Integration of agroecosystems and other working landscapes with protected lands and waters is critical to the conservation of Earth's biodiversity. Rice agroecosystems support many species by providing aquatic habitat where natural wetlands have been altered or drained. In regions with long dry seasons, rice fields and associated irrigation canals provide essential habitat for wetland-dependent species. We quantified the spatial scale and magnitude of the effect of rice growing on the growth and survival of the giant gartersnake (Thamnophis gigas), a threatened species that persists primarily in areas of rice agriculture in the Central Valley of California, USA. We used structural causal models to identify drought condition as a key confounder to adjust for when estimating the total effect of rice growing on demographic rates. We analyzed capture-mark-recapture data from 19 populations of giant gartersnakes with an integrated growth–survival model and used distance-weighted covariates to account for the decline in influence of rice with increasing distance from our study sites. We found strong support for a positive effect of rice grown within 1.9 km of a canal on giant gartersnake growth. There was also support for a positive effect of rice on giant gartersnake survival, although the spatial scale extended out to 5 km or more. Our results demonstrate how active rice growing benefits giant gartersnakes inhabiting irrigation canals and demonstrate an approach for studying landscape effects on wildlife in agroecosystems.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70139","usgsCitation":"Rose, J.P., Nguyen, A.M., Jordan, A., Macias, D., Schoenig, E.J., Napolitano, G., Kim, R., Ersan, J.S., Fulton, A.M., and Halstead, B., 2025, Rice cultivation supports growth and survival of a threatened semi-aquatic reptile: Ecological Applications, v. 35, no. 8, e70139, 15 p., https://doi.org/10.1002/eap.70139.","productDescription":"e70139, 15 p.","ipdsId":"IP-172102","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497730,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70139","text":"Publisher Index Page"},{"id":497649,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1JHAWVT","text":"USGS data release","linkHelpText":"Growth and Capture Mark Recapture Data from Giant Gartersnakes (Thamnophis gigas) in Rice Irrigation Canals 2018 to 2023 (ver. 2.0, July 2025)"},{"id":497576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.17302271960432,\n 39.79287563400288\n ],\n [\n -122.17302271960432,\n 38.80561121822487\n ],\n [\n -121.10358373344488,\n 38.80561121822487\n ],\n [\n -121.10358373344488,\n 39.79287563400288\n ],\n [\n -122.17302271960432,\n 39.79287563400288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 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We propose a model that distinguishes between proximate and ultimate drivers of fire regimes and apply it to a century of fire and climate data to assess regional variation in causal mechanisms.
We analyzed fire statistics (1910–2021) alongside climate and weather data, stratifying the state by 10 ecoregions.
Northern forests had the strongest correlation with the proximate factor fuel aridity, ultimately due to climate. Fire rotation intervals exceeded 100 years, implicating woody fuel accumulation as an additional factor. Lightning ignitions occurred in decadal bursts, with dense strike events potentially overwhelming fire-fighting resources. Lower elevation/latitude foothill ecoregions experienced highest fire activity following wet winters and springs, implicating control by herbaceous fuel loads and a negative effect of global warming on future fires. Human ignitions dominate in these ecoregions, and population growth contributes to expansion of powerlines, a major ignition source.
While climate change may increase fire activity in forested ecoregions, its role is less pronounced in non-forested ecoregions, where human ignition sources are the dominant factor.
Different areas within ecoregions may require different management actions that reflect the specific proximate and ultimate factors at play.
","language":"English","publisher":"CSIRO","doi":"10.1071/WF25166","usgsCitation":"Keeley, J., and Syphard, A.D., 2025, Causal analysis of fire regime drivers in California: International Journal of Wildland Fire, v. 34, no. 12, WF25166, 27 p., https://doi.org/10.1071/WF25166.","productDescription":"WF25166, 27 p.","ipdsId":"IP-166632","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"34","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Syphard, Alexandra D.","contributorId":364829,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","middleInitial":"D.","affiliations":[{"id":38279,"text":"Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":953273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272700,"text":"sir20255091 - 2025 - Geochemical and hydrological investigations of historical data collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","interactions":[],"lastModifiedDate":"2026-02-03T16:46:09.780586","indexId":"sir20255091","displayToPublicDate":"2025-12-08T06:36:04","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5091","displayTitle":"Geochemical and Hydrological Investigations of Historical Data Collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","title":"Geochemical and hydrological investigations of historical data collected at the Lee Acres Landfill and Giant Bloomfield Refinery, New Mexico, 1985–2020","docAbstract":"The Lee Acres Landfill and Giant Bloomfield Refinery are adjacent properties near the City of Farmington, New Mexico, each having undergone monitoring and remediation related to historical site activities. At the landfill, site cleanup has included the installation of a capillary barrier over former liquid waste lagoons and periodic monitoring of groundwater elevations and groundwater quality. At the refinery, remediation has focused on several petrochemical and crude oil release areas and included soil excavation, groundwater treatment, and regular monitoring of groundwater elevations and quality. Groundwater at both sites has higher concentrations of volatile organic compounds and trace metals than background aquifer concentrations. In 2022, the U.S. Geological Survey compiled the Lee Acres-Giant Bloomfield Refinery Database (LAGBRD), which contains publicly available groundwater-elevation data and organic and inorganic groundwater-quality data from both sites, spanning from 1985 to 2020. Data from the LAGBRD and precipitation data from other sources were used to better understand the cause of relatively high manganese concentrations observed in some groundwater wells at the site through comparison of groundwater chemistry to chemical end members, interpretation of spatial and temporal patterns in the groundwater chemistry, and interpretation of groundwater flow properties. In this study, elevated chloride concentrations in groundwater downgradient from the landfill have been attributed to landfill leachate based on the temporal and spatial variability of chloride concentrations and chloride-to-bromide ratios. Installation of a capillary barrier and surface-water runoff controls at the landfill in 2005 appears to have altered infiltration patterns at that site, resulting in a decrease in chloride at some wells but an increase in chloride and dissolved manganese at others. The timing and relation among groundwater elevation, chloride concentration, and manganese concentration suggest that leachate stored in the vadose zone provides a continued source of contamination to groundwater.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Contact Us- USGS Publications Warehouse
