Identifying patterns and processes of sex-biases for an emerging fungal disease of wildlife

Abstract

Anthropogenic changes have facilitated an increase in emerging infectious diseases, threatening biodiversity globally. Identifying the individuals, species, or communities most vulnerable to disease can guide the development of conservation priorities. Processes that structure individual variation, such as demography, can strongly affect the response of populations or species to pathogen introduction. Specifically, sex-biased disease can mediate the size of epidemics as well as the magnitude of populations declines following pathogen introduction. However, the context in which we expect sex-biased disease to occur, and subsequently affect population dynamics, varies among host-pathogen systems. Here, I identified patterns of sex-biased disease across several species of bat hosts impacted by white-nose syndrome and explored novel seasonal processes that gave rise to sex-biased disease, which ultimately scaled up to restructure populations. In scaling ecological dynamics from individuals to populations, I developed an R-based computational package to increase the ease of analyzing advancing PIT tagging technology thus providing tools to study individually based phenology, migratory patterns, network connectedness, and survival of species to a broader audience. Collectively, my work supports conservation of wildlife imperiled by disease, advances the theoretical framework for which we can anticipate sex-biased disease, and expands methods for investigating ecological and evolutionary dynamics, thereby broadening the scope of biological inference.