Functional EcologyEcologyPeer-reviewed journal article
Activity patterns during the mating season predict sex-biased infections in an emerging fungal disease
Macy J. KailingiD, Joseph R. HoytiD, John Paul WhiteiD, Jennifer A. Redell, Heather M. KaarakkaiD, Kate E. LangwigiD
Abstract
O_LIMating dynamics can govern species impacts from rapid global change by influencing population rates of growth and adaptation, as well as individual traits that affect mortality risks from novel pressures. C_LIO_LIHere, we examined sex differences in activity of Myotis lucifugus during their mating season, which coincides with exposure to the lethal fungal pathogen (Pseudogymnoascus destructans) that causes white-nose syndrome. We expected differences in activity between sexes to modify seasonal P. destructans dynamics as the pathogen can replicate only at the cool temperatures at which bats hibernate. C_LIO_LIWe used passive antenna systems installed at the entrances of hibernacula and PIT tags to characterize activity patterns of bats. We also measured pathogen loads on bats during the autumn mating and early hibernation periods to assess how infection changed according to host phenology. C_LIO_LIWe found that females spent fewer days active during autumn, arrived after males, and were primarily active on the warmest nights. Males remained highly active throughout the mating season and later in autumn than females. Importantly, differences in phenology corresponded to higher pathogen loads on females during early hibernation as male activity, and thus warm body temperatures, inhibit pathogen growth. C_LIO_LIDifferences in activity between sexes and in the transition from swarm to hibernation likely reflects males maximizing their mating opportunities while females conserve energy to meet the cost of spring migration and reproduction. More broadly, our results show how activity during the mating season and phenology can contribute to sex-biased impacts of a novel disease and highlight the value of understanding species mating systems to anticipate the impacts of environmental change. C_LI
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