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USGS2026

Improved estimates of relative occurrence and abundance using opportunistic surveys and presence-only observations: A zero-inflated integrated species distribution model

Modeling tools for estimating and forecasting shifts in species distributions are becoming increasingly valuable for conservation planning and response. This is especially true for wild bird populations, which have been declining across habitats and regions. Species distribution models (SDM) represent a diverse set of tools with options for addressing various sources of bias. Complex spatial processes associated with rare or clustered species can be accounted for using zero-inflated SDMs, whereas biased survey data can be integrated with additional data sources to improve estimates. Each option addresses an important and common source of bias, but the two SDM frameworks have not been implemented together previously. We present a novel zero-inflated extension of an integrated SDM framework for a Poisson regression (ZI-iSDM), allowing for the estimation of independent occurrence and abundance processes by integrating opportunistic survey and presence-only data. We validated performance of this ZI-iSDM using simulated datasets under different degrees of species rarity and density on the landscape as well as sampling bias in opportunistic datasets. We additionally applied this model to real survey data for multiple wild bird species using publicly available observation data combined with open-access environmental information to describe habitat associations. We found that integrating presence-only data, such as banding or harvest events, can compensate for potential deficiencies in opportunistic surveys by expanding sampling to be more representative of available and used habitat. Additionally, models that first differentiated occurrence and abundance using a ZI term were better suited for approximating distributions of spatially clustered species.

Ecological Modeling↗

USGS2026

Two-stage approach to automatic detection with machine learning for improved surveillance of the invasive Cuban treefrog

The Cuban treefrog ( Osteopilus septentrionalis ), as an invasive species in the southern United States, presents a need for effective surveillance. Automated detection expedites processing of audio data for large-scale surveillance and monitoring programs. However, current available methods commonly used for anuran species have not been sufficient to detect Cuban treefrogs. Here, we present results from a two-stage method for automated detection that employs both cross-correlation template matching and secondary supervised learning classifiers. In the first stage, audio data are screened for initial detections using template matching, in which the detections contain both true and false positives. In the second stage, the false positives are screened out using classifier algorithms. We used this method to process 139,985 audio recordings, consisting of 596,046 total minutes, collected at 13 locations in Louisiana and Florida from 2014 to 2022. From the stage 1 template matching, we detected 83,191 Cuban treefrog signals across recordings. The stage 2 machine learning model was able to identify stage 1 false positive detections with a testing accuracy of 98.46% and a testing false positive rate of 1.116%. After pruning false positive detections, a total of 20,271 individual Cuban treefrog detections remained, distributed mainly across 3 sites in an area with known presence. Locations with presumed absence had an easily verifiable number of false positive detections ( n = 109 across all other sites). The two-stage methodology utilizing both template matching and machine learning algorithms can be integrated into wildlife surveillance or monitoring programs for species with distinctive, conserved calls as an effective way to achieve sensitive species detection with a low incidence of false positives.

Florida, Louisiana↗

USGS2026

Per- and polyfluoroalkyl substances and pesticides in black bears (Ursus americanus) and grizzly bears (Ursus arctos horribilis) from Montana's Cabinet-Yaak ecosystem: A baseline assessment of emerging and legacy contaminants

Per- and polyfluoroalkyl substances (PFAS) and pesticides are globally distributed contaminants that persist in terrestrial food webs, yet baseline data for large omnivores in the continental U.S. remain limited. This study quantified PFAS and pesticides in whole blood from free-ranging black bears ( Ursus americanus , n = 15) and grizzly bears ( Ursus arctos horribilis , n = 9) in the Cabinet-Yaak Ecosystem of northwestern Montana. Using high-resolution mass spectrometry-based methods (GC-MS/MS and LC-MS/MS), 52 PFAS and 186 pesticides were analyzed. PFAS were detected in all bears, with total PFAS concentrations ranging from 79.5 to 317 pg/mL. PFAS profiles were dominated by long-chain perfluoroalkyl carboxylic acids, particularly PFOA, PFDA, and PFUnDA, with minimal contribution from short-chain compounds. Species was the strongest ecological predictor of PFAS concentrations, although variability across age, sex, and capture location were observed. Only two pesticides, piperonyl butoxide and permethrin, were detected at quantifiable concentrations (2070–12,600 pg/mL), and no correlations were observed between pesticide and PFAS concentrations, indicating independent exposure pathways. The predominance of long-chain PFAS suggests diffuse environmental sources and bioaccumulation within terrestrial food webs. Although measured concentrations were generally low relative to other wildlife toxicological studies, the persistence and protein-binding properties of long-chain PFAS warrant continued monitoring, particularly for long-lived omnivores. These results establish baseline contaminant concentrations for two apex omnivores in a remote ecosystem and highlight the utility of large mammals as integrative sentinels of environmental contaminant exposure for regional monitoring and wildlife conservation. Continued monitoring in the Cabinet-Yaak and across western North America will be critical for assessing temporal trends, identifying new contaminant sources, and evaluating ecological health in bear populations.

