{"pageNumber":"40","pageRowStart":"975","pageSize":"25","recordCount":40778,"records":[{"id":70265842,"text":"70265842 - 2025 - Management and natural regeneration in multiple ponderosa pine forests of the southwestern United States","interactions":[],"lastModifiedDate":"2025-06-12T15:36:39.107884","indexId":"70265842","displayToPublicDate":"2025-02-25T08:51:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1688,"text":"Forest Science","active":true,"publicationSubtype":{"id":10}},"title":"Management and natural regeneration in multiple ponderosa pine forests of the southwestern United States","docAbstract":"Management treatments in ponderosa pine forests of the southwestern United States (SWUS) are largely done for wildfire mitigation and restoration to lower tree densities. However, lack of natural ponderosa pine regeneration in undisturbed forests (i.e., no occurrence of stand-replacing events) may require management treatments to promote regeneration. We conducted a field and modeling study in 77 ponderosa pine forests across 7 SWUS locations, with the goal of evaluating management impacts on recent natural regeneration (∼\">∼20 y). We categorized management into 3 broad categories: unmanaged, thinned from above and/or below (thinning), and thinned +\">+ understory burned (burning). Although climate suitability declined from 1981-2020, management treatments – especially burning – promoted natural regeneration. High density regeneration, an undesirable outcome, occurred in 21%\">% of managed sites. In addition to effects on near-surface temperature and soil moisture, management conducive to natural regeneration was associated with the density of competing tree species, understory litter and debris cover, and adult tree cone production. Natural regeneration occurred ∼\">∼5-10 y following management, underscoring sustained effects of management treatments on tree reproduction success. Our results show that forest management treatments have the potential to promote natural ponderosa pine regeneration in the SWUS, sometimes at undesirable high densities. Study Implications: Natural ponderosa pine regeneration is declining in forests of the southwestern United States (SWUS), and may increasingly be incorporated as a goal of forest management treatments. Across a diverse set of managed and unmanaged SWUS forest sites, we found that contemporary management treatments – especially thinning +\">+ prescribed understory burning – supported natural ponderosa pine regeneration over the past two decades, which were climatically unfavorable in much of the region. Our results show that existing forest management treatments have the potential to promote natural ponderosa pine regeneration in the SWUS, but will require assessment and modification through time to remain effective.
","language":"English","publisher":"Springer","doi":"10.1007/s44391-025-00013-z","collaboration":"US Forest Service","usgsCitation":"Petrie, M., Hubbard, R.M., Bradford, J., Kolb, T.E., Noel, A.R., Schlaepfer, D.R., Bowen, M., Fuller, L., and Moser, W., 2025, Management and natural regeneration in multiple ponderosa pine forests of the southwestern United States: Forest Science, v. 71, p. 203-230, https://doi.org/10.1007/s44391-025-00013-z.","productDescription":"28 p.","startPage":"203","endPage":"230","ipdsId":"IP-153306","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":484676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","noUsgsAuthors":false,"publicationDate":"2025-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrie, Matthew D.","contributorId":206328,"corporation":false,"usgs":false,"family":"Petrie","given":"Matthew D.","affiliations":[{"id":37312,"text":"Department of Plant & Environmental Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":933720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubbard, Robert M. 0000-0003-2601-1798","orcid":"https://orcid.org/0000-0003-2601-1798","contributorId":334944,"corporation":false,"usgs":false,"family":"Hubbard","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":80290,"text":"USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO 80521, USA","active":true,"usgs":false}],"preferred":false,"id":933721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":933722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolb, Tom E.","contributorId":340095,"corporation":false,"usgs":false,"family":"Kolb","given":"Tom","email":"","middleInitial":"E.","affiliations":[{"id":39356,"text":"School of Forestry, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":933723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noel, Adam Roy 