The Strawberry Creek watershed, situated in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the impact of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study we constructed the Strawberry Creek integrated hydrological model (SCIHM) to increase this understanding. The SCIHM is an integrated surface runoff and groundwater model that uses the coupled groundwater and surface-water flow model (GSFLOW), which is based on the integration of the precipitation-runoff modeling system (PRMS) and the modular groundwater flow model commonly called MODFLOW, version MODFLOW-2005 software to simulate surface runoff and infiltration and groundwater flow. The model has three layers, 263 rows, and 176 columns. The model area includes the Strawberry Creek and four adjacent watersheds. The PRMS model was calibrated using two streamflow gaging stations and the GSFLOW model was calibrated to reported spring diversion discharge and a sparse number of groundwater-level measurements. The SCIHM was run with and without diversions active and simulated streamflow was compared, finding that in the headwaters of Strawberry Creek about 35 percent of the diversion flow was captured from base flow.
","language":"English","publisher":"EartharXiv","doi":"10.31223/X5JB2K","usgsCitation":"Ryter, D.W., Hevesi, J.A., and Woolfenden, L.R., 2025, Simulation of the impacts of spring fiversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model: EarthArXiv, https://doi.org/10.31223/X5JB2K.","productDescription":"52 p.","ipdsId":"IP-181734","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":497778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ryter, Derek W. 0000-0002-2488-626X dryter@usgs.gov","orcid":"https://orcid.org/0000-0002-2488-626X","contributorId":3395,"corporation":false,"usgs":true,"family":"Ryter","given":"Derek","email":"dryter@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hevesi, Joseph A.","contributorId":362410,"corporation":false,"usgs":false,"family":"Hevesi","given":"Joseph","middleInitial":"A.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":950447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woolfenden, Linda R.","contributorId":362411,"corporation":false,"usgs":false,"family":"Woolfenden","given":"Linda","middleInitial":"R.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":950448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70274557,"text":"70274557 - 2025 - Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections","interactions":[],"lastModifiedDate":"2026-03-31T13:53:52.426422","indexId":"70274557","displayToPublicDate":"2025-11-21T08:40:53","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections","docAbstract":"Climate change is expected to impact hydrological regimes worldwide, including the Pacific Northwest of the United States. This study investigates how climate change will affect river discharge in the Puget Sound region of the State of Washington, with a focus on King and Pierce Counties. We simulated river discharge under historical and future conditions using
the physically based, spatially distributed wflow_sbm hydrological model, which was calibrated and validated against U.S. Geological Survey discharge records. Future forcing was based on an ensemble of six high-resolution CMIP6 climate models, which were bias corrected using empirical quantile mapping. The results indicate a decrease in summer discharges (5–10%) and an increase in winter discharges (5–10%) across the study region. The high discharges (90th percentile) are projected to increase in winter, and the low discharges are projected to decrease in summer, due to shifts in precipitation regimes, snowpack hydrology, and evapotranspiration. However, variability between individual CMIP6 models often exceeds the magnitude of ensemble mean changes, underscoring substantial uncertainty in climate projections and the importance of including multiple climate models in climate change analysis. Furthermore, model consensus increased with elevation, which could be the result of the higher elevation areas being driven by less diverse hydrological processes. These findings highlight potential challenges for regional water management, ecosystem health, and flood risk mitigation in the Puget Sound region under future climate conditions.
Effects of large-scale flooding on forest composition and structure are a function of flood duration, depth, timing, and frequency. Throughout the Upper Mississippi River System (UMRS), floods in 1993 and 2019 were record-setting events followed by high rates of tree mortality. These events generated interest in species adaptations to flood event characteristics and how forest communities have changed in response to large-scale floods. We investigated associated tree mortality, how the floods differed spatially, and how floodplain forest communities have changed since 1993. Eight UMRS reaches were surveyed in a 1995 study, documenting vegetation species composition, size, and abundance. In 2021, a selection of plots (63%) were revisited and surveyed to quantify 2019 flood effects. For each site, we extracted daily inundation data for flood years and preceding decades from a surface water inundation model. We found post-flood mortality varied spatially and generally reflected inundation duration patterns. Lower latitude reaches experienced longer inundation durations and greater tree mortality in 1993 than in 2019, while higher latitude reaches experienced similar inundation duration and depth and similar mortality between events. Decadal inundation attributes also differed. During 2009–2018, inundation duration was greater and events occurred later than during 1983–1992 in all reaches. Most forest trajectories were Acer saccharinum-dominated and changed relatively little in species composition and structure. The greatest change in composition occurred at plots with high mortality from the 1993 flood, particularly in more flood-prone locations or where there were many small-diameter individuals. In plots dominated by either Quercus spp. or Populus deltoides, species importance shifted toward more shade and flood-tolerant species after 1995 surveys. Self-replacement of these species may be limited by a change in regeneration conditions resulting from an ongoing inundation regime shift in the case of Quercus spp., or succession to more shade-tolerant species in the case of Populus communities. Overall, effects on floodplain forests from the two flood events were heterogeneous. In some cases, forest change was likely just as influenced by shifts in flood regime as it was from singular flood events.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70440","usgsCitation":"Weiss, S.A., Guyon, L.J., De Jager, N.R., Cosgriff, R.J., and Van Appledorn, M., 2025, Quantifying floodplain forest community change following large-scale flood events in the Upper Mississippi River System: Ecosphere, v. 16, no. 11, e70440, 25 p., https://doi.org/10.1002/ecs2.70440.","productDescription":"e70440, 25 p.","ipdsId":"IP-168280","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":502048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70440","text":"Publisher Index Page"},{"id":501951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.95959025406495,\n 44.864528650415735\n ],\n [\n -91.03900071075344,\n 42.05364635279252\n ],\n [\n -91.77356103532435,\n 40.00507367513167\n ],\n [\n -90.02194205702455,\n 36.004010100510584\n ],\n [\n -88.88384187139445,\n 36.26259089451513\n ],\n [\n -90.52583463005158,\n 39.94132189789401\n ],\n [\n -89.73636511669805,\n 42.189192561781\n ],\n [\n -91.24649150402311,\n 45.075229707941105\n ],\n [\n -92.95959025406495,\n 44.864528650415735\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiss, Shelby A.","contributorId":368922,"corporation":false,"usgs":false,"family":"Weiss","given":"Shelby","middleInitial":"A.","affiliations":[{"id":55549,"text":"National Great Rivers Research and Education Center","active":true,"usgs":false}],"preferred":false,"id":958115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guyon, Lyle J.","contributorId":215690,"corporation":false,"usgs":false,"family":"Guyon","given":"Lyle","email":"","middleInitial":"J.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":958116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":958117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosgriff, Robert J.","contributorId":215692,"corporation":false,"usgs":false,"family":"Cosgriff","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":958118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":958119,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272760,"text":"70272760 - 2025 - Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes","interactions":[],"lastModifiedDate":"2025-12-08T16:27:04.053909","indexId":"70272760","displayToPublicDate":"2025-11-20T09:20:07","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":"Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes","docAbstract":"Great subduction earthquakes (Mw ≥ 8.0) can generate devastating tsunamis by rapidly displacing the seafloor and overlying water column. These potentially tsunamigenic seafloor offsets result from coseismic fault slip and deformation beneath or within the accretionary wedge. The mechanics of these shallow rupture phenomena and their dependence on subduction zone properties remain unresolved, partly due to the sparsity of offshore observations of shallow megathrust earthquake deformation. Here, we analyze how offshore structure influences shallow rupture mechanics and slip partitioning using 3D dynamic earthquake simulations of the Cascadia subduction zone (CSZ) megathrust with and without variably dipping seaward- or landward-vergent splay faults in the wedge that sole into the megathrust. Resulting tradeoffs between splay and megathrust slip reveal structural controls on rupture partitioning, with greater splay slip leading to less shallow megathrust slip updip. Gently dipping and seaward-vergent splays host more slip than those with steeper, landward-vergent splays. To isolate the underlying mechanisms, we compare models with Andersonian and plunging principal stresses. Results suggest distinct static and dynamic processes control the dip- and vergence-dependence of splay rupture: static (mis)alignment relative to far-field tectonic loading favors slip on more optimally oriented, shallowly dipping splay faults. In contrast, dynamic stress interactions of an updip-propagating megathrust rupture front with the free surface and potential branch faults favor forward branching onto seaward-vergent splays and inhibit backward branching onto landward-vergent splays. Resulting seafloor displacements suggest splay fault structure may influence coseismic tsunami source processes, highlighting the importance of dynamically viable rupture scenarios in subduction hazard assessments.