Montana↗

USGS2018

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken ( Tympanuchus pallidicinctus ) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

The Auk↗

USGS2019

Recruitment dynamics and reproductive ecology of Blue Sucker in Texas, with a focus on the Big Bend region of the Rio Grande

Blue Sucker Cycleptus elongatus is a state-listed threatened species in Texas and is considered vulnerable throughout its range. Once considered a single, wide-ranging species, blue suckers are now recognized as a complex of closely related, but genetically and morphologically distinct species within the genus Cycleptus , including an undescribed species within the Rio Grande Basin. Numerous factors likely are driving the decline of blue suckers in Texas, including flow alteration, water quality, habitat fragmentation, and changing land-use patterns, but it is not clear how these factors interact to influence the abundance and distribution of the species. Our research integrates a variety of methodologies to provide information critical to the conservation and management of Blue Sucker in the Sabine River (Texas and Louisiana) and Colorado River (Texas) and Rio Grande Blue Sucker Cycleptus sp. cf. elongatus in the Rio Grande. The objectives of this report are to 1) determine the habitat associations of the young-of-year (YOY) Rio Grande Blue Sucker; 2) assess the effects of flow regime on growth and recruitment of Blue Sucker in the lower Sabine River; and 3) examine differences in life-history traits of Blue Suckers and flow regime across river basins in Texas. This study is the first to quantitatively address the sequence of YOY blue sucker mesohabitat use and increases our understanding of early life history of blue suckers, and the results of this work will help to develop conservation and management strategies, e.g., prioritizing conservation areas, developing flow recommendation, etc., for blue suckers throughout their geographic distribution.

Texas↗

USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗

USGS2026

Environment, taxonomy, and socioeconomics predict non-imperilment in freshwater fishes

Freshwater fishes are among the most threatened taxa, yet conservation assessments remain incomplete for many species. Freshwater fishes provide essential ecosystem services such as food security, recreational opportunities, and cultural significance. Despite heavy alterations to freshwater ecosystems, the reasons for species’ sensitivity and resistance to imperilment are unclear. To address this need, we develop a machine learning framework to predict global imperilment status for 10,631 freshwater fish species using a comprehensive set of environmental, socioeconomic, and intrinsic species-level predictors. Using updated IUCN Red List data, we train and validate Random Forest classifiers to distinguish imperiled (Vulnerable, Endangered, Critically Endangered) from non-imperiled species. We examine the relative influence of 52 variables derived from 12 global sources describing extrinsic environmental and socioeconomic factors and intrinsic species-specific characteristics. Our models achieve higher accuracy for non-imperiled species (90.1%) compared to imperiled species (81.8%), reflecting the greater heterogeneity of threats and conditions driving imperilment. Across models, key predictors include habitat variables, taxonomic order, hydrological characteristics, and disturbance indicators, underscoring the interplay between ecology, geography, and human pressures. This integrative, reproducible approach demonstrates the utility of machine learning for guiding proactive conservation and provides a scalable framework for global biodiversity risk assessment.