0000-0002-0891-4005","orcid":"https://orcid.org/0000-0002-0891-4005","contributorId":294761,"corporation":false,"usgs":true,"family":"Noel","given":"Adam","email":"","middleInitial":"Roy","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":933724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":933725,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowen, M.A.","contributorId":340096,"corporation":false,"usgs":false,"family":"Bowen","given":"M.A.","email":"","affiliations":[{"id":81462,"text":"USDA Forest Service, Lincoln National Forest, Cloudcroft, NM, USA","active":true,"usgs":false}],"preferred":false,"id":933726,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fuller, L.R.","contributorId":340098,"corporation":false,"usgs":false,"family":"Fuller","given":"L.R.","email":"","affiliations":[{"id":81463,"text":"USDA Forest Service, Apache-Sitgreaves National Forest, Springerville, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":933727,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moser, W. Keith","contributorId":298271,"corporation":false,"usgs":false,"family":"Moser","given":"W. Keith","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":933728,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"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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0000-0001-8489-4002","orcid":"https://orcid.org/0000-0001-8489-4002","contributorId":296009,"corporation":false,"usgs":false,"family":"Burgin","given":"Amy","email":"","middleInitial":"J.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":931321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Busch, Michelle H.","contributorId":335238,"corporation":false,"usgs":false,"family":"Busch","given":"Michelle H.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":931322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Joshua B.","contributorId":211503,"corporation":false,"usgs":false,"family":"Fisher","given":"Joshua","email":"","middleInitial":"B.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":931323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ladau, 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USA","active":true,"usgs":false}],"preferred":false,"id":931345,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Allen, Daniel C.","contributorId":335231,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":931346,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Herndon, Elizabeth","contributorId":352462,"corporation":false,"usgs":false,"family":"Herndon","given":"Elizabeth","affiliations":[{"id":33221,"text":"Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA","active":true,"usgs":false}],"preferred":false,"id":931347,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Middleton, Beth 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Dame","active":true,"usgs":false}],"preferred":false,"id":931350,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Scamardo, Julianne","contributorId":352464,"corporation":false,"usgs":false,"family":"Scamardo","given":"Julianne","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":931351,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Vander Vorste, Ross","contributorId":352465,"corporation":false,"usgs":false,"family":"Vander Vorste","given":"Ross","affiliations":[{"id":84234,"text":"Department of Biology, University of Wisconsin-La Crosse. 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":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":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 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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
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":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.
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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":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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,{"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":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, https://doi.org/10.1038/s41586-024-08545-z.","productDescription":"7 p.","startPage":"382","endPage":"388","ipdsId":"IP-168262","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":487239,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-024-08545-z","text":"Publisher Index Page"},{"id":482568,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"639","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"GlaMBIE Team","contributorId":351576,"corporation":true,"usgs":false,"organization":"GlaMBIE Team","id":928958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zemp, 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,{"id":70263884,"text":"70263884 - 2025 - Implications of physics-based M9 ground motions on liquefaction-induced damage in the Cascadia Subduction Zone: Looking forward and