Accurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision-making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two-year camera-trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non-circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30%–32% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.
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Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.
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When this approach is used in MODFLOW, adjacent cells within the same model layer are vertically offset from one another, and the standard conductance-based (two-point) formulation for flow between cells does not rigorously account for these offsets. The XT3D multi-point flow formulation in MODFLOW 6 is designed to account for geometric irregularities in the grid, including vertical offsets, and to provide accurate results for both isotropic and anisotropic groundwater flow. A recent study evaluated the performance of the standard formulation and XT3D using a simple, synthetic benchmark model of a steeply dipping aquifer. Although XT3D generally improved the accuracy of flow simulations relative to the standard formulation as expected, neither formulation produced accurate flows in cases that involved large vertical offsets. 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
Withdrawals of water for human use are fundamental to the evaluation of the Nation’s water availability. This chapter provides an analysis of public supply, crop irrigation, and thermoelectric power water use for the conterminous United States (CONUS) during water years 2010–20. These three categories account for about 90 percent of water withdrawals in the Nation. The values presented here are based on modeling approaches that estimate water use at temporal (monthly) and spatial scales (12-digit hydrologic unit code—small watersheds sized 50–100 square kilometers) compatible for integration into a broader national assessment of water availability. Models also provide an understanding of factors that influence water use.
An estimated 244,817 million gallons per day (Mgal/d; 28,677 million cubic meters per month [Mm3/mo]) were withdrawn on average within the CONUS during water years 2010–20 from fresh water and saline water for crop irrigation, public supply, and thermoelectric power, with shares of 43, 14.5, and 42.5 percent for each of these categories, respectively. In the same period, estimated withdrawals and consumptive use (1) for public supply were 35,400 and 4,219 Mgal/d (4,081 and 486 Mm3/mo), respectively; (2) for crop irrigation were 105,497 and 75,698 Mgal/d (12,147 and 8,716 Mm3/mo), respectively; and (3) for thermoelectric power from fresh water were 82,656 and 2,904 Mgal/d (9,952 and 345 Mm3/mo), respectively.
Withdrawals for these categories of water use are highly spatially variable, with western States dominated by crop irrigation and eastern States dominated by thermoelectric-power water use. Public supply accounts for the largest percentage of water use in several heavily populated northeastern States. Reliance on groundwater compared to surface water depends on the availability of water sources and the type of water use. For public supply, withdrawals from groundwater are greater than withdrawals from surface water in the Western aggregated hydrologic regions, whereas the balance shifts to more surface water for the rest of the CONUS. In all aggregated hydrologic regions, the predominant source of water for crop irrigation is groundwater. Most thermoelectric power facilities in the eastern half of the CONUS use surface water from freshwater and saline sources; most thermoelectric power facilities in the western half of the CONUS use groundwater.
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D of U.S. Geological Survey Integrated Water Availability Assessment—2010–20: U.S. Geological Survey Professional Paper 1894–D, 56 p., https://doi.org/10.3133/pp1894D.","productDescription":"ix, 56 p.","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158787","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466179,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1894/d/pp1894D.pdf","text":"Report","size":"42.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1894–D"},{"id":466178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1894/d/coverthb.jpg"},{"id":481885,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/pp/1894/d/pp1894D.XML","linkFileType":{"id":8,"text":"xml"}},{"id":481906,"rank":5,"type":{"id":39,"text":"HTML 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"Degradation of water quality can make water harmful or unusable for humans and ecosystems. Although many studies have assessed the effect of individual constituents or narrow suites of constituents on freshwater systems, no consistent, comprehensive assessment exists over the wide range of water-quality effects on water availability. Using published studies, data, and models completed at regional or national scales in the United States during 2010–20, this chapter moves towards a comprehensive assessment by summarizing how selected anthropogenic and geogenic water-quality constituents affect national-scale water availability for human and ecosystem needs. Several types of human health, agricultural, ecological, and beneficial-use standards or thresholds were used to provide context for categorizing surface-water and groundwater quality.
Water availability for human and ecological use is limited by elevated concentrations of geogenic and anthropogenic constituents in surface and groundwater. Elevated concentrations of five geogenic constituents (arsenic, manganese, strontium, radium, and adjusted gross alpha) are common in groundwater and collectively affect the drinking water supply to over 30 million people. Surface water sourced drinking water supplies are impaired in about a third of assessed stream miles, most commonly because of non-mercury metals and salinity. Health-based violations at community water systems may disproportionately affect socially vulnerable communities. Ecological water uses are predominantly limited by nutrients, sediment, temperature, pathogens, salinity, and pesticides.
