{"pageNumber":"88","pageRowStart":"2175","pageSize":"25","recordCount":165309,"records":[{"id":70267242,"text":"70267242 - 2025 - Carbon dioxide infusion reduces invasive mussel biofouling (quagga mussel; Dreissena rostriformis bugensis) in raw water systems","interactions":[],"lastModifiedDate":"2025-05-19T15:40:50.381767","indexId":"70267242","displayToPublicDate":"2025-02-25T08:32:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21637,"text":"Biofouling","active":true,"publicationSubtype":{"id":10}},"title":"Carbon dioxide infusion reduces invasive mussel biofouling (quagga mussel; Dreissena rostriformis bugensis) in raw water systems","docAbstract":"The efficacy of carbon dioxide (CO2) to reduce biofouling by quagga mussels (Dreissena rostriformis bugensis) in raw water systems was investigated. Experiments were conducted in a mobile laboratory located at Bureau of Reclamation Davis Dam Hydropower Facility and supplied with raw water from Lake Mohave, a reservoir of the Colorado River, USA. Incoming water was split between five chambers, each infused with CO2 at a different rate. Raw reservoir water containing quagga larvae (veligers) was mixed with CO2 chamber outflows and delivered to tanks containing settlement plates. Two experiments were conducted. Experiment 1 tested continuous infusion at target concentrations of 30, 45, 60, 75, and 100 mg L-1 dCO2 (dissolved CO2). Experiment 2 evaluated intermittent infusion schedules: 24 h on/off with 50, 75, and 100 mg L-1 dCO2 and 24 h once/week with 100 mg L-1 dCO2. In Experiment 1, the percent settlement decreased with mean CO2 concentration, ranging from 5.0% to < 0.1% in 28.7 and 92.2 mg L-1 dCO2, respectively. In Experiment 2, the efficacy of 24 h on/off at dCO2 > 72.2 mg L-1 was similar to continuous treatment. The least effective treatment was 24 h once weekly at 95 mg L-1 dCO2. These results demonstrate that CO2 treatment may reduce mussel biofouling in raw water systems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08927014.2025.2468282","usgsCitation":"Barbour, M., Severson, T.J., Wise, J.K., Meulemans, M.J., Kelly, K., Pucherelli, S., and Waller, D.L., 2025, Carbon dioxide infusion reduces invasive mussel biofouling (quagga mussel; Dreissena rostriformis bugensis) in raw water systems: Biofouling, v. 41, no. 3, p. 253-264, https://doi.org/10.1080/08927014.2025.2468282.","productDescription":"12 p.","startPage":"253","endPage":"264","ipdsId":"IP-166502","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":486161,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Lake Havasu, Lake Mead, Lake Mohave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.09753023326218,\n 33.35794111464041\n ],\n [\n -85.09753023326218,\n 30.70192265047531\n ],\n [\n -83.10505296880376,\n 30.70192265047531\n ],\n [\n -83.10505296880376,\n 33.35794111464041\n ],\n [\n -85.09753023326218,\n 33.35794111464041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.83505505661213,\n 36.231331122870714\n ],\n [\n -114.83505505661213,\n 34.240639367342254\n ],\n [\n -114.0365407399222,\n 34.240639367342254\n ],\n [\n -114.0365407399222,\n 36.231331122870714\n ],\n [\n -114.83505505661213,\n 36.231331122870714\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Barbour, Matthew 0000-0002-0095-9188 mbarbour@usgs.gov","orcid":"https://orcid.org/0000-0002-0095-9188","contributorId":195580,"corporation":false,"usgs":true,"family":"Barbour","given":"Matthew","email":"mbarbour@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":937427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":937428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Jeremy K. 0000-0003-0184-6959 jwise@usgs.gov","orcid":"https://orcid.org/0000-0003-0184-6959","contributorId":5009,"corporation":false,"usgs":true,"family":"Wise","given":"Jeremy","email":"jwise@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":937429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meulemans, Matthew J 0000-0003-4584-8737","orcid":"https://orcid.org/0000-0003-4584-8737","contributorId":261521,"corporation":false,"usgs":true,"family":"Meulemans","given":"Matthew","email":"","middleInitial":"J","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":937430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Kevin","contributorId":213642,"corporation":false,"usgs":false,"family":"Kelly","given":"Kevin","email":"","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":937431,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pucherelli, Sherri","contributorId":317860,"corporation":false,"usgs":false,"family":"Pucherelli","given":"Sherri","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":937432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":937433,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70263938,"text":"70263938 - 2025 - lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data","interactions":[],"lastModifiedDate":"2025-03-11T15:25:06.047162","indexId":"70263938","displayToPublicDate":"2025-02-25T07:46:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14424,"text":"Applied Computing and Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data","docAbstract":"Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data.
Here we introduce ![\"\"](\"https://ars.els-cdn.com/content/image/1-s2.0-S2590197425000072-fx1001.jpg\")
, a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the ![\"\"](\"https://ars.els-cdn.com/content/image/1-s2.0-S2590197425000072-fx1002.jpg\")
pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. ![\"\"](\"https://ars.els-cdn.com/content/image/1-s2.0-S2590197425000072-fx1003.jpg\")
can be found at https://doi.org/10.5066/P1DZUR3Z
","language":"English","publisher":"Elseiver","doi":"10.1016/j.acags.2025.100225","usgsCitation":"Lubbers, J.E., Kent, A., and Russo, C., 2025, lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data: Applied Computing and Geosciences, v. 25 p., 100225, 16 p., https://doi.org/10.1016/j.acags.2025.100225.","productDescription":"100225, 16 p.","ipdsId":"IP-168201","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488954,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.acags.2025.100225","text":"Publisher Index Page"},{"id":482732,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25 p.","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lubbers, Jordan Edward 0000-0002-3566-5091","orcid":"https://orcid.org/0000-0002-3566-5091","contributorId":330466,"corporation":false,"usgs":true,"family":"Lubbers","given":"Jordan","email":"","middleInitial":"Edward","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":929191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J.R.","contributorId":351642,"corporation":false,"usgs":false,"family":"Kent","given":"Adam J.R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":929192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russo, Chris","contributorId":351643,"corporation":false,"usgs":false,"family":"Russo","given":"Chris","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":929193,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70267774,"text":"70267774 - 2025 - Declining marine survival of steelhead trout linked to climate and ecosystem change","interactions":[],"lastModifiedDate":"2025-05-30T16:04:28.613244","indexId":"70267774","displayToPublicDate":"2025-02-24T11:01:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Declining marine survival of steelhead trout linked to climate and ecosystem change","docAbstract":"Species with complex life cycles, such as anadromous fish that perform spawning migrations between freshwater and the ocean, may be particularly sensitive to global change because freshwater and marine habitats experience distinct shifts in climate and ecosystem dynamics. Abundances of wild steelhead trout (Oncorhynchus mykiss) have declined across most of their range over the past 40–50 years. We examined whether declines in steelhead survival can be linked to changing climate conditions and species interactions. A novel hierarchical integrated population model that accounts for the species' complex life history was fitted to data from multiple wild steelhead populations on the Washington coast, U.S.A. The model estimates recruitment residuals and kelt survival rates as time-varying processes, which reflect annual variation in survival before and after first maturation. We found that survival rates of immature steelhead (recruits) and adult steelhead (kelts) have declined over time and that survival trends across populations were strongly associated with climate and ecosystem change, specifically summer sea surface temperature and pink salmon abundance in the North Pacific Ocean, the NPGO index and river flows. Including these drivers in the model reduced unexplained annual variation in shared recruitment and kelt survival anomalies and largely accounted for their negative long-term trends. Our findings provide evidence that rising temperatures and increased interspecific competition at sea have contributed to declines in steelhead survival over the last five decades. Considering projected warming and high pink salmon abundances in the ocean, steelhead will likely continue to experience low marine survival rates.