backward","interactions":[],"lastModifiedDate":"2025-02-27T15:45:13.850251","indexId":"70263884","displayToPublicDate":"2025-02-19T08:37:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Implications of physics-based M9 ground motions on liquefaction-induced damage in the Cascadia Subduction Zone: Looking forward and backward","docAbstract":"Given the likelihood of future M9 Cascadia Subduction Zone (CSZ) earthquakes, various estimates of the resulting, regional ground motions have been made, including a suite of 30 physics-based simulations that reflect key modeling uncertainties. However, because the last CSZ interface rupture occurred in 1700 CE, the shaking expected in such an event is especially uncertain, as are the impacts to the built and living environments. Like other coseismic impacts, soil liquefaction poses a significant threat and must be considered by any scenario study used to inform planning and response, or to focus mitigation resources. Liquefaction is also notable for its potential to “ground truth” ground-motion estimates, given that its presence or absence in the geologic record can provide constraint on the intensities of shaking in past events. It is thus an important phenomenon looking both forward and backward. Accordingly, using recent physics-based simulations, this study (1) predicts liquefaction in M9 CSZ ruptures at 400 locations in Oregon, Washington, and British Columbia (BC) using an array of cone-penetration-test based models and (2) uses paleoliquefaction evidence at ten sites spanning from Southern Oregon to Vancouver, BC to constrain possible ground-motion intensities experienced in the 1700 CE earthquake. The forward predictions indicate that liquefaction in M9 events could be pervasive in the region and affect numerous population hubs, with the potential for damage across hundreds of square kilometers. The backward analyses suggest that 1700 CE ground-motion intensities may have been less than expected from M9 simulations in some northern portions of the CSZ (e.g. Seattle), given the paucity of 1700 CE liquefaction evidence in these areas. Ultimately, further discovery and analysis of CSZ paleoliquefaction, or lack thereof, will confirm or modify this possibility and the conclusions drawn herein.","language":"English","publisher":"Sage","doi":"10.1177/87552930251316819","usgsCitation":"Rasanen, R., Grant, A.R., Makdisi, A.J., Maurer, B.W., and Wirth, E.A., 2025, Implications of physics-based M9 ground motions on liquefaction-induced damage in the Cascadia Subduction Zone: Looking forward and backward: Earthquake Spectra, 30 p., https://doi.org/10.1177/87552930251316819.","productDescription":"30 p.","ipdsId":"IP-157098","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.26164781722542,\n 48.65345896049223\n ],\n [\n -125.26164781722542,\n 44.28740331066001\n ],\n [\n -122.25792048153377,\n 44.28740331066001\n ],\n [\n -122.25792048153377,\n 48.65345896049223\n ],\n [\n -125.26164781722542,\n 48.65345896049223\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Rasanen, Ryan A.","contributorId":337148,"corporation":false,"usgs":false,"family":"Rasanen","given":"Ryan A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":928882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":928883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Makdisi, Andrew James 0000-0002-8239-0692","orcid":"https://orcid.org/0000-0002-8239-0692","contributorId":267917,"corporation":false,"usgs":true,"family":"Makdisi","given":"Andrew","email":"","middleInitial":"James","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":928884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maurer, Brett W.","contributorId":139387,"corporation":false,"usgs":false,"family":"Maurer","given":"Brett","email":"","middleInitial":"W.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":928885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wirth, Erin A. 0000-0002-8592-4442","orcid":"https://orcid.org/0000-0002-8592-4442","contributorId":207853,"corporation":false,"usgs":true,"family":"Wirth","given":"Erin","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928886,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264161,"text":"70264161 - 2025 - Not just corticosterone: Further characterization of the endocrine response of Kemp’s ridley sea turtles (Lepidochelys kempii) reveals elevated plasma aldosterone concentrations during field capture events","interactions":[],"lastModifiedDate":"2025-03-07T15:13:34.120709","indexId":"70264161","displayToPublicDate":"2025-02-19T08:06:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Not just corticosterone: Further characterization of the endocrine response of Kemp’s ridley sea turtles (Lepidochelys kempii) reveals elevated plasma aldosterone concentrations during field capture events","docAbstract":"To develop safe and effective