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Brian E. Reichert

Publications and source records attributed to Brian E. Reichert.

At least 19 recordsLinked to original sources
USGS2026

Bayesian model selection to investigate meaningful spatial scales

Ecologists and other statistical practitioners with access to high-resolution spatial data often lack guidance on best approaches for discerning meaningful spatial scales for environmental covariates which is necessary when spatial factors influence environmental processes. Recently developed methods have attempted to automate investigating spatial scales for covariates by evaluating models for which potential explanatory variables are derived from circular extents of increasing size centered at survey locations. However, these methods make a strong assumption on the inclusion of the covariate and do not help discern whether a covariate should be included in the model. We present an approach that utilizes researcher guidance to create informative priors on the model space that, along with parallelizable Reversible Jump Markov chain Monte Carlo techniques, enables efficient estimation of posterior model probabilities to assist with the choice of meaningful spatial scales for environmental covariates.

Ecology and Evolution↗
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

Estimating disease prevalence from preferentially sampled, pooled data

After the onset of the COVID-19 pandemic, scientific interest in coronaviruses endemic in animal populations has increased dramatically. However, investigating the prevalence of disease in animal populations across the landscape, which requires finding and capturing animals can be difficult. Spatial random sampling over a grid could be extremely inefficient because animals can be hard to locate, and the total number of samples may be small. Alternatively, preferential sampling, using existing knowledge to inform sample location, can guarantee larger numbers of samples, but estimates derived from this sampling scheme may exhibit bias if there is a relationship between higher probability sampling locations and the disease prevalence. Sample specimens are commonly grouped and tested in pools which can also be an added challenge when combined with preferential sampling. Here we present a Bayesian method for estimating disease prevalence with preferential sampling in pooled presence-absence data motivated by estimating factors related to coronavirus infection among Mexican free-tailed bats ( Tadarida brasiliensis ) in California. We demonstrate the efficacy of our approach in a simulation study, where a naive model, not accounting for preferential sampling, returns biased estimates of parameter values; however, our model returns unbiased results regardless of the degree of preferential sampling. Our model framework is then applied to data from California to estimate factors related to coronavirus prevalence. After accounting for preferential sampling impacts, our model suggests small prevalence differences between male and female bats.

California↗
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↗
USGS2025

Predicting bat roosts in bridges using Bayesian Additive Regression Trees

Human-built structures can provide important habitat for wildlife, but predicting which structures are most likely to be used remains challenging. To evaluate the predictive capabilities of data-driven ensemble modeling approaches, we conducted surveys for bats and signs of bat use, such as urine and guano staining, at bridges across the southwestern United States. We developed a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that the lack of nearby water resources was associated with a lower predicted probability of bat presence or signs of bat use at bridges. While the presence of nearby water resources was associated with higher average predicted probability of bat presence or signs of bat use, high uncertainty surrounding these estimates indicates that other factors also play a role in determining which bridge roosts bats are more likely to use. As such, our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. We extrapolated our model to unsurveyed bridges across the study region and provide an interactive dashboard application interface for the exploration of these results. Overall, this study demonstrates the application of BART as a predictive tool for prioritizing future bridge surveys for bats roosting in transportation structures.

Arizona, California, Nevada, New Mexico, Texas↗
USGS2025

A novel method for estimating pathogen presence, prevalence, load, and dynamics at multiple scales

The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as ‘inconclusive’ and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling for Pseudogymnoascus destructans (Pd) , the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence of Pd at bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM’s results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM’s estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had been Pd positive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding of Pd dynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability.

Scientific Reports↗
USGS2025

Bayesian model selection to investigate meaningful spatial scales

Ecologists and other statistical practitioners with access to high-resolution spatial data lack guidance on best approaches for discerning meaningful spatial scales for environmental covariates which is necessary when spatial factors influence environmental processes. Recently developed methods have attempted to automate investigating spatial scales for covariates by evaluating models for which potential explanatory variables are derived from concentric circles of increasing size centered at survey locations. However, these methods make a strong assumption on the inclusion of the covariate and do not help discern whether a covariate should be included in the model. We present an approach that utilizes researcher guidance to create informative priors on the model space that, along with parallelizable Reversible Jump MCMC techniques, enables efficient estimation of posterior model probabilities to assist with the choice of meaningful spatial scales for environmental covariates.

