We examined ‘ōpe‘ape‘a, or Hawaiian hoary bat (Lasiurus semotus; Chiroptera: Vespertilionidae), acoustic activity and surveyed potential roost trees at the Ford Island Chief Petty Officer’s (CPO) Bungalows Neighborhood of Pearl Harbor National Memorial (PERL) on the island of O‘ahu. We established four acoustic monitoring stations (PERL1–PERL4) that operated nightly to survey for ‘ōpe‘ape‘a echolocation activity from June to December 2024. Tree physiognomy data were collected at 12 potential roost trees and included tree species, tree height, diameter at breast height (DBH), percent canopy cover, distance to nearest tree, elevation, and canopy geometry. We collected 357,802 acoustic files over 672 station-nights across the four acoustic monitoring stations. ‘Ōpe‘ape‘a echolocation activity was detected over a total of 26 (4%) station-nights and during each month of the survey period except June. Echolocation activity peaked in September and October 2024, which is during the post-lactation and fledging period. These results represent a baseline for assessing ‘ōpe‘ape‘a acoustic activity and potential roosting resources in PERL.

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.

We examined acoustic activity of the endangered Hawaiian hoary bat ('ōpe'ape'a; Lasiurus semotus) at at Pearl Harbor National Memorial (PERL) located on Ford Island, O‘ahu, Hawaii. The study area was located at the Ford Island Chief Petty Officer's (CPO) Bungalows Neighborhood, which covers approximately 4 acres and includes five historic CPO bungalows. Bat echolocation vocalizations were recorded at four acoustic stations (PERL1 - PERL4) located between 20 and 25 m above sea level, that operated nightly from June 2024 through December 2024. At station PERL-1 a total of 176 nights were sampled acoustically with 'ōpe'ape'a activity detected on seven nights. A total of nine 'ōpe'ape'a echolocation call events, zero feeding buzzes, and zero occurrences of multiple bats were documented. At station PERL-2 a total of 173 nights were sampled acoustically with 'ōpe'ape'a activity detected on seven nights. A total of eight 'ōpe'ape'a echolocation call events, zero feeding buzzes, and zero occurrences of multiple bats were documented. At station PERL-3 a total of 148 nights were sampled acoustically with 'ōpe'ape'a activity detected on six nights. A total of six 'ōpe'ape'a echolocation call events, zero feeding buzzes, and zero occurrences of multiple bats were documented. And finally, at station PERL-4 a total of 164 nights were sampled acoustically with 'ōpe'ape'a activity detected on six nights. A total of seven 'ōpe'ape'a echolocation call events, zero feeding buzzes, and zero occurrences of multiple bats were documented.

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.

Bat Acoustical Monitoring data collected at six National Park units in 2017. Appomattox Court House National Historical Park, Booker T. Washington National Monument, Fredericksburg and Spotsylvania County Battlefields Memorial National Military Park, Petersburg National Battlefield, Richmond National Battlefield Park, Shenandoah National Park were surveyed using Acoustic recording equipment and analyzed using Kaleidoscope Pro Software by staff at the USGS Virginia Cooperative Fish and Wildlife Research Unit and Virginia Polytechnic Institute and State University.

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.

Bat Acoustical Monitoring data collected at six National Park units in 2016. Appomattox Court House National Historical Park, Booker T. Washington National Monument, Fredericksburg and Spotsylvania County Battlefields Memorial National Military Park, Petersburg National Battlefield, Richmond National Battlefield Park, Shenandoah National Park were surveyed using Acoustic recording equipment and analyzed using Kaleidoscope Pro Software by staff at the USGS Virginia Cooperative Fish and Wildlife Research Unit and Virginia Polytechnic Institute and State University.

Bat community data were collected in various watersheds in Olympic National Park. This data set contains records of acoustic detections, physical measurements, and reproductive attributes of the species of bats observed from 1998 to 2000. In addition to call detections and physical attributes, vegetation is characterized at each sampling site, and precipitation, weather and lunar phases are described for each sampling period.