Groundwater quality in and around oil fields in the Southern San Joaquin Valley is of interest to many California residents that rely heavily on groundwater for domestic, commercial, and agricultural use. To help assess the effects of historical oil-field activities and natural geologic sources on groundwater near the southwest margins of the Kern County Groundwater Subbasin, a multiple-well monitoring site was installed near the administrative boundary between the Midway-Sunset and Buena Vista Oil Fields in Kern County, California. The installation of the Midway-Sunset Buena Vista multiple-well monitoring site (MSBV) supports regional analysis of the relations of oil and gas sources to groundwater quality by providing information about the geology, hydrology, geophysical properties, and water quality of the alluvial and upper Tulare aquifers in areas where groundwater data were limited. Data collected from the site included drill cuttings, whole core samples, sidewall core samples, mud-gas analysis, borehole geophysical logs, depth to water measurements, and water quality samples. Whole cores were scanned using dual energy computed tomography. Subsamples of selected cores were analyzed for density, porosity, specific retention, and bulk minerology. Thin sections of the subsamples were prepared, photographed, and examined. Two samples were analyzed using scanning electron microscope technology to examine the microporosity of diatomite laden sediment. Instrumentation installed in the wells collect hourly depth to water measurements.
Analysis of the data show there is 355 feet of alluvium overlying the Tulare Formation at the well site. The contact between the two formations is an aquitard resulting in a perched aquifer in the alluvium and unconfined aquifer in the Tulare Formation. The alluvium is more heterogenous and finer grained than the Tulare Formation resulting in markedly higher porosity in the alluvium compared to the Tulare Formation. Higher specific retention observed in the alluvium is attributed to the finer grained sediment and greater abundance of reworked diatomite (as represented by opal-CT [cristobalite-tridymite]) compared to the Tulare Formation. Total dissolved solids (TDS) approached or exceeded 10,000 milligrams per liter (mg/L) in the alluvium from approximately 176 to 242 feet below land surface and at the top of the Amnicola clay at approximately 670 feet below land surface within the Tulare Formation. Elevated TDS, chloride, and boron concentrations in the alluvium and on top of the Amnicola clay likely reflect groundwater that is mixed with oil-field water. Water chemistry and modern-aged groundwater in the alluvial monitoring well (MSBV #3) are consistent with the oil-field water in the alluvium being derived from documented historical surface disposal of oil-field water upslope (northwest) of the site. Water chemistry and pre-modern groundwater age in the deeper Tulare monitoring well (MSBV #1) on top of the Amnicola clay are consistent with oil-field fluids derived from upslope natural geologic sources or old oil wells that leak in the subsurface. Shallow groundwater in the Tulare (MSBV #2) is not affected by mixing with oil-field sources.
Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2026.103652","usgsCitation":"Labuzzetta, C.J., Johnsen, A.(., Andress, A., Bohner, T., Grajal-Puche, A., Seymour, M., Straw, B., Thogmartin, W.E., Udell, B.J., Wiens, A.M., Diffendorfer, J., 2026, Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines: Ecological Informatics, v. 94, 103652, 13 p., https://doi.org/10.1016/j.ecoinf.2026.103652.","productDescription":"103652, 13 p.","ipdsId":"IP-180409","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":500822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2026.103652","text":"Publisher Index Page"},{"id":500334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Labuzzetta, Charles J. 0000-0002-6027-0120","orcid":"https://orcid.org/0000-0002-6027-0120","contributorId":332055,"corporation":false,"usgs":true,"family":"Labuzzetta","given":"Charles","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":956197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnsen, Arnold (Contractor) 0009-0001-2442-249X","orcid":"https://orcid.org/0009-0001-2442-249X","contributorId":366769,"corporation":false,"usgs":true,"family":"Johnsen","given":"Arnold","middleInitial":"(Contractor)","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":956198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andress, Amber","contributorId":366770,"corporation":false,"usgs":false,"family":"Andress","given":"Amber","affiliations":[{"id":87506,"text":"U.S. Fish and Wildlife Service, Illinois-Iowa Ecological Services Field Office","active":true,"usgs":false}],"preferred":false,"id":956199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohner, Teresa 0000-0003-2582-8771","orcid":"https://orcid.org/0000-0003-2582-8771","contributorId":366771,"corporation":false,"usgs":false,"family":"Bohner","given":"Teresa","affiliations":[{"id":85472,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":false}],"preferred":false,"id":956200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grajal-Puche, Alejandro 0000-0003-1807-4799","orcid":"https://orcid.org/0000-0003-1807-4799","contributorId":265397,"corporation":false,"usgs":false,"family":"Grajal-Puche","given":"Alejandro","affiliations":[{"id":54677,"text":"Department of Biological Sciences, P.O. Box 5640, Northern Arizona University, Flagstaff, Arizona 86011, USA","active":true,"usgs":false}],"preferred":false,"id":956201,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Seymour, Megan","contributorId":271173,"corporation":false,"usgs":false,"family":"Seymour","given":"Megan","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956202,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Straw, Bethany R. 0000-0001-9086-4600","orcid":"https://orcid.org/0000-0001-9086-4600","contributorId":271020,"corporation":false,"usgs":true,"family":"Straw","given":"Bethany","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956203,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":956204,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Udell, Bradley James 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":271174,"corporation":false,"usgs":true,"family":"Udell","given":"Bradley","email":"","middleInitial":"James","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956205,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":956206,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":223504,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":956207,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70274086,"text":"70274086 - 2026 - Preface to the focus section on intraplate earthquakes","interactions":[],"lastModifiedDate":"2026-02-24T15:00:12.785791","indexId":"70274086","displayToPublicDate":"2026-02-10T07:54:52","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Preface to the focus section on intraplate earthquakes","docAbstract":"More than a half century after plate tectonics provided an overarching framework to explain earthquakes along active plate boundaries, numerous theories have been proposed to explain where, why, and how often earthquakes occur well away from active plate boundaries, but a paradigm remains elusive. Even the classification of earthquakes away from active plate boundaries as \"intraplate\" raises issues, with potentially important distinctions between Stable Continental Regions and more actively deforming regions including passive margins and failed rifts. Some of the largest known intraplate earthquakes themselves remain enigmatic, having occurred before the modern instrumental era. Hazard assessments are often data-limited: low fault-slip rates relative to landscape modification rates result in poor discoverability of fault sources, challenging the characterization of source zones and earthquake recurrence; the completeness and homogenization of instrumental earthquake catalogs using uncertain magnitude conversions can lead to uncertainties in earthquake recurrence; and, limited strong-motion observations for large-magnitude events at near-source distances leads to uncertainties in the selection and development of ground-motion models for seismic hazard studies. Data from recent intraplate earthquakes around the world—from the moment magnitude M 7.7 2001 Bhuj, India, earthquake 25 years ago to the 2024 M 4.8 Tewksbury, New Jersey earthquake—have yielded both new insights and new questions. The papers in this special focus discuss many of the long-standing challenges involved with intraplate earthquake investigations and provide a snapshot of the state of the art with current research to advance our understanding.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220260004","usgsCitation":"Allen, T.I., Hough, S.E., Boyd, O.S., Waldhauser, F., Assumpcao, M., 2026, Preface to the focus section on intraplate earthquakes: Seismological Research Letters, v. 97, no. 2A, p. 619-625, https://doi.org/10.1785/0220260004.","productDescription":"7 p.","startPage":"619","endPage":"625","ipdsId":"IP-184917","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":500602,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220260004","text":"Publisher Index Page"},{"id":500476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"2A","noUsgsAuthors":false,"publicationDate":"2026-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Trevor I.","contributorId":138667,"corporation":false,"usgs":false,"family":"Allen","given":"Trevor","middleInitial":"I.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":956494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":956496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waldhauser, Felix","contributorId":344893,"corporation":false,"usgs":false,"family":"Waldhauser","given":"Felix","affiliations":[{"id":51448,"text":"Lamont Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":956497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Assumpcao, Marcelo","contributorId":366977,"corporation":false,"usgs":false,"family":"Assumpcao","given":"Marcelo","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":956498,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274559,"text":"70274559 - 2026 - Stepovers and beyond: Structural control of The Geysers geothermal system and the broader Clear Lake region","interactions":[],"lastModifiedDate":"2026-03-30T16:05:54.109213","indexId":"70274559","displayToPublicDate":"2026-02-09T10:47:36","publicationYear":"2026","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Stepovers and beyond: Structural control of The Geysers geothermal system and the broader Clear Lake region","docAbstract":"Fault geometry exerts a first-order control on geothermal systems by governing stress localization, fracture development, and permeability, yet in complex fault networks or broader shear zones, the relative influence of individual geometric features is often difficult to resolve. In the northern California Coast Ranges, The Geysers geothermal field is commonly interpreted to occur within a releasing stepover, although no single, clearly defined stepover is identified in published studies. To investigate the structural controls on The Geysers and the broader Clear Lake region, a two-dimensional elastic boundary element model is developed to evaluate spatial patterns of dilational strain associated with progressively more complete fault geometries. Model results show that dilation in the region is not controlled by a single structure but instead reflects the combined effects of multiple interacting fault elements. Three primary controls are identified: (1) opposing bends in the regional strike-slip fault system, including a releasing bend along the Maacama fault; (2) the southern fault tip of the Collayomi fault, which generates a prominent dilational lobe beneath the southern Geysers; and (3) a releasing stepover between the Collayomi fault and the Geyser Peak–Mercuryville–Big Sulphur Creek fault system, inferred to collectively behave as a right-lateral shear zone bounding the western margin of The Geysers. Predicted dilational strain magnitudes are sufficient to localize permeability between faults. These results highlight that incorporating complete fault networks and bedrock geological mapping can enhance geothermal assessments and provide a transferable framework for evaluating structurally controlled permeability in tectonically active regions.