","tableOfContents":"Quantifying sea turtle nesting behavior is essential for recovery planning and evaluating management actions. Traditional monitoring approaches, based on nest counts from beach surveys, can misclassify non-nesting emergences, obscure true fecundity, and underestimate clutch frequency, metrics that directly influence population models and regulatory decisions. Here, we demonstrate that high-resolution acceleration data loggers (ADLs) can reliably discriminate nesting from non-nesting emergences across four imperiled species of sea turtles at sites in the Gulf of America, southeast USA, and Caribbean. From 60 recovered ADL deployments on green (Chelonia mydas; N = 10), hawksbill (Eretmochelys imbricata; N = 7), Kemp’s ridley (Lepidochelys kempii; N = 21), and loggerhead sea turtles (Caretta caretta; N = 22) lasting on average 17.5 ± 8.7 days (range 2–43 days), we identified 54 nesting events and 76 non-nesting emergences, with >97% accuracy when compared to direct observations. These data provide the first observer-validated, species-specific behavioral signatures of nesting phases and reveal correlations between egg-laying duration and clutch size. All non-nesting emergences occurred within 72 hours of subsequent nesting, allowing managers to anticipate nest deposition windows. By refining inter-nesting intervals and fecundity estimates, ADLs offer a practical path to reduce error in clutch frequency estimates. The integration of ADL-derived algorithms with satellite-transmitting tags would enable the remote, real-time monitoring of nesting activity, creating a system for the remote monitoring of inter-nesting intervals and nest fecundity that are crucial to quantify the impacts of climate change and other threats to sea turtle nesting habitat.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2025.1691053","usgsCitation":"Hart, K., White, C.F., Shaver, D.J., Lamont, M., Cherkiss, M., Crowder, A.G., and Whitney, N.M., 2025, Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles: Frontiers in Marine Science, v. 12, 1691053, 15 p., https://doi.org/10.3389/fmars.2025.1691053.","productDescription":"1691053, 15 p.","ipdsId":"IP-178699","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497743,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1691053","text":"Publisher Index Page"},{"id":497677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, North Carolina, Texas","otherGeospatial":"Bald Head Island, Bon Secour National Wildlife Refuge, Buck Island Reef National Monument, Dry Tortugas National Park, Padre Island National Seashore, St. Croix, T.H. 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Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Understanding the distribution of grizzly bear populations in the lower-48 states, is important for their conservation and management, and for public safety. Previously, our research teams working in grizzly bear ecosystems in the lower-48 states used varying methods to estimate distribution of grizzly bear populations. In the Greater Yellowstone Ecosystem (GYE) and Northern Continental Divide Ecosystem (NCDE), zonal analysis and ordinary kriging were applied to an array of grid cells with or without verified presence of grizzly bears, however the parameters of the methods varied between the two ecosystems. In the Cabinet-Yaak Ecosystem (CYE) and the Selkirk Ecosystem (SE), population distribution was mapped as the Recovery Zone plus “bears outside of Recovery Zone” areas (Allen 2011). Additionally, the U.S. Fish and Wildlife Service developed a method for estimating areas where grizzly bears “may be present” to help agencies or prospective applicants evaluate whether or not proposed actions may affect grizzly bears (U.S. Fish and Wildlife Service 2020). Since the mid 2010s, cooperating agencies have collaborated in documenting and maintaining a database of verified outlier observations that occur between or well outside of grizzly bear Recovery Zones and these data inform the “may be present” mapping.
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Ducks in the PPR depend on wetlands and grasslands which have experienced accelerated losses in extent and quality due to agriculture. While other bird populations have declined, duck abundance reached record highs recently (2013–2017). We explored this discontinuity by examining monitoring data for trends in pond numbers (wetlands with ponded water) and interannual dynamics (water-level dynamics indexed by interannual change in pond numbers) and how those factors influenced duck productivity in the PPR during 1976–2019. Over time, pond numbers increased but their interannual dynamics declined, indicating stabilization of an ecosystem evolved with a dynamic climate. Our models accounted for 67 and 71 % of variation in productivity of PPR-obligate gadwall (Mareca strepera) and redheads (Aythya americana), respectively. Breeding productivity of these sentinel species was positively correlated with pond abundance and dynamics, and systematically declined. Accordingly, our analyses revealed sensitivity of breeding ducks to systematic change in the PPR previously obscured by increasingly abundant pond numbers. Interannual pond dynamics improved duck productivity and pond dynamics have declined indicating a de facto 44-year decline in duck productivity which is likely driven by water-level stabilization decreasing quality of brood-rearing wetlands. Residual temporal effects indicated that productivity has also declined for other reasons, such as agricultural land use changes. While mechanisms behind these correlations are speculative, they demonstrate the importance of further understanding land use and climate changes in the PPR for conservation of these important species and ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.indic.2025.101073","usgsCitation":"Anteau, M.J., Szymanski, M.L., and Pearse, A.T., 2025, Wetland