Water availability for human and ecological use is adversely affected by human activities including human contaminant sources (for example, wastewater, agriculture), processes (for example, dredging, groundwater pumping), or permanent landscape modifications (for example, dams, urbanization). Primary contaminant sources vary spatially and include fertilizer and manure, atmospheric deposition, wastewater treatment plants, urban land, and a range of natural sources. Contaminants of emerging concern, contaminants without regulatory thresholds, and mixtures of geogenic and anthropogenic water contaminants also contribute to ecological degradation and human exposure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894C","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Erickson, M.L., Miller, O.L., Cashman, M.J., Degnan, J.R., Reddy, J.E., Martinez, A.J., and Azadpour, E., 2025, Status of water-quality conditions in the United States, 2010–20 (ver. 1.1, February 2025), chap. 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February 5, 2025","contact":"Integrated Water Availability Assessment
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894B","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Gorski, G., Stets, E.G., Scholl, M.A., Degnan, J.R., Mullaney, J.R., Galanter, A.E., Martinez, A.J., Padilla, J., LaFontaine, J.H., Corson-Dosch, H.R., and Shapiro, A., 2025, Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20 (ver. 1.2, July 2025), chap. 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Contact Integrated Water Availability Assessment Team
","tableOfContents":"The Center for the Advancement of Population Assessment Methodology (CAPAM) was established in 2013, envisioned as an institute that could conduct, organize, and communicate stock assessment research with the aim of benefiting fisheries assessment efforts internationally. CAPAM’s activities have focused on its workshop series and consequent special issues in Fisheries Research. The information generated through CAPAM and its permanent recording as journal articles has greatly benefited the stock assessment community and can potentially contribute to modelling in general. We discuss what has made CAPAM successful, its future, and what could be done to reach the ultimate goal of producing a good practices guide for fisheries stock assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107162","usgsCitation":"Maunder, M., Crone, P., Semmens, B.X., Valero, J., Waterhouse, L., Methot, R., and Punt, A.E., 2025, The Center for the Advancement of Population Assessment Methodology (CAPAM): A perspective on the first 10 years: Fisheries Research, v. 281, 107162, 8 p., https://doi.org/10.1016/j.fishres.2024.107162.","productDescription":"107162, 8 p.","ipdsId":"IP-164132","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"281","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maunder, Mark N.","contributorId":348521,"corporation":false,"usgs":false,"family":"Maunder","given":"Mark N.","affiliations":[{"id":83372,"text":"American Tropical Tuna Commission","active":true,"usgs":false}],"preferred":false,"id":923510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crone, Paul R.","contributorId":348522,"corporation":false,"usgs":false,"family":"Crone","given":"Paul R.","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":923511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Semmens, Brice X.","contributorId":149775,"corporation":false,"usgs":false,"family":"Semmens","given":"Brice","email":"","middleInitial":"X.","affiliations":[{"id":17820,"text":"Scripps Institution of Oceanography, University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":923512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valero, Juan L.","contributorId":348523,"corporation":false,"usgs":false,"family":"Valero","given":"Juan L.","affiliations":[{"id":83375,"text":"Inter-American Tropical Tuna Commission","active":true,"usgs":false}],"preferred":false,"id":923513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waterhouse, Lynn 0000-0002-7455-7632","orcid":"https://orcid.org/0000-0002-7455-7632","contributorId":348524,"corporation":false,"usgs":true,"family":"Waterhouse","given":"Lynn","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923514,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Methot, Richard D.","contributorId":348525,"corporation":false,"usgs":false,"family":"Methot","given":"Richard D.","affiliations":[{"id":83376,"text":"National Marine Fisheries Service – NWFSC","active":true,"usgs":false}],"preferred":false,"id":923515,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Punt, Andre E.","contributorId":172069,"corporation":false,"usgs":false,"family":"Punt","given":"Andre","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":923516,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70262135,"text":"70262135 - 2025 - Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","interactions":[],"lastModifiedDate":"2025-01-15T17:02:19.54134","indexId":"70262135","displayToPublicDate":"2025-01-15T09:54:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","docAbstract":"Invasive species are often central to conservation efforts, particularly when concerns involve potential impacts on rare, endemic native species. The lower New River drainage of the eastern United States is a watershed that warrants conservation assessment, as the system is naturally depauperate of native fish species and it is nearly saturated with non-native fish species: there are 31 natives, including at least nine endemic taxa, and 63 non-natives. For endemic taxa, we examined temporal distribution shifts (range expansions or contractions) based on percent change in the occupied watershed area. We contrasted these findings with time series analyses on distribution trends of non-native minnows (Leuciscidae) and darters (Percidae) based on growth curve models of the cumulative sum of the total area of occupied 12-digit hydrologic unit codes. We documented range reductions for six of nine endemic taxa. We determined that 11 of 18 non-native minnows and 6 of 8 non-native darters were invasive based on range expansions and associated invasion curve models. The endemic taxa are of conservation concern given the limited distribution ranges and documented population declines. Although among-species comparisons of range shifts do not support causal inference, documentation of changes in distribution ranges of endemic and invasive species is critical to inform conservation efforts.
