, and a more compassionate heart because you are my father, and I will always strive to be, and to do, better, in the hopes that I can someday come even close to living up to your example. To Paula Connelly, you have supported me in so many ways, taking me to amazing places, giving me opportunities to have fun and enjoy this crazy ride, and helping me to travel around the world; thank-you. And finally, to Brooks Lustig, my partner, my best friend- I have taken you on a ride that neither one of us ever could have expected, and I do not think there are words enough in this world to express how much I appreciate your help in getting me to the finish line. Thank-you for supporting me when I needed help keeping my head up, making me laugh when I wanted to cry, and pushing me to always have fun and enjoy this life. I am fortunate have received generous financial support for this work through funding from the University of Colorado Department of Ecology and Evolutionary Biology, the University of Colorado Beverley Sears Grant, The University of Colorado Graduate School, and the University of Colorado Museum of Natural History.