","language":"English","publisher":"Wiley","doi":"10.1111/faf.12878","usgsCitation":"Ohlberger, J., Buhle, E.R., Buehrens, T., Kendall, N.W., Harbison, T., Claiborne, A., Losee, J., Whitney, J., and Scheuerell, M.D., 2025, Declining marine survival of steelhead trout linked to climate and ecosystem change: Fish and Fisheries, v. 26, no. 3, p. 331-345, https://doi.org/10.1111/faf.12878.","productDescription":"15 p.","startPage":"331","endPage":"345","ipdsId":"IP-171261","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":498240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/faf.12878","text":"Publisher Index Page"},{"id":489289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.82565481486084,\n 48.44004083179661\n ],\n [\n -124.82565481486084,\n 46.36906210187334\n ],\n [\n -122.42520649872698,\n 46.36906210187334\n ],\n [\n -122.42520649872698,\n 48.44004083179661\n ],\n [\n -124.82565481486084,\n 48.44004083179661\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ohlberger, Jan","contributorId":331939,"corporation":false,"usgs":false,"family":"Ohlberger","given":"Jan","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhle, Eric R.","contributorId":339062,"corporation":false,"usgs":false,"family":"Buhle","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":81244,"text":"Biomark Applied Biological Services","active":true,"usgs":false}],"preferred":false,"id":938814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehrens, Thomas W.","contributorId":288623,"corporation":false,"usgs":false,"family":"Buehrens","given":"Thomas W.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":938815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Neala W.","contributorId":288624,"corporation":false,"usgs":false,"family":"Kendall","given":"Neala","email":"","middleInitial":"W.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":938816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harbison, Toby","contributorId":356162,"corporation":false,"usgs":false,"family":"Harbison","given":"Toby","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938817,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Claiborne, Andrew M.","contributorId":356164,"corporation":false,"usgs":false,"family":"Claiborne","given":"Andrew M.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938818,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Losee, James P.","contributorId":356166,"corporation":false,"usgs":false,"family":"Losee","given":"James P.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938819,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Whitney, Jennifer","contributorId":356168,"corporation":false,"usgs":false,"family":"Whitney","given":"Jennifer","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":938820,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938821,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70264699,"text":"70264699 - 2025 - Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems","interactions":[],"lastModifiedDate":"2025-03-20T14:50:08.933728","indexId":"70264699","displayToPublicDate":"2025-02-24T09:42:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems","docAbstract":"The structure, function, and dynamics of Earth's terrestrial ecosystems are profoundly influenced by how often (frequency) and how long (duration) they are inundated with water. A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-22-995-2025","usgsCitation":"Stegen, J., Burgin, A.J., Busch, M., Fisher, J.B., Ladau, J., Abrahamson, J., Kinsman-Costello, L., Li, L., Chen, X., Datry, T., McDowell, N., Tatariw, C., Braswell, A., Deines, J.M., Guimond, J., Regier, P., Rod, K., Bam, E., Fluet-Chouinard, E., Forbrich, I., Jaeger, K.L., O'Meara, T., Scheibe, T.D., Seybold, E., Sweetman, J.N., Zheng, J., Allen, D.C., Herndon, E., Middleton, B., Painter, S., Roche, K., Scamardo, J., Vander Vorste, R., Boye, K., Wohl, E., Zimmer, M., Hondula, K., Laan, M., Marshall, A., and Patel, K., 2025, Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems: Biogeosciences, v. 22, no. 4, p. 995-1034, https://doi.org/10.5194/bg-22-995-2025.","productDescription":"30 p.","startPage":"995","endPage":"1034","ipdsId":"IP-159303","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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La Crosse, WI, USA","active":true,"usgs":false}],"preferred":false,"id":931352,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Boye, Kristin","contributorId":219255,"corporation":false,"usgs":false,"family":"Boye","given":"Kristin","email":"","affiliations":[{"id":39977,"text":"Stanford Synchrotron Radiation Lightsource (SSRL)","active":true,"usgs":false}],"preferred":false,"id":931353,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Wohl, Ellen","contributorId":313566,"corporation":false,"usgs":false,"family":"Wohl","given":"Ellen","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":931354,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Zimmer, Margaret","contributorId":295996,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":931355,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Hondula, Kelly","contributorId":352466,"corporation":false,"usgs":false,"family":"Hondula","given":"Kelly","affiliations":[{"id":84235,"text":"Arizona State University, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":931356,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Laan, Maggi","contributorId":352467,"corporation":false,"usgs":false,"family":"Laan","given":"Maggi","affiliations":[{"id":28004,"text":"Pacific Northwest National Laboratory, Richland, WA, USA","active":true,"usgs":false}],"preferred":false,"id":931357,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Marshall, Anna","contributorId":352468,"corporation":false,"usgs":false,"family":"Marshall","given":"Anna","affiliations":[{"id":35623,"text":"Colorado State University, Fort Collins, CO, USA","active":true,"usgs":false}],"preferred":false,"id":931358,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Patel, Kaizad F.","contributorId":352469,"corporation":false,"usgs":false,"family":"Patel","given":"Kaizad F.","affiliations":[{"id":28004,"text":"Pacific Northwest National Laboratory, Richland, WA, USA","active":true,"usgs":false}],"preferred":false,"id":931359,"contributorType":{"id":1,"text":"Authors"},"rank":40}]}}
,{"id":70269046,"text":"70269046 - 2025 - Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low-disturbance watersheds.","interactions":[],"lastModifiedDate":"2025-07-15T15:10:57.061077","indexId":"70269046","displayToPublicDate":"2025-02-24T09:31:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low-disturbance watersheds.","docAbstract":"Climate change is predicted to intensify lake algal blooms globally and result in regime shifts. However, observed increases in algal biomass do not consistently correlate with air temperature or precipitation, and evidence is lacking for a causal effect of climate or the nonlinear dynamics needed to demonstrate regime shifts. We modeled the causal effects of climate on annual lake chlorophyll (a measure of algal biomass) over 34 y for 24,452 lakes across broad ecoclimatic zones of the United States and evaluated the potential for regime shifts. We found that algal biomass was causally related to climate in 34% of lakes. In these cases, 71% exhibited abrupt but mostly temporary shifts as opposed to persistent changes, 13% had the potential for regime shifts. Climate was causally related to algal biomass in lakes experiencing all levels of human disturbance, but with different likelihood. Climate causality was most likely to be observed in lakes with minimal human disturbance and cooler summer temperatures that have increased over the 34 y studied. Climate causality was variable in lakes with low to moderate human disturbance, and least likely in lakes with high human disturbance, which may mask climate causality. Our results explain some of the previously observed heterogeneous climate responses of lake algal biomass globally and they can be used to predict future climate effects on lakes.
This study evaluated hydroclimate projections and effects on runoff at National Wildlife Refuges in a semiarid region of the western United States (U.S. Fish and Wildlife Service Region 6) using mean air temperature (TAVE) and precipitation (PPT) inputs and runoff (RO) output from a national application of a Monthly Water Balance Model (MWBM). An ensemble of statistically downscaled global circulation models for two future emissions scenarios from Coupled Model Intercomparison Project 3 and 5 (CMIP3 and 5) were assessed at the refuges for the years 1950–2099. TAVE, PPT, and RO and departures from mean baseline conditions were analyzed from MWBM hydrologic response units within refuge boundaries. Seasonal results were evaluated across four periods: historical (1951–1969), baseline (1981–1999), 2050 (2041–2059), and 2080 (2071–2089). Projected TAVE increases for all refuges and time periods, whereas PPT and RO are much more variable across ecoregions. Using the high emission scenario, summer mean monthly TAVE increases range from 4.8°C to 5.5°C by 2080. Summer mean monthly PPT departures vary from −5.7 to 3.9 mm (up to 14% decrease), with decreases at 41% of refuges. Summer RO departures range from −16.7 to 0.2 mm (up to 60% decrease), with decreases at 71% of refuges. Under the same emission scenario, winter PPT and RO increase at most refuges by 2080. These variable departures will create substantial challenges for future conservation management in the region.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13251","usgsCitation":"Caruso, B., Eng, L., Bock, A.R., and Hall, N.G., 2025, Hydroclimate projections and effects on runoff at National Wildlife Refuges in the semi-arid western U.S.: JAWRA Journal of the American Water Resources Association, v. 61, no. 1, e13251, https://doi.org/10.1111/1752-1688.13251.","productDescription":"e13251","ipdsId":"IP-159661","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":482792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Caruso, Brian S. 0000-0002-2184-4961","orcid":"https://orcid.org/0000-0002-2184-4961","contributorId":257039,"corporation":false,"usgs":false,"family":"Caruso","given":"Brian S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":929370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eng, Lauren Ellissa 0009-0003-9808-4184","orcid":"https://orcid.org/0009-0003-9808-4184","contributorId":332901,"corporation":false,"usgs":true,"family":"Eng","given":"Lauren Ellissa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Nicholas Graff 0000-0002-7331-8947","orcid":"https://orcid.org/0000-0002-7331-8947","contributorId":315497,"corporation":false,"usgs":true,"family":"Hall","given":"Nicholas","email":"","middleInitial":"Graff","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70264627,"text":"70264627 - 2025 - James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains","interactions":[],"lastModifiedDate":"2025-03-19T13:12:59.597752","indexId":"70264627","displayToPublicDate":"2025-02-23T08:21:05","publicationYear":"2025","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: The characteristics of baseflow resilience across diverse ecohydrological terrains","docAbstract":"The dynamic storage of aquifers is the portion of groundwater that can potentially drain to any given point along a stream to create baseflow. Baseflow typically occurs year-round in perennial streams, though the characteristics and stability of dynamic storage are often most important to instream processes during extended dry periods (without precipitation and snowmelt) when runoff and quickflows are minimised. The term ‘baseflow resilience’ is defined for this review as the tendency of baseflow in streams to maintain a consistent volume and water quality year to year while under stress from climate variability and