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025AV001812","usgsCitation":"Biemiller, J.B., Gabriel, A., Staisch, L.M., Ulrich, T., Dunham, A., Wirth, E.A., Watt, J., Lucas, M.C., and Ledeczi, A., 2025, Structural controls on splay fault rupture dynamics during Cascadia megathrust earthquakes: AGU Advances, v. 6, no. 6, e2025AV001812, 22 p., https://doi.org/10.1029/2025AV001812.","productDescription":"e2025AV001812, 22 p.","ipdsId":"IP-178619","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":497403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025av001812","text":"Publisher Index Page"},{"id":497199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.06174594550313,\n 50.792270218333016\n ],\n [\n -123.78891671425012,\n 35.05484640084913\n ],\n [\n -120.83491668887615,\n 36.08348722338981\n ],\n [\n -121.77409533925982,\n 45.94148964580287\n ],\n [\n -124.46022466182565,\n 51.84936657852123\n ],\n [\n -129.06174594550313,\n 50.792270218333016\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Biemiller, James Burkhardt 0000-0001-6663-7811","orcid":"https://orcid.org/0000-0001-6663-7811","contributorId":343684,"corporation":false,"usgs":true,"family":"Biemiller","given":"James","email":"","middleInitial":"Burkhardt","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":951617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gabriel, Alice-Agnes","contributorId":204611,"corporation":false,"usgs":false,"family":"Gabriel","given":"Alice-Agnes","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":951618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ulrich, Thomas","contributorId":204613,"corporation":false,"usgs":false,"family":"Ulrich","given":"Thomas","email":"","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":951620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Audrey 0000-0001-9719-9287","orcid":"https://orcid.org/0000-0001-9719-9287","contributorId":361490,"corporation":false,"usgs":true,"family":"Dunham","given":"Audrey","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":951623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lucas, Madeleine C.","contributorId":336741,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","middleInitial":"C.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":951624,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ledeczi, Anna","contributorId":336740,"corporation":false,"usgs":false,"family":"Ledeczi","given":"Anna","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":951625,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70272630,"text":"70272630 - 2025 - Systematic approach to prioritize wells for effective groundwater monitoring and management in the Arkansas Headwaters Basin, Colorado, USA","interactions":[],"lastModifiedDate":"2025-11-26T15:19:53.684111","indexId":"70272630","displayToPublicDate":"2025-11-20T09:11:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Systematic approach to prioritize wells for effective groundwater monitoring and management in the Arkansas Headwaters Basin, Colorado, USA","docAbstract":"Urban stream rehabilitation plans can benefit from knowledge of the landscape setting and vegetative communities that were adjacent to streams prior to urbanization. Downstream to upstream connections of these characteristics can be relevant for native migratory fish species that have a range of preferred spawning habitats. Based on a need for more quantitative data on these potential connections, the U.S. Geological Survey assembled geomorphic characteristics, surficial geology, and pre-Euro-American settlement vegetation for 333 kilometers of stream segments in the Kinnickinnic River and Menomonee River subbasins of the Milwaukee River, Wisconsin. Channel slopes ranged from less than 0.3 percent to greater than 2 percent, covering at least two channel morphology and bedform types spanning low-energy irregular and pool-riffle complexes. Postglacial surficial geology ranged from coarse-grained outwash sand and gravel to lacustrine silt and clay, allowing for a range of stream substrate sizes. Presettlement riparian vegetation was mainly forest, including forested uplands, forested lowlands, and to a lesser extent, conifer-dominated wetlands in headwaters. This resulting framework of geomorphic habitat response units can be used for habitat rehabilitation projects for migratory native fish in other urban Great Lakes tributaries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251049","collaboration":"Prepared in cooperation with Milwaukee Metropolitan Sewerage District and the University of Wisconsin","usgsCitation":"Fitzpatrick, F.A., Sterner, S.P., Blount, J.D., and Stewart, J.S., 2025, Geomorphic habitat response units for urban stream rehabilitation, Milwaukee, Wisconsin: U.S. Geological Survey Open-File Report 2025–1049, 17 p., https://doi.org/10.3133/ofr20251049.","productDescription":"Report: vi, 17 p.; Data Release","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154626","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496620,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90S2FMB","text":"USGS data release","linkHelpText":"Geomorphic habitat response units attributes for the Wisconsin DNR 24k hydrography flowline network in the Milwaukee River Basin, Wisconsin"},{"id":496619,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1049/ofr20251049.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1049 XML"},{"id":496615,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1049/coverthb.jpg"},{"id":496616,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1049/ofr20251049.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025–1049"},{"id":496617,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1049/images"},{"id":496618,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251049/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025–1049 HTML"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.21,\n 43.3\n ],\n [\n -88.21,\n 42.8\n ],\n [\n -87.8,\n 42.8\n ],\n [\n -87.8,\n 43.3\n ],\n [\n -88.21,\n 43.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Dr.
Madison, WI 53726
The U.S. Geological Survey intersected stream network geomorphic characteristics with maps of original pre-Euro-American settlement vegetation, surficial geology, and land-use attributes for the Kinnickinnic River and Menomonee River subbasins of the Milwaukee River Basin in eastern Wisconsin. The resulting framework of geomorphic habitat response units can be used for planning, designing, and evaluating ongoing and future native fish passage and spawning habitat rehabilitation projects in other urban areas where concrete-lined channels are being replaced with more natural counterparts.
","publicationDate":"2025-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209516,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sterner, Shelby P. 0000-0002-3103-7960","orcid":"https://orcid.org/0000-0002-3103-7960","contributorId":292246,"corporation":false,"usgs":true,"family":"Sterner","given":"Shelby","email":"","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stewart, Jana S. 0000-0002-8121-1373","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":211037,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950542,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271405,"text":"sir20255017 - 2025 - Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","interactions":[],"lastModifiedDate":"2026-02-03T16:32:26.605397","indexId":"sir20255017","displayToPublicDate":"2025-11-19T11:56:06","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":"2025-5017","displayTitle":"Groundwater Response to Managed Aquifer Recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","title":"Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona","docAbstract":"Managed aquifer recharge is a widespread practice for storing water in the subsurface as groundwater. At a managed aquifer recharge facility in southern Arizona, groundwater-level and repeat microgravity data were collected to monitor aquifer response. These data were used to inform parameter identification for an unsaturated-zone flow model used to simulate the recharge process. The facility, the Southeast Houghton Artificial Recharge Project (SHARP), consists of 3 surface basins (about 27,600 square meters [6.8 acres] total surface area) where recycled water is distributed in recharge cycles lasting several months, with dry periods in between. During the study period, December 2020–December 2022, Tucson Water (the City of Tucson’s water utility) reported 6.56×106 cubic meters of water (5,320 acre-feet) recharged.
Monitoring included groundwater-level observations at 3 monitoring wells and repeat microgravity measurements at as many as 22 locations (some stations were destroyed between surveys). Six gravity surveys were carried out using absolute- and relative-gravity meters. Large gravity increases, more than 250 microgals, were observed during the first repeat survey, 3.5 months after the start of recharge, but only in the immediate vicinity of the recharge basins. Data show that water moved downward to the water table, and storage changes in the unsaturated zone away from the facility were likely minimal. Gravity decreased at stations more than 1 kilometer from the facility, consistent with regional groundwater-level changes. Groundwater-level increases in wells adjacent to the recharge basins began 2 months after the second repeat gravity survey, and 5.5 months after recharge began.