hydrologic dynamics and duck productivity are declining in the Prairie Pothole Region, and they are linked: Environmental and Sustainability Indicators, v. 29, 101073, 11 p., https://doi.org/10.1016/j.indic.2025.101073.","productDescription":"101073, 11 p.","ipdsId":"IP-172342","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.indic.2025.101073","text":"Publisher Index Page"},{"id":499373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Iowa, Manitoba, Minnesota, Montana, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.35951256057884,\n 55.830201295287566\n ],\n [\n -115.58338333574763,\n 47.847886890172305\n ],\n [\n -101.7900722437109,\n 47.49234945376459\n ],\n [\n -100.95405193901554,\n 43.77396787878899\n ],\n [\n -96.57786404894601,\n 43.798830626316516\n ],\n [\n -94.52621944089687,\n 42.26192084940283\n ],\n [\n -95.45523589381337,\n 46.222540001545326\n ],\n [\n -97.03293587652475,\n 51.31009651298103\n ],\n [\n -119.35951256057884,\n 55.830201295287566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szymanski, Michael L","contributorId":365789,"corporation":false,"usgs":false,"family":"Szymanski","given":"Michael","middleInitial":"L","affiliations":[{"id":87220,"text":"North Dakota Game and Fish Dept.","active":true,"usgs":false}],"preferred":false,"id":954799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954800,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274097,"text":"70274097 - 2025 - Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities","interactions":[],"lastModifiedDate":"2026-02-25T14:43:00.60868","indexId":"70274097","displayToPublicDate":"2025-12-05T07:37:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities","docAbstract":"Spatio-temporal changes to our world’s surface water resources are escalating. Translating how these changes impact communities and ecosystems requires time-varying data of Global Surface Water Extents (GSWE). Traditionally, GSWE mapping has been limited to static estimates, with recent efforts focusing on annual averages, frequency and occurrence of long-term variations. Building upon these foundational capabilities, we harnessed remotely sensed Sentinel-2 based near real-time Dynamic World (DW) land cover products to produce the first-of-its-kind 10 m resolution GSWE dataset representing 2015–2023. Our dataset estimated 2.5 million km2 of permanent waters and 8 million km2 of seasonal waters worldwide. Comparing our Sentinel-2 based data to contemporary Landsat-based GSWE, we observed that our data mapped less water within the >50% probability of occurrence range, suggesting a lower presence of open permanent water especially in high latitudes, deviating from what we previously learnt from Landsat data. Statistical analysis compared to well-established observational products and widely used GSWE datasets across some of the world’s most ecologically significant regions, including Pantanal in South America and Haor in South Asia, supports the overall physical realism of our data in predicting global open surface water dynamics. Our key contribution is a prototype Open Science operational framework that extracts routinely available DW products, runs geospatial analytics, and creates actionable water information for educators, researchers, and stakeholders at any scale of practical interest. We present examples of this operational capability through instant mapping of flood in Spain and drought in Lake Urmia, Central Asia, frequent monitoring of river extent changes at the Ganges–Brahmaputra confluence, and above all, interoperability with other existing GSWE applications.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ae137b","usgsCitation":"Khare, A., Gupta, B.C., Rajib, A., Vanderhoof, M.K., Wu, Q., 2025, Estimates of global surface water dynamics harnessing near real-time land cover observations and open science geospatial capabilities: Environmental Research Letters, v. 20, no. 12, 124042, 17 p., https://doi.org/10.1088/1748-9326/ae137b.","productDescription":"124042, 17 p.","ipdsId":"IP-164592","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":500606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ae137b","text":"Publisher Index Page"},{"id":500503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Khare, Arushi","contributorId":366982,"corporation":false,"usgs":false,"family":"Khare","given":"Arushi","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":956524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gupta, Bikas C.","contributorId":366983,"corporation":false,"usgs":false,"family":"Gupta","given":"Bikas","middleInitial":"C.","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":956525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rajib, Adnan","contributorId":365158,"corporation":false,"usgs":false,"family":"Rajib","given":"Adnan","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":956526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":956527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Qiusheng","contributorId":208272,"corporation":false,"usgs":false,"family":"Wu","given":"Qiusheng","email":"","affiliations":[{"id":37769,"text":"Binghamton University","active":true,"usgs":false}],"preferred":false,"id":956528,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272705,"text":"70272705 - 2025 - Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective","interactions":[],"lastModifiedDate":"2025-12-05T15:20:57.10495","indexId":"70272705","displayToPublicDate":"2025-12-04T09:11:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective","docAbstract":"Earth System Models (ESM) are crucial for quantifying climate impacts across Earth's interconnected systems and supporting science-based adaptation and mitigation. However, not including end-users, especially decision-makers representing communities vulnerable to climate change, can limit model utility, increase epistemic risks, and lead to information misuse in decision-making. While the ESM community increasingly values broad community engagement, end-users may not initially perceive models as useful for local planning. Co-designing models with end-users fosters two-way learning: users better understand models and their outputs, while modelers gain insights into fine-scale local processes like monitoring practices and management priorities. Higher-level co-design can lead to more customized, priority-driven, and useful modeling products. Despite these benefits, modelers often struggle to initiate meaningful partnerships with local communities. Therefore, this paper explores model co-design from the perspective of modelers. This study presents two case studies where modelers and social scientists collaborated with Indigenous communities' decision-makers to reflect their priorities in model design and application. In the Arctic Rivers Project, high-resolution climate and hydrology data sets for Alaska were developed with guidance from an Indigenous Advisory Council, using optimized, coupled land-atmosphere models. In the Mid-Klamath Project, we partnered with the Karuk Tribe's Department of Natural Resources to assess climate change and prescribed burning impacts on terrestrial hydrology in the Klamath River Basin. Drawing from these studies, we introduce a four-level framework: (a) Co-design Configuration; (b) Model Tuning; (c) Incorporate Contextual Knowledge; (d) Co-develop New Model Functions. We aim to help researchers consider and compare co-design across diverse modeling projects systematically and coherently.