extremes, along with anthropogenic stressors such as water withdrawals, land use change, and water quality degradation. ‘Baseflow resilience’ has, in part, a user-defined meaning spanning water supply and water quality variables of primary interest. Watershed characteristics that directly impact resilience can often produce non-intuitive feedbacks that enhance some attributes of baseflow while simultaneously impairing others. For example, permeable stream corridor geology creates strong stream-groundwater hydrologic connectivity, yet fast groundwater drainage via preferential high-permeability flowpaths can lead to streamflow not being sustained during extended dry periods. Also, shallow groundwater sources are generally more immediately vulnerable to extreme events, warming, salinization, transpiration, and precipitation drought, compared to deeper groundwater. Yet baseflow drought in streams influenced by deeper groundwater can lag precipitation drought by years, and contaminant legacies may propagate through deep groundwater flowpaths to receiving waters for decades to centuries. Finally, irrigation withdrawals can intercept groundwater that would have drained to streams, and the application of irrigation may leach contaminants from the soil zone by unnaturally raising water tables, yet irrigation return flows can sustain baseflow and groundwater-dependent habitats in semiarid areas. This review covers the concept of hydrologic resilience in the context of stream baseflow processes and summarises the common hydrogeological controls on, and multiscale stressors of, dynamic groundwater storage. Further, we present several quantitative metrics to assess a range of water supply to water quality baseflow characteristics using both broadly available and boutique data types, a subset of which are demonstrated using data from the Delaware River Basin, USA.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70101","usgsCitation":"Briggs, M., Newman, C.P., Benton, J., Rey, D., Konrad, C., Ouellet, V., Torgersen, C.E., Gruhn, L.R., Fleming, B.J., Gazoorian, C.L., and Doctor, D.H., 2025, James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains: Hydrological Processes, v. 39, e70101, 21 p., https://doi.org/10.1002/hyp.70101.","productDescription":"e70101, 21 p.","ipdsId":"IP-172740","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488334,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70101","text":"Publisher Index Page"},{"id":483482,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.72740040176602,\n 40.21569215354026\n ],\n [\n -75.72740040176602,\n 39.17926830473752\n ],\n [\n -74.59478267456883,\n 39.17926830473752\n ],\n [\n -74.59478267456883,\n 40.21569215354026\n ],\n [\n -75.72740040176602,\n 40.21569215354026\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2025-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":930998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benton, Joshua Robert 0000-0002-1698-6455","orcid":"https://orcid.org/0000-0002-1698-6455","contributorId":304604,"corporation":false,"usgs":true,"family":"Benton","given":"Joshua Robert","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":931000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Konrad, Christopher 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":220231,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ouellet, Valerie","contributorId":316799,"corporation":false,"usgs":false,"family":"Ouellet","given":"Valerie","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":931003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":931004,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931005,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931006,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931007,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":931008,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70267360,"text":"70267360 - 2025 - Heterogeneity of locked‐pasture snow conditions modulate habitat and movement choices of a facultative migrant","interactions":[],"lastModifiedDate":"2025-05-21T13:59:10.296747","indexId":"70267360","displayToPublicDate":"2025-02-22T08:53:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity of locked‐pasture snow conditions modulate habitat and movement choices of a facultative migrant","docAbstract":"Habitat selection and movement are key mechanisms by which animals can respond to and potentially cope with highly variable environmental conditions. Optimal responses likely vary, however, depending on the severity and scope of conditions. We tested this hypothesis using a facultative migrant species, the Great Gray Owl (Strix nebulosa), which exhibits high inter- and intra-individual variation in the timing, direction, and distance of winter movements. Specifically, we evaluated whether episodic, spatiotemporally variable “locked-pasture” snow conditions, which restrict access to subnivean food, prompted shifts in habitat selection or long-distance movements by owls. We quantified the movement of 42 owls using global positioning system (GPS) data within the Greater Yellowstone Ecosystem, USA, during 2017–2022. We used a novel ecological application of SnowModel, a snow evolution modeling system, to estimate fine-scale, physical snow properties likely to influence access to prey. Variables included snow depth, snow crusts produced by wind, and ice crusts produced by melt-freeze and rain-on-snow events. Owls avoided heterogeneously distributed wind crusts via local shifts in habitat selection. More homogenous ice crusts elicited long-distance movements away from affected home ranges. Finally, owls employed both proximate shifts in habitat selection and long-distance movements to avoid deeper snow. Ultimately, owls exhibited behavioral flexibility in response to limiting snow conditions that can vary in terms of severity, spatial extent, and duration. Such behavioral responses determine species distribution, with implications for population and community dynamics in spatiotemporally variable systems. Understanding the effects of, and responses to, environmental controls is increasingly important given the scope of on-going global change.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70925","usgsCitation":"Gura, K., Liston, G.E., Reinking, A., Bedrosian, B., Elder, K., and Chalfoun, A.D., 2025, Heterogeneity of locked‐pasture snow conditions modulate habitat and movement choices of a facultative migrant: Ecology and Evolution, v. 15, no. 2, e70925, 18 p., https://doi.org/10.1002/ece3.70925.","productDescription":"e70925, 18 p.","ipdsId":"IP-174996","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70925","text":"Publisher Index Page"},{"id":486280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.012,\n 44.672\n ],\n [\n -112.012,\n 42.92\n ],\n [\n -109.63,\n 42.92\n ],\n [\n -109.63,\n 44.672\n ],\n [\n -112.012,\n 44.672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Gura, Katherine","contributorId":333836,"corporation":false,"usgs":false,"family":"Gura","given":"Katherine","email":"","affiliations":[],"preferred":false,"id":937966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liston, Glen E.","contributorId":26244,"corporation":false,"usgs":true,"family":"Liston","given":"Glen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":937967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reinking, Adele K.","contributorId":348037,"corporation":false,"usgs":false,"family":"Reinking","given":"Adele K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":937968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bedrosian, Bryan","contributorId":199738,"corporation":false,"usgs":false,"family":"Bedrosian","given":"Bryan","affiliations":[{"id":35591,"text":"Teton Raptor Center","active":true,"usgs":false}],"preferred":false,"id":937969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elder, Kelly","contributorId":174398,"corporation":false,"usgs":false,"family":"Elder","given":"Kelly","email":"","affiliations":[{"id":5121,"text":"U.S. Forest Service, Rocky Mountain Research Station, 1221 South Main Street, Moscow, ID 83843","active":true,"usgs":false}],"preferred":false,"id":937970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937971,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263820,"text":"70263820 - 2025 - First evidence of lake trout Salvelinus namaycush spawning aggregation in Ohio waters of Lake Erie following reintroduction","interactions":[],"lastModifiedDate":"2025-02-25T14:59:52.64098","indexId":"70263820","displayToPublicDate":"2025-02-22T08:50:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"First evidence of lake trout Salvelinus namaycush spawning aggregation in Ohio waters of Lake Erie following reintroduction","title":"First evidence of lake trout Salvelinus namaycush spawning aggregation in Ohio waters of Lake Erie following reintroduction","docAbstract":"Lake trout Salvelinus namaycush, an important apex predator native to Lake Erie, were extirpated by 1965 due to overexploitation, introduction of invasive species, and habitat degradation. Cooperative lake-wide lake trout stocking has been ongoing since 1982, with stocking strategies adapting as research identifies the age at stocking, locations, and strains that optimize the recovery of lake trout. Despite these efforts, limited evidence of lake trout spawning has been documented in the western half of Lake Erie. On 20 November 2023, n = 99 lake trout were captured via gillnet in Fairport Harbor, Ohio. This sample consisted largely of ripe adults (79.4 %) that were likely spawning within the vicinity of Fairport Harbor. Coded wire tags recovered from these fish revealed that most of these lake trout had been stocked in Fairport Harbor (99.0 %), were of the Seneca Lake strain (92.7 %), and were stocked as age-1 fish (93.7 %). This study demonstrates the survival of fish from Fairport Harbor stockings, suggests evidence of stocking-site fidelity, supports the stocking of the Seneca Lake strain, and suggests that stocking age-1 lake trout may have advantages over younger life stages. Most importantly, this study demonstrates that lake trout are likely spawning near Fairport Harbor. These findings can guide future studies that identify lake trout spawning habitat, recruitment bottlenecks, movement, and stocking-site fidelity in Lake Erie and can be used to inform future recovery strategies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102540","usgsCitation":"Spitz, B., Montague, G., Schmitt, J., Guzzo, F., and Jenkins, P., 2025, First evidence of lake trout Salvelinus namaycush spawning aggregation in Ohio waters of Lake Erie following reintroduction: Journal of Great Lakes Research, https://doi.org/10.1016/j.jglr.2025.102540.","ipdsId":"IP-162106","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":482437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.55472739657642,\n 41.9475113213193\n ],\n [\n -80.65395989361728,\n 42.05062981852603\n ],\n [\n -83.09908183181322,\n 41.59775843222013\n ],\n [\n -82.87842021429307,\n 41.20061540985472\n ],\n [\n -81.32584009993163,\n 41.56581314191055\n ],\n [\n -80.55472739657642,\n 41.9475113213193\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Spitz, Benjamin J.","contributorId":351461,"corporation":false,"usgs":false,"family":"Spitz","given":"Benjamin J.","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":928539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montague, Graham F.","contributorId":351462,"corporation":false,"usgs":false,"family":"Montague","given":"Graham F.","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":928540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":928541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guzzo, Francesco 