Data from: Impacts of white-nose syndrome observed during long-term monitoring of a midwestern bat community

White-nose syndrome (WNS) is an emerging fungal disease suspected to have infected Indiana caves in the winter of 2010–2011.This disease places energetic strains on cave-hibernating bats by forcing them to wake and use energy reserves. It has caused >5.5 million bat deaths across eastern North America, and may be the driving force for extinction of certain bat species. White-nose syndrome infection can be identified in hibernacula, but it may be difficult to determine whether bats in a particular area are affected if no known hibernacula exist. Thus, our aim was to use long-term monitoring data to examine changes in a summer population away from hibernacula that may be attributable to WNS effects during winter. We used capture data from a long-term bat-monitoring project in central Indiana with data from 10 repeatedly netted sites consistent across all reproductive periods. We modeled capture data by WNS exposure probability to assess changes in relative abundance of common species and reproductive classes as WNS exposure probability increases. We base exposure probability on a cokriging spatial model that interpolated WNS infection from hibernaculum survey data. The little brown bat Myotis lucifugus, the Indiana bat M. sodalis, and the tri-colored bat Perimyotis subflavus suffered 12–80% declines; whereas, the big brown bat Eptesicus fuscus, the eastern red bat Lasiurus borealis, and the evening bat Nycticeius humeralis showed 11.5–50.5% increases. We caught more nonreproductive adult females and postlactating females when WNS exposure probabilities were high, suggesting that WNS is influencing reproductive success of affected species. We conclude that, in Indiana, WNS is causing species-specific declines and may have caused the local extinction of M. lucifugus. Furthermore, WNS-affected species appear to be losing pups or forgoing pregnancy. Ongoing long-term monitoring studies, especially those focusing on reproductive success, are needed to measure the ultimate impacts of WNS.Impacts of WNS Figure S1 Oct. 2016Standard error estimate for a 2013 cokriging spatial model predicting white-nose syndrome (WNS) exposure probability across a continuous landscape in eastern North America. The standard error estimate for our long-term monitoring site in central Indiana was 0.06, suggesting that predicted values for WNS presence (see Figure 1) were accurate. Found at DOI: xxx (file size and type).Impacts of WNS Table S1 Nov. 2016Predicted probability of white-nose syndrome (WNS) exposure for a long-term bat monitoring site in central Indiana and number of WNS-infected caves in Indiana by year (2008–2013). Annual values for the central Indiana site were extracted from cokriging spatial models developed using population data from Indiana bat Myotis sodalis hibernacula.Impacts of WNS Table S2 Nov. 2016Records of Indiana bats observed in Indiana caves during hibernation surveys in 2011 and 2013. Bats were originally banded at a long-term monitoring site in central Indiana between 2002 and 2012. The white-nose infection year, distance, and direction is listed for each cave. Caves are grouped by proximity to our study area and represent two major hibernacula concentrations in Indiana.Impacts of WNS Table S4 Jan. 2017Parameter estimates, standard errors, z-values, and P-values for model parameters in the count portion of the final zero-inflated model predicting bat captures at a long-term monitoring site in central Indiana (2002–2014).Impacts of WNS Table S5 Jan. 2017Parameter estimates, standard errors, z-values, and P-values for model parameters in the logistic portion of the final zero-inflated model predicting bat captures at a long-term monitoring site in central Indiana (2002–2014).Impacts of WNS Table S3 Nov. 2016List of factors and distributions for zero-inflated mixed models used to predict bat captures at a long-term monitoring site in central Indiana (2002–2014). The most supported model, as shown by likelihood ratio tests, is the full model with a negative binomial distribution, Model 4.Impacts of WNS Table S6 Jan. 2017Data containing information on bat captures from 2002 to 2014 organized by site visit for a long-term monitoring study in central Indiana.1109_1_cover_art_24433_11y1l1.cs