Unsaturated-zone flow modeling was carried out using software that simulates water movement and parameter estimation. Model calibration was carried out by minimizing an objective function calculated from the differences between simulated and observed groundwater levels, and between simulated and observed repeat microgravity data. Including repeat microgravity data in the objective function reduced the uncertainty in estimated parameter values for saturated hydraulic conductivity and saturated water content. Modeling indicated that the unsaturated zone between the recharge basins and the water table does not become saturated even after 685 days of simulated infiltration. This gradual wetting may account for increasing infiltration rates over time, as hydraulic conductivity increases with increasing water content. Unsaturated-zone water content decreased rapidly between recharge cycles. Model-simulated groundwater mounding extended about 1 kilometer from the center of SHARP after the 685-day period following the onset of recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255017","collaboration":"Prepared in cooperation with Tucson Water","programNote":"Water Availability and Use Program","usgsCitation":"Wildermuth, L.M., Kennedy, J.R., and Conrad, J.L., 2025, Groundwater response to managed aquifer recharge at the Southeast Houghton Artificial Recharge Project in Tucson, Arizona: U.S. Geological Survey Scientific Investigations\nReport 2025–5017, 38 p., https://doi.org/10.3133/sir20255017.","productDescription":"Report: v, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-152298","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":497795,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118986.htm"},{"id":495375,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E19SSK","text":"USGS data release","description":"Landrum, M.T., 2021, Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024): U.S. Geological Survey data release, https://doi.org/10.5066/P9E19SSK.","linkHelpText":"Repeat microgravity data from South Houghton Area Recharge Project, Tucson, Arizona, 2020-2022 (ver. 2.0, August 2024)"},{"id":495371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5017 PDF"},{"id":495370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5017/coverthb.jpg"},{"id":495372,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255017/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5017 HTML"},{"id":495374,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5017/images"},{"id":495373,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5017/sir20255017.XML","description":"SIR 2025-5017 XML"}],"country":"United States","state":"Arizona","city":"Tucson","otherGeospatial":"Southeast Houghton Artificial Recharge Project","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.758333,\n 32.159722\n ],\n [\n -110.758333,\n 32.141667\n ],\n [\n -110.791667,\n 32.141667\n ],\n [\n -110.791667,\n 32.159722\n ],\n [\n -110.758333,\n 32.159722\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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Landscapes encompass both aquatic and terrestrial ecosystems that experience the same climate but may respond to climate in divergent ways. For example, the time lag between seasonal dry-down of terrestrial soil moisture and decline in streamflow has important implications for species and ecosystem processes across the aquatic–terrestrial interface. How these lags between aquatic and terrestrial hydrology vary with climate and spatial location within watersheds remains largely unexplored. Here, we examine seasonal patterns of aquatic–terrestrial dry-down across seven watersheds in the northwestern USA, spanning a wide range of aridity. We compared daily streamflow data from USGS gages at watershed outlets with simulated daily soil moisture (1979–2020) from multiple locations within each watershed. In all watersheds, annual dry cycles progressed sequentially through the following features: evapotranspiration, precipitation, shallow soil moisture, deep soil moisture, and finally streamflow. Seasonal streamflow minima lagged behind soil moisture minima for shorter durations in more arid watersheds and drier years. Within watersheds, lag times varied spatially due to interactions between elevation and aridity, with short lags in low-elevation soils near streams in arid watersheds and longer lags in less arid watersheds. Collectively, these results indicate shorter lags between seasonal aquatic and terrestrial dry periods in drier watersheds and years, and show that these tighter linkages are spatially aggregated in drier watersheds. The co-occurrence of seasonally dry conditions in both aquatic and terrestrial systems under increasing aridification is likely to intensify stressors on ecosystems and services. Recognizing these patterns may be critical for predicting ecosystem vulnerabilities and informing adaptation strategies to mitigate the impacts of seasonally dry conditions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70413","usgsCitation":"Butterfield, B.J., Schlaepfer, D.R., Al-Chokhachy, R., Dunham, J., Groom, J.D., Muhlfeld, C.C., Torgersen, C.E., and Bradford, J., 2025, Aridity reduces lag times between aquatic and terrestrial dry-down among watersheds and across years in the northwest US: Ecosphere, v. 16, no. 11, e70413, 14 p., https://doi.org/10.1002/ecs2.70413.","productDescription":"e70413, 14 p.","ipdsId":"IP-176106","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":496924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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interdisciplinary collaboration coordinated by the Mississippi Alluvial Plain project to provide a tool that stakeholders can use to support water-resource management decisions. Groundwater withdrawals from the Mississippi River Valley alluvial (MRVA) aquifer have been vital to support agricultural production in the region, but substantial groundwater-level declines near Shellmound, Mississippi, have caused concerns for long-term sustainability of the aquifer. To better understand the subsurface and try to mitigate the long-term groundwater-level declines, stakeholders have undertaken actions including a Groundwater Transfer and Injection Pilot (GTIP) project using a riverbank filtration-based managed aquifer recharge approach. The pilot project consisted of extracting groundwater near the Tallahatchie River and reinjecting it into the aquifer 3 kilometers west where water levels have substantially declined. A high-resolution airborne electromagnetic (AEM) survey was also completed to collect electrical resistivity data to support the GTIP project and the development of the groundwater model.
The inset groundwater-flow model was developed to (1) integrate the AEM data into the optimal layering configuration of the MRVA aquifer that the available observation data can support through calibration, and (2) assess the potential effect of the GTIP project on the groundwater levels. The AEM data were processed into three different layering configurations leading to the development of model A (18 layers), model B (16 layers), and model C (8 layers), all at a 100- x 100-meter cell spatial resolution using the U.S. Geological Survey modular finite-difference flow model 6 code with Newton-Raphson formulation. The model development process integrated recent advances in modeling, such as the incorporation of AEM data, the use of outputs from the soil-water-balance (SWB) model, and the Aquaculture and Irrigation Water-Use Model, and was facilitated by robust automation using the open-source python packages Modflow-setup and SFRmaker. Using Parameter Estimation ++ Iterative Ensemble Smoother, the three numerical groundwater-flow models (models A, B, and C) were calibrated against a set of observations, which included aquifer groundwater levels, streamflows, stream stage, and aquifer transmissivity. Results indicate that the detailed representation of MRVA aquifer layers in model A produced the best calibrated model by history matching, and the integration of data representing surficial connectivity played a key role in improving groundwater recharge and enhancing the ability of the model to match groundwater levels in the cone of depression. A forecast model simulated the managed aquifer recharge approach, and the results indicated that, given average irrigation and recharge conditions (2010–15), the GTIP project has the potential to induce groundwater-level increases of as much as 3 meters around the injection site, but a sustained increase would require repetition in subsequent years of water transfer at 2022 rates or above.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255055","collaboration":"Prepared in cooperation with U.S. Department of Agriculture Agricultural Research Service and the Mississippi Department of Environmental Quality","programNote":"Water Availability and Use Science Program","usgsCitation":"Guira, M., Traylor, J.P., Leaf, A.T., and Weisser, A.R., 2025, An inset groundwater-flow model to evaluate the effects of layering configuration on model calibration and assess managed aquifer recharge near Shellmound, Mississippi: U.S. Geological Survey Scientific Investigations Report 2025–5055, 134 p., https://doi.org/10.3133/sir20255055.","productDescription":"Report: ix, 134 p.; 3 Figures: 11.00 x 8.50 inches; Data Release; Dataset","numberOfPages":"148","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154357","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"links":[{"id":497793,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118974.htm"},{"id":495719,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2025/5055/downloads/","text":"Layered figures","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Downloadable layered PDF files for figures 11, 12, and 13"},{"id":495626,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13DWA86","text":"USGS data release","linkHelpText":"Inset models used to evaluate the effects of layering configuration on model calibration from 1900 to 2018, and assess managed aquifer recharge near Shellmound, Mississippi, from 2019 to 2050"},{"id":495670,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255055/full"},{"id":495623,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.XML"},{"id":495622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5055/sir20255055.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5055"},{"id":495625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":495624,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5055/images/"},{"id":495621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5055/coverthb.jpg"}],"country":"United States","state":"Mississippi","city":"Shellmound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.55,\n 33.8\n ],\n [\n -90.55,\n 33.5\n ],\n [\n -90.1667,\n 33.5\n ],\n [\n -90.1667,\n 33.8\n ],\n [\n -90.55,\n 33.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
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In 2021–22, clade 2.3.4.4b highly pathogenic avian influenza (HPAI) viruses were introduced by wild birds into North America, leading to geographically widespread disease. In response to HPAI outbreaks throughout late 2021 and early 2022, we recorded observations of sick and dead birds, estimated abundance of carcasses, collected swab and sera samples to detect viruses, and monitored bird nesting on the Yukon-Kuskokwim Delta region of Alaska to document potential effects of disease. Thirty-six reports of sick and dead birds were registered across the region. Nineteen carcasses were opportunistically collected for diagnostic testing, of which 12 were confirmed to be infected with clade 2.3.4.4b HPAI viruses. Carcass abundance estimates from line-distance sampling provided evidence that the most common species of dead birds from the western Yukon-Kuskokwim Delta region were Cackling Goose (Branta hutchinsii minima), Glaucous Gull (Larus hyperboreus), and Black Brant (Branta bernicla nigricans). Only one paired cloacal and oropharyngeal swab sample from a Northern Pintail (Anas acuta) tested positive for clade 2.3.4.4b HPAI virus, out of 464 live-captured duck and goose samples. Of 195 sera samples from waterfowl screened for antibodies reactive to influenza A viruses, antibodies were found in 41–98% of samples collected from Emperor Goose (Anser canagicus), Cackling Goose, Black Brant, and Spectacled Eider (Somateria fischeri). In addition, 15–98% of the same sera samples were reactive to a clade 2.3.4.4b H5 antigen. Fewer Black Brant and Emperor Goose nests were found on long-term study plots during 2022 than in previous years. Collectively, we found that HPAI viruses affected at least seven species of wild birds inhabiting the region during 2022. The full scope of impacts of HPAI at this location during 2022 is unknown, but our data indicate that acute effects to avian population health on the Yukon-Kuskokwim Delta region were likely modest.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00199","usgsCitation":"Daniels, B., Osnas, E.E., Boldenow, M., Gerlach, R., Ahlstrom, C., Coburn, S., Brook, M.J., Brubaker, M., Fischer, J., Koons, D.N., Matz, A., Murphy, M., Rizzolo, D., Scott, L.C., Sinnett, D.R., Thompson, J.M., Lenoch, J., Kim Torchetti, M., Stallknecht, D., Poulson, R., and Ramey, A.M., 2025, Observational, virological, and serological data provide insights into an outbreak of highly pathogenic avian influenza among wild birds on the Yukon-Kuskokwim Delta, Alaska in 2022: Journal of Wildlife Diseases, v. 61, no. 4, p. 1010-1027, https://doi.org/10.7589/JWD-D-24-00199.","productDescription":"18 p.","startPage":"1010","endPage":"1027","ipdsId":"IP-171898","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":950513,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lenoch, Juliana","contributorId":347254,"corporation":false,"usgs":false,"family":"Lenoch","given":"Juliana","email":"","affiliations":[{"id":83108,"text":"WS National Wildlife Disease Program, U.S. Department of Agriculture, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":950514,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":950515,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":950516,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":950517,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":950518,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70272147,"text":"fs20253042 - 2025 - Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico","interactions":[],"lastModifiedDate":"2026-02-03T16:30:25.529535","indexId":"fs20253042","displayToPublicDate":"2025-11-17T12:20:32","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3042","displayTitle":"Preserving and Increasing Water Resources—Natural Infrastructure in Dryland Streams in Baja California Sur, Mexico","title":"Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico","docAbstract":"The Los Planes watershed of Baja California Sur, Mexico, and its underlying aquifer are experiencing groundwater decline owing to low average annual rainfall (28.1 centimeters per year) and rising water demand from population growth and agricultural activities. This decline in water availability can lead to desertification—a process that changes arable land to desert by degrading soil and vegetation—and can pose serious challenges to livelihoods that depend on the land.
