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Bethany R. Straw

Publications and source records attributed to Bethany R. Straw.

14 recordsLinked to original sources
USGS2026

Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines

Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.

Ecological Informatics↗
USGS2026

Evaluating evidence of changing regional occupancy of four bat species in response to forest management practices

Coordinated, regional strategies to guide effective management and conservation of forests can be used to balance conservation with management for other objectives such as timber, scenic viewsheds, and fire. A key part of these regional strategies is incorporating knowledge of how management actions may affect certain species, especially those that are sensitive or are of concern. However, knowledge of how management actions may affect species is inferred from studies conducted across small areas where the species’ behavior and forest conditions are easily assessed. Here, we examine how occupancy of four bat species responds to forest management across the eastern United States at regional scales. We used range-wide capture and stationary acoustic surveys from the North American Bat Monitoring Program from 2010 to 2020 to estimate yearly summer occupancy for four bat species of conservation concern identified in the U.S. Department of Agriculture Forest Service (USFS) Southern and Eastern Regions Bat Conservation Strategy: little brown bat ( Myotis lucifugus ), northern long-eared bat ( Myotis septentrionalis ), Indiana bat ( Myotis sodalis ), and tricolored bat ( Perimyotis subflavus ), and assessed the degree to which occupancy of each species changed after different vegetation management actions were implemented on USFS lands. We identified 78 different management actions that were hypothesized to influence summer bat occupancy at two spatial scales (5-km and 10-km) across the eastern United States from the Forest Service Activity Tracking System and grouped these management actions into four vegetation management types: clear-cutting, fire, thinning, and ground vegetation management. To evaluate potential effects of these vegetation management types on bat occupancy, we created a yearly management metric representing the average number of years that had passed since any one of the included management actions in each management type had been implemented in each 5-km or 10-km grid cell, weighted by the proportion of the grid cell covered by the management treatment history. We chose these metrics to ask if more management or management done recently had a larger effect on bat occupancy than less management or management done long-ago. We then fit Bayesian hierarchical multi-scale occupancy models for each species to assess how occupancy changed in response to the amount and time since implementation of each vegetation management type. Using the estimated relationships between the yearly metrics of management and bat occupancy, we created predictions for how bat occupancy responded at 1- and 5- years after implementation. We found substantial differences in the response of the four species to the four vegetation management types. Ground vegetation management provided the greatest increase in expected occupancy at 1 year after implementation for little brown bat, long-eared bat, and tricolored bat, while fire provided the greatest increase in expected occupancy for Indiana bat. Thinning provided increases for all species at 1 year after implementation, but even greater increases at 5 years after implementation. Clear-cutting, on the other hand, tended to result in decreased occupancy at both 1- and 5-years after implementation for each species and had the greatest effect on tricolored bat at 1 year after implementation. Clear evidence for how management types like these may be affecting bat populations can be used at regional scales to help private and public forest managers achieve their strategic goals.

eastern United States↗
USGS2025

Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States

Historically, Myotis septentrionalis (Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).

Journal of North American Bat Research↗
USGS2025

Summer roost site suitability analyses for 4 special status bat species in the Eastern United States

Data describing habitat suitability are crucial for implementing effective conservation planning but are often lacking at regional and continental scales. We address this gap for 4 bat species that are listed, proposed for listing, or under Endangered Species Act listing review by highlighting a framework for estimating summer roost suitability with a presence-background approach to aid development of conservation policy and management plans. The 4 species of concern are the Little Brown Bat ( Myotis lucifugus ), the Northern Long-eared Bat ( M. septentrionalis ), the Indiana Bat ( M. sodalis ), and the Tricolored Bat ( Perimyotis subflavus ). Our estimates of summer roost suitability were developed for the eastern United States at a fine spatial resolution (250 m pixels) suitable for conservation planning across multiple scales. Summer roost habitat suitability was higher in areas with higher tree canopy cover for each of these species, though subtle differences were observed between the species that often use buildings (e.g., Little Brown Bat), tree crevices, cavities, and elements of dead or dying trees (e.g., Northern Long-eared Bat and Indiana Bat), and foliage (e.g., Tricolored Bat). To this end, roost suitability was not identical among species, and each showed subtly different relationships to the environmental covariates considered here. We also use a novel approach, gradient surface metrics, to quantify differences in the spatial pattern of summer roost suitability among the 4 species and found that tricolored bats and northern long-eared bats showed the most homogeneous and spatially smooth habitat suitability surfaces. Estimates of summer roost suitability developed here were also used to identify areas of good summer habitat where our models showed the least uncertainty that may be beneficial for targeted conservation, such as limiting disturbance to potential roost habitat. We also identified areas where additional data would benefit future summer roost modeling efforts. This work provides a first step toward developing multistate inventories of summer roost habitat suitable for implementing effective conservation planning at multiple scales.