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This study provides the first fine-scale, regionally modeled valuations of how flood risk reductions associated with hybrid coral reef restoration could benefit people, property, and economic activity along Florida and Puerto Rico’s 1005 kilometers of reef-lined coasts. Restoration of up to 20% of the regions’ coral reefs could provide flood reduction benefits greater than costs. Reef habitats with the greatest benefits are shallow, nearshore, and fronting low-lying, vulnerable communities, which are often where reef impacts and loss are the greatest. Minorities, children, the elderly, and those below the poverty line could receive more than double the hazard risk reduction benefits of the overall population, demonstrating that reef restoration as a nature-based solution can have positive returns on investment economically and socially by providing protection to the most vulnerable people.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.adn4004","usgsCitation":"Storlazzi, C.D., Reguero, B., Alkins, K.C., Shope, J.B., Cole, A., Gaido-Lassarre, C., Viehman, S., and Beck, M.W., 2025, Hybrid coral reef restoration can be a cost-effective nature-based solution to provide protection to vulnerable coastal populations: Science Advances, v. 11, no. 3, eadn4004, 14 p., https://doi.org/10.1126/sciadv.adn4004.","productDescription":"eadn4004, 14 p.","ipdsId":"IP-151030","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489894,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adn4004","text":"Publisher Index Page"},{"id":481411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Puerto 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\"}}]}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":925287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":925288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alkins, Kristen C. 0000-0003-3647-2678 kalkins@usgs.gov","orcid":"https://orcid.org/0000-0003-3647-2678","contributorId":333714,"corporation":false,"usgs":true,"family":"Alkins","given":"Kristen","email":"kalkins@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":925289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shope, James B.","contributorId":135949,"corporation":false,"usgs":false,"family":"Shope","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":10653,"text":"University of California at Santa Cruz, Earth and Planetary Science Department","active":true,"usgs":false}],"preferred":false,"id":925290,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Aaron","contributorId":214198,"corporation":false,"usgs":false,"family":"Cole","given":"Aaron","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":925291,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gaido-Lassarre, Camila","contributorId":335650,"corporation":false,"usgs":false,"family":"Gaido-Lassarre","given":"Camila","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":925292,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Viehman, Shay","contributorId":336815,"corporation":false,"usgs":false,"family":"Viehman","given":"Shay","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":925293,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beck, Michael W.","contributorId":259298,"corporation":false,"usgs":false,"family":"Beck","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":925294,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264662,"text":"70264662 - 2025 - A Colorado Front Range grassland exhibits decreasing dominance of cheatgrass (Bromus tectorum) over time","interactions":[],"lastModifiedDate":"2025-03-19T15:06:38.608284","indexId":"70264662","displayToPublicDate":"2025-01-15T07:59:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A Colorado Front Range grassland exhibits decreasing dominance of cheatgrass (Bromus tectorum) over time","docAbstract":"Causes, consequences, and potentials for recovery from invasions by the invasive annual grass, cheatgrass (Bromus tectorum), in western North America have been extensively documented. The vast majority of these studies have come from regions where yearly precipitation is dominated by “winter-wet” patterns, but this species has also demonstrated its ability to invade plant communities in “spring/summer-wet” areas as well. In grasslands of the Front Range of Colorado, a region experiencing a “spring/summer-wet” precipitation pattern, cheatgrass can exploit early-season soil moisture, but moderate rainfall continues into the growing season beyond the time of cheatgrass senescence. In this study, we measured how cheatgrass dominance changed over a 13-year interval in a disturbed meadow along the Front Range of Colorado with a “spring/summer-wet” precipitation pattern. Cheatgrass cover declined in absolute abundance by about 50% while total vegetation cover increased over this time period. The site was neither grazed nor burned during this interval. A “spring/summer-wet” precipitation pattern with high interannual variation in amounts occurred during the study, but no relationships between the seasonality or amounts of precipitation and the directional decline in cheatgrass abundance were observed. Rainout shelter manipulations showed that the seasonality of precipitation influenced cheatgrass abundance, with winter drought treatments reducing cheatgrass cover relative to plots that experienced summer drought treatments. The cheatgrass decline corresponded with a lesser decline in native grass cover and no change in native forb cover, while the abundance of non-native perennial grasses and forb species increased over the study interval. Although cheatgrass can invade communities across broad climatic gradients following disturbance, results from this study show that the persistence of cheatgrass within invaded areas may depend on the seasonality of precipitation and plant communities that vary across these gradients.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70154","usgsCitation":"Prevey, J.S., and Seastedt, T., 2025, A Colorado Front Range grassland exhibits decreasing dominance of cheatgrass (Bromus tectorum) over time: Ecosphere, v. 16, no. 1, e70154, 15 p., https://doi.org/10.1002/ecs2.70154.","productDescription":"e70154, 15 p.","ipdsId":"IP-165941","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488339,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70154","text":"Publisher Index Page"},{"id":483524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Boulder","otherGeospatial":"foothills north of Boulder","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.59529184734308,\n 40.283537448541296\n ],\n [\n -105.59529184734308,\n 40.04839334476242\n ],\n [\n -105.11113649546341,\n 40.04839334476242\n ],\n [\n -105.11113649546341,\n 40.283537448541296\n ],\n [\n -105.59529184734308,\n 40.283537448541296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Prevey, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevey","given":"Janet","email":"","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":931158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seastedt, Timothy R.","contributorId":347353,"corporation":false,"usgs":false,"family":"Seastedt","given":"Timothy R.