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Results for “Integrated Environmental Assessment and Management”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,662 records · Page 4Linked to original sources
USGS1999

Water-quality assessment of the New England coastal basins in Maine, Massachusetts, New Hampshire, and Rhode Island: Environmental settings and implications for water quality and aquatic biota

The New England Coastal Basins in Maine, Massachusetts, New Hampshire, and Rhode Island constitute one of 59 study units selected for water-quality assessment as part of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. England Coastal Basins study unit encompasses the fresh surface waters and ground waters in a 23,000 square-mile area that drains to the Atlantic Ocean. Major basins include those of the Kennebec, Androscoggin, Saco, Merrimack, Charles, Blackstone, Taunton, and Pawcatuck Rivers. Defining the environmental setting of the study unit is the first step in designing and conducting a multi-disciplinary regional water-quality assessment. The report describes the natural and human factors that affect water quality in the basins and includes descriptions of the physiography, climate, geology, soils, surface- and ground-water hydrology, land use, and the aquatic ecosystem. Although surface-water quality has greatly improved over the past 30 years as a result of improved wastewater treatment at municipal and industrial wastewater facilities, a number of water-quality problems remain. Industrial and municipal wastewater discharges, combined sewer overflows, hydrologic modifications from dams and water diversions, and runoff from urban land use are the major causes of water-quality degradation in 1998. The most frequently detected contaminants in ground water in the study area are volatile organic compounds, petroleum-related products, nitrates, and chloride and sodium. Sources of these contaminants include leaking storage tanks, accidental spills, landfills, road salting, and septic systems and lagoons. Elevated concentrations of mercury are found in fish tissue from streams and lakes throughout the study area.

Maine, Massachusetts, New Hampshire, Rhode Island↗
USGS2025

Simulation of the impacts of spring diversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model

The Strawberry Creek watershed, situated in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the impact of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study we constructed the Strawberry Creek integrated hydrological model (SCIHM) to increase this understanding. The SCIHM is an integrated surface runoff and groundwater model that uses the coupled groundwater and surface-water flow model (GSFLOW), which is based on the integration of the precipitation-runoff modeling system (PRMS) and the modular groundwater flow model commonly called MODFLOW, version MODFLOW-2005 software to simulate surface runoff and infiltration and groundwater flow. The model has three layers, 263 rows, and 176 columns. The model area includes the Strawberry Creek and four adjacent watersheds. The PRMS model was calibrated using two streamflow gaging stations and the GSFLOW model was calibrated to reported spring diversion discharge and a sparse number of groundwater-level measurements. The SCIHM was run with and without diversions active and simulated streamflow was compared, finding that in the headwaters of Strawberry Creek about 35 percent of the diversion flow was captured from base flow.

EarthArXiv↗
USGS2026

Cultural benefits knowledge and social learning in Elwha River dam removal and ecosystem decision-making

In a retrospective case study of the seminal Elwha River dam removal in Washington State, USA, we explore pathways through which ecosystem services (ES) knowledge can inform environmental decision-making. We specifically investigate how knowledge of cultural benefits linked to the Elwha River ecosystem was made available. Through interviews and historical document review we identify diverse forms of cultural benefits knowledge (i.e., how individuals or groups know the contributions of an ecosystem to their identities, experiences, and capabilities), including both knowledge in the form of practices – embodied or enacted forms of knowledge, and knowledge in the form of products – quantitative or written documentation. Recognizing and learning from the diverse forms in which benefits knowledges are conveyed can support more accurate and equitable consideration of the diverse values, well-beings, and human-nature relationships linked to ecosystems. With this case study, we illuminate pathways for meaningful consideration of multiple knowledge forms, and the plural ecosystem values they convey, with relevance for environmental decision processes in the Puget Sound and beyond.

