Through the North American Bat Monitoring Program, Bat Conservation International and U.S. Geological Survey (USGS) collaborated with the U.S. Fish and Wildlife Service to provided technical and science support to assistance in U.S. Fish and Wildlife Services’ Species Status Assessment (“SSA”) for the northern long-eared bat (Myotis septentrionalis), little brown bat (Myotis lucifugus), and tri-colored bat (Perimyotis subflavus). We conducted analyses to estimate changes in bat echolocation activity recorded during mobile transect surveys. Bat activity recorded during mobile acoustic transects provide an index of abundance and can be used to determine changes in populations over time (Roche et al. 2011, Jones et al. 2013). We hypothesized that mobile transect surveys would detect changes in populations for Myotis lucifugus, Myotis septentrionalis, and Perimyotis subflavus over the past decade related to two main stressors on North American bat populations: the emergence of White-nose Syndrome (WNS) and increases in installed wind energy facilities. We obtained data stored in the North American Bat Monitoring Program (NABat) (U.S. Fish and Wildlife Service, 3-Species Status Assessment - Mobile Transect Acoustic Monitoring Data Accessed 2020-11-23. NABat Request Number 11. Database Version v5.3.0), West Virginia (West Virginia Division of Natural Resources), and New York (New York State Department of Environmental Conservation). West Virginia and New York have mobile acoustic sampling programs that began in 2009 but their mobile acoustic data have not been contributed to the NABat Program database. These data were joined with stressor and habitat covariates (year of Pd arrival, wind energy risk index, habitat composition) with SSAmobile_04_combineData.R. A dataset for each species was created by filtering for grid cells within a species range (as defined by the USFWS). The following data were removed from final analyses: • Data from Canada were removed due to our inability to calculate a comparable wind energy index in Canada (see below) • Data collected from September to April as this does not represent the summer maternity season • Data where no observations of a species were recorded on any run at a site (i.e., all zeros) were removed to prevent zero inflation • Sites with only one run were removed due to the lack of information they provide for trend analysis. Note: Sites with multiple runs within a single year were retained for analysis because these data provide information on the effect of day of year and sampling variability. To determine changes in bat populations, we first modeled bat activity as counts of echolocation call sequences recorded along mobile acoustic transects. We used three categories of variables to model the count of call sequences along a transect: 1) Stressors to populations — We examined the influence of WNS and wind energy development over time 2) Spatial variation in activity — We used latitude, longitude, and habitat covariates to account for changes in activity across landscapes 3) Sampling variation — We accounted for day of year, sampled transect length, detector type, and ID software used. We then predicted the number of call sequences at each spatial scale and year. Finally, we derived the rate of change in population from the change in the predicted number of call sequences.

Through the North American Bat Monitoring Program, Bat Conservation International and U.S Geological Survey (USGS) provided technical and science support to assistance in U.S. Fish and Wildlife Service Species Status Assessment (“SSA”) for the northern long-eared bat (Myotis septentrionalis), little brown bat (Myotis lucifugus), and tri-colored bat (Perimyotis subflavus). USGS facilitated the SSA data call providing data archival for repeatable and transparent analyses, provided statistical support to assess the historical, current, an future population status for each of the three species, and developed a demographic projection tool to evaluate future viability of each species under multiple threat scenarios. We assessed population trends from count surveys of wintering colonies at hibernacula for these three bat species. Winter colony counts were downloaded from the database of the North American Bat Monitoring Program (U.S. Geological Survey North American Bat Monitoring Program. Accessed 2020-12-01. NABat Request Number 12. Database Version v5.4.0).

Through the North American Bat Monitoring Program, Bat Conservation International and U.S Geological Survey (USGS) provided technical and science support to assistance in U.S. Fish and Wildlife Service Species Status Assessment (“SSA”) for the northern long-eared bat (Myotis septentrionalis), little brown bat (Myotis lucifugus), and tri-colored bat (Perimyotis subflavus). USGS facilitated the SSA data call providing data archival for repeatable and transparent analyses, provided statistical support to assess the historical, current, an future population status for each of the three species, and developed a demographic projection tool to evaluate future viability of each species under multiple threat scenarios. We assessed population trends from count surveys of wintering colonies at hibernacula for these three bat species. Winter colony counts were downloaded from the database of the North American Bat Monitoring Program (U.S. Geological Survey North American Bat Monitoring Program. Accessed 2020-12-01. NABat Request Number 12. Database Version v5.4.0).