","conferenceTitle":"51st Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 9-11, 2026","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford","usgsCitation":"Melosh, B.L., 2026, Stepovers and beyond: Structural control of The Geysers geothermal system and the broader Clear Lake region, 51st Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 9-11, 2026, 10 p.","productDescription":"10 p.","ipdsId":"IP-185865","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501816,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/IGAstandard/record_detail.php?id=38346"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake region, Geysers geothermal system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.08882992251972,\n 39.16306777840023\n ],\n [\n -123.08882992251972,\n 38.698271344676584\n ],\n [\n -122.51130712624908,\n 38.698271344676584\n ],\n [\n -122.51130712624908,\n 39.16306777840023\n ],\n [\n -123.08882992251972,\n 39.16306777840023\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2026-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Melosh, Benjamin L. 0000-0002-8017-7193","orcid":"https://orcid.org/0000-0002-8017-7193","contributorId":217215,"corporation":false,"usgs":true,"family":"Melosh","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":958309,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70273880,"text":"70273880 - 2026 - The petrogenesis of Þingmúli volcano, East Fjords, Iceland","interactions":[],"lastModifiedDate":"2026-02-25T14:21:56.5345","indexId":"70273880","displayToPublicDate":"2026-02-09T07:57:30","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The petrogenesis of Þingmúli volcano, East Fjords, Iceland","docAbstract":"In this work we revisit Þingmúli volcano (Þ = Th), a classic locality known as an example of a complete tholeiitic differentiation. Þingmúli is a ~ 9.5 Ma extinct central volcano located in the East Fjords of Iceland, in which the whole compositional spectrum from basalt to rhyolites have erupted. These volcanic products have been previously considered as petrogenetically related by an ideal fractionation trend, regardless any temporal relationship or volumetric considerations.
Here we report new whole-rock geochemistry, mineral chemistry, isotope analyses, estimation of residence times of the different eruptive deposits, and an update of the original petrogenetic model. Our results highlight that an enriched source, likely spinel lherzolites, generated transitional-alkaline basaltic melts after 15–20% of partial melting at depths of 40–45 km. Many of these basaltic melts erupted at various stages of the volcano's history, while others remained longer in the volcanic plumbing system. These evolved by fractional crystallisation into basaltic andesite magmas with a residence time of ~5 years based on the crystal size distribution of the plagioclase population. Isotopic differences between the basalts/basaltic andesites (87Sr/86Sr ~ 0.7034; 143Nd/144Nd ~ 0.51315) and the erupted rhyolites (87Sr/86Sr ~ 0.7037; 143Nd/144Nd ~ 0.51304) indicate that the latter are not petrogenetically related to the former. Therefore, instead of a fractional crystallisation mechanism to generate the rhyolites, we propose the partial melting of ignimbrite layers located beneath the volcano. The broad range of trace element concentrations in andesites and dacites and their different isotopic values compared to the basalts strongly suggest that these magmas have been generated by magma mixing between basaltic and rhyolitic melts, similar to modern day Icelandic volcanoes such as Hekla. These results highlight the need to revisit previously studied Icelandic classic localities and reassess their traditionally proposed petrogenetic models.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2026.108561","usgsCitation":"Hughes, A., Cortès, J.A., McGarvie, D., Moscati, R.J., and Olive, V., 2026, The petrogenesis of Þingmúli volcano, East Fjords; Iceland: Journal of Volcanology and Geothermal Research, 108561, 64 p., https://doi.org/10.1016/j.jvolgeores.2026.108561.","productDescription":"108561, 64 p.","ipdsId":"IP-182556","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":499746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iceland","otherGeospatial":"Þingmúli volcano, East Fjords","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -23.540028058288044,\n 66.59258513859314\n ],\n [\n -25.126290149179766,\n 65.22506991722106\n ],\n [\n -22.087340842076145,\n 63.19806647357345\n ],\n [\n -13.158892284515474,\n 63.28606024776602\n ],\n [\n -13.158892284515474,\n 66.7304685435675\n ],\n [\n -23.540028058288044,\n 66.59258513859314\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"472","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hughes, Amanda L. 0000-0003-2481-444X","orcid":"https://orcid.org/0000-0003-2481-444X","contributorId":346354,"corporation":false,"usgs":false,"family":"Hughes","given":"Amanda L.","affiliations":[{"id":82839,"text":"Edge Hill University, UK","active":true,"usgs":false}],"preferred":false,"id":955407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cortès, Joaquín A. 0000-0003-0062-6954","orcid":"https://orcid.org/0000-0003-0062-6954","contributorId":366198,"corporation":false,"usgs":false,"family":"Cortès","given":"Joaquín","middleInitial":"A.","affiliations":[{"id":87379,"text":"Edge Hill Univ","active":true,"usgs":false}],"preferred":false,"id":955408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGarvie, Dave","contributorId":366200,"corporation":false,"usgs":false,"family":"McGarvie","given":"Dave","affiliations":[{"id":87380,"text":"Lancaster Univ","active":true,"usgs":false}],"preferred":false,"id":955409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moscati, Richard J. 0000-0002-0818-4401 rmoscati@usgs.gov","orcid":"https://orcid.org/0000-0002-0818-4401","contributorId":2462,"corporation":false,"usgs":true,"family":"Moscati","given":"Richard","email":"rmoscati@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":955410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olive, Valerie 0000-0002-3905-2946","orcid":"https://orcid.org/0000-0002-3905-2946","contributorId":366201,"corporation":false,"usgs":false,"family":"Olive","given":"Valerie","affiliations":[{"id":87381,"text":"Univ of Glasgow","active":true,"usgs":false}],"preferred":false,"id":955411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274021,"text":"70274021 - 2026 - Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model","interactions":[],"lastModifiedDate":"2026-02-23T18:01:56.100429","indexId":"70274021","displayToPublicDate":"2026-02-07T10:57:05","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model","docAbstract":"In the western United States, conservation practitioners are increasingly working with private landowners to restore habitat for North American beavers (Castor canadensis) and to use nonlethal mitigation techniques when beavers damage crops and infrastructure. Effective communication is critical for promoting coexistence, yet on-the-ground conservation messaging seldom links to behavior change theories. We conducted 23 semistructured interviews with practitioners to examine the approaches they used to communicate with private landowners about beaver coexistence in Oregon (USA). Although we did not set out to interview practitioners about their messages targeting capability, opportunity, and motivation (elements of the COM-B model of behavior), we used the COM-B model to synthesize the primary dimensions of practitioners’ complex, real-world communication about human–wildlife coexistence. We found that practitioners used multiple communication channels to listen for and respond to landowners’ capability, opportunity, and motivation. They tailored messages to affirm and enhance knowledge and skills, identify and address site-specific and social contexts, and align beaver impacts with landowner goals. Our findings suggest the COM-B model can go beyond guiding audience analysis and behavioral intervention design to help practitioners tailor real-time communication with landowners about coexistence behavior. The model, based on our use of COM-B to analyze existing communication, could be used to provide practitioners with techniques for making sense of their existing communication efforts, for identifying gaps, and for dynamically tailoring their communication.