Washington↗
USGS2025

Land-based nutrient flux to a fringing reef: Insights from Ofu Island, American Samoa

Submarine groundwater discharge (SGD) is a critical driver of nutrient transport in coral reef ecosystems, shaping water quality, primary productivity, and overall reef health. This study quantifies SGD fluxes and associated nutrient dynamics in two reef flat pools within the Ofu Unit of the National Park of American Samoa: Papaloloa and Fatuana. A multi-method approach integrating unoccupied aerial system-based thermal infrared (UAS-TIR) surveys, radon-based SGD measurements, multichannel electrical resistivity tomography (ERT), and discrete water sampling was used to assess SGD rates and nutrient contributions. UAS-TIR imagery revealed cooler sea surface temperatures in both pools, indicative of SGD, with the higher fluxes observed in Papaloloa. Radon measurements revealed a strong inverse correlation between SGD rates and tidal stage, with a more immediate SGD response at Papaloloa due to its highly permeable calcareous sand and gravel substrate. In contrast, a 2–3-hour lag in SGD response at Fatuana suggests discharge from a more inland aquifer that has lower diffusivity. Nutrient concentrations correlated with temperature and salinity, confirming SGD as the dominant nutrient transport mechanism, whereas isotopic analyses indicated inputs from both groundwater and potential anthropogenic sources. Despite lower SGD flux at Fatuana, higher algal cover suggests additional factors influencing algal proliferation, including substrate availability and hydrodynamic conditions. Excess nutrient inputs from SGD may contribute to algal overgrowth, which threatens Ofu’s thermally tolerant corals by increasing competition for space and light. These findings underscore the complexity of SGD-mediated nutrient dynamics in reef environments and emphasize the need for integrated hydrological and ecological assessments to support effective reef conservation and management strategies.

American Samoa, Ofu Island, Olosega Island↗
USGS2026

Multi-objective optimization of a hydro-economic model in an over-allocated agricultural basin

Groundwater depletion for agricultural irrigation poses significant environmental and economic challenges. This study introduces a proof-of-concept that combines hydro-economic modeling, scenario-based modeling, and multi-objective optimization to manage pumping curtailment in an over-allocated basin in the western United States. Three optimization scenarios were evaluated, each offering different degrees of management flexibility. Results reveal that scenarios with finer spatial resolution achieved greater environmental benefits per unit profit loss. Additionally, strategies allowing fractional reductions in curtailed wells–rather than complete shutdowns based on water rights seniority–substantially improved efficiency, highlighting the value of increased decision-making flexibility. Although scenario testing can aid stakeholder engagement and strategy exploration, multi-objective optimization provides a systematic framework to quantify tradeoffs between competing objectives. This combined approach demonstrates promise for building consensus and supporting the design of sustainable water management strategies that balance agricultural livelihoods with ecosystem preservation.

Oregon↗
USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗
USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗
USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗
USGS2025

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗
USGS2025

Using visualization science to inform the design of environmental decision-support tools—A case study of the U.S. Geological Survey Waterwatch

Environmental decision-support tools are increasingly being used to serve both expert and non-expert audiences. Many existing tools are primarily expert-focused, and redesigning them can be challenging because experts and non-experts interact with tools differently, existing users may be resistant to changes, and there is little guidance on how to prioritize redesign efforts and demonstrate their efficacy. In this report, we present a case study of a user-centered redesign of an established environmental decision-support tool—the U.S. Geological Survey WaterWatch. WaterWatch supports flood, drought, and other water resource management decisions through the display of water levels at gages across the United States. Using a participatory process, we identified a functional change (replacing the existing rainbow colormap), created an alternative design, and tested the alternative’s usability through two general public surveys. The results showed that replacing the rainbow colormap with a more intuitive diverging colormap improves usability, regardless of the audience’s subjective preference for the rainbow color scheme. In addition, we demonstrated the importance of using legends to improve the audience’s understanding of the map symbols. This study demonstrates how user-centered design approaches can be used to inform the design of high-profile products and tools.

Scientific Investigations Report↗
USGS2025

Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health

Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022, https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf ). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.