To address these issues, a ranch in the Los Planes watershed has installed many natural infrastructures in dryland streams (NIDS) in channels for soil and water conservation. In 2022, the U.S. Geological Survey (USGS) began working with regional researchers and land managers to investigate the effects of NIDS on natural biological, geochemical, and physical processes and determine the efficacy of NIDS for water augmentation in the Los Planes watershed. The USGS also worked with local academic institutions and nonprofit organizations to create public educational opportunities focused on the area’s hydrogeology. These and other collaborative efforts with the U.S. Water Partnership and Innovaciones Alumbra aim at enhancing water resources in the Baja California Sur region and promoting water security and safeguarding community well-being.
La cuenca de Los Planes, ubicada en Baja California Sur, México, y su acuífero subyacente, están sufriendo una disminución de las aguas subterráneas debido a la baja precipitación media anual (28.1 centímetros por año) y la alta demanda de agua por parte de una población creciente y la actividad agrícola. Esta disminución de la disponibilidad de agua puede conducir a la desertificación—un proceso que por medio de la degradación del suelo y la vegetación convierte a la tierra cultivable en desierto—representando un serio desafío para los medios de vida de las personas.
Para abordar estos problemas, un rancho en la cuenca de Los Planes ha instalado numerosas obras de Infraestructura Natural en Arroyos de Tierras Áridas (INATS) para conservación del suelo y del agua. En 2022, el Servicio Geológico de los Estados Unidos (USGS, por sus siglas en inglés) comenzó a trabajar con investigadores regionales y gestores de tierras para estudiar los efectos de INATS en los procesos biológicos, geoquímicos y físicos, y determinar su eficacia en el aumento de los recursos hídricos en la cuenca de Los Planes. El USGS se ha asociado con instituciones académicas y organizaciones locales sin fines de lucro para crear oportunidades educativas públicas centradas en la hidrogeología de la zona. Estos y otros esfuerzos colaborativos con la Asociación del Agua de Estados Unidos (U.S. Water Partnership) e Innovaciones Alumbra, tienen como objetivo mejorar el uso de los recursos hídricos en la región de Baja California Sur, promover la seguridad hídrica y proteger el bienestar de la comunidad.
","language":"English, Spanish","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253042","usgsCitation":"Anides Morales, A., Norman, L.M., and Mack, T.J., 2025, Preserving and increasing water resources—Natural infrastructure in dryland streams in Baja California Sur, Mexico: U.S. Geological Survey Fact Sheet 2025–3042, 4 p., https://doi.org/10.3133/fs20253042.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-167963","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":496556,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3042/fs20253042.pdf","text":"Report (English)","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3042 PDF (English)"},{"id":496555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3042/coverthb.jpg"},{"id":496557,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3042/fs20253042_spanish.pdf","text":"Report (Español)","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3042 PDF (Spanish)"}],"country":"Mexico","state":"Baja California Sur","otherGeospatial":"Los Planes watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.61060380724068,\n 24.369517436874077\n ],\n [\n -110.61060380724068,\n 22.79088429619047\n ],\n [\n -109.36626743882256,\n 22.79088429619047\n ],\n [\n -109.36626743882256,\n 24.369517436874077\n ],\n [\n -110.61060380724068,\n 24.369517436874077\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Geographic Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
Stable isotopes are commonly used to understand the role of fishes in aquatic food webs. However, variability in species- and tissue-specific isotopic values can affect the inference that is drawn from a stable isotope study. We evaluated differences in stable isotopes of carbon (δ13C) and nitrogen (δ15N) among three tissue types (white muscle, caudal fin rays, and eye lenses) for Santa Ana Sucker Pantosteus santaanae and Arroyo Chub Gila orcuttii to inform the design of a stable isotope study in the Santa Ana River, an urban river that is located in southern California.
We used multivariate analyses to test for differences in the stable isotopes of carbon (δ13C) and nitrogen (δ15N) among the three tissue types that were collected from Santa Ana Sucker and Arroyo Chub. We also summarized the variability in isotopic values that was recorded over time in fish eye lenses and interpreted this variability in reference to the spatial patterns in isotopic values that have been previously reported throughout the Santa Ana River.
We found that fin ray tissue and white muscle tissue were not significantly different for either isotope or fish species. Fish eye lenses were significantly higher in δ13C than muscle tissue, and eye lenses were significantly higher in δ15N than fin ray tissue for both fishes. We also found a greater range in δ13C and δ15N across eye lens layers for Santa Ana Sucker (δ13C = 2.01 ± 0.96‰, δ15N = 4.93 ± 4.18‰) than for Arroyo Chub (δ13C = 0.96 ± 0.65‰, δ15N = 4.63 ± 1.45‰).
Our results indicate that fin rays may be a viable nonlethal alternative to white muscle tissue for use in a stable isotope study of native fish of the Santa Ana River. Additionally, eye lenses could provide a chemical history of fishes within the river, but species-specific correction factors may be needed if stable isotope values for eye lenses are to be compared with more conventional tissue types (e.g., white muscle).
David A. Johnston Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Building 10, Suite 100
Vancouver, WA 98683
Email: askCVO@usgs.gov
","tableOfContents":"This study presents a quantitative PCR (qPCR) assay for the detection of the endangered diamond darter Crystallaria cincotta from environmental DNA (eDNA) in water samples. The assay design is based on an alignment of mitochondrial cytochrome b DNA sequences from 58 individuals representing 25 percid species. Leveraging genetic differences, a species-specific qPCR assay was designed, incorporating alocked nucleic acid (LNA)-enriched probe and a secondary blocking probe to enhance specificity. The assay targets a 93-base pair fragment that includes a diagnostic single nucleotide polymorphism in the probe region; combined with multiple primer mismatches, this provides specificity for distinguishing C. cincotta from other sympatric percid species. Specificity was validated by testing genomic DNA from 16 percid species and synthetic templates, confirming no cross-reactivity. Performance metrics, including the standard curve, qPCR efficiency, limit of detection, and limit of quantification, are reported. The qPCR assay exhibited sufficient sensitivity to detect C. cincotta eDNA in environmental water samples collected from occupied riverine habitats. This study illustrates the effectiveness of LNA-enriched and blocking probes in developing species-specific qPCR assays for eDNA applications, demonstrating their utility in accurately distinguishing closely related species within diverse fish communities.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12686-025-01407-4","usgsCitation":"Kinziger, A.P., Layne, C., and Welsh, S.A., 2025, Quantitative PCR detection of endangered diamond darter Crystallaria Cincotta in environmental DNA: Employing locked nucleic acids and blocking probe for specificity: Conservation Genetics Resources, v. 18, 2, 6 p., https://doi.org/10.1007/s12686-025-01407-4.","productDescription":"2, 6 p.","ipdsId":"IP-176804","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2025-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kinziger, Andrew P.","contributorId":364132,"corporation":false,"usgs":false,"family":"Kinziger","given":"Andrew","middleInitial":"P.","affiliations":[{"id":86765,"text":"Aquatrace Genomics","active":true,"usgs":false}],"preferred":false,"id":952250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Layne, Cameron M.","contributorId":349281,"corporation":false,"usgs":false,"family":"Layne","given":"Cameron M.","affiliations":[{"id":40299,"text":"West Virginia Division of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":952251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952252,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271966,"text":"ofr20251037 - 2025 - Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia","interactions":[],"lastModifiedDate":"2026-02-03T16:28:45.074551","indexId":"ofr20251037","displayToPublicDate":"2025-11-14T14:55:00","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":"2025-1037","displayTitle":"Reconnaissance of Potential Alternate Water Supply Sources for the City of Gary, West Virginia","title":"Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia","docAbstract":"Seven potential sources of water, consisting of free-flowing discharge from abandoned coal mines at six locations and one abandoned flooded underground coal mine air shaft, were sampled for chemical analysis to assess the quality of the groundwater emanating from the seven mine sources. The six free-flowing mine discharge sources were also assessed for discharge by current-meter measurements on two separate occasions. The U.S. Geological Survey assessed these seven sources to provide information to the City of Gary, West Virginia (W. Va.), and the City of Gary’s consulting engineer with groundwater-quality and flow data to allow them to assess the seven sites as potential alternate sources of water for the City of Gary to augment its existing supply.