US Geological Survey and National Park Service researchers designed and implemented an acoustic monitoring program for bats in the three large parks of Western Washington, all part of the North Coast and Cascades Network (NCCN) of National Parks.This work was part of the larger NCCN bat population monitoring and white-nose syndrome (WNS) surveillance program, designed to understand bat distribution, activity, and disease dynamics on the leading edge of WNS spread in the state. Data were collected throughout each park along elevational, precipitation, and seasonal gradients. This monitoring program examines questions of interest at the national, regional, and park scale to increase the understanding of bat distribution, occurrence, and seasonal/annual dynamics before extensive spread of WNS in the state. This data release contains acoustic detections of bat species in Mount Rainier National Park during 2019-2020 monitoring.

Microsoft Access database contains mobile acoustic bat detections along road-based transects on NWRs and several Ecological Service Field Offices. Species identification was based on BCID version 2.7c software. Call id was constrained to a minimum of five pulses and a time between calls of 1 second. Routes were not created based on the NABat grid priority. Database contains survey data, call classifications, point locations and route metrics. Each route used a site level filter to minimize false positive and negative detections.

US Geological Survey and National Park Service researchers designed and implemented an acoustic monitoring program for bats in the three large parks of Western Washington, all part of the North Coast and Cascades Network (NCCN) of National Parks.This work was part of the larger NCCN bat population monitoring and white-nose syndrome (WNS) surveillance program, designed to understand bat distribution, activity, and disease dynamics on the leading edge of WNS spread in the state. Data were collected throughout each park along elevational, precipitation, and seasonal gradients. This monitoring program examines questions of interest at the national, regional, and park scale to increase the understanding of bat distribution, occurrence, and seasonal/annual dynamics before extensive spread of WNS in the state. This data release contains acoustic detections of bat species in North Cascades National Park during 2019-2020 monitoring.

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This dataset contains results from acoustic monitoring for bats at 276 sites across the Great Lakes basin and Upper Midwest From 2010 - 2018. These data provide information on the magnitude, timing, and species composition of bat activity across the region. These data were collected by the US Fish and Wildlife Service Region 3 Avian Radar Team (https://www.fws.gov/radar) funded by the Great Lakes Restoration Initiative, as well as USFWS Field Offices, the University of Minnesota, and various collaborators including Bat Conservation International, Texas Christian University, US Geological Survey, Western Ecosystems Technology Inc., and organizations listed here: https://www.fws.gov/radar/links/index.html METHODS: All detectors (Wildlife Acoustics SM2Bat+) were deployed at approximately 1 m above ground level on fence posts or existing structures. PVC cups were placed around microphones to block extraneous ground noise but allow acoustic signals from overhead. Detectors were not placed beneath completely closed canopy where possible, to provide partially or fully open sky above. Detectors ran autonomously for 10 - 14 days on external batteries. Recordings were made via triggering operation under default settings with a 1 s trigger window, recording to 15-minute WAC compressed files. A low-pass filter excluding sounds below 16 kHz was applied. Data were recorded to SD cards and transferred to headquarters by field personnel. WAC files were decompressed using WAC2WAV utility, with split triggers ON. Kaleidoscope Pro v. 4.3.2 (-1 liberal setting) was used for species identification, with species classifiers (the group of species included in analysis as potential species to be identified) selected for each site using IUCN range maps, plus a 50 km buffer. Automated species identifications have not been manually vetted for accuracy, and may contain false identifications. Nightly Pass Counts represent only nights when 8 or more WAC files (indicating 2 hours or more of detector operation) were recorded. Nights with fewer than 8 WAC files, or with data that indicated detector malfunction were removed from Nightly Pass Counts, but may be represented in Pass Lists. For more information on data collection, please refer to: Heist KW. Assessing bat and bird fatality risk at wind farm sites using acoustic detectors. PhD Dissertation, University of Minnesota. 2014.

These data were compiled as part of an effort to compare the relative data quality and modeling performance of bat data recorded with two different acoustic detectors. The objective of our study was to construct models evaluating the relative predictive quality of data collected by these two detectors. These data represent 48 paired sampling events where acoustic bat data was collected using a Song Meter SM4 Acoustic Recorder and with an Echo Meter Touch 2 bat detector in parallel with sampling insect prey using a light trap. These data were collected in Grand Canyon National Park between April 17 and October 10, 2022. These data were collected by several river guides through a community science program organized by the U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and Research Center. These data can be used to compare the two acoustic methods to each other and relative to insect prey catch rates.