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.70210","usgsCitation":"Erickson, B.D., Jones, M.S., 2026, Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model: Conservation Biology, e70210, 14 p., https://doi.org/10.1111/cobi.70210.","productDescription":"e70210, 14 p.","ipdsId":"IP-180694","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.70210","text":"Publisher Index Page"},{"id":500437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2026-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Brian D.","contributorId":339269,"corporation":false,"usgs":false,"family":"Erickson","given":"Brian","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":956184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956185,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70274541,"text":"70274541 - 2026 - Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals","interactions":[],"lastModifiedDate":"2026-03-31T15:00:24.211725","indexId":"70274541","displayToPublicDate":"2026-02-06T09:53:39","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals","title":"Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals","docAbstract":"Using Alaskan lake sediment oxygen isotope records (δ18O), which trace the δ18O of precipitation, we establish that abrupt atmospheric shifts occurred during the last deglacial period in the North Pacific-Arctic. The robust lake δ18O chronologies confidently correlate Younger-Dryas (YD) atmospheric adjustments in Alaska with Greenland ice-core records and their seasonal sensitivity are consistent with cooling during winter. In contrast, abrupt δ18O decreases during the late Holocene observed in our records, of similar magnitude as the YD, are best explained by atmospheric modes involving long-distance transport of sub-tropical Pacific moisture. Our sediment cores are among the most reliably dated records yet produced in the circum-Arctic and show that similar decreases in δ18O of winter precipitation during the YD and late Holocene were driven by different atmospheric teleconnections. These results underscore major roles for seasonality and atmospheric patterns in the conceptual understanding of global scale climate oscillations, both past and future.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-026-68841-2","usgsCitation":"Anderson, L., Finney, B.P., and Baxter, W.B., 2026, Shifting winter atmospheric teleconnections to the North Pacific reconcile Younger-Dryas and Holocene δ18O signals: Nature Communications, v. 17, 2287, 11 p., https://doi.org/10.1038/s41467-026-68841-2.","productDescription":"2287, 11 p.","ipdsId":"IP-173518","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":502072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-026-68841-2","text":"Publisher Index Page"},{"id":501859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.5838715688011,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 58.64385747164533\n ],\n [\n -140.97306433569628,\n 61.71714669073339\n ],\n [\n -154.5838715688011,\n 61.71714669073339\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -54.47050647646307,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 68.64845510387647\n ],\n [\n -23.062966953169052,\n 76.12487765561002\n ],\n [\n -54.47050647646307,\n 76.12487765561002\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2026-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":368960,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":958185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":368961,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce","middleInitial":"P.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":958186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, W. 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Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.
","language":"English","publisher":"Wiley","doi":"10.1002/we.70099","usgsCitation":"Rand, J., Kramer, L., Hoen, B., Diffendorfer, J., and Garrity, C., 2026, Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering: Wind Energy, v. 29, no. 3, e70099, 13 p., https://doi.org/10.1002/we.70099.","productDescription":"e70099, 13 p.","ipdsId":"IP-182443","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/we.70099","text":"Publisher Index Page"},{"id":499676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Rand, Joseph","contributorId":290223,"corporation":false,"usgs":false,"family":"Rand","given":"Joseph","affiliations":[{"id":41633,"text":"DOE Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":955277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kramer, Louisa 0000-0002-6776-9768","orcid":"https://orcid.org/0000-0002-6776-9768","contributorId":204878,"corporation":false,"usgs":true,"family":"Kramer","given":"Louisa","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoen, Ben 0000-0002-9512-5572","orcid":"https://orcid.org/0000-0002-9512-5572","contributorId":204879,"corporation":false,"usgs":false,"family":"Hoen","given":"Ben","email":"","affiliations":[{"id":37001,"text":"DOE Lawrence Berkeley National Labs","active":true,"usgs":false}],"preferred":false,"id":955279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":223504,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":955280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrity, Christopher 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":220994,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":955281,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273860,"text":"70273860 - 2026 - James Buttle Review: A synthesis of riparian plant water use over two decades in North American drylands","interactions":[],"lastModifiedDate":"2026-02-09T15:06:28.28691","indexId":"70273860","displayToPublicDate":"2026-02-05T07:57:07","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"James Buttle Review: A synthesis of riparian plant water use over two decades in North American drylands","docAbstract":"Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70408","usgsCitation":"Palmquist, E.C., Nagler, P., Ogle, K., DiMartini, C., Kennedy, J.R., and Sankey, J., 2026, James Buttle Review: A synthesis of riparian plant water use over two decades in North American drylands: Hydrological Processes, v. 40, no. 2, e70408, 19 p., https://doi.org/10.1002/hyp.70408.","productDescription":"e70408, 19 p.","ipdsId":"IP-180955","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Texas, Wyoming","otherGeospatial":"western Pacific Coastal Plain, western Sierra Madre Piedmont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.30356692213257,\n 42.70636820692536\n ],\n [\n -121.30356692213257,\n 26.163421921669297\n ],\n [\n -103.74141493477907,\n 26.163421921669297\n ],\n [\n -103.74141493477907,\n 42.70636820692536\n ],\n [\n -121.30356692213257,\n 42.70636820692536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":955301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":363777,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","middleInitial":"L.","affiliations":[],"preferred":true,"id":955302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ogle, Kiona","contributorId":360747,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","affiliations":[{"id":86099,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":955303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiMartini, Claudia 0009-0001-2457-0513","orcid":"https://orcid.org/0009-0001-2457-0513","contributorId":356930,"corporation":false,"usgs":false,"family":"DiMartini","given":"Claudia","affiliations":[{"id":85285,"text":"formerly: US Geological Survey, Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":955304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":176478,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":955305,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":955306,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273788,"text":"sir20255112 - 2026 - Flood- inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026","interactions":[],"lastModifiedDate":"2026-02-05T22:03:23.350948","indexId":"sir20255112","displayToPublicDate":"2026-02-04T15:25:00","publicationYear":"2026","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":"2025-5112","displayTitle":"Flood- Inundation Maps for Río Grande De Loíza In and Near Caguas, Puerto Rico, 2026","title":"Flood- inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026","docAbstract":"Digital flood- inundation maps for a 2.7- mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water- surface profiles were computed for the stream reach by using a one- dimensional, steady- state, step- backwater model. The model was calibrated to the current (2025) stage- streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water- surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00- foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water- surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile.