0009-0007-3207-6543","orcid":"https://orcid.org/0009-0007-3207-6543","contributorId":351463,"corporation":false,"usgs":true,"family":"Guzzo","given":"Francesco","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":928542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jenkins, Peter I.","contributorId":351464,"corporation":false,"usgs":false,"family":"Jenkins","given":"Peter I.","affiliations":[{"id":13589,"text":"Ohio DNR","active":true,"usgs":false}],"preferred":false,"id":928543,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264062,"text":"70264062 - 2025 - Did the Aleutian Basin form by plate capture or backarc basin opening?","interactions":[],"lastModifiedDate":"2025-07-09T15:56:31.474959","indexId":"70264062","displayToPublicDate":"2025-02-22T08:34:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2020,"text":"International Geology Review","active":true,"publicationSubtype":{"id":10}},"title":"Did the Aleutian Basin form by plate capture or backarc basin opening?","docAbstract":"The origin of the Aleutian Basin is unresolved because its crust is deeply buried beneath sediments. It has been interpreted as forming in the Eocene when the Beringian convergent margin jumped seaward to south of the Aleutian arc, thereby capturing a large sector of Cretaceous Pacific crust. Alternatively, it may have formed by backarc spreading. We present new magnetic and seismic reflection data compilations and review other pertinent data to evaluate these two possibilities. Arguments for entrapment are: 1) Palaeomagnetic and geologic data document that the Aleutian arc formed approximately in place and as a seaward, on-strike continuation of the Alaska Peninsula; 2) basin-central spreading anomalies trend N-S, normal to the Aleutian arc and exhibit amplitudes and lengths typically formed at mid-ocean ridges; 3) seismic reflection profiles document that cross-basin depositional sequences are like those expected of filling a fixed-width basin. Arguments for a backarc spreading origin include: 1) The perpendicular orientation of magnetic anomalies in the Aleutian Basin and the northern Pacific Plate suggest different origins; 2) the sub-parallel orientation of Aleutian Basin spreading magnetic fabric and Palaeogene rift basins on the Bering Shelf suggest a common extensional regime; 3) thinner continental crust beneath outer-shelf basins is consistent with extension; 4) lineated magnetic fabrics on the margins of the basin are similar to early rifting magnetic fabrics found in other backarc basins; 5) basin heat flow is consistent with Palaeogene seafloor spreading; 6) its marginal basin setting is analogous to marginal basins elsewhere that formed by extension and seafloor spreading, not entrapment; and 7) entrapment requires formation of the Aleutian subduction zone by transference, a mode of subduction initiation that has not yet been documented. We present evidence for both interpretations and underscore the need for continued data collection (e.g. scientific drilling) to test competing hypotheses. Similar approaches may be useful for understanding thickly sedimented marginal basins elsewhere.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00206814.2025.2467447","usgsCitation":"Stern, R.J., Scholl, D., Malkowski, M., Martin, K., Barth, G., and Scheirer, D.S., 2025, Did the Aleutian Basin form by plate capture or backarc basin opening?: International Geology Review, v. 67, no. 13, p. 1697-1719, https://doi.org/10.1080/00206814.2025.2467447.","productDescription":"23 p.","startPage":"1697","endPage":"1719","ipdsId":"IP-157041","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":482901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -176.25963109659818,\n 70.19147740706583\n ],\n [\n -176.25963109659818,\n 58.60834104749597\n ],\n [\n -163.92859263594565,\n 58.60834104749597\n ],\n [\n -163.92859263594565,\n 70.19147740706583\n ],\n [\n -176.25963109659818,\n 70.19147740706583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"67","issue":"13","noUsgsAuthors":false,"publicationDate":"2025-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Robert J.","contributorId":204361,"corporation":false,"usgs":false,"family":"Stern","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":929633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholl, David W.","contributorId":351869,"corporation":false,"usgs":false,"family":"Scholl","given":"David W.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":929634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malkowski, Matthew A.","contributorId":221753,"corporation":false,"usgs":false,"family":"Malkowski","given":"Matthew A.","affiliations":[{"id":40415,"text":". Department of Geological Sciences, Stanford University, Stanford CA 94305","active":true,"usgs":false}],"preferred":false,"id":929635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Kylara M.","contributorId":351871,"corporation":false,"usgs":false,"family":"Martin","given":"Kylara M.","affiliations":[{"id":64648,"text":"California State University, East Bay","active":true,"usgs":false}],"preferred":false,"id":929636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Ginger 0000-0003-0867-7799 gbarth@usgs.gov","orcid":"https://orcid.org/0000-0003-0867-7799","contributorId":264955,"corporation":false,"usgs":true,"family":"Barth","given":"Ginger","email":"gbarth@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929637,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scheirer, Daniel S. 0000-0001-8015-7072 dscheirer@usgs.gov","orcid":"https://orcid.org/0000-0001-8015-7072","contributorId":214825,"corporation":false,"usgs":true,"family":"Scheirer","given":"Daniel","email":"dscheirer@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":929638,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263944,"text":"70263944 - 2025 - Reservoir thermal energy storage pre-assessment for the United States","interactions":[],"lastModifiedDate":"2025-03-05T17:34:49.937548","indexId":"70263944","displayToPublicDate":"2025-02-22T08:33:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Reservoir thermal energy storage pre-assessment for the United States","docAbstract":"Storing thermal energy underground for later use in electricity production or direct-use heating/cooling is a promising, viable, and economical green energy option. Reservoir thermal energy storage (RTES) is one such option, which stores energy in underutilized permeable strata with low ambient groundwater flow rates and more geochemically evolved (e.g. brackish/saline) waters relative to overlying principal aquifer systems. The U.S. Geological Survey has begun assessing RTES potential nationally by focusing on five generalized geologic regions (Basin and Range, Coastal Plain, Illinois Basin, Michigan Basin, Pacific Northwest) across the United States. Hydrogeologic reservoir models are developed for the following eight metropolitan area cities within those regions to evaluate RTES performance across different climates and subsurface conditions: Albuquerque, New Mexico; Charleston, South Carolina; Chicago and Decatur, Illinois; Lansing, Michigan; Memphis, Tennessee; Phoenix, Arizona; and Portland, Oregon. Evaluated metrics include estimated required well spacing, thermal storage capacity, and thermal recovery efficiency through time. Also considered for each reservoir are potential complicating factors, including reservoir depth, thermally driven free convection, and groundwater salinity. This work focuses on direct-use cooling because the need for cooling modern office buildings greatly exceeds that for heating in most parts of the country (Falta and others, 2016); however, the evaluated metrics are also relevant to heating and electricity applications. Results indicate that favorable RTES conditions exist in each region, with the Coastal Plain and Basin and Range being especially favorable for thermal storage capacity, while the Pacific Northwest and Michigan Basin excel at energy recovery for the evaluated cooling application. The results underscore the utility of developing maps of thermal storage capacity, subsurface temperature models, and volumetric estimates of thermal storage capacity to serve as key RTES resource classification standards. Overall, this pre-assessment provides a basic understanding of RTES potential in several cities and geologic regions throughout the country and will aid ongoing thermal energy storage assessment efforts.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2025.103256","usgsCitation":"Pepin, J.D., Burns, E., Cahalan, R.C., Hayba, D.O., Dickinson, J.E., Duncan, L.L., and Kuniansky, E.L., 2025, Reservoir thermal energy storage pre-assessment for the United States: Geothermics, v. 129, 103256, 18 p., https://doi.org/10.1016/j.geothermics.2025.103256.","productDescription":"103256, 18 p.","ipdsId":"IP-160218","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":489977,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"www.osti.gov/servlets/purl/2522111","text":"Publisher Index Page"},{"id":482741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Illinois, Michigan, New Mexico, Oregon, South Carolina, Tennessee","otherGeospatial":"Basin and Range, Coastal Plain, Illinois Basin, Michigan Basin, Pacific 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0000-0002-5581-0225","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":214542,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":929217,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70263739,"text":"tm14A3 - 2025 - Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation","interactions":[],"lastModifiedDate":"2026-01-26T19:50:21.220267","indexId":"tm14A3","displayToPublicDate":"2025-02-21T10:59:08","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"14-A3","displayTitle":"Grfin Tools—User Guide and Methods for Modeling Landslide Runout and Debris-Flow Growth and Inundation","title":"Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation","docAbstract":"The software package, Grfin Tools, can estimate potential runout from landslides or inundation from geophysical mass flows such as debris flows, lahars from volcanoes, and rock avalanches within a digital elevation model (DEM). Grfin is an acronym of growth + flow + inundation. The tools within this package apply simple, well-tested, empirical models of runout that are computationally efficient and require minimal parameters. These tools can be used individually (for example, to estimate debris-flow inundation) or in combination to represent a more complete series of linked processes, from landslide source areas, to unchannelized transport, to channelized flows. Grfin Tools can rapidly assess potential runout and inundation over large areas and the results are readily visualized in a geographic information system.
Tools for assessing areas affected by runout and flow inundation include a height-to-length (H/L) ratio, angle-of-reach approach for estimating open-slope, unchannelized landslide runout, and volume-area scaling relations for assessing flow inundation in channels. Potential landslide areas that constitute the sources of runout or inundation can be delineated with topographic features, such as slope and (or) curvature, derived by the software package, or by employing potential sources derived from other landslide susceptibility models. Grfin Tools also has the capability to assess inundation from flows that grow volumetrically downstream. This is a vital feature, as larger flows commonly result in longer runout and larger inundation. The software uses empirically derived growth factors applied over upslope contributing source areas or upstream channel lengths to integrate the effects of various growth processes, such as channel entrainment, streambank failures, adjacent landslides, and hillslope erosion. Inundation follows a drainage network defined with a separate tool that uses topographic curvature to identify channel initiation locations.