Journal of Mammalogy↗
USGS2025

Integrated distribution modeling resolves asynchrony between bat population impacts and occupancy trends through latent abundance

Monitoring populations is challenging for cryptic species with seasonal life cycles, where data from multiple field techniques are commonly collected and analyzed as multiple lines of evidence. Data integration can provide comprehensive inferences while improving accuracy, precision, and scope but faces challenges in modeling misaligned resolutions and observational uncertainties. We developed a multi-scale, integrated species distribution model (MS-iSDM) for North American bats to combine data across monitoring types and seasons using joint likelihood methods, observational models with false-negatives and false-positives, and seasonal migratory connectivity. We applied this model to 11 years of data for an imperiled bat species (tricolored bat, Perimyotis subflavus ). Relative abundance and occupancy were linked with multi-scale predictors, revealing clear patterns of population declines, but with important differences in spatial trends (abundance: corresponded with white-nose syndrome impacts, occupancy: at the range periphery) and overall severity (abundance: -74.8%, 95% CRI: -79.7% to -69.3%; occupancy: -35.5%, 95% CRI: -41.1% to -30.2%). The asynchrony between occupancy trends and population impacts was explained as an emergent pattern of spatiotemporal variation in abundance in the integrated distribution model. Compared to multiple lines of evidence, the integrated model provided consensus-estimates, increased precision and spatiotemporal scope, and strengthened evidence of population declines.

Communications Biology↗
USGS2024

Using mobile acoustic monitoring and false-positive N-mixture models to estimate bat abundance and population trends

Estimating the abundance of unmarked animal populations from acoustic data is challenging due to the inability to identify individuals and the need to adjust for observation biases including detectability (false negatives), species misclassification (false positives), and sampling exposure. Acoustic surveys conducted along mobile transects were designed to avoid counting individuals more than once, where raw counts are commonly treated as an index of abundance. More recently, false-positive abundance models have been developed to estimate abundance while accounting for imperfect detection and misclassification. We adapted these methods to model summertime abundance and trends of three species of bats at multiple spatial scales using acoustic recordings collected along mobile transects by partners of the North American Bat Monitoring Program (NABat) from 2012 to 2020. This multiscale modeling spanned individual transect routes, larger NABat grid cells (10 km × 10 km), and across the entire extent of modeled species ranges. We estimated relationships between species abundances and a suite of abiotic and biotic predictors (landcover types, climatological variables, physiographic diversity, building density, and the impacts of white-nose syndrome [WNS]) and found varying levels of support between species. We present clear evidence of substantial declines in populations of tricolored bats ( Perimyotis subflavus ) and little brown bats ( Myotis lucifugus ), declines that corresponded in space and time with the progression of WNS, a devastating disease of hibernating bats. In contrast, our analysis revealed that similar population-wide declines probably have not occurred in big brown bats ( Eptesicus fuscus ), a species known to be less affected by WNS. This study provides the first abundance-based species distribution predictions and population trends for bats in their summer ranges in North America. These models will probably be applicable to assessing wildlife populations in other monitoring programs where acoustic data are used or where false-negative and false-positive detections are present. Finally, our abundance framework (as a spatial point pattern process) can serve as a foundation from which more sophisticated integrated species distribution models that incorporate additional streams of monitoring data (e.g., stationary acoustics, captures) can be developed for North American bats.