The flood- inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood- mitigation strategies and to define flood- hazard areas to help protect life and property, to coordinate flood- response activities such as evacuations and road closures, and to aid post- flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255112","usgsCitation":"Ostheimer, C.J., Torres- Garcia, L.M., and Gomez- Fragoso, J.M., 2026, Flood- inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026: U.S. Geological Survey Scientific Investigations Report 2025–5112, 16 p., https://doi.org/10.3133/sir20255112.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-179822","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":499609,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_119202.htm","linkFileType":{"id":5,"text":"html"}},{"id":499280,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1IZ6D5V","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for Río Grande De Loíza in Caguas, Puerto Rico"},{"id":499279,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5112/images/"},{"id":499278,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5112/sir20255112.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5112 XML"},{"id":499277,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255112/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5112 HTML"},{"id":499276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5112/sir20255112.pdf","size":"3.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5112 PDF"},{"id":499274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5112/coverthb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.09390482728071,\n 18.33190261334512\n ],\n [\n -66.09390482728071,\n 18.134783495693256\n ],\n [\n -65.97456945279221,\n 18.134783495693256\n ],\n [\n -65.97456945279221,\n 18.33190261334512\n ],\n [\n -66.09390482728071,\n 18.33190261334512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229-1737
Chinook salmon population declines span their geographic range with climate hypothesized as a major driver. Concerns of warming freshwater temperatures in their northern range gained urgency during 2019 when a heatwave coincided with premature mortality. This study examined heat stress during the 2019 heatwave compared to subsequent years and described water temperatures in western Alaska to understand the degree to which freshwater temperatures may be a stressor. Heat stress was prevalent among Chinook salmon captured in the 2019 heatwave (Kuskokwim tributaries: 90% in Kwethluk and 63% Takotna river), and variable in subsequent years (∼8% to 60% across Kuskokwim tributaries and Norton Sound rivers). A review of water temperature data indicated that potentially stressful temperatures (≥18 °C) were most common and prolonged in the Yukon River, moderately common and prolonged in the Kuskokwim River, and relatively rare in the Norton Sound region. Water temperatures in 2019 broke several records for overall maximum and frequency of temperatures ≥ 18 °C. Migration water temperatures and heat stress in northern Pacific salmon habitats vary more widely than previously recognized (up to 25 °C).
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0109","usgsCitation":"von Biela, V.R., Regish, A.M., McCormick, S.D., Spaeder, J., Whitworth, K., Leon, J., Gillikin, D., Liller, Z., Ivanoff, R., Bell, J., Larson, S.D., Carey, M.P., and Zimmerman, C.E., 2026, Migration water temperature and heat stress assessments in western Alaska Chinook salmon overlapping the 2019 heatwave: Canadian Journal of Fisheries and Aquatic Sciences, https://doi.org/10.1139/cjfas-2025-0109.","ipdsId":"IP-171279","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":499750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"western Alaska","edition":"Online 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Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5098","displayTitle":"Water-Budget Simulations for Selected Watersheds in Cameron County, Texas, 2022–23","title":"Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Brownsville, Texas, configured and calibrated a set of hydrologic models for a 217-square-mile study area in Cameron County in south Texas during 2022–23. The models were used for estimating runoff and quantities of water diverted from the Rio Grande/Rio Bravo del Norte (hereinafter referred to as the “Rio Grande”) to maintain water-surface elevations in the canals and resacas (former distributary channels cut off from the main channel of the Rio Grande). Resacas provide habitat to aquatic species and help reduce the effects of flooding.
Because of the large size of the study area and diversity of hydrologic conditions, the study area was divided into 11 watersheds, and separate hydrologic models were developed for 9 of the watersheds. Six of the nine modeled watersheds are drained mostly by canals (canal watersheds), and three of the modeled watersheds drain to resacas (resaca watersheds). The Hydrological Simulation Program—FORTRAN was selected for modeling the study area watersheds because it is flexible in simulating a wide variety of watershed conditions.
The models were calibrated with streamflow data collected during 2022–23. The calibrated models were used to simulate water budgets (streamflow, evapotranspiration, water-storage volumes, and water diversions and withdrawals) during 2022–23. Model simulations showed that the resaca watersheds required more diversions from the Rio Grande and released less runoff than did the canal watersheds. Management practices maintaining resaca water levels constrained their runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255098","issn":"2328-0328","collaboration":"Prepared in cooperation with the City of Brownsville, Texas","usgsCitation":"Ockerman, D.J., and Choi, N., 2026, Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23: U.S. Geological Survey Scientific Investigations Report 2025–5098, 37 p., https://doi.org/10.3133/sir20255098.","productDescription":"Report: viii, 37 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-167896","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":499763,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255098/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5098 HTML"},{"id":499608,"rank":6,"type":{"id":36,"text":"NGMDB Index 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Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and qualitatively compare the results and performance to the stepwise history matching approach. In the latter approach, subsets of parameters and observations were sequentially calibrated to a diverse range of observations to mitigate non-uniqueness and local minima. In iES, localization simulates the same causal connections between parameters and observations without the need (and computational cost) of sequential history matching steps. iES uses a weighted sum-of-squared-errors objective function which allows differential weighting of multiple data sources. Formal adoption of range observation also pushes results to within ranges of observation values rather than discrete values. Overall, the ensemble approach performs similarly to the stepwise approach. Both approaches performed poorly for the cutout representing a snowmelt-dominated watershed, indicating a structural issue in the process representation of the model. The main advantage of iES is quantification of uncertainty in both the history matching and the predictions of interest.
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world","interactions":[],"lastModifiedDate":"2026-03-23T14:47:40.529718","indexId":"70273852","displayToPublicDate":"2026-02-04T08:07:16","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23291,"text":"FEBS Letters","active":true,"publicationSubtype":{"id":10}},"title":"A fresh perspective - Advancing fish immunotoxicology in a complex world","docAbstract":"Understanding how environmental changes affect the health of organisms and ecosystems is complex, but recent interdisciplinary advances and the recognition of immune function as a dynamic mediator offer exciting progress. Environmental immunotoxicology in teleost fishes is evolving beyond cataloguing stressors towards a mechanistic, integrative framework that leverages omics, in vivo tracking and cross-disciplinary modelling. However, knowledge gaps in immune mechanisms, toxicokinetics and multi-stressor interactions remain. The present work highlights these gaps, advocating for immune function as both a mechanistic lens and an integrative health indicator. Such a framework can improve predictive risk assessments, management strategies and our understanding of contaminant effects on resilience, disease susceptibility and population viability. While challenges remain, the field is poised for significant growth through collaborative innovation and advancing technology.