This document includes information on using Grfin Tools, the basis and methods underlying the tools and models, detailed descriptions of the software input and output files, and tips for handling special conditions such as roads and large water bodies. Multiple detailed examples illustrating different applications are also presented. Grfin Tools relies on the freely available TauDEM software package (Tarboton, 2005). The Grfin Tools software release is available from Cronkite-Ratcliff and others (2025).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm14A3","usgsCitation":"Reid, M.E., Brien, D.L., Cronkite-Ratcliff, C., and Perkins, J.P., 2025, Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation: U.S. Geological Survey Techniques and Methods, book 14, chap. A3, 105 p., https://doi.org/10.3133/tm14A3.","productDescription":"Report: xi, 105 p.; Data Release","numberOfPages":"105","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-159767","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":482304,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/14/a3/tm14a3.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":482303,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/14/a3/covrthb.jpg"},{"id":482305,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9NVKFE2","text":"USGS Software Release","description":"Cronkite-Ratcliff, C., Reid, M.E., Brien, D.L., Perkins, J.P., 2025, Grfin Tools—Software package and runtime documentation for users: U.S. Geological Survey software release, https://doi.org/10.5066/P9NVKFE2.","linkHelpText":"- Grfin Tools—Software package and runtime documentation for users"},{"id":499059,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118455.htm","text":"Naranjito, Puerto Rico","linkFileType":{"id":5,"text":"html"}},{"id":499058,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118454.htm","text":"Coast Range, Oregon","linkFileType":{"id":5,"text":"html"}},{"id":499057,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118453.htm","text":"Utuado, Puerto Rico","linkFileType":{"id":5,"text":"html"}},{"id":499056,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118452.htm","text":"Transverse Ranges, California","linkFileType":{"id":5,"text":"html"}},{"id":499055,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118451.htm","text":"Lassen Peak, California","linkFileType":{"id":5,"text":"html"}},{"id":499054,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118450.htm","text":"Kosrae","linkFileType":{"id":5,"text":"html"}}],"contact":"Alaska Volcano Observatory
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
","tableOfContents":"- Abstract
- 1. Introduction
- 2. Using Grfin Tools
- 3. Methods Underlying Different Tools
- 4. Program Input and Output Files
- 5. Handling Special Conditions
- 6. Examples of Applications
Identifying and building solutions to help people and ecosystems adapt to climate change requires participation of all people; however, Science, Technology, Engineering, and Mathematics (STEM) fields, including environmental sciences, continue to lack diversity. To address this issue, many institutions have increased programming to recruit and retain people from historically marginalized backgrounds in STEM fields. Institutions use surveys to evaluate the experiences of community members and identify areas for improvement; however, surveys often summarize and reflect majority perspectives and disregard voices of historically marginalized individuals. In June 2021, a survey of graduate students, postdocs, faculty, staff, and researchers affiliated with the Northeast Climate Adaptation Science Center (NE CASC) evaluated their experiences of diversity, equity, inclusion, and justice (DEIJ) using Likert-based and long-answer questions. We analyzed the results as a whole, but also focused on the responses of people who self-identified as members of a marginalized group (“marginalized respondents”) in climate adaptation science to center their voices. Marginalized respondents reported being motivated to enter climate adaptation science to improve society and the environment rather than for intellectual curiosity, which motivated one third of non-marginalized respondents. Once in science, marginalized respondents reported feeling less supported and comfortable at work and were more likely to have considered leaving science and academia in the last year. Long-answer responses of marginalized respondents indicated distrust in the ability of leadership and existing DEIJ initiatives to effectively tackle systemic issues and emphasized the importance of focusing on equity and inclusion before recruitment. Marginalized respondents identified additional funding to support existing DEIJ efforts and undergraduates as priorities. By allowing participants to self-identify as part of a marginalized group, we were able to highlight experiences and needs without risking exposure based on race, gender, disability status, or sexual orientation. This approach can be applied to other small organizations with limited demographic diversity.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0318438","usgsCitation":"Marjadi, M., Smith, R.A., Tu, H., Ajmani, A., Holland, A., Lopez, B., Morelli, T.L., and Bradley, B., 2025, Centering voices of scientists from marginalized backgrounds to understand experiences in climate adaptation science and inform action: PLoS ONE, v. 20, no. 2, e0318438, 25 p., https://doi.org/10.1371/journal.pone.0318438.","productDescription":"e0318438, 25 p.","ipdsId":"IP-169487","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":489020,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0318438","text":"Publisher Index Page"},{"id":486084,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Marjadi, Meghna N.","contributorId":317779,"corporation":false,"usgs":false,"family":"Marjadi","given":"Meghna N.","affiliations":[{"id":69149,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":937176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Rebecca A.","contributorId":365351,"corporation":false,"usgs":false,"family":"Smith","given":"Rebecca","middleInitial":"A.","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":937177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tu, Hsin Fei","contributorId":355365,"corporation":false,"usgs":false,"family":"Tu","given":"Hsin Fei","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajmani, Asha M.","contributorId":355366,"corporation":false,"usgs":false,"family":"Ajmani","given":"Asha M.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holland, Addie Rose","contributorId":355367,"corporation":false,"usgs":false,"family":"Holland","given":"Addie Rose","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lopez, Bianca E.","contributorId":355368,"corporation":false,"usgs":false,"family":"Lopez","given":"Bianca E.","affiliations":[{"id":56643,"text":"American Association for the Advancement of Science","active":true,"usgs":false}],"preferred":false,"id":937181,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":937182,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Bethany A. 0000-0003-4912-4971","orcid":"https://orcid.org/0000-0003-4912-4971","contributorId":299998,"corporation":false,"usgs":true,"family":"Bradley","given":"Bethany A.","affiliations":[{"id":64995,"text":"University of Massachusetts, Northeast Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":937183,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70263799,"text":"70263799 - 2025 - Overcoming the data limitations in landslide susceptibility modelling","interactions":[],"lastModifiedDate":"2025-02-25T15:23:08.146759","indexId":"70263799","displayToPublicDate":"2025-02-21T09:19:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Overcoming the data limitations in landslide susceptibility modelling","docAbstract":"Data-driven models widely used for assessing landslide susceptibility are severely limited by the landslide and environmental data needed to create them. They rely on inventories of past landslide locations, which are difficult to collect and often nonrepresentative. Furthermore, susceptibility maps are most needed in regions without the means to assemble an inventory. To overcome these challenges, we develop a method for assessing shallow landslide susceptibility based on a probabilistic morphometric analysis of the landscape’s topography, rather than the characteristics of landslides. The model assumes that hillslopes with higher relief and gradient compared to the surrounding landscape are more prone to landslides. We demonstrate the superior performance of this approach over contrasting data-driven models across the northwestern United States. As our morphometric model only requires elevation data, it overcomes the major limitations of data-driven models and facilitates the creation of effective susceptibility models in areas where it was previously unfeasible.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adt1541","usgsCitation":"Woodard, J.B., and Mirus, B., 2025, Overcoming the data limitations in landslide susceptibility modelling: Science Advances, v. 11, no. 8, eadt1541, 13 p., https://doi.org/10.1126/sciadv.adt1541.","productDescription":"eadt1541, 13 p.","ipdsId":"IP-170424","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":489957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adt1541","text":"Publisher Index Page"},{"id":482443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.432878344216,\n 48.94761592494433\n ],\n [\n -124.54708923390476,\n 48.94761592494433\n ],\n [\n -124.54708923390476,\n 41.82426100626475\n ],\n [\n -117.432878344216,\n 41.82426100626475\n ],\n [\n -117.432878344216,\n 48.94761592494433\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodard, Jacob Bryson 0000-0002-3095-0774","orcid":"https://orcid.org/0000-0002-3095-0774","contributorId":305507,"corporation":false,"usgs":true,"family":"Woodard","given":"Jacob","email":"","middleInitial":"Bryson","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":928330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":928331,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70264671,"text":"70264671 - 2025 - A Cftr-independent, Ano1-rich seawater-adaptive ionocyte in sea lamprey gills","interactions":[],"lastModifiedDate":"2025-04-17T15:39:22.792637","indexId":"70264671","displayToPublicDate":"2025-02-20T10:00:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2275,"text":"Journal of Experimental Biology","active":true,"publicationSubtype":{"id":10}},"title":"A Cftr-independent, Ano1-rich seawater-adaptive ionocyte in sea lamprey gills","docAbstract":"All ionoregulating marine fishes examined to date utilize seawater-type ionocytes expressing the apical Cl- channel, cystic fibrosis transmembrane conductance regulator (Cftr) to secrete Cl−. We performed transcriptomic, molecular, and functional studies to identify Cl− transporters in the seawater-type ionocytes of sea lamprey (Petromyzon marinus). Gill cftr expression was minimal or undetectable in larvae and post-metamorphic juveniles. We identified other Cl− transporters highly expressed in the gills and/or upregulated following metamorphosis and further investigated two candidates that stood out in our analysis, a Ca2+-activated Cl− channel, anoctamin 1 (ano1), and the Clc chloride channel family member 2 (clcn2). Of these, ano1 was expressed 10-100 times more than clcn2 in the gills; moreover, ano1 was upregulated during seawater acclimation, while clcn2 was not. Using an antibody raised against sea lamprey Ano1, we did not detect Ano1 in the gills of larvae, found elevated levels in juveniles and observed a 4-fold increase in juveniles after seawater acclimation. Ano1 was localized to seawater-type branchial ionocytes but, surprisingly, was localized to the basolateral membrane. In vivo pharmacological inhibition experiments demonstrated that a DIDS-sensitive mechanism was critical to the maintenance of osmoregulatory homeostasis in seawater- but not freshwater-acclimated sea lamprey. Taken together, our results provide evidence of a Cftr-independent mechanism for branchial Cl− secretion in sea lamprey that leverages Ano1-expressing ionocytes. Once further characterized, the Cftr-independent, Ano1-rich ionocytes of sea lamprey could reveal novel strategies for branchial Cl− secretion, whether by Ano1 or some other Cl− transporter, not previously known in ionoregulating marine organisms.
