Effects of White-Nose Syndrome on Bat Diets and Interspecific Competition By Derek Morningstar A Thesis presented to the University of Guelph In partial fulfilment of requirements for the degree of Masters of Science in Integrative Biology Guelph, Ontario, Canada © Derek Morningstar, January, 2017 ABSTRACT Effects of White-Nose Syndrome on Bat Diets and Interspecific Competition Derek Morningstar Advisor: University of Guelph, 2016 John Fryxell, Brock Fenton Competition is commonly invoked to explain variation in abundance, activity patterns, and resource use, but is difficult to detect in nature. Introduction of white-nose syndrome (WNS) in bats provides a natural experiment to test the impact of interspecific competition on bat communities. Acoustic monitoring at locations in Southern Ontario showed an increase in activity of Big Brown Bats (Eptesicus fuscus) and corresponding decline in the activity of Little Brown Myotis (Myotis lucifugus), following the introduction of WNS. Next generation sequencing of bat stomachs and guano in Southern Ontario before and after WNS allowed for the characterization of diet changes of these species. As a function of competitive release, E. fuscus consumed a wider breadth of prey and many of the insect species once consumed by M. lucifugus, including several pest insects. These results suggest that interspecific competition has a detectable effect on bat communities in Southern Ontario. ACKNOWLEDGEMENTS This work could not have been completed without the contributions, support and assistance from so many individuals. Most importantly, I would like to thank my family, especially my wife Vicky, my kids Owen and Mya and my parents Dave and Carol for tolerating my continued passion for research and my need to work on a “bat’s schedule” with a “bat’s stamina”. I appreciate the guidance and help from John Fryxell, Mehrdad Hajibabaei, Shadi Shokrolla, Brock Fenton and the members of the Fryxell and Hajibabaei lab. Field assistance provided by Benoit Talbot, Lucas Greville, Alejandra Cebalos-Vasquez, Luke Owens, Al Sandilands and review and technical advice from Gustavo Betini, Danielle Ethier, Eric McNeil, Rebecca Viejou. Studies from Elizabeth Clare preceeded this research and laid the foundation upon which to build, along with guidance on methods and interpretation. The processing of DNA data was conducted through the Hajibabaei lab at the University of Guelph. Allen Kempert and Al Kurta helped to make connections and find roosts. Lenny Shirose and the Canadian Wildlife Health Cooperative made bat carcasses available for this study. Golder Associates Ltd. provided the flexibility to accomplish this work, the connection to pre-existing project data and technical equipment to collect new data. The landowners and data owners of the many acoustic monitoring and roost locations wish to remain anonymous, but their contribution won’t go unrecognized. iii Table of Contents ABSTRACT ............................................................................................................................. ii ACKNOWLEDGEMENTS ......................................................................................................... iii Table of Contents ................................................................................................................. iv LIST OF TABLES ...................................................................................................................... v LIST OF FIGURES ................................................................................................................... vi INTRODUCTION ..................................................................................................................... 1 METHODS ............................................................................................................................. 7 Study system ........................................................................................................................... 7 Acoustic Survey of Bat Activity ............................................................................................. 8 Collection of Guano ................................................................................................................ 9 Collection of Stomachs ......................................................................................................... 11 Next Generation Sequencing Methods ................................................................................. 12 Statistical methods ................................................................................................................ 15 RESULTS .............................................................................................................................. 17 Acoustics .............................................................................................................................. 17 Results of Capture and Tracking .......................................................................................... 18 Diet ....................................................................................................................................... 19 Pest Insects ........................................................................................................................... 21 DISCUSSION ........................................................................................................................ 23 REFERENCES ........................................................................................................................ 31 TABLES AND FIGURES .......................................................................................................... 36 Appendix A: Bat Capture and Tracking in Dunnville Results .................................................. 49 Appendix B: Insects in bat diets that could be identified to the species level ........................ 53 iv LIST OF TABLES Table 1: Direction of change in mean passes per night at each acoustic bat monitoring station ................................................................................................................................. 46 Table 2: Species Richness in guano samples, based on the Chao estimator .......... 47 Table 3: Pest Insects Observed in Bat Diets .......................................................... 48 v LIST OF FIGURES Figure 1. Extent of confirmed WNS from winter assessment at bat hibernacula as of September 3, 2014 ............................................................................................................. 36 Figure 2: Map of acoustic monitoring stations ...................................................... 37 Figure 3: Map of roost locations for collection of E. fuscus guano ....................... 37 Figure 4: Dunnville bat capture locations and roosts............................................. 38 Figure 5: Overall mean bat passes per night for M. lucifugus and E. fuscus ......... 39 Figure 6: Changes in mean bat passes per year for M. lucifugus at the Dun station40 Figure 7: Changes in mean bat passes per night for M. lucifugus ......................... 40 Figure 8: Changes in mean bat passes per year for E. fuscus at the Dun station ... 41 Figure 9: Changes in mean bat passes per night for E. fuscus ............................... 41 Figure 10: Percent richness by order for all E. fuscus roosts and the M. lucifugus roost (SAND) .............................................................................................................................. 42 Figure 11: AOTU's per insect order across E. fuscus roosts and one M. lucifugus roost (SAND) .............................................................................................................................. 43 Figure 12: Rarefaction curves for E. fuscus roosts ................................................ 44 Figure 13: Mean percent richness of AOTU's by order for stomachs ................... 44 Figure 14: Rarefaction curves for E. fuscus stomachs pre-WNS and post-WNS .. 45 vi INTRODUCTION Interspecific competition has long been posited as a driving mechanism in the diversification of species (Darwin, 1859) and continues to be an important topic of ecological study (Meyer and Kassen, 2007; Terborgh, 2015). For decades, competitive interactions have been investigated in theoretical and imperical studies and core in the training of ecology and wildlife management (Fryxell et al, 2014). It is described as the interactions between members of two or more different species to obtain essential resources that are in limited supply. This mechanism can be broken into two categories: exploitative competition and interference competition (Park, 1954; Faas and Weckerly, 2010). Interference competition refers to direct conflict between individuals, including aggression of physically excluding the opponent from access to resources. Under exploitative competition, such as the interaction in my study, each species has different means of obtaining the resources without direct combat, such as specialized abilities to pursue prey or access habitat. Exploitative competition is often difficult to study in nature because it can be hard to separate superior strategies of obtaining resources from other environmental factors. Competition does not always drive one of the competitors to extinction. The Lotka- Volterra model of competition predicts that it is possible under some conditions for competitors to coexist in nature (Schreiber et al, 2011; Amaresekare,