","language":"English","publisher":"FEBS Press","doi":"10.1002/1873-3468.70296","usgsCitation":"Smith, C.R., Burattin, L., Iglesias, N.R., Sullivan, R., Rice, C.D., Segner, H., and Tort, L., 2026, A fresh perspective - Advancing fish immunotoxicology in a complex world: FEBS Letters, v. 600, no. 5, p. 572-590, https://doi.org/10.1002/1873-3468.70296.","productDescription":"19 p.","startPage":"572","endPage":"590","ipdsId":"IP-180147","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499675,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499935,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/1873-3468.70296","text":"Publisher Index Page"}],"volume":"600","issue":"5","noUsgsAuthors":false,"publicationDate":"2026-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":true,"id":955256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burattin, Laura","contributorId":366092,"corporation":false,"usgs":false,"family":"Burattin","given":"Laura","affiliations":[{"id":66158,"text":"University of Namur","active":true,"usgs":false}],"preferred":false,"id":955257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iglesias, Nuria Ruiz","contributorId":366093,"corporation":false,"usgs":false,"family":"Iglesias","given":"Nuria","middleInitial":"Ruiz","affiliations":[{"id":87357,"text":"Autonomous University of Barcelona","active":true,"usgs":false}],"preferred":false,"id":955258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Roisin","contributorId":366094,"corporation":false,"usgs":false,"family":"Sullivan","given":"Roisin","affiliations":[{"id":84564,"text":"The University of Sydney","active":true,"usgs":false}],"preferred":false,"id":955259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Charles D.","contributorId":366095,"corporation":false,"usgs":false,"family":"Rice","given":"Charles","middleInitial":"D.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":955260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Segner, Helmut","contributorId":366096,"corporation":false,"usgs":false,"family":"Segner","given":"Helmut","affiliations":[{"id":25430,"text":"University of Bern","active":true,"usgs":false}],"preferred":false,"id":955261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tort, Lluis","contributorId":169142,"corporation":false,"usgs":false,"family":"Tort","given":"Lluis","email":"","affiliations":[],"preferred":false,"id":955262,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273955,"text":"70273955 - 2026 - Large streamflow differences between forested and urbanized watersheds in the energy-limited eastern United States: The role of evapotranspiration and impervious surfaces","interactions":[],"lastModifiedDate":"2026-02-19T15:12:36.147521","indexId":"70273955","displayToPublicDate":"2026-02-03T09:07:45","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Large streamflow differences between forested and urbanized watersheds in the energy-limited eastern United States: The role of evapotranspiration and impervious surfaces","docAbstract":"Urban forests and other green infrastructures have been viewed as part of the “Nature-based Solutions” (NbS) to mitigate emerging urban environmental change. This study focuses on the role of evapotranspiration (ET) in regulating water balances of small watersheds in the eastern United States. We compared streamflow and ET patterns at daily, monthly and annual scales and linked these hydrological variables to the physical properties of 11 paired watersheds dominated by forests (FW) or urban (UW) land covers. The annual precipitation ranged from 1028 mm to 1683 mm and potential ET (PET) from 815 mm to 1450 mm. The mean annual flow/precipitation (Q/P) ratios were 0.26 ± 0.13 and 0.41 ± 0.1 for FW and UW, respectively. Overall, UW had lower annual ET (772 mm in UW vs. 947 mm in FW), but higher mean annual and (∼58% higher), monthly water yield (17%–186% higher), and peakflow rates (up to 100 times higher) than FW. The streamflow differences between FW and UW were most pronounced during the growing season and early winter (June-November). The mean Q/P ratios for 30 large hurricane events (2016–2021) were 0.12 ± 0.11 and 0.38 ± 0.23 for FW and UW, respectively. The flow rates in the dormant season (around December-May) in UW were similar or lower than FW. We developed conceptual models to explain the seasonal and storm event streamflow differences using background climate (PET), ET, and land surface characteristics. Urban NbS designs should factor in strategies that maximize ET while minimizing impervious surfaces enhancing watershed “sponge” and “pump” functions.
","language":"English","publisher":"American Geophysical Union (AGU)","doi":"10.1029/2025WR041340","usgsCitation":"Sun, G., Bian, Z., Khand, K., Caldwell, P.V., Boggs, J., Wang, C., Chen, Y., Liu, N., Zhang, Y., Chen, X., Senay, G., and McNulty, S.G., 2026, Large streamflow differences between forested and urbanized watersheds in the energy-limited eastern United States: The role of evapotranspiration and impervious surfaces: Water Resources Research, v. 62, no. 2, e2025WR041340, 20 p., https://doi.org/10.1029/2025WR041340.","productDescription":"e2025WR041340, 20 p.","ipdsId":"IP-185235","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":500255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr041340","text":"Publisher Index Page"},{"id":500183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.13910817442056,\n 42.504366194491354\n ],\n [\n -96.89658092237323,\n 42.504366194491354\n ],\n [\n -96.89658092237323,\n 25.74722198798669\n ],\n [\n -68.13910817442056,\n 25.74722198798669\n ],\n [\n -68.13910817442056,\n 42.504366194491354\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sun, G.","contributorId":205528,"corporation":false,"usgs":false,"family":"Sun","given":"G.","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":955905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bian, Z.","contributorId":366435,"corporation":false,"usgs":false,"family":"Bian","given":"Z.","affiliations":[{"id":78585,"text":"Nanjing Normal University","active":true,"usgs":false}],"preferred":false,"id":955906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khand, K.","contributorId":366436,"corporation":false,"usgs":false,"family":"Khand","given":"K.","affiliations":[{"id":87483,"text":"AFDS, contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":955907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell, P. V.","contributorId":366437,"corporation":false,"usgs":false,"family":"Caldwell","given":"P.","middleInitial":"V.","affiliations":[{"id":87484,"text":"Center for Integrated Forest Science, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":955908,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boggs, J.","contributorId":366438,"corporation":false,"usgs":false,"family":"Boggs","given":"J.","affiliations":[{"id":87485,"text":"Eastern Forest Environmental Threat Assessment Center, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":955909,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, C.","contributorId":366439,"corporation":false,"usgs":false,"family":"Wang","given":"C.","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":955910,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Y.","contributorId":272912,"corporation":false,"usgs":false,"family":"Chen","given":"Y.","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":955911,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liu, N.","contributorId":366440,"corporation":false,"usgs":false,"family":"Liu","given":"N.","affiliations":[{"id":87486,"text":"CSIRO Environment Australia","active":true,"usgs":false}],"preferred":false,"id":955912,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhang, Y.","contributorId":274978,"corporation":false,"usgs":false,"family":"Zhang","given":"Y.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":955913,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chen, X.","contributorId":203813,"corporation":false,"usgs":false,"family":"Chen","given":"X.","email":"","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":955914,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Senay, Gabriel 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":955915,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McNulty, S. G.","contributorId":366441,"corporation":false,"usgs":false,"family":"McNulty","given":"S.","middleInitial":"G.","affiliations":[{"id":87485,"text":"Eastern Forest Environmental Threat Assessment Center, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":955916,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70274206,"text":"70274206 - 2026 - Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation","interactions":[],"lastModifiedDate":"2026-03-12T14:13:31.609824","indexId":"70274206","displayToPublicDate":"2026-02-02T09:08:50","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation","docAbstract":"The Fairbanks region of central Alaska is part of a broad zone of intraplate crustal deformation, situated north of the Denali fault and north of the ongoing collision and flat‐slab subduction of the Yakutat oceanic plateau. Seismicity in the Fairbanks region occurs both in diffuse areas as well as in well‐defined lineaments, such as the left‐lateral Salcha fault, which hosted the 1937 M8 7.3 earthquake. Starting with the regional seismicity catalog, we perform waveform cross‐correlation, network‐matched filtering, and relative relocation to obtain an enhanced seismicity catalog over the time period 2014–2024. Based on the relocated catalog, we interpret a set of 15 fault segments, including two conjugate faults and two new faults east of the previously documented fault system. Considering the combined seismicity in the Minto and Fairbanks regions, the median depth of seismicity decreases from east (6 km) to west (20 km). Our interpreted faults provide guidance for future tectonic modeling and assessment of seismic hazards in this region.