Ecological Monographs↗
USGS2022

North American Bat Monitoring Program (NABat) mobile acoustic transect surveys standard operating procedure 1—Locating and establishing mobile transect routes

This document is the first of three standard operating procedures (SOPs) providing instructions and considerations for conducting mobile acoustic surveys along road transects to collect bat acoustic data following the North American Bat Monitoring Program (NABat) protocol and sample design. This SOP focuses specifically on selecting NABat grid cells and establishing mobile transect survey routes using online tools available through the NABat Partner Portal. Intended audiences for this document include those in charge of facilitating surveys within their region (for example, State or provincial managers, and NABat regional hub coordinators), and project leaders or survey coordinators responsible for setting up and organizing NABat mobile transect monitoring for their organization or area.

Techniques and Methods↗
USGS2022

North American Bat Monitoring Program (NABat) Mobile Acoustic Transect Surveys Standard Operating Procedure 2—Field Season and Survey Preparation

This document is the second of three standard operating procedures providing instructions and considerations for conducting mobile acoustic surveys along road transects to collect bat acoustic data following the North American Bat Monitoring Program (NABat) protocol and sample design. This standard operating procedure focuses specifically on considerations for establishing the field survey season and preparing to conduct mobile acoustic transect surveys. Intended audiences for this document include those in charge of facilitating surveys within their region (for example, state or provincial mangers and NABat regional hub coordinators), project leaders or survey coordinators responsible for setting up and organizing NABat mobile transect monitoring for their organization or area, and field staff preparing to conduct surveys within the field.

Techniques and Methods↗
USGS2022

North American Bat Monitoring Program (NABat) mobile acoustic transect surveys standard operating procedure 3—Conducting mobile transect surveys

This standard operating procedure (SOP) provides instructions and considerations for conducting mobile acoustic surveys along road transects to collect bat acoustic data following the North American Bat Monitoring Program (NABat) protocol and sample design. This report discusses measures for ensuring the safety of surveyors and efficiency of mobile transect surveys. This guidance is intended to aid surveyors in equipment setup and operation, including how to mount and orient equipment. Finally, this document provides guidance on driving the route, performing end of survey procedures, and steps for data management.

Techniques and Methods↗
USGS2022

NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions. Here, we present NABat ML , an automated machine-learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet-based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted-average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud-environment computing instance, the entire model training process took <16 h. Synthesis and applications . Our convolutional neural network (CNN)-based model, NABat ML , classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species-level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open-source and reproducible, enabling future implementations as software on end-user devices and cloud-based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big-data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad-scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.