Nature Communications↗

USGS2026

Plasticity in the reproductive biology of Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake following lake trout Salvelinus namaycush invasion

Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri in Yellowstone Lake are the focus of intensive conservation efforts due to the threat of predation by invasive lake trout Salvelinus namaycush . Suppression gillnetting has reduced the abundance of predatory lake trout, and the Yellowstone cutthroat trout population is recovering. Long-term monitoring indicates the size structure of the population shifted following lake trout invasion, suggesting that reproductive demographic rates of Yellowstone cutthroat trout may have changed. Length at 50% probability of maturity, as assessed using histological analysis of gonadal tissue, was 479 mm (95% confidence interval [CI] 467–490 mm) for females and 406 mm (95% CI 386–430 mm) for males, compared to 330 mm for males and females historically. Currently, age at 50% probability of maturity is 6.6 for females and 5.4 for males. The rate of skipped spawning was 3% for females and 38% for males. Mean absolute fecundity was 2897 ovarian follicles/individual at present compared to 1141 ovarian follicles/individual before lake trout invasion. Mean relative fecundity was 2157 ovarian follicles/kg. This research illustrates the plasticity in the reproductive strategies of fishes as a result of an invasive species. Understanding the reproductive biology of fish populations is vital for effective fisheries management, and these results are integral to a population model that can be used to develop new conservation benchmarks for Yellowstone cutthroat trout.

Wyoming↗

USGS2007

Second chance for the plains bison

Before European settlement the plains bison ( Bison bison bison ) numbered in the tens of millions across most of the temperate region of North America. Within the span of a few decades during the mid- to late-1800s its numbers were reduced by hunting and other factors to a few hundred. The plight of the plains bison led to one of the first major movements in North America to save an endangered species. A few individuals and the American Bison Society rescued the remaining animals. Attempts to hybridize cattle and bison when bison numbers were low resulted in extensive cattle gene introgression in bison. Today, though approximately 500,000 plains bison exist in North America, few are free of cattle gene introgression, 96% are subject to anthropogenic selection for commodity production, and only 4% are in herds managed primarily for conservation purposes. Small herd size, artificial selection, cattle-gene introgression, and other factors threaten the diversity and integrity of the bison genome. In addition, the bison is for all practical purposes ecologically extinct across its former range, with multiple consequences for grassland biodiversity. Urgent measures are needed to conserve the wild bison genome and to restore the ecological role of bison in grassland ecosystems. Socioeconomic trends in the Great Plains, combined with new information about bison conservation needs and new conservation initiatives by both the public and public sectors, have set the stage for significant progress in bison conservation over the next few years.

Biological Conservation↗

USGS2026

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗

USGS2022

Africa’s drylands in a changing world: Challenges for wildlife conservation under climate and land-use changes in the Greater Etosha Landscape

Proclaimed in 1907, Etosha National Park in northern Namibia is an iconic dryland system with a rich history of wildlife conservation and research. A recent research symposium on wildlife conservation in the Greater Etosha Landscape (GEL) highlighted increased concern of how intensification of global change will affect wildlife conservation based on participant responses to a questionnaire. The GEL includes Etosha and surrounding areas, the latter divided by a veterinary fence into large, private farms to the south and communal areas of residential and farming land to the north. Here, we leverage our knowledge of this ecosystem to provide insight into the broader challenges facing wildlife conservation in this vulnerable dryland environment. We first look backward, summarizing the history of wildlife conservation and research trends in the GEL based on a literature review, providing a broad-scale understanding of the socioecological processes that drive dryland system dynamics. We then look forward, focusing on eight key areas of challenge and opportunity for this ecosystem: climate change, water availability and quality, vegetation and fire management, adaptability of wildlife populations, disease risk, human-wildlife conflict, wildlife crime, and human dimensions of wildlife conservation. Using this model system, we summarize key lessons and identify critical threats highlighting future research needs to support wildlife management. Research in the GEL has followed a trajectory seen elsewhere reflecting an increase in complexity and integration across biological scales over time. Yet, despite these trends, a gap exists between the scope of recent research efforts and the needs of wildlife conservation to adapt to climate and land-use changes. Given the complex nature of climate change, in addition to locally existing system stressors, a framework of forward-thinking adaptive management to address these challenges, supported by integrative and multidisciplinary research could be beneficial. One critical area for growth is to better integrate research and wildlife management across land-use types. Such efforts have the potential to support wildlife conservation efforts and human development goals, while building resilience against the impacts of climate change. While our conclusions reflect the specifics of the GEL ecosystem, they have direct relevance for other African dryland systems impacted by global change.