","language":"English","publisher":"The Company of Biologists","doi":"10.1242/jeb.250110","usgsCitation":"Shaughnessy, C.A., Hall, D., Norstog, J., Barany, A., Regish, A.M., Ferreira-Martins, D., Breves, J.P., Komoroske, L.M., and McCormick, S.D., 2025, A Cftr-independent, Ano1-rich seawater-adaptive ionocyte in sea lamprey gills: Journal of Experimental Biology, v. 228, no. 7, jeb250110, 10 p., https://doi.org/10.1242/jeb.250110.","productDescription":"jeb250110, 10 p.","ipdsId":"IP-154524","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488338,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/jeb.250110","text":"Publisher Index Page"},{"id":483523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"228","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaughnessy, Ciaran A. 0000-0003-2146-9126","orcid":"https://orcid.org/0000-0003-2146-9126","contributorId":229634,"corporation":false,"usgs":false,"family":"Shaughnessy","given":"Ciaran","email":"","middleInitial":"A.","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":931186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Daniel J","contributorId":292080,"corporation":false,"usgs":false,"family":"Hall","given":"Daniel J","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":931187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norstog, Jessica L.","contributorId":352422,"corporation":false,"usgs":false,"family":"Norstog","given":"Jessica L.","affiliations":[{"id":84213,"text":"Organismic and Evolutionary Biology, University of Massachusetts, Amherst, MA, USA","active":true,"usgs":false}],"preferred":false,"id":931188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barany, Andre","contributorId":228958,"corporation":false,"usgs":false,"family":"Barany","given":"Andre","email":"","affiliations":[{"id":41532,"text":"Univ of Cadiz","active":true,"usgs":false}],"preferred":false,"id":931189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":931190,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ferreira-Martins, Diogo","contributorId":228920,"corporation":false,"usgs":false,"family":"Ferreira-Martins","given":"Diogo","email":"","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":931191,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Breves, Jason P.","contributorId":6349,"corporation":false,"usgs":false,"family":"Breves","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":931192,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Komoroske, Lisa M.","contributorId":287670,"corporation":false,"usgs":false,"family":"Komoroske","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":931193,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":931194,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70263777,"text":"70263777 - 2025 - Cancer risk and estimated lithium exposure in drinking groundwater in the US","interactions":[],"lastModifiedDate":"2025-02-24T15:22:49.778702","indexId":"70263777","displayToPublicDate":"2025-02-20T09:17:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20081,"text":"JAMA Network Open","active":true,"publicationSubtype":{"id":10}},"title":"Cancer risk and estimated lithium exposure in drinking groundwater in the US","docAbstract":"Importance Lithium is a naturally occurring element in drinking water and is commonly used as a mood-stabilizing medication. Although clinical studies have reported associations between receiving lithium treatment and reduced cancer risk among patients with bipolar disorder, to our knowledge, the association between environmental lithium exposure and cancer risk has never been studied in the general population.
Objectives To evaluate the association between exposure to lithium in drinking groundwater and cancer risk in the general population.
Design, Setting, and Participants This cohort study included participants with electronic health record and residential address information but without cancer history at baseline from the All of Us Research Program between May 31, 2017, and June 30, 2022. Participants were followed up until February 15, 2023. Statistical analysis was performed from September 2023 through October 2024.
Exposure Lithium concentration in groundwater, based on kriging interpolation of publicly available US Geological Survey data on lithium concentration for 4700 wells across the contiguous US between May 12, 1999, and November 6, 2018.
Main Outcome and Measures The main outcome was cancer diagnosis or condition, obtained from electronic health records. Stratified Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% CIs for risk of cancer overall and individual cancer types for increasing quintiles of the estimated lithium exposure in drinking groundwater, adjusting for socioeconomic, behavioral, and neighborhood-level variables. The analysis was further conducted in the western and eastern halves of the US and restricted to long-term residents living at their current address for at least 3 years.
Results A total of 252 178 participants were included (median age, 52 years [IQR, 36-64 years]; 60.1% female). The median follow-up time was 3.6 years (IQR, 3.0-4.3 years), and 7573 incident cancer cases were identified. Higher estimated lithium exposure was consistently associated with reduced cancer risk. Compared with the first (lowest) quintile of lithium exposure, the HR for all cancers was 0.49 (95% CI, 0.31-0.78) for the fourth quintile and 0.29 (95% CI, 0.15-0.55) for the fifth quintile. These associations were found for all cancer types investigated in both females and males, among long-term residents, and in both western and eastern states. For example, for the fifth vs first quintile of lithium exposure for all cancers, the HR was 0.17 (95% CI, 0.07-0.42) in females and 0.13 (95% CI, 0.04-0.38) in males; for long-term residents, the HR was 0.32 (95% CI, 0.15-0.66) in females and 0.24 (95% CI, 0.11-0.52) in males; and the HR was 0.01 (95% CI, 0.00-0.09) in western states and 0.34 (95% CI, 0.21-0.57) in eastern states.
Conclusions and Relevance In this cohort study of 252 178 participants, estimated lithium exposure in drinking groundwater was associated with reduced cancer risk. Given the sparse evidence and unknown mechanisms of this association, follow-up investigation is warranted.
","language":"English","publisher":"American Medical Association","doi":"10.1001/jamanetworkopen.2024.60854","usgsCitation":"Luo, J., Zheng, L., Jin, Z., Yang, Y., Krakowka, W., Hong, E., Lombard, M.A., Ayotte, J.D., Ahsan, H., Pinto, J., and Aschebrook-Kilfoy, B., 2025, Cancer risk and estimated lithium exposure in drinking groundwater in the US: JAMA Network Open, v. 8, no. 2, e2460854, 15 p., https://doi.org/10.1001/jamanetworkopen.2024.60854.","productDescription":"e2460854, 15 p.","ipdsId":"IP-167705","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":487675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1001/jamanetworkopen.2024.60854","text":"Publisher Index Page"},{"id":482374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n 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,{"id":70264271,"text":"70264271 - 2025 - Conservation translocation immediately reverses decline in imperiled sage-grouse populations","interactions":[],"lastModifiedDate":"2025-03-10T14:16:06.154979","indexId":"70264271","displayToPublicDate":"2025-02-20T09:09:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Conservation translocation immediately reverses decline in imperiled sage-grouse populations","docAbstract":"Conservation translocation (hereafter translocation), the intentional movement of organisms from one location to another as a management tool, can be an extremely useful conservation action to increase the abundance of isolated populations following successful habitat restoration. However, managers seek to weigh the benefits against costs to the source population from which individuals are removed. Using two small and imperiled greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) populations, we demonstrated the usefulness of translocation as a conservation management tool and the value of evaluating the potential consequences of translocation action. Using integrated population models and a before-after-control-impact (BACI) design, we quantified the extent to which translocation influenced the finite rate of change (λ\">λ) of apparent abundance (N\">N) in both reinforced and source populations. We also assessed changes in underlying demographic rates in one population, allowing for identification of the specific mechanisms causing differences in population trends following translocation. In both reinforced populations, λ̂\">λ̂ substantially increased following translocation. In the population for which we had sufficient demographic data, the increase in λ̂\">λ̂ resulted from a 179 % increase in egg hatchability following reinforcement. In one translocation, we did not observe adverse effects on the source populations. The source population for the second translocation exhibited reduced population growth rates after translocation, although BACI ratios indicated causes for population declines independent of translocation effects, highlighting the need to investigate processes together with observed patterns. Overall, we demonstrated the ability to rescue isolated sage-grouse populations via translocation, preserving population viability and metapopulation persistence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.110986","usgsCitation":"Meyerpeter, M., Coates, P., Milligan, M.C., Prochazka, B.G., Lazenby, K.D., Abele, S., Tull, J.C., Miller, K., Kolar, J.L., Mathews, S.R., Dehlgren, D., and Delehanty, D.J., 2025, Conservation translocation immediately reverses decline in imperiled sage-grouse populations: Biological Conservation, v. 304, 110986, 10 p., https://doi.org/10.1016/j.biocon.2025.110986.","productDescription":"110986, 10 p.","ipdsId":"IP-158354","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":486980,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2025.110986","text":"Publisher Index Page"},{"id":483133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Montana, Nevada, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.00262602042469,\n 38.960489793630984\n ],\n [\n -120.00262602042469,\n 37.42814016372904\n ],\n [\n -118.09479169135818,\n 37.42814016372904\n ],\n [\n -118.09479169135818,\n 38.960489793630984\n ],\n [\n -120.00262602042469,\n 38.960489793630984\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.88544244488307,\n 46.66853834505463\n ],\n [\n -111.06921118448022,\n 46.66853834505463\n ],\n [\n -111.06921118448022,\n 40.88855914003949\n ],\n [\n -102.88544244488307,\n 40.88855914003949\n ],\n [\n -102.88544244488307,\n 46.66853834505463\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"304","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meyerpeter, Mary B.","contributorId":352179,"corporation":false,"usgs":false,"family":"Meyerpeter","given":"Mary B.","affiliations":[{"id":51998,"text":"Western EcoSystems Technology","active":true,"usgs":false}],"preferred":false,"id":930223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":352181,"corporation":false,"usgs":true,"family":"Coates","given":"Peter S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":930224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milligan, Megan C. 0000-0001-8466-7803","orcid":"https://orcid.org/0000-0001-8466-7803","contributorId":296042,"corporation":false,"usgs":true,"family":"Milligan","given":"Megan","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":930225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":930226,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lazenby, Kade D.","contributorId":257564,"corporation":false,"usgs":false,"family":"Lazenby","given":"Kade","email":"","middleInitial":"D.","affiliations":[{"id":52056,"text":"Department of Wildland Resources, Jack H. 