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":931159,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70262233,"text":"70262233 - 2025 - Enhanced hydrologic monitoring and characterization of groundwater drainage features","interactions":[],"lastModifiedDate":"2025-01-27T16:47:24.222862","indexId":"70262233","displayToPublicDate":"2025-01-14T11:17:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced hydrologic monitoring and characterization of groundwater drainage features","docAbstract":"Groundwater drains to the land surface, generating the baseflow of streams, lakes, and wetlands. The hydrologic resilience of baseflow during prolonged dry periods and after disturbance can be assessed with evolving remote sensing analysis paired with localized monitoring of groundwater drainage features and creative model calibration strategies.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00376-6","usgsCitation":"Briggs, M., 2025, Enhanced hydrologic monitoring and characterization of groundwater drainage features: Nature Water, v. 3, p. 2-3, https://doi.org/10.1038/s44221-024-00376-6.","productDescription":"2 p.","startPage":"2","endPage":"3","ipdsId":"IP-172738","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":466645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2025-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923616,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70268847,"text":"70268847 - 2025 - Bayesian model selection to investigate meaningful spatial scales","interactions":[],"lastModifiedDate":"2025-07-08T15:06:33.404154","indexId":"70268847","displayToPublicDate":"2025-01-14T10:04:12","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19836,"text":"Authorea","active":true,"publicationSubtype":{"id":32}},"title":"Bayesian model selection to investigate meaningful spatial scales","docAbstract":"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.
","language":"English","publisher":"Authorea","doi":"10.22541/au.173685828.82162349/v1","usgsCitation":"Hoegh, A., Irvine, K., Banner, K., de Wit. Luz, and Reichert, B., 2025, Bayesian model selection to investigate meaningful spatial scales: Authorea, preprint posted January 14, 2025, https://doi.org/10.22541/au.173685828.82162349/v1.","productDescription":"26 p.","ipdsId":"IP-175898","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":492052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.22541/au.173685828.82162349/v1","text":"Publisher Index Page"},{"id":491798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoegh, Andrew","contributorId":265906,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":942355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":221555,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":942356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banner, Katharine M.","contributorId":244876,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":942357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Wit. Luz","contributorId":357726,"corporation":false,"usgs":false,"family":"de Wit. Luz","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":942358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942359,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262095,"text":"ofr20241078 - 2025 - Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20","interactions":[],"lastModifiedDate":"2025-07-10T15:35:39.574031","indexId":"ofr20241078","displayToPublicDate":"2025-01-13T14:18:55","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1078","displayTitle":"Review of the Lake Washington Ship Canal and Ballard Locks Model, Seattle, Washington, 2014–20","title":"Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20","docAbstract":"The Hiram M. Chittenden (Ballard) Locks and Lake Washington Ship Canal connect freshwater Lake Washington and saline Shilshole Bay of Puget Sound in Seattle, Washington. The locks and canal allow for ships to traverse this reach. Anadromous salmonids also migrate through, transitioning between saline and freshwater environments, and making use of a fish ladder at the locks when traveling upstream. WEST Consultants, Inc., constructed a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) simulating flow, water temperature, and salinity for the Ballard Locks and the Lake Washington Ship Canal. An initial model was built for calendar years 2014–15, and the model was updated using a more recent and modern dataset for calendar years 2016–20. The U.S. Army Corps of Engineers requested that the U.S. Geological Survey review this model and its documentation to evaluate the technical aspects of its development and calibration. Findings from this review include the following:
Director, Oregon Water Science Center
U.S. Geological Survey
601 SW Second Avenue, Suite 1950
Portland, Oregon 97204
There is a growing need for consistent, large-scale estimates of water availability to identify and avoid potential conflicts among human and ecosystem uses of water. We present an assessment of water limitation, defined as the monthly balance (difference) between water supply (ws) and human consumptive water use (wc), for the conterminous United States (CONUS) during water years 2010–2020. We estimate that 26.7 million Americans, 8% of CONUS population, live in areas with chronic high or severe water limitation. Although ws greatly exceeds wc at the CONUS scale, water is limited locally or regionally due to spatial and temporal patterns in climate and wc. Our water limitation metric, the monthly supply and use index (SUI), peaked in 2012 during a widespread drought when 38% of the CONUS land area experienced elevated water stress. The central and southwestern U.S. experienced the highest SUI due to the combination of low ws and high wc, especially for crop irrigation. Spatial overlays of SUI and habitat ranges for fish species, including those of conservation concern, revealed that several species had notable proportions of their habitat exposed to high or severe water limitation during spawning season over the modeled time period, especially the Arkansas River shiner. Water supply (ws) was calculated from two CONUS, physically based, hydrologic models while wc was calculated from three CONUS models of water use for crop irrigation, thermoelectric power generation, and public supply. The ws and wc values were routed through a stream network and used to calculate water limitation for human populations and fish species at the scale of 12-digit hydrologic unit codes (HUC12s, 50-100 km2 catchments) and then analyzed using SUI. Evaluation of water availability at higher spatial and temporal resolution promotes more comprehensive analyses of the drivers of water availability and can be combined with complementary studies of water quality and water limiting thresholds to better understand the limitations on water availability.
