DOI: 10.5061/dryad.cf273
title: Data from: Impacts of white-nose syndrome observed during long-term monitoring of a midwestern bat community

description: 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 &gt;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.
description: 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.csv