Predicting migration routes for three species of migratory bats using species distribution models

Understanding seasonal variation in the distribution and movement patterns of migratory species is essential to monitoring and conservation efforts. While there are many species of migratory bats in North America, little is known about their seasonal movements. In terms of conservation, this is impo...

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Bibliographic Details
Published inPeerJ (San Francisco, CA) Vol. 9; p. e11177
Main Authors Wieringa, Jamin G, Carstens, Bryan C, Gibbs, H Lisle
Format Journal Article
LanguageEnglish
Published United States PeerJ, Inc 16.04.2021
PeerJ Inc
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Summary:Understanding seasonal variation in the distribution and movement patterns of migratory species is essential to monitoring and conservation efforts. While there are many species of migratory bats in North America, little is known about their seasonal movements. In terms of conservation, this is important because the bat fatalities from wind energy turbines are significant and may fluctuate seasonally. Here we describe seasonally resolved distributions for the three species that are most impacted by wind farms ( (eastern red bat), (hoary bat) and (silver-haired bat)) and use these distributions to infer their most likely migratory pathways. To accomplish this, we collected 2,880 occurrence points from the Global Biodiversity Information Facility over five decades in North America to model species distributions on a seasonal basis and used an ensemble approach for modeling distributions. This dataset included 1,129 data points for , 917 for and 834 for . The results suggest that all three species exhibit variation in distributions from north to south depending on season, with each species showing potential migratory pathways during the fall migration that follow linear features. Finally, we describe proposed migratory pathways for these three species that can be used to identify stop-over sites, assess small-scale migration and highlight areas that should be prioritized for actions to reduce the effects of wind farm mortality.
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ISSN:2167-8359
2167-8359
DOI:10.7717/peerj.11177