","language":"English","publisher":"ESS Open Archive","doi":"10.22541/essoar.173655431.12049152/v1","usgsCitation":"Stets, E.G., Miller, O.L., Cashman, M.J., Powlen, K., Martinez, A., Archer, A.A., and Padilla, J., 2025, Local water use and climate drive water stress over the conterminous United States with substantial impacts to fish species of conservation concern: ESS Open Archive, https://doi.org/10.22541/essoar.173655431.12049152/v1.","productDescription":"29 p.","ipdsId":"IP-171942","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466656,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/essoar.173655431.12049152/v1","text":"External Repository"},{"id":466211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": 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frogs","interactions":[],"lastModifiedDate":"2025-01-10T17:44:37.528257","indexId":"70262006","displayToPublicDate":"2025-01-10T10:36:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Understanding and predicting infection dynamics for an endangered amphibian using long-term surveys of wild and translocated frogs","docAbstract":"Amphibians are a prominent component of Earth's sixth mass extinction and the fungal pathogen Batrachochytrium dendrobatidis (Bd) is a primary driver of declines. Although Bd dynamics are well studied, the environmental drivers, exacerbating risk factors, and value of conservation interventions like translocations remain challenging to predict. Here, we present results from two decades of Bd monitoring for mountain yellow-legged frogs (Rana muscosa) in the southern California Transverse and Peninsular mountain ranges. We describe Bd prevalence and infection intensity across sites; model how variables associated with climate, habitat, and populations relate to prevalence; and integrate Bd data from wild and translocated frogs to test whether a machine learning system can predict infection prevalence at new sites. Our findings indicate substantial spatiotemporal variation in Bd dynamics. Bd was present at all sites but prevalence and infection intensities were often low. Environmental features including temperature, precipitation, vegetation, and shortwave radiation explained significant variation in Bd prevalence, but their predictive value varied across mountain ranges. Although clear environmental predictors across populations remain elusive, we provide evidence for the importance of warmer and wetter springs and winters, with implications of increased risk under climate change predictions. We also found evidence for higher Bd prevalence among translocated than wild frogs. Although our machine learning model predicted a Bd prevalence threshold with relatively high accuracy, understanding the factors driving within- and between-population Bd dynamics is complex. Taken together, our findings provide new insights into the complicated role of Bd in amphibian declines and suggest revised management approaches.
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This improved understanding as captured in innovations in our data, knowledge, and modeling capabilities, needs to be accelerated through better integration and coordination across scientific disciplines, programs, and U.S. agencies. The Integrated Hydro-Terrestrial Modeling (IHTM) community holds promise to accelerate the progress required to manage the U.S. water resources sustainably, equitably, and effectively. The U.S. Global Change Research Program (USGCRP) coordinates research on the impacts of global change on the water cycle through interagency collaboration. USGCRP agencies and their partners jointly held the IHTM 2.0 workshop for U.S. federal and non-federal scientists and managers in fall 2023, aiming to advance community modeling and integrated water resources management capabilities following open science principles. This workshop focused on developing both national and regional testbeds that employ state-of-the-art modeling approaches to explore gaps and opportunities for improving the representation and extensibility of hydrologic processes and modeling. Integrated regional testbeds in Mid-Atlantic, Great Lakes, Colorado River Basin, and Gulf Coast/Mississippi regions were proposed to leverage existing investments and seek actionable collaboration on issues such as water extremes, water quality, water use, and urbanization. Collaborations focused on advancing iterative cycles of model development and testing offer a means for regional scale studies to inform national scale modeling applications and yield nationally consistent modeling frameworks that are also locally relevant. This presentation will highlight key takeaways, findings, and future directions for the IHTM community that have been laid out in the IHTM 2.0 workshop report.","language":"English","publisher":"Pacific Northwest National Laboratory","usgsCitation":"Skalak, K., Voisin, N., Read, P., and Reinfelder, Y., 2025, Integrated Hydro-terrestrial Modeling 2.0: Progress and path forward on building a national capability, 98 p.","productDescription":"98 