For the six sites where discharge could be measured, discharge ranged from a minimum of 0.082 cubic feet per second (ft3/s) to a maximum of 3.685 ft3/s. Of the six sites measured, only two, Harmon Branch at Thorpe, W. Va. (USGS site 372201081303501) and the abandoned public-supply water wells near Havaco, W. Va. (USGS site 372358081344601), had discharge in excess of 1.00 ft3/s. Discharge from the abandoned public supply wells was 3.685 ft3/s on September 20, 2023, and 2.888 ft3/s on October 16, 2023, and discharge from Harmon Branch at Thorpe, W. Va., was 1.049 ft3/s on September 22, 2023, and 1.038 ft3/s on October 17, 2023. Discharge in the abandoned underground mine air shaft (USGS site 372224081340901) could not be assessed, but the air shaft drains an abandoned mine that likely contains water stored in approximately 1.7 square miles (mi2) of abandoned underground coal mines in the Pocahontas No. 3 coal seam, and possibly an additional 0.9 mi2 of leakage from the overlying Pocahontas No. 4 coal seam. Discharge for the six sites measured for the study was measured during a period between September 20 and October 18, 2023, and corresponded to the 12th to the 15th percentile of flow-duration statistics for the Tug Fork downstream of Elkhorn Creek at Welch, W. Va. streamgage (USGS site 03212750).
Water-quality data for the seven sites sampled overall were acceptable with respect to drinking water standards. Of the 203 constituents analyzed, only a few failed to meet applicable U.S. Environmental Protection Agency (EPA) drinking water standards. Iron exceeded the 300 micrograms per liter (μg/L) secondary maximum contaminant level (SMCL) at only 1 of the 7 sites (14.3 percent) sampled. Iron concentrations ranged from a minimum of less than (<) 5.00 μg/L to a maximum of 724 μg/L with a median concentration of 7.62 μg/L. Manganese exceeded the 50.0 μg/L SMCL at 2 of the 7 sites (28.6 percent) sampled. Manganese concentrations ranged from a minimum of 1.93 μg/L to a maximum of 271 μg/L with a median concentration of 4.03 μg/L. No sites sampled exceeded the arsenic maximum contaminant level (MCL) of 10 μg/L. Arsenic concentrations ranged from a minimum of <0.100 μg/L to a maximum of 2.35 μg/L with a median arsenic concentration of 0.200 μg/L. None of the seven sites sampled for selenium for this study exceeded the EPA MCL of 50.0 μg/L. Selenium concentrations ranged from a minimum of <0.050 μg/L to a maximum of 5.26 μg/L with a median concentration of 3.21 μg/L.
All seven sites were sampled for volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and polychlorinated biphenyls (PCBs), but most had concentrations below the detection limit. Of the 10 PCB compounds analyzed for the seven sites sampled, none contained detectable concentrations of PCBs or Aroclor compounds. Of the 44 SVOCs analyzed at each of the seven sites sampled, only 1 SVOC, acenaphthene, was detected, at a concentration of 0.02 μg/L. Of the 96 VOCs analyzed, from each of the seven sites sampled, only two were found at detectable concentrations. Trichloromethane was detected only at 1 of the 7 (14.3 percent) sites sampled at a concentration of 0.027 μg/L, and benzene was detected at the same site and 3 additional sites (4 of the 7 sites or 57.1 percent of the sites sampled) at concentrations of 0.028, 0.029, 0.021, and 0.035 μg/L, but none exceeded the EPA MCL for benzene of 5.00 μg/L.
Total coliform bacteria are ubiquitous in the environment, and their presence only suggests the potential for contamination by near-surface processes. Escherichia coli (E. coli) bacteria are derived from either human or animal fecal material and can be an indicator of potential contamination by pathogenic bacteria or viruses. Total coliform bacteria were detected at all 7 sites sampled at concentrations ranging from 17.5 to greater than (>) 2,420 most probable number per 100 mL (MPN/100 mL) of sample, with a median total coliform concentration of 1,553 MPN/100 mL. Escherichia coli bacteria were detected at 4 of the 7 sites sampled at concentrations ranging from <1 to 11.9 MPN/100 mL, with a median E. coli concentration of 5.1 MPN/100 mL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251037","collaboration":"Prepared in cooperation with the City of Gary, West Virginia","usgsCitation":"Kozar, M.D., and Austin, S.H., 2025, Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia: U.S. Geological Survey Open-File Report 2025–1037, 27 p., https://doi.org/10.3133/ofr20251037.","productDescription":"Report: viii, 27 p.; Appendix","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-176784","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":496467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1037/ofr20251037.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1037 PDF"},{"id":496466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1037/coverthb.jpg"},{"id":497789,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118952.htm"},{"id":496471,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2025/1037/ofr20251037_app2.csv","text":"Appendix 2","size":"222 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Water-Quality Data Collected During the Study"},{"id":496470,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1037/ofr20251037.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1037 XML"},{"id":496469,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1037/images/"},{"id":496468,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251037/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1037 HTML"}],"country":"United States","state":"West Virginia","city":"Gary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.616667,\n 37.433333\n ],\n [\n -81.616667,\n 37.25\n ],\n [\n -81.45,\n 37.25\n ],\n [\n -81.45,\n 37.433333\n ],\n [\n -81.616667,\n 37.433333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Chesapeake Bay Activities
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Massachusetts extends from the mountains of the Appalachian system in the west of the State to the sandy beaches and rocky shorelines of the Atlantic coast in the east. Inland topographic data support a wide range of important activities, including geologic mapping, transportation planning, forest and wildlife management, quantifying ecological services, water supply protection, commonwealth-wide infrastructure planning, local site planning, and flood-plain management. Nearshore bathymetry can be used to support coastal portions of the Commonwealth by addressing the combined threats of ocean warming, strong storm surge, and rising sea levels. The maintenance and (or) expansion of Massachusetts ports (for instance, Boston, New Bedford) and Cape Cod sediment management depends upon the accurate mapping of bathymetry and the frequent influx of sediment and redeposition. Critical applications that address the broad range of requirements depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Massachusetts. The status of available and in-progress 3DEP baseline lidar data in Massachusetts is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.23 million in new benefits annually to Massachusetts. The top 10 Massachusetts business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Basin morphometry, climate and geology control how a hydrological network evolves over time, controlling the efficiency of weathering of elements from geological materials, and ultimately the input of sediment and dissolved constituents to river systems. Exceedances to the Navajo Nation surface water quality standards for trace metals have been reported in the San Juan River watershed. Because metals are transported adsorbed to fine-grain sediment, the identification of areas with elevated sources of trace metals and/or areas with increased erosion and sediment transport potential is an important first step in protecting water quality. Physical factors such as elevation, slope, relief and stream order were used to quantify morphometric parameters that effect the contribution of trace metals into the stream network. By correlating these parameters with water quality data that were collected from tributaries along the San Juan River, we identified statistically significant regressions between morphometric parameters and total Al, Pb, U, Fe and Mn in surface water. Positive correlations with trace metals include tributary drainage basin perimeter, pour point elevation and total number of streams, while negative correlations include stream length ratio, ruggedness number and longest basin axis. Stream reach measurements within geological units that contain known trace metal constituents reveal that Gallegos Canyon and Desert Creek are the most susceptible to sediment mobilization and transport, while other tributary drainage basins, such as Desert, Recapture and Salt creeks, are associated with naturally elevated concentrations of Al, As, Pb and U.