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220250342","usgsCitation":"Sims, N.E., Tape, C., Ruppert, N., and West, M.E., 2026, Earthquake catalog for the Fairbanks region of central Alaska, 2014–2024, based on waveform cross-correlation: Seismological Research Letters, v. 97, no. 2A, p. 877-896, https://doi.org/10.1785/0220250342.","productDescription":"20 p.","startPage":"877","endPage":"896","ipdsId":"IP-184501","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0220250342","text":"Publisher Index Page"},{"id":500986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Fairbanks region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154,\n 66.5\n ],\n [\n -154,\n 63\n ],\n [\n -144,\n 63\n ],\n [\n -144,\n 66.5\n ],\n [\n -154,\n 66.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"2A","noUsgsAuthors":false,"publicationDate":"2026-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Sims, Nealey E.","contributorId":367184,"corporation":false,"usgs":false,"family":"Sims","given":"Nealey","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":956981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":956982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Natalia A. 0000-0003-0589-1159","orcid":"https://orcid.org/0000-0003-0589-1159","contributorId":351514,"corporation":false,"usgs":true,"family":"Ruppert","given":"Natalia A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":956983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"West, Michael E.","contributorId":367185,"corporation":false,"usgs":false,"family":"West","given":"Michael","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":956984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273806,"text":"70273806 - 2026 - Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations","interactions":[],"lastModifiedDate":"2026-02-03T14:43:09.95163","indexId":"70273806","displayToPublicDate":"2026-02-02T08:37:01","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations","docAbstract":"In April 2020, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center introduced a Level 2 provisional Aquatic Reflectance (AR) product for the Landsat 8 Operational Land Imager (OLI), marking the initial phase in developing a standardized global product for Landsat-derived surface water measurements. The goal of USGS EROS aquatic product research and development is to prepare for an operational processing architecture for Landsat Collection 3 in the late 2020s that will enable use of quality-controlled data for emerging Landsat aquatic science applications. To achieve this, we released a subset of the Landsat 8/9 provisional AR products (Crawford et al., 2025, https://doi.org/10.5066/P14MBBRM) and examined its general performance through the Science Algorithms to Operations (SATO) framework alongside quantitative assessment using community made inland water data records (GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments, GLORIA) and radiometric coastal validation platforms (NASA’s Ocean Color component of the Aerosol Robotic Network, AERONET-OC). Variability within the validation datasets indicate that the performance of the Landsat 8/9 provisional AR retrieval is highly context-dependent; errors are minimal in optically simple waters (e.g., clear to moderately turbid coastal waters) but increase considerably in optically complex waters where factors such as elevated levels of turbidity, chlorophyll (Chl a) concentrations, or colored dissolved organic matter (CDOM) dominate the water column. Additionally, this paper examines key algorithmic considerations for atmospheric correction, highlighting factors that influence accuracy, scalability, and computational efficiency necessary for collection processing in the operational Landsat Product Generation System (LPGS). This paper is intended to communicate with aquatic scientists, satellite oceanographers, and the broader Earth observation community on the origins, requirements, challenges, successes, and future objectives for operationalizing global AR data products for Landsat satellite missions.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-2025-317","usgsCitation":"Benjamin Page, Crawford, C., Arab, S., Gail Schmidt, Barnes, C., and Wellington, D., 2026, Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations: Earth System Science Data, v. 18, no. 2, p. 779-800, https://doi.org/10.5194/essd-2025-317.","productDescription":"22 p.","startPage":"779","endPage":"800","ipdsId":"IP-170237","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin Page 0000-0002-9871-2406","orcid":"https://orcid.org/0000-0002-9871-2406","contributorId":359007,"corporation":false,"usgs":false,"family":"Benjamin Page","affiliations":[{"id":85733,"text":"Earth Space Technology Services (ESTS)","active":true,"usgs":false}],"preferred":false,"id":954888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":954889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":299964,"corporation":false,"usgs":false,"family":"Arab","given":"Saeed","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":954890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gail Schmidt 0000-0002-9684-8158","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":359008,"corporation":false,"usgs":false,"family":"Gail Schmidt","affiliations":[{"id":57411,"text":"KBR, Inc.","active":true,"usgs":false}],"preferred":false,"id":954891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnes, Christopher 0000-0002-4608-4364","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":359949,"corporation":false,"usgs":false,"family":"Barnes","given":"Christopher","affiliations":[{"id":68993,"text":"KBR Inc., Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":954892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wellington, Danika F. 0000-0002-2130-0075","orcid":"https://orcid.org/0000-0002-2130-0075","contributorId":237074,"corporation":false,"usgs":false,"family":"Wellington","given":"Danika F.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":954893,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273992,"text":"70273992 - 2026 - Assimilation efficiency of rainbow trout fed natural diets","interactions":[],"lastModifiedDate":"2026-02-23T15:18:01.627278","indexId":"70273992","displayToPublicDate":"2026-02-02T08:14:23","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Assimilation efficiency of rainbow trout fed natural diets","docAbstract":"Assimilation efficiency is a critical assumption of stable isotope mixing models and bioenergetics models, yet few studies examine how assimilation efficiency influences modeling inferences. We conducted laboratory experiments to determine rainbow trout (Oncorhynchus mykiss) assimilation efficiencies. Assimilation efficiency averaged 55.8% (SE ± 0.90) and 64.5% (SE ± 1.98) at the 10% and 25% ration levels, respectively, and did not differ significantly. Caloric energy egested in feces was not significantly different between ration levels. Caloric energy excreted in ammonia and urea was significantly different between the ration levels, with a higher amount at the 25% ration level. Absorption efficiency was significantly greater at a higher ration level. Percent energy egested in feces was significantly greater at lower ration levels. Percent energy excreted as ammonia and urea was high compared to previous studies and did not differ significantly by ration level. Our estimates of assimilation efficiency of rainbow trout (56% and 65%) were lower than some previously reported estimates, and our estimates of energy losses (feces and ammonia) were higher than some previous estimates. As knowledge of species-specific assimilation efficiencies increases, our ability to draw strong inferences and improve the accuracy of model predictions will improve.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-026-01804-0","usgsCitation":"Flinders, J.M., Magoulick, D.D., 2026, Assimilation efficiency of rainbow trout fed natural diets: Environmental Biology of Fishes, v. 109, 40, 7 p., https://doi.org/10.1007/s10641-026-01804-0.","productDescription":"40, 7 p.","ipdsId":"IP-176944","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10641-026-01804-0","text":"Publisher Index Page"},{"id":500402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","noUsgsAuthors":false,"publicationDate":"2026-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Flinders, Jon M.","contributorId":366527,"corporation":false,"usgs":false,"family":"Flinders","given":"Jon","middleInitial":"M.