p.","ipdsId":"IP-172814","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":481982,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnnl.gov/publications/integrated-hydro-terrestrial-modeling-20-progress-and-path-forward-building-national","linkFileType":{"id":5,"text":"html"}},{"id":481983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":926910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voisin, Nathalie","contributorId":242715,"corporation":false,"usgs":false,"family":"Voisin","given":"Nathalie","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":926912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Patrick","contributorId":350756,"corporation":false,"usgs":false,"family":"Read","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":926911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reinfelder, Ying Fan","contributorId":350757,"corporation":false,"usgs":false,"family":"Reinfelder","given":"Ying Fan","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":926913,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263616,"text":"70263616 - 2025 - Reply to, “Comment on ‘The 1886 Charleston, South Carolina, earthquake: Relic railroad offset reveals rupture,’ by Roger Bilham and Susan E. Hough”","interactions":[],"lastModifiedDate":"2025-02-18T15:25:57.906281","indexId":"70263616","displayToPublicDate":"2025-01-10T09:23:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Reply to, “Comment on ‘The 1886 Charleston, South Carolina, earthquake: Relic railroad offset reveals rupture,’ by Roger Bilham and Susan E. Hough”","docAbstract":"We welcome this opportunity to respond to Pratt et al. (2024) (hereinafter P24). Bilham and Hough (2023) proposed a “first-cut” elastic deformation model for the 1886 earthquake, a quantitative source model constrained by identified coseismic constraints. A key observation was the measurement of a lateral offset of a railroad line south of Summerville, leading to a model with predominately dextral slip and minor convergence, from which we concluded that active faulting had raised the Penholoway Marine Terrace >6 m since ∼770 ka. P24 questioned these constraints and proposed an alternative rupture model with predominantly reverse slip. This alternative model is neither consistent with coseismic constraints nor with other geophysical data. In a revised model presented here, we recognize that uplift of the Penholoway Terrace is confined to the eastern edge of the terrace, which we conclude results from active folding and tectonic transpression centered on the dextral fault that offset the railroad in 1886.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320240027","usgsCitation":"Bilham, R., and Hough, S.E., 2025, Reply to, “Comment on ‘The 1886 Charleston, South Carolina, earthquake: Relic railroad offset reveals rupture,’ by Roger Bilham and Susan E. Hough”: The Seismic Record, v. 5, no. 1, p. 23-34, https://doi.org/10.1785/0320240027.","productDescription":"12 p.","startPage":"23","endPage":"34","ipdsId":"IP-169814","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487648,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320240027","text":"Publisher Index Page"},{"id":482156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.064132039187,\n 32.91802637733042\n ],\n [\n -80.064132039187,\n 32.686509409955505\n ],\n [\n -79.85592767630018,\n 32.686509409955505\n ],\n [\n -79.85592767630018,\n 32.91802637733042\n ],\n [\n -80.064132039187,\n 32.91802637733042\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":927582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927583,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70263133,"text":"70263133 - 2025 - Modelling and mapping burn severity of prescribed and wildfires across the southeastern United States (2000-2022)","interactions":[],"lastModifiedDate":"2025-01-30T19:45:29.695647","indexId":"70263133","displayToPublicDate":"2025-01-10T08:54:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Modelling and mapping burn severity of prescribed and wildfires across the southeastern United States (2000-2022)","docAbstract":"The southeastern United States (‘Southeast’) experiences high levels of fire activity, but the preponderance of small and prescribed fires means that existing burn severity products are incomplete across the region.
We developed and applied a burn severity model across the Southeast to enhance our understanding of regional burn severity patterns.
We used Composite Burn Index (CBI) plot data from across the conterminous US (CONUS) to train a gradient-boosted decision tree model. The model was optimised for the Southeast and applied to the annual Landsat Burned Area product for 2000–2022 across the region.
The burn severity model had a root mean square error (RMSE) of 0.48 (R2 = 0.70) and 0.50 (R2 = 0.37) for the CONUS and Southeast, respectively. The Southeast, relative to CONUS, had lower mean absolute residuals in low and moderate burn severity categories. Burn severity was consistently lower in areas affected by prescribed burns relative to wildfires.
Although regional performance was limited by a lack of high burn severity CBI plots, the burn severity dataset demonstrated patterns consistent with low-severity, frequent fire regimes characteristic of Southeastern ecosystems.
More complete data on burn severity will enhance regional management of fire-dependent ecosystems and improve estimates of fuels and fire emissions.