","language":"English","publisher":"Geological Society of London","doi":"10.1144/geochem2024-037","usgsCitation":"Miltenberger, K.E., Shephard, Z., Mixon, R., Blake, J., Chavarria, S., and Yager, D., 2025, Morphometric and geological characterization with statistical correlations for 33 tributary drainage basins of the San Juan River watershed in the Four Corners region, USA: Geochemistry: Exploration, Environment, Analysis, v. 25, no. 4, geochem2024-037, 13 p., https://doi.org/10.1144/geochem2024-037.","productDescription":"geochem2024-037, 13 p.","ipdsId":"IP-165506","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":496901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"San Juan River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111,\n 38\n ],\n [\n -111,\n 35.5\n ],\n [\n -106,\n 35.5\n ],\n [\n -106,\n 38\n ],\n [\n -111,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Miltenberger, K. E. 0000-0002-3874-4609","orcid":"https://orcid.org/0000-0002-3874-4609","contributorId":243647,"corporation":false,"usgs":true,"family":"Miltenberger","given":"K.","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary 0000-0003-2994-3355 zshephard@usgs.gov","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":187680,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"zshephard@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mixon, Rachel Lynn 0000-0001-9863-6784","orcid":"https://orcid.org/0000-0001-9863-6784","contributorId":328595,"corporation":false,"usgs":true,"family":"Mixon","given":"Rachel Lynn","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chavarria, Shaleene 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":222578,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yager, Douglas 0000-0001-5074-4022","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":305726,"corporation":false,"usgs":false,"family":"Yager","given":"Douglas","affiliations":[],"preferred":false,"id":951021,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272251,"text":"70272251 - 2025 - Satellite tracking supports hypotheses of breeding allochrony and allopatry in the Endangered Pterodroma hasitata (Black-capped Petrel, Diablotin)","interactions":[],"lastModifiedDate":"2025-11-21T17:30:22.295666","indexId":"70272251","displayToPublicDate":"2025-11-11T08:32:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5532,"text":"Journal of Caribbean Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Satellite tracking supports hypotheses of breeding allochrony and allopatry in the Endangered Pterodroma hasitata (Black-capped Petrel, Diablotin)","title":"Satellite tracking supports hypotheses of breeding allochrony and allopatry in the Endangered Pterodroma hasitata (Black-capped Petrel, Diablotin)","docAbstract":"Pterodroma hasitata, the Black-capped Petrel (locally known as Diablotin), is the only extant Pterodroma petrel nesting in the Caribbean. The species is listed as globally Endangered by the IUCN and was recently listed as endangered under the U.S. Endangered Species Act. Pterodroma hasitata show a phenotypic gradient, ranging from a darker, smaller form to a paler, heavier form, that is reflected in a strong genetic structure. This phylogenetic divergence suggests the existence of at least two distinct breeding populations. We report on pre-breeding movements of two male Pterodroma hasitata, one of each form, tracked by satellite from non-breeding areas in Gulf Stream waters of the western North Atlantic Ocean to breeding locations in Hispaniola in late 2019. Based on a combination of tracking locations, location error classes, battery voltage, and satellite communication schedules, we infer that the light-form petrel visited a nest in central Dominican Republic during 2 to 8 October and 9 to 15 October, and the dark form visited a nest in southeastern Haiti during 9 to 22 November and 29 November to 3 December. This information supports earlier suggestions that Pterodroma hasitata forms breed in allochrony and in allopatry, both of which may be a driver of speciation.
","language":"English","publisher":"BirdsCaribbean","doi":"10.55431/jco.2025.38.59-66","usgsCitation":"Satgé, Y.G., Patteson, J.B., Keitt, B.S., Gaskin, C.P., and Jodice, P.G., 2025, Satellite tracking supports hypotheses of breeding allochrony and allopatry in the Endangered Pterodroma hasitata (Black-capped Petrel, Diablotin): Journal of Caribbean Ornithology, v. 38, p. 59-66, https://doi.org/10.55431/jco.2025.38.59-66.","productDescription":"8 p.","startPage":"59","endPage":"66","ipdsId":"IP-172425","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496755,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.55431/jco.2025.38.59-66","text":"Publisher Index Page"},{"id":496685,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Hatteras","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.73141232128476,\n 35.43896398098414\n ],\n [\n -75.73141232128476,\n 34.94563549138148\n ],\n [\n -75.34437447029681,\n 34.94563549138148\n ],\n [\n -75.34437447029681,\n 35.43896398098414\n ],\n [\n -75.73141232128476,\n 35.43896398098414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","noUsgsAuthors":false,"publicationDate":"2025-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Satgé, Yvan G.","contributorId":362516,"corporation":false,"usgs":false,"family":"Satgé","given":"Yvan","middleInitial":"G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":950577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patteson, J. Brian","contributorId":362517,"corporation":false,"usgs":false,"family":"Patteson","given":"J.","middleInitial":"Brian","affiliations":[{"id":83919,"text":"Seabirding Pelagic Trips","active":true,"usgs":false}],"preferred":false,"id":950578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keitt, Bradford S.","contributorId":362520,"corporation":false,"usgs":false,"family":"Keitt","given":"Bradford","middleInitial":"S.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":950579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaskin, Chris P.","contributorId":362522,"corporation":false,"usgs":false,"family":"Gaskin","given":"Chris","middleInitial":"P.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":950580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950581,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272218,"text":"70272218 - 2025 - Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey","interactions":[],"lastModifiedDate":"2025-11-19T15:47:46.625525","indexId":"70272218","displayToPublicDate":"2025-11-06T09:37:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey","docAbstract":"Silver carp (Hypophthalmichthys nobilis), bighead carp (H. molitrix) and their hybrids, collectively known as bigheaded carps, have been introduced to Lake Balaton, Hungary. The current stock sizes are difficult to assess. We investigated environmental DNA (eDNA) techniques targeted for bigheaded carps, assessed the spatial distribution of eDNA in Lake Balaton, compared eDNA concentrations to environmental variables to assess potential habitat selection based on those variables, and provided an estimate of biomass of bigheaded carps relative to eDNA shedding rates per unit biomass observed in controlled experiments. Water samples were collected from 70 sites in an array across the lake. Biomass estimation was calculated using mean eDNA concentration obtained by quantitative PCR of the samples and previously determined eDNA shedding rates of bigheaded carps under controlled conditions in a laboratory. Concentration of eDNA was highly variable between sites, resulting in wide confidence intervals. Basins did not significantly differ in eDNA concentration, and there were no strong relationships between environmental variables and eDNA concentration, indications that bigheaded carps use the entire lake. The model provided an estimate of 4,830 metric tonnes (2,750–8,030 tonnes) of bigheaded carps in Lake Balaton, or 81.0 kg/ha. The eDNA method produced a value close to previous estimates by traditional means of total biomass of bigheaded carps in the lake, and like traditional methods, there was a broad confidence interval on the estimate of the mean. The results of the present study support the utility of aquatic eDNA analysis, and the need for further comparisons with fisheries methods and supporting data from laboratory studies.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0335950","usgsCitation":"Boross, N., Laszlo, A., Chapman, D.C., Boros, G., Vitál, Z., Tóth, V., Thompson, N., Klymus, K.E., and Richter, C.A., 2025, Spatial distribution and relative biomass of bigheaded carps in Lake Balaton, Hungary estimated from an environmental DNA survey: PLoS ONE, v. 20, no. 11, 0335950, 15 p., https://doi.org/10.1371/journal.pone.0335950.","productDescription":"0335950, 15 p.","ipdsId":"IP-178103","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":496746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0335950","text":"Publisher Index Page"},{"id":496639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hungary","otherGeospatial":"Lake Balaton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 18.21350370081612,\n 47.10491295878799\n ],\n [\n 17.172489215123477,\n 47.10491295878799\n ],\n [\n 17.172489215123477,\n 46.62325119241811\n ],\n [\n 18.21350370081612,\n 46.62325119241811\n ],\n [\n 18.21350370081612,\n 47.10491295878799\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Boross, Nora","contributorId":362434,"corporation":false,"usgs":false,"family":"Boross","given":"Nora","affiliations":[{"id":86526,"text":"HUN-REN Balaton Limnological Research Institute, Hungary","active":true,"usgs":false}],"preferred":false,"id":950467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Laszlo, Ardo","contributorId":362435,"corporation":false,"usgs":false,"family":"Laszlo","given":"Ardo","affiliations":[{"id":86527,"text":"Hungarian University of Agricultural and Life Science, Hungary","active":true,"usgs":false}],"preferred":false,"id":950468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Duane C.","contributorId":362436,"corporation":false,"usgs":false,"family":"Chapman","given":"Duane","middleInitial":"C.","affiliations":[{"id":86529,"text":"(retired) USGS Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":950469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boros, Gergely","contributorId":295274,"corporation":false,"usgs":false,"family":"Boros","given":"Gergely","email":"","affiliations":[{"id":63813,"text":"Centre for Ecological Research, Balaton Limnological Institute","active":true,"usgs":false}],"preferred":false,"id":950470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vitál, Zoltán","contributorId":352562,"corporation":false,"usgs":false,"family":"Vitál","given":"Zoltán","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":950471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tóth, Viktor","contributorId":362437,"corporation":false,"usgs":false,"family":"Tóth","given":"Viktor","affiliations":[{"id":86526,"text":"HUN-REN Balaton Limnological Research Institute, Hungary","active":true,"usgs":false}],"preferred":false,"id":950472,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950473,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950475,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274065,"text":"70274065 - 2025 - Imaging hyporheic exchange by integrating deep learning and physics-informed inversion of time-lapse self-potential data","interactions":[],"lastModifiedDate":"2026-02-23T16:27:39.210077","indexId":"70274065","displayToPublicDate":"2025-11-05T10:24:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Imaging hyporheic exchange by integrating deep learning and physics-informed inversion of time-lapse self-potential data","docAbstract":"Self-potential (SP) monitoring is increasingly used for subsurface flow characterization due to its sensitivity to hydrogeological and geochemical processes. However, SP inversion remains challenging due to its ill-posed nature, sparse data coverage, and strong transient noise. This study proposes a hybrid framework to image hyporheic exchange using a time-lapse SP data set monitored from a streamflow site in Oak Ridge, Tennessee. Dipole moment tomography grids generated from the physics-informed numerical inversion is first used to train a Vision Transformer (ViT) model that maps surface SP sequences to 2D source distributions. While the numerical method is more responsive to transient signals, the ViT model better captures persistent spatial structures. Their complementary outputs are jointly analyzed in the spatiotemporal domain to isolate dynamic hyporheic exchange zones and distinguish transient from steady state subsurface flow features. This approach integrates physical inversion and deep learning to enhance interpretability, generalization, and temporal awareness in SP analysis.