Environmental Health Perspectives↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2024

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Sardon catchment↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2025

Shallow geologic framework of the Mississippi Sound and the potential for sediment resources

The Mississippi Sound, an estuarine environment located between the mainland and barrier islands bordering the northern Gulf of America (formerly the Gulf of Mexico), serves as a vital ecosystem for the States of Mississippi and Alabama. Spanning approximately 100 kilometers from east to west and covering 1,400 square kilometers, the sound is home to marine industry and ports, and its shallow and brackish waters sustain a diverse array of marine life. Barrier islands along the southern edge of the sound separate the microtidal estuary from the Gulf of America. This protection from gulf wave action mediates current flow within the sound, resulting in predominantly fine-grained sediment deposition along the seafloor. This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, provides insight on fluvial and tidal processes spanning the past 5,000 years. The report synthesizes existing research to provide a comprehensive overview of the sound geology, from Pleistocene origins to present-day morphology, and utilizes high-resolution single channel seismic profiles and sediment data to identify and map sedimentary deposits and morphologic features at and below the seafloor. Despite its ecological significance, the Mississippi Sound faces environmental challenges, including water-quality issues, habitat degradation, storm-induced erosion, and the ongoing threats of sea-level rise and environmental changes. This study uses the present-day understanding of the sound's geology to inform coastal management decisions, hazard assessment, and potential mineral resources.

Louisiana, Mississippi↗
USGS2025

Statewide cumulative human health risk assessment of inorganics-contaminated groundwater wells, Montana, USA

Across the United States, rural residents rely on unregulated and generally unmonitored private wells for drinking water, which may pose serious health risks due to unrecognized contaminants. We assessed the nature, degree, and spatial distribution of cumulative health risks from inorganic contaminants in groundwater. Our analysis included nearly 84,000 data points from 6500+ wells, across 51 of Montana's 98 watersheds, using a public groundwater database. We compared a drinking water screening level cumulative risk assessment (CRA) for inorganics based on the U.S. Environmental Protection Agency (EPA) protective health thresholds (Maximum Contaminant Level Goals, Health Advisories [MCLG-HAs]) to a CRA based on EPA public supply enforceable Maximum Contaminant Levels (MCLs). Based on median concentrations of 19 inorganics (antimony, arsenic, barium, beryllium, boron, cadmium, chromium, copper, fluoride, manganese, molybdenum, nickel, nitrate, lead, selenium, strontium, thallium, uranium, zinc), 75% of watersheds had MCLG-HA-based cumulative risk values > 1.0; arsenic and uranium contributed the most risk, followed by strontium, fluoride, manganese and boron. Hence, this screening level (Tier I) CRA indicated widespread potential for unrecognized human health risk to private well users from inorganic contaminants considering both carcinogenic and non-carcinogenic risks. Sensitivity analysis showed that benchmarks applied (MCLG-HAs versus MCLs) exerted the largest control on results. Our findings identify priority regions for Tier 2 risk assessments to elucidate local sources and distributions of geogenic versus anthropomorphic contaminants. Our study is the first statewide assessment of cumulative health risk from groundwater that we are aware of, and results support increased statewide drinking water education and testing to reduce human health risks from contaminated private well water.

Montana↗
USGS2025

Comparative assessment of a restored and natural wetland using 13C-DNA SIP reveals a higher potential for methane production in the restored wetland

Wetlands are the largest natural source of methane (CH 4 ), a potent greenhouse gas produced by methanogens. Methanogenesis rates are controlled by environmental factors such as redox potential, temperature, and carbon and electron acceptor availability and are presumably dependent on the composition of the active methanogen community. We collected intact soil cores from a restored and natural freshwater depressional wetland on Maryland’s Delmarva Peninsula (USA) to assess the effects of wetland restoration and redox shifts on microbial processes. Intact soil cores were incubated under either saturated (anoxic) or unsaturated (oxic) conditions and amended with 13 C-acetate for quantitative stable isotope probing (qSIP) of the 16S rRNA gene. Restored wetland cores supported a distinct community of methanogens compared to natural cores, and acetoclastic methanogens putatively identified in the genus Methanosarcina were among the most abundant taxa in restored anoxic and oxic cores. The active microbial communities in the restored wetland cores were also distinguished by the unique presence of facultatively anaerobic bacteria belonging to the orders Firmicutes and Bacteroidetes . In natural wetland incubations, methanogen populations were not among the most abundant taxa, and these communities were instead distinguished by the unique presence of aerobic bacteria in the phyla Acidobacteria , Actinobacteria , and class Alphaproteobacteria . Iron-reducing bacteria, in the genus Geobacter , were active across all redox conditions in both the restored and the natural cores, except the natural oxic–anoxic condition. These findings suggest an overall higher potential for methanogenesis in the restored wetland site compared to the natural wetland site, even when there is evidence of Fe reduction.

Maryland↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