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Quinney College of Natural Resources, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":930227,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abele, Steve","contributorId":299010,"corporation":false,"usgs":false,"family":"Abele","given":"Steve","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":true,"id":930228,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":930229,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, Katherine","contributorId":259248,"corporation":false,"usgs":false,"family":"Miller","given":"Katherine","email":"","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":true,"id":930230,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kolar, Jesse L.","contributorId":259247,"corporation":false,"usgs":false,"family":"Kolar","given":"Jesse","email":"","middleInitial":"L.","affiliations":[{"id":36989,"text":"North Dakota Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":930231,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mathews, Steven R. 0000-0002-3165-9460 smathews@usgs.gov","orcid":"https://orcid.org/0000-0002-3165-9460","contributorId":176922,"corporation":false,"usgs":true,"family":"Mathews","given":"Steven","email":"smathews@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":930232,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dehlgren, David K.","contributorId":352185,"corporation":false,"usgs":false,"family":"Dehlgren","given":"David K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":930233,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":930234,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70268964,"text":"70268964 - 2025 - Range-wide ecology, conservation, and research needs for yellow lampmussel (Lampsilis cariosa)","interactions":[],"lastModifiedDate":"2025-07-11T15:15:24.854385","indexId":"70268964","displayToPublicDate":"2025-02-20T08:09:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Range-wide ecology, conservation, and research needs for yellow lampmussel (Lampsilis cariosa)","docAbstract":"The freshwater mussel yellow lampmussel (Lampsilis cariosa) is declining throughout its range along the Atlantic Slope of the eastern United States and Canada, and the species is a target for proactive conservation to avoid federal listing. This paper synthesizes information about the ecology (physiology and life history, host fishes, and habitat), species distribution, genetics, and threats to L. cariosa. Identified threats include climate change, habitat alteration, and invasive species, dependent on location. We outline 16 emergent research and conservation management needs based on literature review and discussion with stakeholders (state and federal mussel biologists, researchers, and tribal groups). These needs range from research on the basic physiology and behavior of the species, to creating standardized protocols for surveys and DNA sampling, to ultimately developing a range-wide species conservation and restoration plan. Addressing these information gaps and incorporating the findings into future management may facilitate the implementation and success of large-scale restoration and conservation initiatives such as habitat protection and reintroduction of L. cariosa to historical locations.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10750-024-05765-2","usgsCitation":"Farrington, S., Murphy, C.A., Perkins, D., and Roy, A.H., 2025, Range-wide ecology, conservation, and research needs for yellow lampmussel (Lampsilis cariosa): Hydrobiologia, v. 852, p. 2729-2754, https://doi.org/10.1007/s10750-024-05765-2.","productDescription":"26 p.","startPage":"2729","endPage":"2754","ipdsId":"IP-165902","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":492476,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10750-024-05765-2","text":"Publisher Index Page"},{"id":492135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.2116373830845,\n 44.09913691401181\n ],\n [\n -80.50374108682163,\n 41.85845354508396\n ],\n [\n -80.99912161104155,\n 39.63960771569129\n ],\n [\n -82.43337791555581,\n 37.77339486928925\n ],\n [\n -85.76310658933828,\n 33.88933798331024\n ],\n [\n -84.74697530374709,\n 30.712478092443988\n ],\n [\n -79.6611750181294,\n 30.848363324108078\n ],\n [\n -59.414970432845266,\n 46.31029094614682\n ],\n [\n -64.10136367360452,\n 49.62997543691469\n ],\n [\n -79.2116373830845,\n 44.09913691401181\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"852","noUsgsAuthors":false,"publicationDate":"2025-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Farrington, Stefanie J.","contributorId":357879,"corporation":false,"usgs":false,"family":"Farrington","given":"Stefanie J.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":942736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, David","contributorId":340494,"corporation":false,"usgs":false,"family":"Perkins","given":"David","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":942738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942739,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70268954,"text":"70268954 - 2025 - The relative influence of climate extremes and species richness on the temporal variability of bird communities","interactions":[],"lastModifiedDate":"2025-07-11T15:12:24.557526","indexId":"70268954","displayToPublicDate":"2025-02-19T10:09:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The relative influence of climate extremes and species richness on the temporal variability of bird communities","docAbstract":"Understanding the relationship between biodiversity and ecological stability is increasingly urgent as rapid species extinction continues. Though evidence of positive diversity–stability relationships is accumulating, empirical results are inconsistent, and effect sizes tend to be small, raising questions about relative contributions of intrinsic (i.e., species composition/interactions) and extrinsic (i.e., environmental) drivers of stability. Community stability may be more strongly influenced by environmental conditions than by community diversity in some contexts, yet little is known about the comparative importance of diversity and climate means, extremes, and variability in regulating stability. We used a half-century of continental-scale bird data to quantify avian community temporal variability (a metric often used to approximate ecological stability) at 1379 sites and compared relative effects of climatic variables and species richness. We found that extreme heat and extremely low precipitation at decadal scales are associated with high bird community variability and these climate variables outperformed species richness in terms of variance explained and magnitude of effect. This provides empirical support for the theoretical concept that, at a continental, decadal scale, environmental conditions can play a larger role than intrinsic factors in determining community stability. Our findings also increase understanding of how climate extremes cause diverse ecological responses.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70005","usgsCitation":"Cady, S., Fuhlendorf, S., Davis, C., Luttbeg, B., Roberts, C.P., and Loss, S., 2025, The relative influence of climate extremes and species richness on the temporal variability of bird communities: Ecology, v. 106, no. 2, e70005, 8 p., https://doi.org/10.1002/ecy.70005.","productDescription":"e70005, 8 p.","ipdsId":"IP-146673","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498238,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.70005","text":"Publisher Index Page"},{"id":492134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Cady, Samantha M.","contributorId":357859,"corporation":false,"usgs":false,"family":"Cady","given":"Samantha M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":942711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuhlendorf, Samuel D.","contributorId":357861,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel D.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":942712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Craig A.","contributorId":357863,"corporation":false,"usgs":false,"family":"Davis","given":"Craig A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":942713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luttbeg, Barney","contributorId":357865,"corporation":false,"usgs":false,"family":"Luttbeg","given":"Barney","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":942714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":942715,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loss, Scott","contributorId":357867,"corporation":false,"usgs":false,"family":"Loss","given":"Scott","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":942716,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70267891,"text":"70267891 - 2025 - Spatially explicit capture-recapture using fecal DNA to estimate elk population abundance and growth in western North Carolina, USA","interactions":[],"lastModifiedDate":"2025-06-06T15:09:09.499879","indexId":"70267891","displayToPublicDate":"2025-02-19T10:05:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit capture-recapture using fecal DNA to estimate elk population abundance and growth in western North Carolina, USA","docAbstract":"In an effort to restore extirpated elk to their historical range, 52 elk were reintroduced to Great Smoky Mountains National Park (GRSM) in North Carolina, USA, during 2001 and 2002. Since their reintroduction, elk numbers have increased, and elk have extended their range beyond GRSM boundaries. We used spatially explicit capture-recapture (SCR) methods based on fecal DNA to identify individual elk and estimate population abundance (N), apparent survival (φ), per capita recruitment (f), and population growth rate (λ) in western North Carolina. We walked a series of transects during 3 winter field seasons (2020–2022) and collected elk pellets encountered along those transects. We created spatially explicit capture histories and incorporated those data into both closed and open population SCR models. The top performing closed SCR models for males and females estimated density by year and as a function of the scaled distance to the nearest field, with densities decreasing as the distance increased. Combined male and female N were 179 elk (95% CI = 149–215) in 2020, 220 elk (95% CI = 188–256) in 2021, and 240 elk (95% CI = 207–279) in 2022. The top open population model estimated both φ and λ as functions of sex and year. The estimate of φ for males was 0.682 (95% CI = 0.317–0.908) during 2020–2021 and 0.339 (95% CI = 0.152–0.596) during 2021–2022 and for females was 0.953 (95% CI = 0.830–1.000) during 2020–2021 and 0.829 (95% CI = 0.601–1.000) during 2021–2022. The annual population growth rate (λ) for males was 1.127 (95% CI = 0.806–1.575) during 2020–2021 and 0.811 (95% CI = 0.566–1.163) during 2021–2022 and for females was 1.559 (95% CI = 1.162–2.091) during 2020–2021 and 1.122 (95% CI = 0.876–1.437) during 2021–2022. Our elk abundance estimates in areas >300 m from fields were negligible, and we suggest that sampling only the areas in and adjacent to fields in the future will result in reliable but more cost-efficient population estimates. Confidence intervals for vital rate parameters were wide for our 3-year dataset, but continued annual pellet sampling will increase sample sizes for vital rate estimation and thus improve precision. If elk herd expansion on public lands is desired, we suggest habitat modification to establish open grasslands adjacent to forests.