","language":"English","publisher":"Americal Geophysical Union","doi":"10.1029/2025GL118772","usgsCitation":"Yin, H., Ikard, S., Rucker, D.F., Brooks, S.C., Dai, Z., Carroll, K.C., 2025, Imaging hyporheic exchange by integrating deep learning and physics-informed inversion of time-lapse self-potential data: Geophysical Research Letters, v. 52, no. 21, e2025GL118772, 11 p., https://doi.org/10.1029/2025GL118772.","productDescription":"e2025GL118772, 11 p.","ipdsId":"IP-180027","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":500584,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl118772","text":"Publisher Index Page"},{"id":500417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"21","noUsgsAuthors":false,"publicationDate":"2025-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Yin, Huichao 0000-0001-6172-5580","orcid":"https://orcid.org/0000-0001-6172-5580","contributorId":366938,"corporation":false,"usgs":false,"family":"Yin","given":"Huichao","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":201775,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rucker, Dale F. 0000-0002-8930-2747","orcid":"https://orcid.org/0000-0002-8930-2747","contributorId":294463,"corporation":false,"usgs":false,"family":"Rucker","given":"Dale","email":"","middleInitial":"F.","affiliations":[{"id":63573,"text":"hydroGEOPHYSICS, Inc.","active":true,"usgs":false}],"preferred":false,"id":956408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Scott C. 0000-0002-8437-9788","orcid":"https://orcid.org/0000-0002-8437-9788","contributorId":294464,"corporation":false,"usgs":false,"family":"Brooks","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":956409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dai, Zhenxue 0000-0002-0805-7621","orcid":"https://orcid.org/0000-0002-0805-7621","contributorId":366941,"corporation":false,"usgs":false,"family":"Dai","given":"Zhenxue","affiliations":[{"id":87510,"text":"Jilin University","active":true,"usgs":false}],"preferred":false,"id":956410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carroll, Kenneth C. 0000-0003-2097-9589","orcid":"https://orcid.org/0000-0003-2097-9589","contributorId":247827,"corporation":false,"usgs":false,"family":"Carroll","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956411,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272288,"text":"70272288 - 2025 - Too hot for comfort: Elevated temperatures influence gene expression and exceed thermal tolerance of bigmouth shiners, Ericymba dorsalis","interactions":[],"lastModifiedDate":"2025-11-20T16:16:07.21305","indexId":"70272288","displayToPublicDate":"2025-11-05T09:10:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"title":"Too hot for comfort: Elevated temperatures influence gene expression and exceed thermal tolerance of bigmouth shiners, Ericymba dorsalis","docAbstract":"Environmental and associated ecosystem change may affect the persistence of fish species based on their ability to adapt to changing conditions, including decreasing flows and rising water temperatures. Exceeding the thermal tolerances of stream fish will likely result in a loss of ability to maintain metabolic processes. We evaluated the critical thermal maximum (CTmax) of bigmouth shiner (Ericymba dorsalis) and analysed the expression of heat shock protein 70 messenger RNA (mRNA) (HSP70) to quantify a thermal stress response over a gradient of temperatures (25°C–31°C). E. dorsalis HSP70 mRNA expression was upregulated in response to temperatures >25°C, indicating a stress response. This study supports the existence of a thermal stress threshold for E. dorsalis. The frequency at which this threshold is exceeded may increase under forecasted future climate scenarios for Nebraska.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.70268","usgsCitation":"Humphrey, E.K., Spurgeon, J.J., Bowen, L., Wilson, R.E., Waters-Dynes, S.C., Newkirk, B.M., and Sonsthagen, S.A., 2025, Too hot for comfort: Elevated temperatures influence gene expression and exceed thermal tolerance of bigmouth shiners, Ericymba dorsalis: Journal of Fish Biology, 10 p., https://doi.org/10.1111/jfb.70268.","productDescription":"10 p.","ipdsId":"IP-179318","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jfb.70268","text":"Publisher Index Page"},{"id":496694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.04584044142557,\n 43.01103305017659\n ],\n [\n -104.09163887010574,\n 40.978861384617716\n ],\n [\n -102.07396809262718,\n 40.994152837401764\n ],\n [\n -102.10374412471413,\n 39.986154865063796\n ],\n [\n -95.30329180208444,\n 39.96701839571119\n ],\n [\n -96.36971775777259,\n 42.71578133925061\n ],\n [\n -98.30779398660637,\n 42.983212934161486\n ],\n [\n -104.04584044142557,\n 43.01103305017659\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Humphrey, Ella K.","contributorId":362647,"corporation":false,"usgs":false,"family":"Humphrey","given":"Ella","middleInitial":"K.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":950686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":950688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Robert E.","contributorId":362649,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert","middleInitial":"E.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":950689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":950690,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Newkirk, Braxton M.","contributorId":362652,"corporation":false,"usgs":false,"family":"Newkirk","given":"Braxton","middleInitial":"M.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":950691,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":353767,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950692,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272091,"text":"70272091 - 2025 - Changes in phosphorus concentration and flux from 2011 to 2023 in major U.S. tributaries to the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2026-01-05T16:49:14.640082","indexId":"70272091","displayToPublicDate":"2025-11-02T10:46:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Changes in phosphorus concentration and flux from 2011 to 2023 in major U.S. tributaries to the Laurentian Great Lakes","docAbstract":"Reducing phosphorus (P) flux to the Great Lakes is critical for improving water quality and controlling eutrophication. We used 13 water years (2011–2023) of U.S. Geological Survey data from 24 major U.S. tributaries (representing 47% of the U.S. Great Lakes watershed area) to evaluate temporal changes in orthophosphate (PO4-P) and total P (TP) using Weighted Regressions on Time, Discharge, and Season. We assessed actual and flow-normalized P concentrations and fluxes. Between 2011 and 2023, P concentrations and fluxes declined in many tributaries, although the extent and significance of these declines varied. Decreases were more common and statistically likely for TP than PO4-P, and several high-loading watersheds had modest or non-significant changes. Flow-normalized PO4-P:TP flux ratios increased in over half the tributaries, suggesting that even where P reductions occurred, reductions in the more bioavailable P fraction were proportionally smaller. Actual P fluxes were strongly correlated with streamflow, and year-to-year variability in actual fluxes was, on average, three times greater than variability related to trends in flow-normalized fluxes. This underscores the role of hydrology in modulating P export and highlights how changing precipitation and runoff patterns can obscure or counteract management progress. Spring accounted for the largest share of annual P flux in most tributaries, though many showed declining spring contributions. Our basin-wide analysis reveals that while management efforts may have yielded progress in reducing TP in many watersheds, additional strategies would be needed to address PO4-P reductions and account for changing hydrology, especially in high-contributing watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102669","usgsCitation":"Kincaid, D., Diebel, M.W., Bertke, E., Bonville, D.B., Koltun, G.F., Robertson, D., and Loken, L.C., 2025, Changes in phosphorus concentration and flux from 2011 to 2023 in major U.S. tributaries to the Laurentian Great Lakes: Journal of Great Lakes Research, v. 51, no. 6, 102669, 13 p., https://doi.org/10.1016/j.jglr.2025.102669.","productDescription":"102669, 13 p.","ipdsId":"IP-178201","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496717,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2025.102669","text":"Publisher Index Page"},{"id":496502,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.60633559922388,\n 48.148551186404575\n ],\n [\n -88.2067643812503,\n 40.60216025077551\n ],\n [\n -83.23151190577836,\n 39.05980019478196\n ],\n [\n -80.80498690897306,\n 40.234426092092406\n ],\n [\n -80.13264358698466,\n 41.74623034694679\n ],\n [\n -75.68002709570973,\n 41.69292244621492\n ],\n [\n -75.72465463652733,\n 42.23052760530962\n ],\n [\n -74.88658728745591,\n 44.40491984342111\n ],\n [\n -79.06485288677936,\n 43.305925528873495\n ],\n [\n -78.99574717113413,\n 42.844586701072004\n ],\n [\n -81.75752883413966,\n 41.63784527164743\n ],\n [\n -82.97923399054226,\n 42.07649353088971\n ],\n [\n -82.35201917635362,\n 43.23951025772632\n ],\n [\n -82.4731703330764,\n 45.44772983144884\n ],\n [\n -86.77797304973124,\n 47.58223992997367\n ],\n [\n -92.60633559922388,\n 48.148551186404575\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kincaid, Dustin William 0000-0003-1640-685X","orcid":"https://orcid.org/0000-0003-1640-685X","contributorId":353877,"corporation":false,"usgs":true,"family":"Kincaid","given":"Dustin William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diebel, Matthew W. 0000-0002-5164-598X mdiebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5164-598X","contributorId":33762,"corporation":false,"usgs":true,"family":"Diebel","given":"Matthew","email":"mdiebel@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bertke, Erin E. 0000-0003-3172-280X","orcid":"https://orcid.org/0000-0003-3172-280X","contributorId":330809,"corporation":false,"usgs":true,"family":"Bertke","given":"Erin E.