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":956030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956031,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273899,"text":"70273899 - 2026 - New methods provide a 300–year perspective on modern area burned in two wilderness areas of the southwest United States","interactions":[],"lastModifiedDate":"2026-02-12T15:12:38.190359","indexId":"70273899","displayToPublicDate":"2026-02-02T08:05:57","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"New methods provide a 300–year perspective on modern area burned in two wilderness areas of the southwest United States","docAbstract":"Climate change, expanding human ignitions, and increased fuels from fire exclusion are driving increases in area burned and fire severity in dry conifer forests of the western United States. Increasing area burned is occurring against the backdrop of a large fire deficit caused by over a century of fire exclusion. A key land management question is whether historically frequent fire regimes can be restored. Accurate estimates of historical annual area burned (prior to circa 1900) are necessary to evaluate modern area burned (after circa 1900), but are difficult to derive, and have rarely been calibrated or validated against modern fires, leaving their accuracy uncertain. We developed new methods to use tree-ring fire scars to reconstruct historical annual area burned and compare it to modern annual area burned. We focused on two southwestern US wilderness areas—Saguaro National Park (SAGU) and the Gila Wilderness (GILA)—that have a long history of using prescribed and managed fires. The abundant modern low- and moderate-severity fires allowed us to (1) calibrate and validate the fire-scar models against mapped fires to derive the first uncertainty estimates of reconstructed annual area burned and (2) test whether active fire management can help restore annual area burned to historical levels. A multi-model ensemble consisting of 10 individual member models accurately estimated area burned of mapped modern fires with no consistent biases. Each member model had distinct strengths and assumptions that made them suitable for specific applications (e.g., the synchrony model is easily applied, and Thiessen polygons provide spatially explicit area burned estimates). The accurate reconstruction of modern area burned from relatively sparse fire-scar data at GILA suggests that dense grids may not be necessary for accurate reconstructions. Our findings reveal that despite the near absence of fire in the early 20th century, both annual and 20-year sums of area burned in recent decades are back within historical levels at GILA, and trending toward historical levels at SAGU. These results demonstrate that fire management can help restore the historically prevalent, ecologically important process of widespread, frequent, low-to-moderate-severity fire in dry conifer forests.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70471","usgsCitation":"Farris, C.A., Margolis, E.Q., Iniguez, J., Falk, D., Gerow, K., Baisan, C., Allen, C., and Swetnam, T., 2026, New methods provide a 300–year perspective on modern area burned in two wilderness areas of the southwest United States: Ecosphere, v. 17, no. 2, e70471, 29 p., https://doi.org/10.1002/ecs2.70471.","productDescription":"e70471, 29 p.","ipdsId":"IP-178352","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":499947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70471","text":"Publisher Index Page"},{"id":499800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","otherGeospatial":"Gila Wilderness, Saguaro National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.86590653888511,\n 33.756145710724184\n ],\n [\n -108.86590653888511,\n 32.727467884242714\n ],\n [\n -107.59931693774328,\n 32.727467884242714\n ],\n [\n -107.59931693774328,\n 33.756145710724184\n ],\n [\n -108.86590653888511,\n 33.756145710724184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.76309644861847,\n 32.38160500186068\n ],\n [\n -110.76309644861847,\n 32.04323490904622\n ],\n [\n -110.3491545222334,\n 32.04323490904622\n ],\n [\n -110.3491545222334,\n 32.38160500186068\n ],\n [\n -110.76309644861847,\n 32.38160500186068\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2026-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Farris, Calvin A.","contributorId":292802,"corporation":false,"usgs":false,"family":"Farris","given":"Calvin","email":"","middleInitial":"A.","affiliations":[{"id":63015,"text":"National Park Service, Division of Fire and Aviation Management, P.O. 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Soil amplification is modeled using one-dimensional soil profiles. A stochastic source-based approach is employed to generate the dataset, incorporating randomization of input-model parameters to account for the aleatory uncertainty in seismic activity. The accuracy of the dataset is verified through a comprehensive validation framework, showing that the randomization effectively captures variance and inter-period correlation observed in records. This work provides a robust dataset for advancing seismic hazard and risk assessment in the Azores Plateau.
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However, widespread degradation from thermal stress, storms, disease, and human impacts has caused significant coral cover and reef structure loss, increasing coastal vulnerability and economic risks. While coral loss is well-documented, degradation of underlying reef infrastructure and surrounding seafloor changes remain poorly understood. This study addresses this knowledge gap by quantifying seafloor elevation and volume changes across 234.2 km2 of the Upper Florida Keys (UFK) reef tract using historical bathymetric and modern lidar (light detection and ranging) data collected from two periods with distinctly different disturbance regimes: 1935–2002 (frequent storms and major coral loss) and 2002–2016 (few storms and persistently low coral cover). Analysis of over 25,000 data points revealed substantial elevation and volume loss during 1935–2002 (−0.1 ± 0.8 m; 13.6 × 106 m3 net loss), shifting to minimal gains by 2002–2016 (0.0 ± 0.3 m; 1.6 × 106 m3 net gain). Despite this shift, benthic cover data showed continued declines in stony coral, with increases in macroalgae and octocorals, indicating that limited reef accretion persists even with reduced storm activity. Spatial analyses highlighted variable accretion and erosion patterns across habitats and subregions, underscoring the limitations of localized measurements for ecosystem-wide assessments. Our findings demonstrate the value of integrating historical and modern datasets for regional reef monitoring, establishing baselines for restoration planning, and emphasizing the need for continued high-resolution monitoring to guide adaptive management amid ongoing environmental change.
","language":"English","publisher":"MDPI","doi":"10.3390/rs18030463","usgsCitation":"Johnson, S.A., Zawada, D.G., Yates, K., and Jenkins, C., 2026, Long- versus short-term changes in seafloor elevation and volume of the Upper Florida Keys Reef Tract: 1935–2002 and 2002–2016: Remote Sensing, v. 18, no. 3, 463, 28 p., https://doi.org/10.3390/rs18030463.","productDescription":"463, 28 p.","ipdsId":"IP-112501","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs18030463","text":"Publisher Index Page"},{"id":499437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Upper Florida Keys Reef Tract","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.0833,\n 25.5\n ],\n [\n -80.5,\n 25.5\n ],\n [\n -80.5,\n 24.9\n ],\n [\n -80.0833,\n 24.9\n ],\n [\n -80.0833,\n 25.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"3","noUsgsAuthors":false,"publicationDate":"2026-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Selena Anne-Marie 0000-0003-1015-1788","orcid":"https://orcid.org/0000-0003-1015-1788","contributorId":296373,"corporation":false,"usgs":true,"family":"Johnson","given":"Selena","email":"","middleInitial":"Anne-Marie","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":954900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":331852,"corporation":false,"usgs":true,"family":"Zawada","given":"David","email":"dzawada@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":954901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yates, Kimberly 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":202055,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":954902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, Connor Monroe 0000-0003-1807-3665","orcid":"https://orcid.org/0000-0003-1807-3665","contributorId":357343,"corporation":false,"usgs":true,"family":"Jenkins","given":"Connor Monroe","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":954903,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274101,"text":"70274101 - 2026 - Frameworks for assessing tsunami hazard and risk","interactions":[],"lastModifiedDate":"2026-02-25T15:50:11.734549","indexId":"70274101","displayToPublicDate":"2026-01-31T09:19:28","publicationYear":"2026","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Frameworks for assessing tsunami hazard and risk","docAbstract":"Tsunamis are multiscale phenomena resulting from a water column displacement that may be induced by multiple sources, and range from local scale inundation processes to ocean-wide scale wave propagation. Different strategies may be required to model tsunami evolution at different scales and to characterize various intensity measures. Research in tsunami hazard and risk has focused mostly on the tsunami effects such as the wave heights or flow depths. This chapter reviews the evolution of tsunami hazard and risk assessment methodologies, with particular emphasis on the development of probabilistic approaches. Building on advances in numerical modeling and uncertainty analysis, two main frameworks for Probabilistic Tsunami Hazard and Risk Analysis (PTHA/PTRA) are described. Framework 1 (FW1) focuses on quantitative methods, including fully simulation-based assessments (FW1A), integration of hazard with vulnerability and loss models (FW1B), consideration of dynamic processes such as tidal and sea-level variations (FW1C), and approaches using limited scenario sets (FW1D). Framework 2 (FW2) complements this by incorporating indicator-based vulnerability assessments, both physical (FW2A) and social, multi-dimensional (FW2B).