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025AV001921","usgsCitation":"Cheng, Y., Herman-Mercer, N.M., Newman, A.J., Musselman, K., Woelfle-Hazard, C., Blaskey, D., Brooks, C.M., Carlson, T., Koch, J.C., Morrison, M., Mutter, E., Sarna-Wojcicki, D., Thomas, P., Tlen, J., and Toohey, R.C., 2025, Toward co-designed Earth System Models: Reflecting end-user priorities in local applications from a modeler's perspective: AGU Advances, v. 6, no. 6, e2025AV001921, 22 p., https://doi.org/10.1029/2025AV001921.","productDescription":"e2025AV001921, 22 p.","ipdsId":"IP-180103","costCenters":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":497389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025av001921","text":"Publisher Index Page"},{"id":497138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.81342926294906,\n 43.10561588671308\n ],\n [\n -124.48040635076697,\n 43.10561588671308\n ],\n [\n -124.48040635076697,\n 40.206104446782575\n ],\n [\n -120.81342926294906,\n 40.206104446782575\n ],\n [\n -120.81342926294906,\n 43.10561588671308\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -134.3515714377868,\n 54.21401982837219\n ],\n [\n -129.6567253884985,\n 55.448838662658915\n ],\n [\n -135.22819993126652,\n 59.90471003527469\n ],\n [\n -137.5718554227408,\n 59.27306781866508\n ],\n [\n -140.1719287726436,\n 60.887401823457054\n ],\n [\n -141.29803380842512,\n 70.13465386032021\n ],\n [\n -159.35092543271705,\n 71.93980230779283\n ],\n [\n -168.77768266130207,\n 66.4070220804696\n ],\n [\n -173.27479921730367,\n 63.087644787979826\n ],\n [\n -170.49847785815396,\n 54.72140652436224\n ],\n [\n -179.22972703122795,\n 52.19095364355289\n ],\n [\n -179.15904264949774,\n 50.99859454461824\n ],\n [\n -167.48667021150578,\n 52.360855523237205\n ],\n [\n -152.11412379152463,\n 56.65675207331881\n ],\n [\n -145.63785436419175,\n 58.89837720034234\n ],\n [\n -138.264490234756,\n 58.22681850225416\n ],\n [\n -134.3515714377868,\n 54.21401982837219\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheng, Yifan","contributorId":332342,"corporation":false,"usgs":false,"family":"Cheng","given":"Yifan","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":951377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herman-Mercer, Nicole M. 0000-0001-5933-4978 nhmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-5933-4978","contributorId":3927,"corporation":false,"usgs":true,"family":"Herman-Mercer","given":"Nicole","email":"nhmercer@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - 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2025 - Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds","interactions":[],"lastModifiedDate":"2025-12-09T14:17:39.30669","indexId":"70272740","displayToPublicDate":"2025-12-04T07:52:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds","docAbstract":"Animal-borne trackers are commonly used to study bird movements, including in long-distance migrants such as shorebirds. Selecting a tracker and attachment method can be daunting, and methodological advancements often have been made by trial and error and conveyed by word of mouth. We synthesized tracking outcomes across 2745 dorsally mounted trackers on 37 shorebird species around the world. We evaluated how attachment method, power source, data retrieval method, relative tracker mass, and biological traits affected success, where success was defined as whether or not each tag deployment reached its expected tracking duration (i.e. all aspects succeeded for the intended duration of the study: attachment, tracking, data acquisition, and bird survival). We conducted separate analyses for tag deployments with remote data retrieval (‘remote-upload tag deployments') and those that archived data and had to be recovered (‘archival tag deployments'). Among remote-upload tag deployments, those that were a lighter mass relative to the bird, were beyond their first year of production, transmitted data via satellite, or were attached with a leg-loop harness were most often successful at reaching their expected tracking duration. Archival tag deployments were most successful when applied at breeding areas, or when applied to males in any season. Remote-upload tag deployments with solar power, satellite data retrieval, or leg-loop harnesses continued tracking for longer than those with battery power, other types of data retrieval, or glue attachments. However, the majority of tag deployments failed to reach their expected tracking duration (71% of remote-upload, 83% of archival), which could have been due to tracker failure, attachment failure, or bird mortality. Our findings highlight that many tag deployments may fail to meet the goals of a study if tracking duration is crucial. Using our results, we provide guidelines for selecting a tracker and attachment to improve success at meeting study goals.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/jav.03487","usgsCitation":"Weiser, E.L., Lanctot, R., Ruthrauff, D.R., Saalfeld, S.T., Tibbitts, L., Abad-Gómez, J., Aldabe, J., de Almeida, J.B., Alves, J., Anderson, G., Battley, P.F., Belting, H., Bêty, J., Bianchini, K., Bishop, M.A., Bom, R.A., Bowgen, K., Brown, G.S., Brown, S.C., Bugoni, L., Burton, N., Bybee, D.R., Carneiro, C., Castresana, G., Chan, Y., Choi, C., Christie, K., Clark, N., Conklin, J.R., Cruz-López, M., Dinsmore, S., Dodd, S., Douglas, D., Eberhart-Hertel, L., English, W.B., Ewing, H., Faria, F.A., Franks, S.E., Fuller, R., Gill, R., Giroux, M., Gratto-Trevor, C.L., Green, D., Green, R.E., Green, R., Gunnarsson, T., Gutiérrez, J.S., Harrison, A., Hartman, C.A., Hassell, C., Hoepfner, S., Hooijmeijer, J.C., Johnson, J., Johnson, O.W., Kempenaers, B., Klaassen, M., Kok, E., Krietsch, J., Küpper, C., Kwarteng, A., Kwon, E., Lamarre, J., Latty, C., Lecomte, N., Loonstra, A., Ma, Z., Mander, L., 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2070","title":"Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070","docAbstract":"In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070.
Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones.
To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.