The paleothermometer based on the alkenone unsaturation index (
We evaluated measurable attributes describing the current and future distribution of Cervus elaphus canadensis (elk) across a region surrounding Jackson, Wyoming, for five feedground management alternatives proposed by the U.S. Fish and Wildlife Service as a revision to the 2007 “Bison and Elk Management Plan” of the National Elk Refuge. A resource selection function evaluated measurable attributes of interest to managers, including elk use of private property and sensitive habitat types at monthly timesteps and varying winter conditions. The study area boundaries were created through an expert elicitation process and consist of the Jackson Elk Herd Unit, Grand Teton National Park, the National Elk Refuge, and the northern third of the Fall Creek Elk Herd Unit. For each of the five alternatives, we distributed monthly elk numbers calculated in a concurrent analysis that simulated chronic wasting disease dynamics in this system for 20 years. Measurable attributes representing potential elk use of (1) private property, (2) cattle properties as an index of Brucella abortus risk, and sensitive habitats consisting of (3) Populus tremuloides Michx. (quaking aspen), (4) Populus angustifolia E. James (narrowleaf cottonwood), and (5) Salix L. (willow) in core winter use areas all closely followed the declines of elk abundance projected by the elk chronic wasting disease model. After 20 years, the continue feeding alternative ranked most favorably in terms of limiting elk days on private property and reducing brucellosis risk from elk to cattle because this alternative concentrated elk on the National Elk Refuge and resulted in the lowest elk population sizes. However, other management alternatives, including increase harvest and reduce feeding, tended to limit elk use of sensitive quaking aspen, narrowleaf cottonwood, and willow habitats during winter (December–April).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245119C","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Research Program and the Species Management Research Program","usgsCitation":"Cotterill, G.G., Cross, P.C., Cole, E.K., Cook, J.D., McEachran, M.C., and Graves, T.A., 2025, Evaluating elk distribution and conflict under proposed management alternatives at the National Elk Refuge in Jackson, Wyoming, chap. C of Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2024–5119, 32 p., https://doi.org/10.3133/sir20245119C.","productDescription":"Report: vii, 32 p.; Software Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-165791","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":465767,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245119C/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5119 Chap. C HTML"},{"id":465766,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5119/c/sir20245119C.pdf","text":"Report","size":"6.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5119 Chap. C PDF"},{"id":465765,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5119/c/coverthb2.jpg"},{"id":465769,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5119/c/images/"},{"id":465768,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5119/c/sir20245119C.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5119 Chap. C XML"},{"id":465770,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P14FF6E6","text":"USGS software release","linkHelpText":"- Supporting code for—Evaluating elk distribution and conflict under proposed management alternatives at the National Elk Refuge in Jackson, Wyoming"}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.78225266437141,\n 43.46790181387567\n ],\n [\n -110.72445411600302,\n 43.480764457816235\n ],\n [\n -110.70981181708308,\n 43.502568770827935\n ],\n [\n -110.6897749869821,\n 43.51262964481907\n ],\n [\n -110.6628023310768,\n 43.52213004158219\n ],\n [\n -110.64353614828745,\n 43.53665716685947\n ],\n [\n -110.62349931818646,\n 43.55620738705895\n ],\n [\n -110.5972973095928,\n 43.598637460483474\n ],\n [\n -110.59883860421601,\n 43.62653567653447\n ],\n [\n -110.6520132687147,\n 43.62207283164909\n ],\n [\n -110.6897749869821,\n 43.60477617840215\n ],\n [\n -110.73216058911865,\n 43.56458411181504\n ],\n [\n -110.74680288803886,\n 43.517100606095084\n ],\n [\n -110.76067453964718,\n 43.50480466552287\n ],\n [\n -110.78225266437141,\n 43.46790181387567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
Bozeman, MT 59715
Bison bison (bison) were once abundant across North America but declined due to overharvesting in the late 1800s. The reintroduced population in and around Jackson, Wyoming has averaged 485 individuals between 2018–2023 and is the subject of a planning process to inform management strategies that will guide the U.S. Fish and Wildlife’s next “Bison and Elk Management Plan” for the National Elk Refuge. This small population may benefit from historical winter-feeding operations on the National Elk Refuge because those operations may increase overwinter survival and limit human-bison conflicts, which are the number of individual bison that engage in nuisance, damaging, or otherwise aggressive behaviors with humans and livestock, that may lead to culling and other sources of mortality (for example, vehicle collisions). To inform the next “Bison and Elk Management Plan,” the U.S. Geological Survey used a population model to evaluate five management alternatives for bison and Cervus elaphus canadensis (elk) feedground operations that included continuing the elk and bison feeding program, immediately stopping the feeding program, and three other alternatives that would phase out the feeding program after a period of time. The results indicate that the bison population would be expected to decline over the next 20 years under all alternatives that stop feeding bison on the refuge. Further, this decline would lead to an associated reduction in bison harvest opportunities for resident, nonresident, and Tribal hunters. Finally, human-bison conflicts would also be expected to increase under the no feeding alternatives because bison may venture onto private lands in greater numbers if feed is not provisioned during winter months. In combination, these effects suggest that feeding may lead to better outcomes for bison over the next 20 years; however, these effects may be traded off against other downsides of the feedground program, such as increased rates of animal-to-animal contact on feedgrounds that can lead to disease transmission.