Africa, Greater Etosha Landscape↗

USGS2012

Common coastal foraging areas for loggerheads in the Gulf of Mexico: Opportunities for marine conservation

Designing conservation strategies that protect wide-ranging marine species is a significant challenge, but integrating regional telemetry datasets and synthesizing modeled movements and behavior offer promise for uncovering distinct at-sea areas that are important habitats for imperiled marine species. Movement paths of 10 satellite-tracked female loggerheads ( Caretta caretta ) from three separate subpopulations in the Gulf of Mexico, USA, revealed migration to discrete foraging sites in two common areas at-sea in 2008, 2009, and 2010. Foraging sites were 102–904 km away from nesting and tagging sites, and located off southwest Florida and the northern Yucatan Peninsula, Mexico. Within 3–35 days, turtles migrated to foraging sites where they all displayed high site fidelity over time. Core-use foraging areas were 13.0–335.2 km 2 in size, in water <50 m deep, within a mean distance to nearest coastline of 58.5 km, and in areas of relatively high net primary productivity. The existence of shared regional foraging sites highlights an opportunity for marine conservation strategies to protect important at-sea habitats for these imperiled marine turtles, in both USA and international waters. Until now, knowledge of important at-sea foraging areas for adult loggerheads in the Gulf of Mexico has been limited. To better understand the spatial distribution of marine turtles that have complex life-histories, we propose further integration of disparate tracking data-sets at the oceanic scale along with modeling of movements to identify critical at-sea foraging habitats where individuals may be resident during non-nesting periods.

Florida↗

USGS2017

Using resilience and resistance concepts to manage persistent threats to sagebrush ecosystems and greater sage-grouse

Conservation of imperiled species often demands addressing a complex suite of threats that undermine species viability. Regulatory approaches, such as the US Endangered Species Act (1973), tend to focus on anthropogenic threats through adoption of policies and regulatory mechanisms. However, persistent ecosystem-based threats, such as invasive species and altered disturbance regimes, remain critical issues for most at-risk species considered to be conservation-reliant. We describe an approach for addressing persistent ecosystem threats to at-risk species based on ecological resilience and resistance concepts that is currently being used to conserve greater sage-grouse (Centrocercus urophasianus) and sagebrush ecosystems. The approach links biophysical indicators of ecosystem resilience and resistance with species-specific population and habitat requisites in a risk-based framework to identify priority areas for management and guide allocation of resources to manage persistent ecosystem-based threats. US federal land management and natural resource agencies have adopted this framework as a foundation for prioritizing sage-grouse conservation resources and determining effective restoration and management strategies. Because threats and strategies to address them cross-cut program areas, an integrated approach that includes wildland fire operations, postfire rehabilitation, fuels management, and habitat restoration is being used. We believe this approach is applicable to species conservation in other largely intact ecosystems with persistent, ecosystem-based threats.

Rangeland Ecology and Management↗

USGS2014

Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene

Historical ecology is becoming an important focus in conservation biology and offers a promising tool to help guide ecosystem management. Here, we integrate data from multiple disciplines to illuminate the past, present, and future of biodiversity on California's Channel Islands, an archipelago that has undergone a wide range of land-use and ecological changes. Our analysis spans approximately 20,000 years, from before human occupation and through Native American hunter–gatherers, commercial ranchers and fishers, the US military, and other land managers. We demonstrate how long-term, interdisciplinary research provides insight into conservation decisions, such as setting ecosystem restoration goals, preserving rare and endemic taxa, and reducing the impacts of climate change on natural and cultural resources. We illustrate the importance of historical perspectives for understanding modern patterns and ecological change and present an approach that can be applied generally in conservation management planning.