management policies, it is important to understand the physiologic effects of fishing interactions and scientific research methods on endangered marine species. In the present study, validated assays for plasma corticosterone, free thyroxine (fT4), and aldosterone were used to assess the endocrine status of 61 presumed healthy, wild Kemp's ridley sea turtles (Lepidochelys kempii) that were captured for separate ecological studies using two capture methods (trawl net n = 40; manual capture n = 21). Plasma hormone concentrations were also assessed in relation to eight clinical plasma biochemical analytes. Corticosterone and aldosterone concentrations were moderately high after capture, with significantly higher concentrations in turtles captured by trawl net vs. manual capture. Free thyroxine concentrations were within previously published ranges for healthy individuals of this species. Clinical biochemical data revealed moderately elevated potassium and lactate concentrations in many individuals, with significantly greater lactate concentrations in trawl-captured turtles. Aldosterone concentrations were positively correlated with corticosterone. The results of the present study indicate that Kemp's ridley sea turtles have robust adrenocortical activity immediately after capture, resulting in high plasma concentrations of corticosterone and aldosterone. Researchers who use such methods to access sea turtles can consider these results in planning careful and efficient field studies.
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,{"id":70273877,"text":"70273877 - 2025 - What is a specialist? Quantifying host breadth enables impact prediction for invasive herbivores","interactions":[],"lastModifiedDate":"2026-02-11T14:55:48.532321","indexId":"70273877","displayToPublicDate":"2025-02-19T07:50:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"What is a specialist? Quantifying host breadth enables impact prediction for invasive herbivores","docAbstract":"Herbivores are commonly classified as host specialists or generalists for various purposes, yet the definitions of these terms, and their intermediates, are often imprecise and ambiguous. We quantified host breadth for 240 non-native, tree-feeding insects in North America using phylogenetic diversity. We demonstrated that a partitioning of host breadth: (1) causes 67% of non-native insects to shift from a generalist to specialist category, (2) displays a reduction in host breadth from the native to introduced range, (3) identifies an inflection point in a model predicting the likelihood of non-native insect ecological impact, with a corresponding change in behaviour associated with specialists versus generalists, and (4) enables three models for strong prediction of whether a non-native forest insect will cause high impacts. Together, these results highlight the primacy of how herbivore host recognition and plant defences mediate whether novel host interactions will result in high impact after invasion.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.70083","usgsCitation":"Schulz, A.N., Havill, N.P., Marsico, T.D., Ayres, M.P., Gandhi, K.J., Herms, D.A., Hoover, A., Hufbauer, R.A., Liebhold, A.M., Raffa, K.F., Thomas, K.A., Tobin, P.C., Uden, D.R., and Mech, A.M., 2025, What is a specialist? Quantifying host breadth enables impact prediction for invasive herbivores: Ecology Letters, v. 28, no. 2, e70083, 12 p., https://doi.org/10.1111/ele.70083.","productDescription":"e70083, 12 p.","ipdsId":"IP-158243","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499745,"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 -182.681888554713,\n 53.85389979192047\n ],\n [\n -118.28676622689468,\n 32.88061586567801\n ],\n [\n -98.02837651680895,\n 26.779616505270788\n ],\n [\n -78.36191912659696,\n 24.831321950270947\n ],\n [\n -51.957456444544675,\n 47.112649634321606\n ],\n [\n -64.21831161600105,\n 60.73216659039127\n ],\n [\n -118.7391214000643,\n 70.7115126428508\n ],\n [\n -163.08695093879513,\n 72.42372463033631\n ],\n [\n -182.681888554713,\n 53.85389979192047\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulz, Ashley N.","contributorId":366147,"corporation":false,"usgs":false,"family":"Schulz","given":"Ashley","middleInitial":"N.","affiliations":[{"id":87367,"text":"Mississippi State University, Department of Forestry, Box 9681, Mississippi State, MS 39762, USA","active":true,"usgs":false}],"preferred":false,"id":955359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Havill, Nathan P.","contributorId":366148,"corporation":false,"usgs":false,"family":"Havill","given":"Nathan","middleInitial":"P.","affiliations":[{"id":87368,"text":"USDA Forest Service Northern Research Station, 51 Mill Pond Rd., Hamden, CT 