Journal of Applied Ecology↗
USGS2022

Status and trends of North American bats: Summer occupancy analysis 2010-2019

• We developed an analytical pipeline supported by web-based infrastructure for integrating continental scale bat monitoring data (stationary acoustic, mobile acoustic, and capture records) to estimate summer (May 1–Aug 31) occupancy probabilities and changes in occupancy over time for 12 North American bat species. This serves as one of multiple lines of evidence that inform the status and trends of bat populations. • We analyzed data from a total of 12 bat species (Table 1), 11 of which have tested positive for Pseudogymnoascus destructans (Pd), a fungal pathogen that causes white-nose syndrome (WNS)—a disease that has led to significant rates of mortality for subterranean hibernating bat species in North America. A twelfth species was also selected because of high rates of mortality at wind energy facilities. Additional species were considered but not selected due to data limitations. • We estimated occupancy probabilities for 2010 through 2019 for three species ( Myotis lucifugus , MYLU; Myotis septentrionalis , MYSE; and P erimyotis subflavus , PESU). For an additional nine species, we estimated occupancy probabilities for 2016 through 2019 ( Myotis evotis , MYEV; Myotis grisescens , MYGR; Myotis leibii , MYLE; Myotis thysanodes , MYTH; Myotis volans , MYVO; Myotis yumanensis , MYYU; Eptesicus fuscus , EPFU; Lasionycteris noctivagans , LANO; and Lasiurus cinereus , LACI). • For each species, we provide range-wide occupancy probability predictions (e.g., predicted summer occupancy distribution maps) each year at a spatial resolution of 100 km2 and provide regional estimates of mean occupancy probability aggregated at larger spatial scales (state/province/territory, range-wide). • For each species, we also provide trends over time (average annual change rate and total change rate) in mean occupancy probabilities at multiple spatial scales (state/province/territory, range-wide) and when possible, over multiple timescales (short, medium, long). • Results suggest that over the short-term (2016-2019), two ( Myotis lucifugus and Perimyotis subflavus ) of 12 species have experienced declines in range-wide average occupancy probability with at least 95% certainty. Seven species showed either minor increases or decreases in range-wide average occupancy probability but with less than 95% certainty in both trend indicators. Results over the longer term (eight years and 10 years of sampling) suggest that three hibernating species known to be highly affected by white-nose syndrome ( Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus ) have experienced marked declines in range-wide average occupancy probabilities, with severity varying by species and region. Finally, the results for three species ( Eptesicus fuscus , Lasiurus cinereus , Lasionycteris noctivagans ) were inconclusive due to 1) borderline convergence issues in the model fitting procedure which suggests potentially unreliable estimates, 2) failure to reliably distinguish between false positives and true positive detections for ambiguous detections, and 3) largely uninformative covariates for occupancy and detection. • For Myotis lucifugus , Myotis septentrionalis , and Perimyotis subflavus we found meaningful associations in space and time between declining winter populations (likely a result of WNS) and summer occupancy distributions. • The representativeness of sampling data for each species’ status and trend estimates (e.g., state/province/territory) were also evaluated based on the percent of grid cells sampled each year with a goal of understanding the reliability of regional estimates and improving future monitoring efforts. • This work represents the most comprehensive effort to date to model North American bat distributions across their continental ranges. Despite current limitations highlighted in the discussion, the analytical methods and resulting status and trends estimates provide the best available science on summer bat populations across North America and will continue to improve over time as monitoring data sets and analytical methods improve. • Moving forward, our occupancy analyses will continue to improve with submission of more 1) data from currently underrepresented areas (i.e., improved geographic representation), 2) manually-vetted acoustic recordings, 3) capture records, and 4) roost location and count data (summer and winter).

Report↗
USGS2021

Acoustic and genetic data can reduce uncertainty regarding populations of migratory tree-roosting bats impacted by wind energy

Wind turbine-related mortality may pose a population-level threat for migratory tree-roosting bats, such as the hoary bat ( Lasiurus cinereus ) in North America. These species are dispersed within their range, making it impractical to estimate census populations size using traditional survey methods. Nonetheless, understanding population size and trends is essential for evaluating and mitigating risk from wind turbine mortality. Using various sampling techniques, including systematic acoustic sampling and genetic analyses, we argue that building a weight of evidence regarding bat population status and trends is possible to (1) assess the sustainability of mortality associated with wind turbines; (2) determine the level of mitigation required; and (3) evaluate the effectiveness of mitigation measures to ensure population viability for these species. Long-term, systematic data collection remains the most viable option for reducing uncertainty regarding population trends for migratory tree-roosting bats. We recommend collecting acoustic data using the statistically robust North American Bat Monitoring Program (NABat) protocols and that genetic diversity is monitored at repeated time intervals to show species trends. There are no short-term actions to resolve these population-level questions; however, we discuss opportunities for relatively short-term investments that will lead to long-term success in reducing uncertainty.

Animals↗
USGS2021

Influencing activity of bats by dimly lighting wind turbine surfaces with ultraviolet light

Wind energy producers need deployable devices for wind turbines that prevent bat fatalities. Based on the speculation that bats approach turbines after visually mistaking them for trees, we tested a potential light-based deterrence method. It is likely that the affected bats see ultraviolet (UV) light at low intensities. Here, we present the results of a multi-month experiment to cast dim, flickering UV light across wind turbine surfaces at night. Our objectives were to refine and test a practical system for dimly UV-illuminating turbines while testing whether the experimental UV treatment influenced the activity of bats, birds, and insects. We mounted upward-facing UV light arrays on turbines and used thermal-imaging cameras to quantify the presence and activity of night-flying animals. The results demonstrated that the turbines can be lit to the highest reaches of the blades with “invisible” UV light, and the animal responses to such experimental treatment can be concurrently monitored. The UV treatment did not significantly change nighttime bat, insect, or bird activity at the wind turbine. Our findings show how observing flying animals with thermal cameras at night can help test emerging technologies intended to variably affect their behaviors around wind turbines.

Animals↗