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U.S. Geological Survey
1770 Corporate Drive, suite 500
Norcross, GA 30093
Contact Us- USGS Publications Warehouse
","tableOfContents":"Models of coastal barrier geomorphic and ecologic change are valuable tools for understanding and predicting when, where, and how barriers evolve and transition between ecogeomorphic states. Few existing models of barrier systems are designed to operate over spatiotemporal scales congruous with effective management practices (i.e., decades/kilometers, referred to herein as “mesoscales”), incorporate important ecogeomorphic feedbacks, and provide probabilistic projections of future change. Here, we present a new numerical model designed to address these gaps by explicitly yet efficiently simulating coupled aeolian, marine, vegetation, and shoreline components of barrier evolution over spatiotemporal scales relevant to management. The Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) simulates subaerial ecomorphologic change of undeveloped barrier systems over kilometers and decades using meter-scale spatial resolution and weekly time steps. MEEB applies simplified parameterizations to represent and couple key ecogeomorphic processes: dune growth, vegetation expansion and mortality, beach and foredune erosion, barrier overwash, and shoreline and shoreface change. The model is parameterized and calibrated with observed elevation, vegetation, and water level data for a case study site of North Core Banks, NC, USA. Simulated ecogeomorphic change in model hindcasts agrees well with observations, demonstrating both favorable skill scores and qualitatively correct behavior. We also describe an additional model framework for producing probabilistic projections that account for uncertainties related to future forcing conditions and intrinsic stochastic dynamics and demonstrate the probabilistic framework's utility with example forecast simulations. As a mesoscale model, MEEB is designed to investigate questions about future barrier ecogeomorphic change of moderate complexity, offering semi-qualitative predictions and semi-quantitative explanations. For example, MEEB can be used to investigate how climate-induced shifts in ecological composition may alter the likelihood of morphologic impacts or to generate probabilistic projections of ecogeomorphic state change.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-18-9319-2025","usgsCitation":"Reeves, I.R., Ashton, A.D., Lentz, E.E., Sherwood, C.R., Passeri, D., and Zeigler, S., 2025, Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0: Geoscientific Model Development, v. 18, p. 9319-9348, https://doi.org/10.5194/gmd-18-9319-2025.","productDescription":"30 p.","startPage":"9319","endPage":"9348","ipdsId":"IP-170312","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":497392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-18-9319-2025","text":"Publisher Index Page"},{"id":497142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Reeves, Ian Robert 0000-0002-6675-3756","orcid":"https://orcid.org/0000-0002-6675-3756","contributorId":363346,"corporation":false,"usgs":true,"family":"Reeves","given":"Ian","middleInitial":"Robert","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashton, Andrew D. 0000-0002-0241-3090","orcid":"https://orcid.org/0000-0002-0241-3090","contributorId":363347,"corporation":false,"usgs":false,"family":"Ashton","given":"Andrew","middleInitial":"D.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":951467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zeigler, Sara 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951471,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272985,"text":"70272985 - 2025 - Review and synthesis of the applications of machine learning to coalbed methane recovery","interactions":[],"lastModifiedDate":"2025-12-12T14:56:51.475904","indexId":"70272985","displayToPublicDate":"2025-12-02T08:46:30","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Review and synthesis of the applications of machine learning to coalbed methane recovery","docAbstract":"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.
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The reduced-to-pole (RTP) transformation of regional-scale aeromagnetic data shows that allochthonous island-arc rocks west of the Salmon River suture are significantly more magnetic than the Laurentian continental rocks east of the suture and that the granitoids of the Idaho batholith have moderate to low magnetization in both early, metaluminous, and late, peraluminous phases. Application of tilt derivative to aeromagnetic data highlights major crustal-scale structures. The 5-km upward continued magnetic data indicate island-arc rocks have deep magnetic sources. The 110-km-long MT profile images resistivity structure to depths around 30 km. At shallow depths, resistivity corresponds to mapped geologic units, with moderate resistivities underlying volcanic and roof-pendant metasedimentary rocks and moderate to high resistivities occurring beneath the Idaho batholith. Crustal-scale moderate resistivities beneath the suture image the results of tectonomagmatic processes that accompanied suturing and translating allochthonous terranes. Low resistivity values beneath and fringing the batholith are derived from metasedimentary rocks that may have served as a melt source and reductant during melt generation and provided metals during later ore formation.
In the Stibnite-Yellow Pine mining district, a high-resolution aeromagnetic compilation is shown to correlate with mapped lithologies and mineral deposit-related structures. The RTP transform distinguishes magnetic and nonmagnetic granitoid phases of the Idaho batholith. The tilt derivative highlights metasedimentary rocks, some of which are favorable ore hosts. The Meadow Creek fault hosts the Stibnite and Hangar Flats deposits and is imaged as a magnetic low due to hydrothermal alteration. Reconstructions of magnetic anomaly offsets and orebodies indicate around 3 km of post-95 Ma dextral separation, with some or all of the offset inferred to postdate the main Au mineralization episode (61–66 Ma).
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The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiome studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.
","language":"English","publisher":"Nature","doi":"10.1038/s41564-025-02186-2","usgsCitation":"Kelliher, J., Mirzayi, C., Bordenstein, S.R., Oliver, A., Kellogg, C.A., Hatcher, E.L., Berg, M., Baldrian, P., Aljumaah, M., Miller, C.M., Mungall, C., Novak, V., Palucki, A., Smith, E., Tabassum, N., Bonito, G., Brister, J.R., Chain, P.S., Dundore-Arias, J.P., Emerson, J.B., Fernandes, V.M., Flores, R., Gonzalez, A., Hansen, Z.A., Jackson, S.A., Moustafa, A.M., Northen, T.R., Pariente, N., Pett-Ridge, J., Record, S., Reji, L., Reysenbach, A., Rich, V.I., Richardson, L., Roux, S., Schriml, L.M., Shabman, R.S., Sierra, M.A., Sullivan, M.B., Sundaramurthy, P., Thibault, K.M., Thompson, L.R., Tighe, S.W., Vereen, E., STREAMS Consortium, and Eloe-Fadrosh, E., 2025, STREAMS guidelines: Standards for technical reporting in environmental and host-associated microbiome studies: Nature Microbiology, v. 10, p. 3059-3068, https://doi.org/10.1038/s41564-025-02186-2.","productDescription":"10 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This study introduces a cloud-native, open-source workflow designed to evaluate the geometric accuracy and consistency of 3DEP lidar data sets at a national scale. Leveraging tools such as the Point Data Abstraction Library, Open3D, and Amazon Web Services infrastructure, the workflow integrates global navigation satellite system‐surveyed ground control points and terrestrial laser scanning data to validate airborne lidar collections. Two case studies demonstrate the application of this process. In Puerto Rico, the process identified vertical biases and inconsistencies in vegetated areas, while in Iowa and Arizona, the process confirmed high vertical accuracy with minimal bias. The results underscore the effectiveness of combining cloud computing with open-source tools to perform large-scale lidar data quality assessments. This process offers a reproducible, efficient solution for nationwide validation of 3DEP data sets, supporting enhanced decision-making in geospatial applications.