06514, USA","active":true,"usgs":false}],"preferred":false,"id":955360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marsico, Travis D.","contributorId":366149,"corporation":false,"usgs":false,"family":"Marsico","given":"Travis","middleInitial":"D.","affiliations":[{"id":87369,"text":"Arkansas State University, Department of Biological Sciences, PO Box 599, State University, AR 72467, USA","active":true,"usgs":false}],"preferred":false,"id":955361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ayres, Matthew P.","contributorId":366150,"corporation":false,"usgs":false,"family":"Ayres","given":"Matthew","middleInitial":"P.","affiliations":[{"id":87370,"text":"Dartmouth College, Department of Biological Sciences, 78 College Street, Hanover, NH 03755, USA","active":true,"usgs":false}],"preferred":false,"id":955362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gandhi, Kamal J.K.","contributorId":366151,"corporation":false,"usgs":false,"family":"Gandhi","given":"Kamal","middleInitial":"J.K.","affiliations":[{"id":87371,"text":"The University of Georgia, Daniel B. Warnell School of Forestry and Natural Resources, 180 E. Green St., Athens, GA 30602, USA","active":true,"usgs":false}],"preferred":false,"id":955363,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herms, Daniel A.","contributorId":366152,"corporation":false,"usgs":false,"family":"Herms","given":"Daniel","middleInitial":"A.","affiliations":[{"id":87372,"text":"The Davey Tree Expert Company, 1500 N Mantua St., Kent, OH 44240, USA","active":true,"usgs":false}],"preferred":false,"id":955364,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoover, Angela M. 0000-0003-0401-5587","orcid":"https://orcid.org/0000-0003-0401-5587","contributorId":337614,"corporation":false,"usgs":false,"family":"Hoover","given":"Angela M.","affiliations":[{"id":81032,"text":"formerly: USGS Southwest Biological Science Center, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":955365,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hufbauer, Ruth A.","contributorId":366153,"corporation":false,"usgs":false,"family":"Hufbauer","given":"Ruth","middleInitial":"A.","affiliations":[{"id":87373,"text":"Department of Agricultural Biology, Graduate Degree Program in Ecology, Colorado State University; Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":955366,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liebhold, Andrew M.","contributorId":366154,"corporation":false,"usgs":false,"family":"Liebhold","given":"Andrew","middleInitial":"M.","affiliations":[{"id":87374,"text":"USDA Forest Service Northern Research Station, Morgantown; WV 26505, USA; Faculty of Forestry and Wood Sciences, Czech University of Life Sciences; Prague, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":955367,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Raffa, Kenneth F.","contributorId":366155,"corporation":false,"usgs":false,"family":"Raffa","given":"Kenneth","middleInitial":"F.","affiliations":[{"id":87375,"text":"Department of Entomology, University of Wisconsin; Madison, WI 53706, USA","active":true,"usgs":false}],"preferred":false,"id":955368,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":955369,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tobin, Patrick C.","contributorId":366156,"corporation":false,"usgs":false,"family":"Tobin","given":"Patrick","middleInitial":"C.","affiliations":[{"id":87376,"text":"School of Environmental and Forest Sciences, University of Washington; Seattle, WA 98195, USA","active":true,"usgs":false}],"preferred":false,"id":955370,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Uden, Daniel R.","contributorId":366157,"corporation":false,"usgs":false,"family":"Uden","given":"Daniel","middleInitial":"R.","affiliations":[{"id":87377,"text":"School of Natural Resources, Department of Agronomy and Horticulture, Center for Resilience in Agricultural Working Landscapes, University of Nebraska‐Lincoln; Lincoln, NE 68583, USA","active":true,"usgs":false}],"preferred":false,"id":955371,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mech, Angela M.","contributorId":366158,"corporation":false,"usgs":false,"family":"Mech","given":"Angela","middleInitial":"M.","affiliations":[{"id":87378,"text":"School of Biology and Ecology, University of Maine; Orono, ME 04469, USA;","active":true,"usgs":false}],"preferred":false,"id":955372,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70265933,"text":"70265933 - 2025 - Quantifying regional ecological dynamics using agency monitoring data, ecological site descriptions, and ecological site groups","interactions":[],"lastModifiedDate":"2025-04-22T16:09:28.804094","indexId":"70265933","displayToPublicDate":"2025-02-18T11:02:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying regional ecological dynamics using agency monitoring data, ecological site descriptions, and