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950040,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950041,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950042,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273911,"text":"70273911 - 2025 - Analysis of trends in terrestrial vegetation at Mediterranean Coast Network Parks: Channel Islands National Park","interactions":[],"lastModifiedDate":"2026-02-17T17:24:13.996226","indexId":"70273911","displayToPublicDate":"2025-11-01T11:15:09","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":18517,"text":"Science Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/SR-2025/358","displayTitle":"Analysis of Trends in Terrestrial Vegetation at Mediterranean Coast Network Parks: Channel Islands National Park","title":"Analysis of trends in terrestrial vegetation at Mediterranean Coast Network Parks: Channel Islands National Park","docAbstract":"The five islands comprising Channel Islands National Park (CHIS) experience natural gradients in temperature and moisture driven by ocean currents. Additionally, the islands were used as ranchlands and military land before becoming a national park, resulting in widespread erosion and vegetation change. As a result, CHIS spans gradients in climate as well as ranching duration and time since animal removal. Vegetation monitoring was initiated in 1984 on three islands (Anacapa, Santa Barbara, San Miguel), in 1990 on Santa Rosa Island, and in 1998 on Santa Cruz Island, with the goal of documenting the long-term response of island vegetation to ranch animal removal and climate fluctuations. Since that time, monitoring has documented the range of natural fluctuation in island environments over decades and provided insights into vegetation change in ecosystems unencumbered by ongoing development. Long-term vegetation monitoring at CHIS is therefore a rare example of an ecosystem experiment that demonstrates the results of management actions and serves as a baseline for land managers and scientists worldwide.
Terrestrial vegetation data collected between 1984 and 2018 were modeled to estimate trends over time and to characterize relationships with covariates related to site characteristics, nonnative mammal removal programs, and water balance metrics. Data were analyzed for trends in vegetation cover, woody plant density, and plant community diversity grouped by life form and nativity across all islands and within individual islands, as well as for several individual species that dominate plant communities or present challenges to native plant recovery. In all, a total of 162 trend and covariate models were tested in this study, the details of which are provided in this report. Briefly, results reflect a decline in nonnative annual disturbance-thriving species with the reduction in animal grazing and trampling. Increasing trends were observed in native shrub density and native shrub recruitment density, as well as native shrub cover across all islands averaged together and on Santa Cruz Island. However, opposite trends were seen on the smaller islands of Santa Barbara and Anacapa, where increasing seabird activity may be damaging vegetation. Further results indicate the importance of soil moisture, relative humidity, fog, precipitation, site exposure, and solar radiation for vegetation patterns and trends. In many instances, there are apparent interacting effects of environmental variables with trends related to nonnative mammal removal and site location. Vegetation patterns in space and time emerge in the dataset as nuanced responses to interacting drivers.
","language":"English","publisher":"National Park Service","doi":"10.36967/2315831","usgsCitation":"Starcevich, L.A., Murray, C., Lee, L.F., Williams, C.B., and McEachern, K., 2025, Analysis of trends in terrestrial vegetation at Mediterranean Coast Network Parks: Channel Islands National Park: Science Report NPS/SR-2025/358, xvi, 176 p., https://doi.org/10.36967/2315831.","productDescription":"xvi, 176 p.","ipdsId":"IP-144822","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":500096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Calfornia","otherGeospatial":"Channel Islands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.7325747,\n 34.3878669\n ],\n [\n -120.6273817,\n 33.7780062\n ],\n [\n -119.4370392,\n 32.9735463\n ],\n [\n -118.1857956,\n 32.6851079\n ],\n [\n -118.2300874,\n 33.4875961\n ],\n [\n -119.4591851,\n 34.2049123\n ],\n [\n -120.2398283,\n 34.3513079\n ],\n [\n -120.7325747,\n 34.3878669\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Starcevich, Leigh Ann","contributorId":366371,"corporation":false,"usgs":false,"family":"Starcevich","given":"Leigh","middleInitial":"Ann","affiliations":[{"id":38051,"text":"Western EcoSystems Technology, Inc.","active":true,"usgs":false}],"preferred":false,"id":955748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Christopher","contributorId":340084,"corporation":false,"usgs":false,"family":"Murray","given":"Christopher","affiliations":[{"id":81451,"text":"School of Marine and Environmental Affairs and Washington Ocean Acidification Center, 7 University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":955749,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Lena F.S.","contributorId":366372,"corporation":false,"usgs":false,"family":"Lee","given":"Lena","middleInitial":"F.S.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":955750,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Cameron B.","contributorId":366373,"corporation":false,"usgs":false,"family":"Williams","given":"Cameron","middleInitial":"B.","affiliations":[{"id":6993,"text":"Channel Islands National Park","active":true,"usgs":false}],"preferred":false,"id":955751,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McEachern, Kathryn 0000-0003-2631-8247 kathryn_mceachern@usgs.gov","orcid":"https://orcid.org/0000-0003-2631-8247","contributorId":146324,"corporation":false,"usgs":true,"family":"McEachern","given":"Kathryn","email":"kathryn_mceachern@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":955752,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272225,"text":"70272225 - 2025 - Amphibian diversity of the western Colorado canyonlands including potential threats from nonnative bullfrogs and disease","interactions":[],"lastModifiedDate":"2025-11-19T16:44:02.732723","indexId":"70272225","displayToPublicDate":"2025-11-01T10:39:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Amphibian diversity of the western Colorado canyonlands including potential threats from nonnative bullfrogs and disease","docAbstract":"Throughout the canyons of the Colorado and Uncompahgre Plateaus, water is a limited resource for wildlife, with patchy distribution and seasonal availability. Tributary creeks within these canyons drain into mainstem rivers, providing habitat and breeding sites for native amphibians. Yet, little is known about the diversity and distribution of amphibians that live in these harsh, dynamic environments. In addition, the rivers that border these canyon tributaries may serve as corridors for nonnative species and disease. The American Bullfrog (Lithobates catesbeianus) is a nonnative species in western Colorado known to prey on native amphibians and act as a reservoir for pathogens such as Batrachochytrium dendrobatidis (Bd). From 2019 to 2022, we surveyed for amphibians using visual encounter surveys (VES) and environmental DNA (eDNA) surveys throughout the McInnis Canyons National Conservation Area (MCNCA), the Dominguez–Escalante National Conservation Area (DENCA), and the Dolores River Canyon Wilderness Study Area (DRCWSA). Our primary goals were to document the diversity and distribution of native amphibians in the canyonlands and evaluate potential threats to these species from bullfrogs and Bd. We confirmed that sensitive species, such as the Great Basin Spadefoot (Spea intermontana) and the Northern Leopard Frog (Lithobates pipiens), inhabit these protected areas. In most cases, bullfrogs were not detected within ephemeral tributaries, but bullfrog DNA was detected in some tributaries at the confluence with the mainstem rivers. In Mee Canyon (MCNCA), however, bullfrogs were found within the tributary, up to 3 km from the Colorado River. A bullfrog individual removed from this canyon tested positive for Bd, and diet contents suggested that native amphibians are potential prey in this system. Nonnative predators and disease pose a threat to native amphibians, alongside environmental changes such as drought and hydrological shifts driven by ongoing climate change.
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