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.25-00093R2","usgsCitation":"Sampath, A., Irwin, J., and Stoker, J.M., 2025, Evaluating Three-Dimensional Elevation Program lidar consistency and accuracy at scale using cloud-native, open-source methods: Photogrammetric Engineering and Remote Sensing, v. 91, no. 12, p. 777-785, https://doi.org/10.14358/PERS.25-00093R2.","productDescription":"9 p.","startPage":"777","endPage":"785","ipdsId":"IP-180351","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":498590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Sampath, Aparajithan 0000-0002-6922-4913","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":222486,"corporation":false,"usgs":false,"family":"Sampath","given":"Aparajithan","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":952695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irwin, Jeffrey 0000-0001-5828-0787 jrirwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5828-0787","contributorId":222485,"corporation":false,"usgs":true,"family":"Irwin","given":"Jeffrey","email":"jrirwin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":952696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":952697,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274537,"text":"70274537 - 2025 - What is the (real) rate of soil health practice adoption? Making sense of three data sources","interactions":[],"lastModifiedDate":"2026-04-01T14:57:42.259853","indexId":"70274537","displayToPublicDate":"2025-12-01T09:53:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"What is the (real) rate of soil health practice adoption? Making sense of three data sources","docAbstract":"Conservation stakeholders looking to quantify the impact of their investments to increase soil health practice adoption over time often face challenges in interpreting practice adoption data due to discrepancies in language and results among data sources. Similarly, efforts to estimate environmental outcomes of practice adoption, such as water quality and greenhouse gas emissions, can vary depending on different practice adoption input data. To help make sense of different adoption data sources, we compared county-level adoption data for winter cover crops (WCC), no-till (NT), and reduced tillage (RT) in three areas of the United States with contrasting climates and production systems: central Illinois (CIL), southern Illinois (SIL), and western New York (WNY). We analyzed data available during 2015 through 2022 from the Operational Tillage Information System (OpTIS, remote sensing), US Census of Agriculture (AgCensus, a farmer survey), and, specifically in Illinois, the Illinois Soil Conservation Transect Survey (Transect, a roadside survey). The magnitude of differences between the datasets depended on the practice and geographic location. For example, OpTIS and AgCensus tillage data were much more similar in Illinois (average difference of less than 4 percentage points) compared to New York (average differences of 20 percentage points). Similarly, there was less variability and smaller differences between OpTIS and AgCensus WCC data in Illinois compared to WNY. AgCensus tended to report lower WCC adoption for Illinois and greater adoption in WNY compared to OpTIS. All data sources agreed that the rate of change in tillage practices is slow (mainly –1% to 1%) and that adoption of WCC is low (assuming linear growth, it could take nearly a century to reach 50% WCC adoption in CIL). Differences among the datasets were attributed to definitional inconsistencies for RT and NT and how WCC data were acquired. For example, the AgCensus asks if a WCC was planted, whereas OpTIS and Transect evaluate the presence of a standing WCC. Data sources also reflect different time periods (calendar years or crop years) and types of cropland assessed (corn [Zea mays L.], soybean [Glycine max {L.} Merr.], or all cropland). We propose two recommendations to improve interpretation and consistency: (1) a working group to harmonize definitions and protocols and develop educational materials for data users, and (2) a research effort that integrates different adoption data types and produces publicly available adoption data at HUC-10 and county scales. Such activities could help improve data access and utility for evidence-based conservation decision-making and enhance the accuracy of environmental models that rely on adoption data as input.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00224561.2025.2580218","usgsCitation":"McGill, B.M., Hively, W.D., Puntel, L.A., Shriver, J., Thieme, A.N., Manter, D.K., and Moore, J.M., 2025, What is the (real) rate of soil health practice adoption? Making sense of three data sources: Journal of Soil and Water Conservation, v. 80, no. 6, p. 724-733, https://doi.org/10.1080/00224561.2025.2580218.","productDescription":"10 p.","startPage":"724","endPage":"733","ipdsId":"IP-172017","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":501927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"6","noUsgsAuthors":false,"publicationDate":"2026-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McGill, Bonnie M.","contributorId":368946,"corporation":false,"usgs":false,"family":"McGill","given":"Bonnie","middleInitial":"M.","affiliations":[{"id":87675,"text":"American Farmland Trust","active":true,"usgs":false}],"preferred":false,"id":958154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":958156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puntel, Laila A.","contributorId":368947,"corporation":false,"usgs":false,"family":"Puntel","given":"Laila","middleInitial":"A.","affiliations":[{"id":87676,"text":"Syngenta Group","active":true,"usgs":false}],"preferred":false,"id":958155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriver, John","contributorId":368948,"corporation":false,"usgs":false,"family":"Shriver","given":"John","affiliations":[{"id":87677,"text":"Regrow","active":true,"usgs":false}],"preferred":false,"id":958157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thieme, Alison N.","contributorId":368949,"corporation":false,"usgs":false,"family":"Thieme","given":"Alison","middleInitial":"N.","affiliations":[{"id":87678,"text":"USDA-ARS-SASL","active":true,"usgs":false}],"preferred":false,"id":958158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Manter, Daniel K.","contributorId":368950,"corporation":false,"usgs":false,"family":"Manter","given":"Daniel","middleInitial":"K.","affiliations":[{"id":87679,"text":"USDA-ARS-SMSBR","active":true,"usgs":false}],"preferred":false,"id":958159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Jennifer M.","contributorId":368951,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","middleInitial":"M.","affiliations":[{"id":87680,"text":"USDA-ARS-FSCRU","active":true,"usgs":false}],"preferred":false,"id":958160,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273263,"text":"70273263 - 2025 - The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi","interactions":[],"lastModifiedDate":"2025-12-29T15:58:04.83704","indexId":"70273263","displayToPublicDate":"2025-12-01T09:52:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi","title":"The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi","docAbstract":"Palila (Loxioides bailleui) are critically endangered Hawaiian honeycreepers specializing on māmane (Sophora chrysophylla) seeds and restricted to Mauna Kea volcano on the Island of Hawaiʻi. Recently, the population was estimated to decline by 89% between 1998 and 2021, despite decades of ungulate removal, fence construction, māmane regeneration, fire suppression, and predator control. To inform managers with the most recent update on the status and trends of the Palila population, we analyzed annual bird survey data collected using point-transect distance sampling since 1998, including new annual survey data from 2022, 2023, and 2024. Prior to analysis, we predicted the population trajectory would change between 2021 and 2024 because of continued management actions promoting habitat recovery. We used distance sampling, log-linear regression, and state-space modeling to produce the new estimates and analyze trends across the time series. The 2022 population estimate was 367 to 742 birds (95% confidence interval; point estimate: 545), the lowest in recorded history. The 2023 and 2024 estimates of 374 to 842 birds (point estimate: 596) and 412 to 970 birds (point estimate: 666) were the second and third lowest in our time series, respectively. Our estimates for years before 2022 show population fluctuations between 4000 to 6800 birds from 1998 to 2005, then a steep decline through 2010. For the next decade, abundance fluctuated around 1000 birds, before declining again in 2021 to less than 700 birds. From 1998 to 2024, the population declined by more than 90%, or 205 birds per year, with 100% statistical support for an overall downward trend, despite significant management efforts and research. The greatest threats facing the Palila, if familiar, are not being eliminated swiftly enough to promote their recovery. The currently small and range-limited population is vulnerable to future climate-related events such as drought and fire. Continued monitoring can help to assess the response of Palila to adaptive management actions and changing environmental conditions.