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245119D","collaboration":"Prepared in cooperation with the National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Research Program","usgsCitation":"Cook, J.D., McEachran, M.C., Cotterill, G.G., and Cole, E.K., 2025, Bison population dynamics, harvest, and conflict potential under feedground management alternatives at the National Elk Refuge in Jackson, Wyoming, chap. D of Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2024–5119, 24 p., https://doi.org/10.3133/sir20245119D.","productDescription":"Report: vi, 24 p.; Software Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166368","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":465783,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P1QZGZSN","text":"USGS software release","linkHelpText":"- Jackson bison population projections"},{"id":465782,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5119/d/images/"},{"id":465779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5119/d/sir20245119D.pdf","text":"Report","size":"5.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5119 Chap. D PDF"},{"id":465778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5119/d/coverthb2.jpg"},{"id":465781,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5119/d/sir20245119D.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5119 Chap. D XML"},{"id":465780,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245119D/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5119 Chap. D HTML"}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.78225266437141,\n 43.46790181387567\n ],\n [\n -110.72445411600302,\n 43.480764457816235\n ],\n [\n -110.70981181708308,\n 43.502568770827935\n ],\n [\n -110.6897749869821,\n 43.51262964481907\n ],\n [\n -110.6628023310768,\n 43.52213004158219\n ],\n [\n -110.64353614828745,\n 43.53665716685947\n ],\n [\n -110.62349931818646,\n 43.55620738705895\n ],\n [\n -110.5972973095928,\n 43.598637460483474\n ],\n [\n -110.59883860421601,\n 43.62653567653447\n ],\n [\n -110.6520132687147,\n 43.62207283164909\n ],\n [\n -110.6897749869821,\n 43.60477617840215\n ],\n [\n -110.73216058911865,\n 43.56458411181504\n ],\n [\n -110.74680288803886,\n 43.517100606095084\n ],\n [\n -110.76067453964718,\n 43.50480466552287\n ],\n [\n -110.78225266437141,\n 43.46790181387567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039
The U.S. Fish and Wildlife Service National Elk Refuge (NER) in Jackson, Wyoming, supplementally feeds Cervus elaphus canadensis (elk) and Bison bison (American bison) during winter months, but the costs and benefits of this management strategy are being reevaluated considering the potential effects of chronic wasting disease (CWD) on elk. U.S. Geological Survey scientists worked with the U.S. Fish and Wildlife Service on a structured decision-making process that considered five alternative feeding strategies and their effects on bison, elk, and humans. This chapter focuses on elk population dynamics and CWD using computer models. Our modeling results highlight a short- versus long-term tradeoff between the continue feeding and no feeding alternatives. Management alternatives associated with a cessation of supplemental feeding were assumed to make elk more susceptible to severe winters, resulting in initially lower population sizes and less CWD transmission. The increased CWD prevalence and transmission associated with the continue feeding alternative resulted in lower elk population sizes by year 20 (mean=6,700, standard deviation=1,600 in the analysis area) in 70 percent of simulations compared to no feeding (mean=8,400, standard deviation=1,500). No feeding alternatives resulted in higher elk populations than the continue feeding alternative between years 7 and 13 when CWD prevalence exceeded 20 percent in the Jackson elk herd. The increased harvest alternative minimized CWD and natural mortality in 83 out of 100 simulations compared to the continue feeding alternative.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245119B","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture, National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","programNote":"Ecosystems Mission Area—Biological Threats & Invasive Species Program and the Environmental Health Program","usgsCitation":"Cross, P.C., Cook, J.D., and Cole, E.K., 2025, Predictions of elk and chronic wasting disease dynamics at the National Elk Refuge in Jackson, Wyoming, and surrounding areas, chap. B of Cook, J.D., and Cross, P.C., eds., Decision analysis in support of the National Elk Refuge bison and elk management plan: U.S. Geological Survey Scientific Investigations Report 2024–5119, 22 p., https://doi.org/10.3133/sir20245119B.","productDescription":"Report: vi, 22 p.; Software Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166360","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":465758,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5119/b/coverthb2.jpg"},{"id":465759,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5119/b/sir20245119B.pdf","text":"Report","size":"4.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5119 Chap. B PDF"},{"id":465760,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245119B/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5119 Chap. B HTML"},{"id":465761,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5119/b/sir20245119B.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5119 Chap. B XML"},{"id":465762,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5119/b/images/"},{"id":465763,"rank":6,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P14EPY3U","text":"USGS software release","linkHelpText":"- CWD software code for simulating elk and chronic wasting disease dynamics on the National Elk Refuge (version 0.1.0)"}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"National Elk Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.78225266437141,\n 43.46790181387567\n ],\n [\n -110.72445411600302,\n 43.480764457816235\n ],\n [\n -110.70981181708308,\n 43.502568770827935\n ],\n [\n -110.6897749869821,\n 43.51262964481907\n ],\n [\n -110.6628023310768,\n 43.52213004158219\n ],\n [\n -110.64353614828745,\n 43.53665716685947\n ],\n [\n -110.62349931818646,\n 43.55620738705895\n ],\n [\n -110.5972973095928,\n 43.598637460483474\n ],\n [\n -110.59883860421601,\n 43.62653567653447\n ],\n [\n -110.6520132687147,\n 43.62207283164909\n ],\n [\n -110.6897749869821,\n 43.60477617840215\n ],\n [\n -110.73216058911865,\n 43.56458411181504\n ],\n [\n -110.74680288803886,\n 43.517100606095084\n ],\n [\n -110.76067453964718,\n 43.50480466552287\n ],\n [\n -110.78225266437141,\n 43.46790181387567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Northern Rocky Mountain Science Center
U.S. Geological Survey
2327 University Way, Suite 2
Bozeman, MT 59715