North American Bat Monitoring Program (NABat) OneHealth (ver. 2.0, June 2025)
This dataset documents the results of large-scale surveillance efforts to assess coronavirus prevalence in North American bats. Wildlife monitoring is critical for establishing disease baselines and identifying key factors that inform conservation strategies aimed at reducing pathogen exposure among wildlife, domestic animals, and humans. Reports of SARS-CoV-2 in free-ranging wildlife in North America have raised concerns about potential exposure in bats, with potential implications for both conservation and human health. Here, we leveraged the North American Bat Monitoring Program to (1) assess whether bats were actively shedding coronaviruses, including SARS-CoV-2, (2) examine whether landscape variation in coronavirus shedding was associated with resource availability, and (3) investigate temporal variation in shedding and its relationship with individual characteristics such as body mass, sex, and reproductive status. We also used the same data to develop a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. In this initial version of the data release for the broader NABat OneHealth project, we provide the survey data from bridge surveys which were used as inputs for our roost prediction model.
Citation Information
Publication Year | 2025 |
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Title | North American Bat Monitoring Program (NABat) OneHealth (ver. 2.0, June 2025) |
DOI | 10.5066/P14HVQHW |
Authors | Amy K Wray, Luz de Wit, Amanda Adams, Katharine Banner, Jeffrey Foster, Winfred Frick, Alexandra Gibson, Andrew Hoegh, Kathryn M Irvine, Jason Ladner, Victor Lopez-Durazo, Jacob K Oram, Bethany R Straw, Brian E Reichert |
Product Type | Data Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Fort Collins Science Center |
Rights | This work is marked with CC0 1.0 Universal |