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regional simulation modeling framework for evaluating invasive annual grass management across the sagebrush biome","docAbstract":"Invasive annual grasses (IAG) continue to spread within the sagebrush biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildfire risk. Effective management of IAGs requires action and long-term strategic planning across the sagebrush biome, but the cumulative effects of IAG treatments over time and space are not well understood, especially over broad extents defined for strategies like the Sagebrush Conservation Design. We developed a simulation model and sampling framework that allow local-scale actions to be ‘scaled up’ to evaluate large-scale regional and biome-wide management strategy outcomes. We worked with natural resource managers and experts to co-develop a spatially explicit state-and-transition simulation model of IAG dynamics in sagebrush landscapes that can be used to evaluate alternative management strategies. We evaluated our framework by contrasting two baseline scenarios in terms of their long-term effects on the sagebrush biome. We show that focusing management efforts on moderate to high IAG cover was effective at reducing full conversion to IAGs but failed to prevent widespread establishment of IAGs in core sagebrush areas, exposing them to increased risk of wildfire and wildlife habitat degradation. The results of our model help quantify the extent of the problem that IAGs pose to sagebrush ecosystems given current knowledge and management efforts. Our framework provides a platform to explore alternative management strategy outcomes and can help managers develop informed conservation plans with realistic expectations for return on investment of resources committed to sagebrush landscapes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2026.111720","usgsCitation":"Orning, E.K., Tarbox, B.C., Jarnevich, C.S., Garner, L., Meldrum, J., and Aldridge, C.L., 2026, A regional simulation modeling framework for evaluating invasive annual grass management across the sagebrush biome: Biological Conservation, v. 315, 111720, 19 p., https://doi.org/10.1016/j.biocon.2026.111720.","productDescription":"111720, 19 p.","ipdsId":"IP-175263","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":500671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.04873040039705,\n 48.969093375270745\n ],\n [\n -122.15093216891552,\n 41.61844242365967\n ],\n [\n -120.36137118253703,\n 37.459440266876\n ],\n [\n -115.83673874996727,\n 34.988223821930276\n ],\n [\n -112.66061043883839,\n 34.89444932252573\n ],\n [\n -106.65961794672178,\n 34.412142548803914\n ],\n [\n -104.5627600166407,\n 38.626395744474536\n ],\n [\n -104.05454708106471,\n 43.41458363186885\n ],\n [\n -102.57922958883718,\n 45.20546860686733\n ],\n [\n -102.45591531116487,\n 48.92480518371224\n ],\n [\n -121.04873040039705,\n 48.969093375270745\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"315","noUsgsAuthors":false,"publicationDate":"2026-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Orning, Elizabeth Kari 0000-0002-1376-729X","orcid":"https://orcid.org/0000-0002-1376-729X","contributorId":315548,"corporation":false,"usgs":true,"family":"Orning","given":"Elizabeth","email":"","middleInitial":"Kari","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tarbox, Bryan C. 0000-0001-5040-3949","orcid":"https://orcid.org/0000-0001-5040-3949","contributorId":288930,"corporation":false,"usgs":true,"family":"Tarbox","given":"Bryan","email":"","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garner, Lindy","contributorId":349700,"corporation":false,"usgs":false,"family":"Garner","given":"Lindy","affiliations":[{"id":83506,"text":"US Department of Interior, US Fish and Wildlife Service, Great Falls, MT 59405","active":true,"usgs":false}],"preferred":false,"id":956689,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":956690,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":956691,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273801,"text":"70273801 - 2026 - Restoration based on cost-benefit optimization: A grasslands pilot study","interactions":[],"lastModifiedDate":"2026-02-03T14:09:24.4545","indexId":"70273801","displayToPublicDate":"2026-01-29T15:35:19","publicationYear":"2026","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Restoration based on cost-benefit optimization: A grasslands pilot study","docAbstract":"Ecological restoration is essential to meeting global biodiversity conservation goals. Given limited conservation budgets, deciding where to restore habitat is a key challenge for the coming decade. We developed a spatially explicit framework to optimize ecological restoration site selection by integrating land use history, species distributions, and economic costs. The framework includes the following steps: identify potential restoration area based on relevant environmental measures like land use; identify species of interest; calculate restoration benefits by modeling habitat and climate suitability and estimating reduced extinction risk associated with restoring a particular land parcel based on a modified species–area relationship; aggregate benefits across species; and compare to parcel-level land acquisition costs. We applied linear programming to maximize conservation benefit/restoration cost ratios to identify optimized restoration sites. We illustrate this approach using a case study for highly threatened grassland ecosystems in the Great Plains region of Kansas, USA. We selected five grassland animal species (greater prairie chickens [Tympanuchus cupido], lesser prairie chickens [Tympanuchus pallidicinctus], swift fox [Vulpes velox], pronghorn [Antilocapra americana], and regal fritillary [Speyeria idalia]) as indicators of restoration benefit across taxa. For the indicator species that we chose, shortgrass and mixed-grass prairies had the highest conservation benefit to cost ratio. Setting a minimum restoration threshold for each habitat type allowed us to identify high-priority tallgrass prairie sites. Despite increasing interest in ecological restoration, optimizing restoration site selection is challenging because one must consider habitat features that do not currently exist. The modeling approach described here is flexible and can be updated for different ecosystems, species, and conservation priorities. 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a four-dimensional petrogenetic model of a distributed volcanic field on the southern edge of the Colorado Plateau","docAbstract":"A detailed characterization of the >3,000 square kilometer (km2) Springerville volcanic field, located on the southern tip of the Colorado Plateau in Arizona, United States, with its more than 501 volcanic units and widely distributed >420 cinder cones and lava flows, provides constraints toward an integrated petrogenetic model for the field. Large-volume effusive tholeiitic eruptions at 2–1.5 mega-annum (Ma) transitioned to more numerous, smaller volume alkali olivine basalt (AOB) events at 1.5–1.0 Ma, with increasing abundances of evolved alkalic rocks (EARs), and a final 1.0–0.3 Ma period dominated by smaller volume, more explosive alkalic eruptions.
Early large-scale melting in a relatively enriched lithospheric mantle (EM) source generated large-volume effusive tholeiitic magmas. Depths of tholeiite magma generation average about 90 kilometers (km) across the field, but depths for individual units decreased southward, consistent with lithospheric thinning toward the Colorado Plateau margin. Early and middle-stage transitional basalts, alkali olivine basalts (AOBs), and basanites originate from a progressively deeper (>100 km) region in a prevalent mantle (PREMA)-like asthenospheric source produced by increasingly smaller degrees of melting, as low as about 2 percent. The chemical signature of the basanites is consistent with small degrees of melting in a carbonated, asthenospheric source to depths of about 140 km. As heat waned, the last phase of volcanism was dominated by more explosive EARs derived at shallower lithospheric pressures but that have isotopic and trace element similarities to the deeper asthenospheric magmas. This suggests mixing between deeper basanitic and shallower tholeiitic magmas. With waning heat, eruptions became more localized along alignments, likely related to boundaries between blocks of Proterozoic crust with differing properties that affected magma ascent.
The petrogenetic patterns are consistent with a variety of processes. Basin and Range Province extension, melting, and heat-induced weakening progressively eroded the Colorado Plateau’s thicker lithosphere, giving rise to relatively high degrees of partial melting from shallower (<90 km) sources that produced the early large volumes of effusive tholeiitic magma. Possible lithosphere delamination and removal, and a resulting steep boundary step with the asthenosphere, may have given rise to mantle edge convection, resulting in the mixing of basanitic and tholeiitic magmas. With plate motion, shear-driven upwelling likely gave an eastward component to convection, affecting relative amounts of melting at the field’s western boundary and corresponding with volcanism moving eastward during times of peak vent production by eruption of alkalic lavas, giving rise to more explosive and lower volume eruptions.
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U.S. Geological Survey
1300 SE Cardinal Court Bldg. 10
Vancouver, WA 98683