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Carolina\",\"nation\":\"USA \"}}]}","volume":"89","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Braunstein, Jessica L.","contributorId":342231,"corporation":false,"usgs":false,"family":"Braunstein","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":939280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":939281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Augustine, Benjamin C.","contributorId":356383,"corporation":false,"usgs":false,"family":"Augustine","given":"Benjamin C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":939282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hickman, Caleb R.","contributorId":356386,"corporation":false,"usgs":false,"family":"Hickman","given":"Caleb R.","affiliations":[{"id":84985,"text":"Eastern Band of Cherokee Indians","active":true,"usgs":false}],"preferred":false,"id":939283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McVey, Justin","contributorId":356387,"corporation":false,"usgs":false,"family":"McVey","given":"Justin","affiliations":[{"id":84988,"text":"North Carolina Wildlife Resources Agency","active":true,"usgs":false}],"preferred":false,"id":939284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yarkovich, Joseph G.","contributorId":244820,"corporation":false,"usgs":false,"family":"Yarkovich","given":"Joseph","email":"","middleInitial":"G.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":939285,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70269931,"text":"70269931 - 2025 - Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","interactions":[],"lastModifiedDate":"2025-08-07T15:03:38.484781","indexId":"70269931","displayToPublicDate":"2025-02-19T09:55:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","title":"Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States","docAbstract":"The nine-banded armadillo (Dasypus novemcinctus: hereafter armadillo) was first recorded in the United States (U.S.) in the state of Texas in 1849 and has been expanding its range northward and eastward since then. With the widespread adoption of participatory science as well as the proliferation of nationwide wildlife game camera studies, occurrence data of armadillos can be compiled more rapidly and thoroughly than at any time in the past. Here, we use disparate data sources to update the current geographic distribution of the armadillo in the United States and use occurrence data from the leading edge of its range expansion to create a species distribution model to understand their relationship with landscape and bioclimatic factors. Since the last report on the geographic distribution of the armadillo in 2014, we show that armadillos have expanded to cover the entirety of Missouri and established in southern Iowa, expanded modestly within Kansas and Illinois, expanded northward and eastward in Indiana, expanded eastward in both Kentucky and Tennessee, established throughout the entirety of South Carolina and Georgia and established in the western third of North Carolina. Our species distribution model indicates that there is substantial opportunity for the species to continue to expand its geographic range, particularly in the Eastern United States. These results provide information to managers who are now or might soon be co-existing with the armadillo to proactively manage the species or inform the public regarding potential conflicts.
","language":"English","publisher":"MDPI","doi":"10.3390/d17020138","usgsCitation":"DeGregorio, B.A., and Deshwal, A., 2025, Current distribution of the nine-banded armadillo (Dasypus novemcinctus) in the United States: Diversity, v. 17, no. 2, 138, 14 p., https://doi.org/10.3390/d17020138.","productDescription":"138, 14 p.","ipdsId":"IP-174450","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493797,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d17020138","text":"Publisher Index Page"},{"id":493710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.46443710699266,\n 43.482544866418095\n ],\n [\n -98.46009009198762,\n 41.85543820530121\n ],\n [\n -103.40240986276783,\n 39.849442113752225\n ],\n [\n -106.57489778026832,\n 32.18560045351303\n ],\n [\n -103.13881240687051,\n 29.004932608997777\n ],\n [\n -102.01381568185428,\n 29.684127826701868\n ],\n [\n -100.5588846777174,\n 28.719938827643247\n ],\n [\n -98.90079539428103,\n 26.21067054924025\n ],\n [\n -97.28797850165715,\n 25.80528820642506\n ],\n [\n -95.08083877123178,\n 28.68104484993762\n ],\n [\n -90.13838335666708,\n 29.279435161004997\n ],\n [\n -83.97820912015521,\n 29.550506198188735\n ],\n [\n -81.62615042652806,\n 25.175140663968392\n ],\n [\n -79.20159572289897,\n 24.880530509938623\n ],\n [\n -81.26833756114897,\n 30.9638453530741\n ],\n [\n -75.67958860575126,\n 35.58409243159953\n ],\n [\n -75.80680620450346,\n 38.817069169317364\n ],\n [\n -81.47311820007566,\n 41.86626002921978\n ],\n [\n -87.65021677565505,\n 42.44570766588616\n ],\n [\n -90.16529470749337,\n 42.5611294229177\n ],\n [\n -91.36833985870564,\n 43.39180921040943\n ],\n [\n -96.46443710699266,\n 43.482544866418095\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":944986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deshwal, Anant","contributorId":350109,"corporation":false,"usgs":false,"family":"Deshwal","given":"Anant","affiliations":[{"id":17862,"text":"Bradley University","active":true,"usgs":false}],"preferred":false,"id":944987,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70264308,"text":"70264308 - 2025 - Short-term ecological effects of solar energy development depend on plant community, soil type, and disturbance intensity","interactions":[],"lastModifiedDate":"2025-04-17T15:35:41.563426","indexId":"70264308","displayToPublicDate":"2025-02-19T09:23:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Short-term ecological effects of solar energy development depend on plant community, soil type, and disturbance intensity","docAbstract":"- Solar energy is rapidly growing to decarbonize the electrical grid. Maintaining ecosystem function with solar energy generation can be promoted through construction methods that minimize negative impacts on soils and vegetation. However, the disturbance created by less-impactful construction methods at utility-scale solar energy (USSE) facilities and the ecosystem responses remain relatively unknown.
- We monitored soils and vegetation before and after the USSE build-out to assess the short-term impacts of construction on soils and vegetation at the Gemini Solar Project in the Mojave Desert. The facility was constructed with methods intended to be less impactful than traditional techniques. Our goal was to answer three questions: (1) What are the short-term effects of construction on soils and vegetation? (2) Do construction effects vary by the initial plant community and soil type? and (3) Does disturbance intensity from construction affect soil and vegetation response?
- We found strong evidence that the construction of the Gemini facility increased bare soil and soil compaction, and decreased dark biocrust cover and soil stability in the short term. For every 1% increase in disturbance intensity, we found a 0.23% increase in bare soil cover and a 0.10% decrease in dark biocrust cover. Plant responses varied more than soil responses and depended on the initial plant community and soil type, with decreases in plant canopy cover highest in sandy soils dominated by creosote bush (Larrea tridentata) and white bursage (Ambrosia dumosa) shrubs.
- Synthesis and applications: Many impacts of USSE facility construction depend on the underlying vegetation and soils and the level of disturbance intensity. The use of less-impactful construction methods, including a combination of overland travel and drive-and-crush examined in our study, can ameliorate negative effects relative to traditional construction practices and provide a pathway to maintain ecosystem function.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14882","usgsCitation":"Karban, C.C., Munson, S.M., Kobelt, L., and Lovich, J.E., 2025, Short-term ecological effects of solar energy development depend on plant community, soil type, and disturbance intensity: Journal of Applied Ecology, v. 62, no. 4, p. 945-957, https://doi.org/10.1111/1365-2664.14882.","productDescription":"14 p.","startPage":"945","endPage":"957","ipdsId":"IP-167668","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498249,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14882","text":"Publisher Index Page"},{"id":483196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Karban, Claire C 0000-0002-6157-031X","orcid":"https://orcid.org/0000-0002-6157-031X","contributorId":344987,"corporation":false,"usgs":true,"family":"Karban","given":"Claire","email":"","middleInitial":"C","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":930380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kobelt, Lara A.","contributorId":350355,"corporation":false,"usgs":false,"family":"Kobelt","given":"Lara A.","affiliations":[{"id":83722,"text":"Bureau of Land Management, Southern Nevada District Office, 4701 North Torrey Pines Dr., Las Vegas, NV 89130","active":true,"usgs":false}],"preferred":false,"id":930381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":930382,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263890,"text":"70263890 - 2025 - Community estimate of global glacier mass changes from 2000 to 2023","interactions":[],"lastModifiedDate":"2025-04-17T15:33:54.867443","indexId":"70263890","displayToPublicDate":"2025-02-19T09:03:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Community estimate of global glacier mass changes from 2000 to 2023","docAbstract":"Glaciers are indicators of ongoing anthropogenic climate change1. Their melting leads to increased local geohazards2, and impacts marine3 and terrestrial4,5 ecosystems, regional freshwater resources6, and both global water and energy cycles7,8. Together with the Greenland and Antarctic ice sheets, glaciers are essential drivers of present9,10 and future11,12,13 sea-level rise. Previous assessments of global glacier mass changes have been hampered by spatial and temporal limitations and the heterogeneity of existing data series14,15,16. Here we show in an intercomparison exercise that glaciers worldwide lost 273 ± 16 gigatonnes in mass annually from 2000 to 2023, with an increase of 36 ± 10% from the first (2000–2011) to the second (2012–2023) half of the period. Since 2000, glaciers have lost between 2% and 39% of their ice regionally and about 5% globally. Glacier mass loss is about 18% larger than the loss from the Greenland Ice Sheet and more than twice that from the Antarctic Ice Sheet17. Our results arise from a scientific community effort to collect, homogenize, combine and analyse glacier mass changes from in situ and remote-sensing observations. Although our estimates are in agreement with findings from previous assessments14,15,16 at a global scale, we found some large regional deviations owing to systematic differences among observation methods. Our results provide a refined baseline for better understanding observational differences and for calibrating model ensembles12,16,18, which will help to narrow projection uncertainty for the twenty-first century11,12,18.
","language":"English","publisher":"Nature","doi":"10.1038/s41586-024-08545-z","usgsCitation":"GlaMBIE Team, Zemp, M., Jakob, L., Dussaillant, I., Nussbaumer, S., Gourmelen, N., Dubber, S., Geruo, A., Abdullahi, S., Andreassen, L.M., Berthier, E., Bhattacharya, A., Blazquez, A., Boehm Vock, L., Bolch, T., Box, J., Braun, M.H., Brun, F., Cicero, E., Colgan, W., Eckert, N., Farinotti, D., Florentine, C., Floricioiu, D., Gardner, A., Harig, C., Hassan, J., Hugonnet, R., Huss, M., Jóhannesson, T., Liang, C., Ke, C., Abbas, S., King, O., Kneib, M., Krieger, L., Maussion, F., Mattea, E., McNabb, R., Menounos, B., Miles, E., Moholdt, G., Nilsson, J., Palsson, F., Pfeffer, J., Piermattei, L., Plummer, S., Richter, A., Sasgen, I., Schuster, L., Seehaus, T., Shen, X., Sommer, C., Sutterley, T., Treichler, D., Velicogna, I., Wouters, B., Zekollari, H., and Zheng, W., 2025, Community estimate of global glacier mass changes from 2000 to 2023: Nature, v. 639, p. 382-388, 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