","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-02920-200210","usgsCitation":"Hunt, N., Asing, C.K., Nietmann, L., Banko, P.C., and Camp, R.J., 2025, The continued decline of the Palila (Loxioides bailleui) on Mauna Kea, Island of Hawaiʻi: Avian Conservation and Ecology, v. 20, no. 2, 10, 18 p., https://doi.org/10.5751/ACE-02920-200210.","productDescription":"10, 18 p.","ipdsId":"IP-177477","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":498272,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02920-200210","text":"Publisher Index Page"},{"id":498146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Kea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.62,\n 19.84\n ],\n [\n -155.62,\n 19.736678155129184\n ],\n [\n -155.4741502151662,\n 19.736678155129184\n ],\n [\n -155.4741502151662,\n 19.84\n ],\n [\n -155.62,\n 19.84\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunt, Noah","contributorId":355564,"corporation":false,"usgs":false,"family":"Hunt","given":"Noah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":952938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asing, Chauncey K.","contributorId":272645,"corporation":false,"usgs":false,"family":"Asing","given":"Chauncey","email":"","middleInitial":"K.","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":952939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nietmann, Lindsey","contributorId":331548,"corporation":false,"usgs":false,"family":"Nietmann","given":"Lindsey","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":952940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":952941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":952942,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273727,"text":"70273727 - 2025 - Geothermal potential of orphan oil and gas wells","interactions":[],"lastModifiedDate":"2026-01-26T15:42:24.150439","indexId":"70273727","displayToPublicDate":"2025-12-01T09:34:07","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geothermal potential of orphan oil and gas wells","docAbstract":"The United States is estimated to have hundreds of thousands of orphan oil and gas wells. Orphan wells are abandoned wells that are both unremediated and have no responsible operator. While traditionally considered environmental and economic liabilities, orphan oil and gas wells may offer new opportunities in sustainable geothermal energy development. This study evaluates the potential of repurposing orphan wells for geothermal energy production. We analyzed more than 1.4 million bottom-hole temperature (BHT) records from oil and gas well logs to create corrected temperature-depth profiles in a grid across the United States. Total depth values, where available, in documented orphan wells from a U.S. Geological Survey (USGS) database were then correlated to these temperature-depth profiles to estimate a corrected BHT for each orphan well. The orphan wells were then categorized as having low (<90°C), moderate (90–150°C), and high (>150°C) geothermal potential, identifying them as wells in the U.S. that could be used to access geothermal resources. In addition, repurposing these wells could contribute to broader environmental and economic goals, including well remediation, rogue methane emissions reduction, and energy production. 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and liquid water potential with basin modeling","docAbstract":"Assessing the potential for geothermal energy and liquid water presence in the Martian subsurface is crucial for future exploration and habitability studies. In this work, we employed comprehensive finite element model simulations adapted specifically for Martian conditions to estimate subsurface temperatures and the potential for liquid water at depth within Martian crater basins. Rock and fluid property values for basin fill were carefully adjusted to match Martian gravity, radiogenic heat generation, and compositional characteristics derived from rover analyses, Martian meteorite samples, and orbital spectroscopy data. Multiple modeling scenarios were explored to systematically evaluate end-member cases across critical variables such as heat flow, lithological composition, and average surface temperature. Sensitivity testing revealed that heat flow and average annual surface temperatures are the most important variables. Results were used in calculations based on a database of Martian craters to estimate the temperature of crater fill at depth. Our model results indicate significant potential for sustained liquid water in the subsurface within sedimentary deposits across a range of crater sizes and latitudes. They further suggest that viable geothermal reservoirs likely exist and are potentially accessible for future Martian missions seeking energy sources or exploring astrobiological hypotheses. This study provides a methodological framework for geothermal and hydrological assessments for the subsurface of Mars, contributing to ongoing planetary exploration strategies.
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2025 - Potential for co-production of lithium and geothermal resources in the Gulf Coast","interactions":[],"lastModifiedDate":"2026-01-26T15:53:11.820202","indexId":"70273723","displayToPublicDate":"2025-12-01T09:13:50","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Potential for co-production of lithium and geothermal resources in the Gulf Coast","docAbstract":"Lithium brine extractions and geothermal resource developments often are not economically viable as standalone projects, but they May become cost effective when the potential for both resources exist within the same reservoir. Subsurface datasets were analyzed to identify areas in the U.S. Gulf Coast region with potential for lithium brine and geothermal heat recovery. Temperature, lithium brine content, and reservoir quality data for thirty-four depositional units were evaluated using spatial analysis to interpret high-grade areas where both resources likely coexist. For sedimentary geothermal systems, potential resource areas are sorted by resource grade: as low temperature (<90°C, direct use potential), moderate temperature (90–150°C, direct use and electricity generation), and high temperature (>150°C, primarily electricity generation). Lithium resources were defined by Li lithium brine concentrations in parts per million (ppm): low potential (<100ppm), moderate potential (100–200ppm), and high potential (>200ppm). Reservoir quality affects the viability of both resources and is evaluated using interpreted lithofacies that describe the depositional environments of each unit. Using the results, a series of play fairway analysis maps were generated to support regional evaluations of lithium and geothermal resources and to identify areas of interest for detailed, prospect-scale studies.
