Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region

Ecological Indicators
By: , and 

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Abstract

We assessed the sampling effort requirements for detecting the presence of extant bat species following the impact of white-nose syndrome in the mid-Atlantic region of the United States. We acoustically sampled 27,796 nights across 846 sites between 15 May and 15 August 2016–2018 within the District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia. We developed simulations to determine the number of sites required to document bat species when each site was sampled different numbers of nights. We examined these simulations with respect to land cover, physiographic region, and time period. We generally found that sampling a greater number of sample sites within a survey area increased detection more than increasing the number of nights at individual sampling sites. The sampling effort required to detect a given bat species varied by species, as well as land-cover type and physiographic region. Our results suggest that land managers and researchers should use caution in using protocols developed with other objectives, e.g., the U.S. Fish and Wildlife Service endangered and threatened bat species and the North American Bat monitoring programs’ methods are designed relative to their specific needs. Unfortunately, neither protocol may be adequate for accurately detecting bat communities within all mid-Atlantic areas.

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Publication type Article
Publication Subtype Journal Article
Title Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region
Series title Ecological Indicators
DOI 10.1016/j.ecolind.2021.107489
Volume 125
Year Published 2021
Language English
Publisher Elsevier
Contributing office(s) Coop Res Unit Leetown
Description 107489, 9 p.
First page 1
Last page 9
Country United States
State Maryland, Pennsylvania, Virginia, West Virginia
City Washington, D. C.
Other Geospatial Blue Ridge Mountains
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