California↗

USGS2001

GRA prospectus: optimizing design and management of protected areas

Protected areas comprise one major type of global conservation effort that has been in the form of parks, easements, or conservation concessions. Though protected areas are increasing in number and size throughout tropical ecosystems, there is no systematic method for optimally targeting specific local areas for protection, designing the protected area, and monitoring it, or for guiding follow-up actions to manage it or its surroundings over the long run. Without such a system, conservation projects often cost more than necessary and/or risk protecting ecosystems and biodiversity less efficiently than desired. Correcting these failures requires tools and strategies for improving the placement, design, and long-term management of protected areas. The objective of this project is to develop a set of spatially based analytical tools to improve the selection, design, and management of protected areas. In this project, several conservation concessions will be compared using an economic optimization technique. The forest land use portfolio model is an integrated assessment that measures investment in different land uses in a forest. The case studies of individual tropical ecosystems are developed as forest (land) use and preservation portfolios in a geographic information system (GIS). Conservation concessions involve a private organization purchasing development and resource access rights in a certain area and retiring them. Forests are put into conservation, and those people who would otherwise have benefited from extracting resources or selling the right to do so are compensated. Concessions are legal agreements wherein the exact amount and nature of the compensation result from a negotiated agreement between an agent of the conservation community and the local community. Funds are placed in a trust fund, and annual payments are made to local communities and regional/national governments. The payments are made pending third-party verification that the forest expanse and quality have been maintained.

Open-File Report↗

USGS2020

Wetlands in agricultural landscapes—Significant findings and recent advances from CEAP-Wetlands

The Wetlands Component of the USDA's Conservation Effects Assessment Project (CEAP-Wetlands) is a multi-agency effort advancing science related to quantifying and interpreting effects and effectiveness of conservation practices and programs on ecosystem services provided by wetlands in agricultural landscapes. This special section originated from a symposium held at the 73rd Soil and Water Conservation Society's International Annual Conference in Albuquerque New Mexico, July 29 to August 1, 2018. The symposium was jointly organized by the USDA Natural Resources Conservation Service and the US Geological Survey. To facilitate CEAP-Wetlands efforts, several regional assessments were conducted across the United States. These regional assessments were designed to address science gaps hindering wetland conservation and to develop tools facilitating conservation assessments. Conservation decisions affect not just agricultural wetlands, but also the services that these complex ecosystems provide to society. Papers in this special section of the Journal of Soil and Water Conservation present key findings and recent advances from several CEAP-Wetlands regional assessments and discuss the significant contributions of each assessment to an ever-increasing understanding of wetland ecosystems and their provisioning of ecosystem services. Modeling efforts using the Agricultural Policy and Environmental eXtender (APEX) and other process-based models are an integral component of CEAP-Wetlands. Results of these modeling efforts are also presented, and conservation implications are discussed.

Journal of Soil and Water Conservation↗

USGS2023

Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales

Monitoring species to better understand their status, ecology, and management needs is a major expense for agencies tasked with biodiversity conservation. Community science data have the potential to improve monitoring for minimal cost, given appropriate analytical frameworks. We describe a framework for integrating data from the eBird community science platform with agency-collected monitoring data using a multistate occupancy model. Our model accounts for the structural differences across datasets and allows for estimation of both occupancy and breeding probabilities. The framework was applied to Common Loons ( Gavia immer ) in Washington State. A total of 766 sites had observation effort, of which 713 sites had only eBird effort, 26 sites had only Washington Department of Fish and Wildlife (WDFW) effort, and 27 sites had both. We predicted that the probability of occupancy was only 0.07 (95% Bayesian credible interval, BCI = 0.02–0.51) at the 2324 sites in our sampling frame, though the probability that Common Loons were breeding at occupied sites was 0.95 (95% BCI = 0.71–1.00). We found that probability of occupancy was positively related to waterbody size (probability of a positive effect = 0.88) and negatively related to an index of human influence (probability of a negative effect = 0.94). We found that probability of breeding at occupied sites was positively related to tree canopy cover (0.86), negatively related to elevation (0.99), and negatively related to barren, scrub/shrub, and herbaceous land cover (0.98). We found that state agency biologists were 16 times more likely to detect breeding Common Loons at a site than were eBird users (0.94, 95% BCI = 0.78–0.99 for agency biologists vs. 0.08, 95% BCI = 0.06–0.10 for eBird users). However, the amount of effort expended by eBird users meant that they confirmed Common Loons at 94 sites while agency biologists confirmed them at just 24 sites, although evidence of reproduction was only contributed by agency biologists. Our results provide a better understanding of the distribution of Common Loons in Washington, while further demonstrating that community science data can be a valuable complement to agency-collected data, if appropriate frameworks are developed to integrate these data sources.

Ecosphere↗

USGS2019

Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors

Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat ( Myotis lucifugus ) and the hoary bat ( Lasiurus cinereus ). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat ( = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ( = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.

Oregon, Washington↗