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","language":"English","publisher":"Project Euclid","doi":"10.1214/25-AOAS2096","usgsCitation":"Oram, J., Banner, K.M., Stratton, C., Hoegh, A., and Irvine, K., 2025, Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data: Annals of Applied Statistics, v. 19, no. 4, p. 2957-2980, https://doi.org/10.1214/25-AOAS2096.","productDescription":"24 p.","startPage":"2957","endPage":"2980","ipdsId":"IP-149507","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":497379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/25-aoas2096","text":"Publisher Index Page"},{"id":497320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oram, Jacob 0009-0001-8405-529X","orcid":"https://orcid.org/0009-0001-8405-529X","contributorId":353522,"corporation":false,"usgs":false,"family":"Oram","given":"Jacob","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Katharine M.","contributorId":363761,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":951957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272620,"text":"dr1217 - 2025 - Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","interactions":[],"lastModifiedDate":"2026-02-03T16:40:49.220576","indexId":"dr1217","displayToPublicDate":"2025-12-01T07:18:23","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1217","displayTitle":"Range-wide Population Trend Analysis for Greater Sage-Grouse (Centrocercus urophasianus)—Updated 1960–2024","title":"Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","docAbstract":"Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population trend analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefiting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2024. Included in this report are methodological updates to lek count data aggregation, state-space model forecasting, and targeted annual warning system signals, which are detailed under individual Modification sections. State-space models estimated a 2.9-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.2 and 3.4 percent. Cumulative declines were 41.2, 64.1, and 78.8 percent range-wide in Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1217","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Ecosystems Mission Areas—Species Management Research Program and Land Management Research Program","usgsCitation":"Prochazka, B.G., Coates, P.S., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2025, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024: U.S. Geological Survey Data Report 1217, 22 p., https://doi.org/10.3133/dr1217.","productDescription":"Report: viii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-182475","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496879,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.XML"},{"id":496877,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"USGS data release","description":"USGS data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (ver. 4.0, November 2025)"},{"id":496878,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1217/images"},{"id":496874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1217/coverthb.jpg"},{"id":496875,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1217"},{"id":496876,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1217/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1217"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.02726904687307,\n 37.11378745198651\n ],\n [\n -107.91246282672654,\n 39.23148053932573\n ],\n [\n -104.18656479624082,\n 42.68923879351195\n ],\n [\n -104.09712675152082,\n 44.90768367632023\n ],\n [\n -103.10713250018665,\n 45.28903162099806\n ],\n [\n -103.07124138706033,\n 46.81624492709619\n ],\n [\n -105.38823344586734,\n 48.94676636341262\n ],\n [\n -120.30657593063506,\n 48.87342393238805\n ],\n [\n -120.60087183124688,\n 42.81488245718879\n ],\n [\n -120.58608571052426,\n 38.32426094909158\n ],\n [\n -117.42786260245566,\n 36.55795546064512\n ],\n [\n -113.02726904687307,\n 37.11378745198651\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
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The Hawaiian Volcanoes Supersite was established in 2008 with the goal of making large amounts of volcano monitoring data, especially satellite measurements, freely available at a site of international interest, scientific importance, and impactful natural hazards. The location was chosen because of the long history of volcanological research and innovation on the Island of Hawaiʻi, as well as the need for monitoring, assessing, and mitigating volcanic hazards for the local population. Ground-based data are provided by the U.S. Geological Survey Hawaiian Volcano Observatory, and several national space agencies have contributed thousands of satellite synthetic aperture radar and other data that would have otherwise required special grants or commercial purchase. Since the Hawaiian Volcanoes Supersite was initiated, the vast quantity of open space-based data has resulted in the development of new applications and methodologies, successful responses to volcanic crises, and research that has informed monitoring and hazards mitigation activities. While there remain opportunities for additional coordination among supersite users and for synergistic studies that make use of the full spectrum of available ground- and space-based data, the Hawaiian Volcanoes Supersite has achieved its goals of stimulating basic research to better understand Hawaiian volcanism and aiding in responses to hazardous geologic processes. The effort serves as a model for the benefits of open, low-latency, and comprehensive satellite data applied to disaster risk management and reduction, meeting a vision that has been laid out repeatedly in international agreements and accords.
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hydrologic connectivity through the analyses of landscape drivers of hysteresis","interactions":[],"lastModifiedDate":"2025-12-05T14:42:36.637757","indexId":"70272712","displayToPublicDate":"2025-11-28T08:34:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling geomorphic equifinality in sediment and hydrologic connectivity through the analyses of landscape drivers of hysteresis","docAbstract":"Sources, transport mechanisms and pathways of fine sediment in river systems are dependent on a multitude of climatic, geomorphic and anthropogenic factors, resulting in geomorphic equifinality, in which it is difficult to parse how different landscape processes affect sediment transport across different spatiotemporal scales. The objectives of this study are to 1) provide a conceptual model to consider how differing spatial distributions and hydrologic timing of sediment sources, both upland and in-channel, can result in equifinal sediment transport outcomes, and 2) utilize analytical methods with widely available environmental datasets to infer sediment processes from stream gaging data. Hysteretic patterns of observed storm events were classified based on their direction and timing of peak sediment concentration, relative to streamflow, using records from 35 U.S. Geological Survey stream gages in the period between 2007 and 2023 within two different physiographic regions: the Mid-Atlantic Delaware River Basin (DRB) and the Midwestern Illinois River Basin (IRB). The DRB contains mixed forest, urban, suburban and agricultural watersheds over diverse topography, and the IRB is primarily an intensively managed agricultural watershed on flat terrain. We use principal component analysis and linear discriminant analysis to infer regional hydrologic relations with turbidity dynamics, and to identify the primary hydrologic and land surface characteristics most effective at distinguishing between hysteretic classes in each region. These analyses reveal underlying regional relations in storm event hydrodynamics and landscape characteristics that contribute to varying patterns in sediment dynamics. Incorporating these sediment dynamic relations with spatial distributions and hydrologic timing of sediment sources could help to improve process understanding and predictive capability of fine sediment transport in watersheds.
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