Authorea↗
USGS2024

The state of the bats in North America

The world's rich diversity of bats supports healthy ecosystems and important ecosystem services. Maintaining healthy biological systems requires prompt identification of threats to biodiversity and immediate action to protect species, which for wide-ranging bat species that span geopolitical boundaries warrants international coordination. Anthropogenic forces drive the threats to bats throughout North America and the world. We conducted an international expert elicitation to assess the status of 153 bat species in Canada, the United States, and Mexico. We used expert assessment to determine the conservation status, highest impact threats, and recent population trends for these species. We found that 53% of North American bat species have moderate to very high risk of extinction in the next 15 years. The highest impact threats varied with species and country, and four IUCN threat categories had the greatest overall impacts: Climate Change, Problematic Species (including disease), Agriculture, and Energy Production. Experts estimated that 90% of species assessed had decreasing population trends over the past 15 years, demonstrating the need for conservation action. Although the state of North American bats is concerning, we identify threats that can be addressed through internationally collaborative, proactive, and protective actions to support the recovery and resilience of North American bat species.

Annals of the New York Academy of Sciences↗
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↗
USGS2024

Understanding gaps in early detection of and rapid response to invasive species in the United States: A literature review and bibliometric analysis

While concepts regarding invasive species establishment patterns and eradication possibilities have long been a topic of invasion biology, the specific terminology referring to early detection of and rapid response to (EDRR) invasive species emerged in scientific literature during the early 2000s. Since then, the EDRR approach has expanded to include a suite of detection, planning, and management tools. By conducting a systematic literature review, we attempt to characterize the field of EDRR in the United States and its territories as reflected by publication records. Specifically, we assessed publication data such as the number of publications per year, the most common journals where papers were published, and the relationship between author’s keywords for studies focusing on aquatic and terrestrial habitats. For publications that used invasive species occurrence or abundance data (whether collected for the purposes of the respective publication or acquired from another data source), we manually vetted additional information such as focal taxa, data collection years and locations, sources of other data used, and whether data or code were deposited in open access formats. We also conducted network analyses for the author institutions that coauthored papers together most frequently and for the references most cited by EDRR publications. Overall, we found that silos existed in terms of which author institutions worked together, which existing literature was cited, and which topics were frequently explored. We also found evidence of substantial gaps in data access and use. For example, although a wide variety of data sources for invasive species occurrences are available, these sources were seldom cited by published literature, and newly collected data was not often deposited into invasive species databases or other open-source data repositories. Considering the continued advocation for a centralized national EDRR information system, our study suggests that facilitating access to data, decision support tools, and other informational resources represents a key opportunity for improving EDRR capabilities.

Ecological Informatics↗
USGS2023

Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States

Executive Summary In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin. The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change. Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources. Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands. The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert). Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats. The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level. The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗
USGS2023

America's most wanted fishes: Cataloging risk assessments to prioritize invasive species for management action

Hundreds of fish species enter the United States through human intervention (e.g., importation) and some of these fishes pose a substantial risk to the nation’s assets and ecosystems. Prevention, early detection, and rapid response (EDRR) are vital to stop species invasions, but time and resources to manage the large suite of fish species that enter the nation are limited. Evaluating the risk of a species’ invasion in a location is one way to prioritize among many species for management action. Species risk assessments are often associated with information systems or are published within grey literature or peer-reviewed journal articles. Improving access to available risk assessments could help in prioritizing management action for the most potentially invasive fish species. We aggregated fish species risk assessments, synthesizing the current knowledge on the risk of fish invasions in the United States. To accomplish this, we searched information systems and conducted a literature review. We then summarized risk assessment results along with the importation statuses of fish species and identified if imported, high-risk species are managed under federal or state policy. Within the scope of the conterminous U.S., we found 98 high-risk fish species. Eighteen of these species are imported to the country, but only three species have been recently prohibited from importation according to the Lacey Act. We observed similar patterns at the scales of the Great Lakes region and Florida. Collectively, our work provides a baseline estimate of the high-risk fish invaders that enter the U.S. through importation, underscoring species to consider for priority management action, as well as a benchmark of species that lack risk assessments. Insights from this work can be enriched when joined with other invasive species information, which could be accomplished through a national EDRR information system, an information sharing hub in development by the U.S. Geological Survey.

Management of Biological Invasions↗
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↗