ecological site groups","docAbstract":"Information about what ecological conditions are likely, causes or drivers of degradation, and potential management actions to restore degraded lands may support land conservation and restoration decisions. State-and-transition models (STMs) describe persistent plant and ecological conditions that are possible (the “state”) within a given abiotic setting and drivers or actions that can cause shifts between states (the “transitions”). These primarily conceptual models are widely used to inform resource and conservation decisions. Data-driven STMs have been developed for some lands, but not at regional or national scales. Here, we demonstrate a new repeatable workflow for developing data-driven STMs in the United States (US). The approach leverages predictive maps of Ecological Site Groups (ESGs), extensive field-based Federal monitoring databases, information from Ecological Site Description (ESD) STMs, soil erosion models, remotely sensed productivity, and other available spatial information (fire, land protection, and drought) to provide context and descriptions of the data-driven states, including likely drivers of transitions. Results of this workflow applied to one dryland ESG in the Upper Colorado River Basin in the southwestern US suggest that an Invaded state (16% of 1352 plots) and some occurrences of a Grassland state (30% of plots) are in a degraded or at-risk condition with reduced ecosystem services. The most common drivers of state transitions in the associated ESDs (n = 26) are related to livestock grazing and fire. The Invaded state in the ESG has evidence of degraded habitat quality and accelerated run-off while the Grassland state occurrences show reduced richness, productivity, and elevated erosion risk by wind. Areas subject to wildfire and with lower protection status had greater probability of Invaded state occurrence, generally supporting drivers in ESDs. The workflow presented here can serve as a template for describing ecological dynamics at regional scales, and support prioritization of land for conservation and climate adaptation activities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.12.006","usgsCitation":"Duniway, M.C., Knight, A.C., Nauman, T., Bishop, T., McCord, S.E., Webb, N.P., Williams, C., and Humphries, J.T., 2025, Quantifying regional ecological dynamics using agency monitoring data, ecological site descriptions, and ecological site groups: Rangeland Ecology & Management, v. 99, p. 119-142-142, https://doi.org/10.1016/j.rama.2024.12.006.","productDescription":"24 p.","startPage":"119-142","endPage":"142","ipdsId":"IP-158948","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":490994,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.12.006","text":"Publisher Index Page"},{"id":484842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","noUsgsAuthors":false,"publicationDate":"2025-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W.","contributorId":310519,"corporation":false,"usgs":false,"family":"Nauman","given":"Travis W.","affiliations":[{"id":67201,"text":"USDA-NRCS National Soil Survey Center, 2290 SW Resource Blvd., Moab, UT, 84532, USA","active":true,"usgs":false}],"preferred":false,"id":934068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bishop, Tara B.B.","contributorId":215034,"corporation":false,"usgs":false,"family":"Bishop","given":"Tara B.B.","affiliations":[{"id":39160,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT USA","active":true,"usgs":false}],"preferred":false,"id":934069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":934070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Webb, Nicholas P.","contributorId":195924,"corporation":false,"usgs":false,"family":"Webb","given":"Nicholas","email":"","middleInitial":"P.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":934071,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, C. Jason","contributorId":292512,"corporation":false,"usgs":false,"family":"Williams","given":"C. Jason","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":934072,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Humphries, Joel T.","contributorId":270937,"corporation":false,"usgs":false,"family":"Humphries","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":56221,"text":"US Bureau of Land Management, Colorado State Office, Lakewood, CO 80215, USA","active":true,"usgs":false}],"preferred":false,"id":934073,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70264360,"text":"70264360 - 2025 - Reduction of red bed sedimentary rocks in connection with energy metal ore formation: A case study from the Sinbad seep, Mesa County, Colorado","interactions":[],"lastModifiedDate":"2025-04-17T15:36:43.417614","indexId":"70264360","displayToPublicDate":"2025-02-18T08:43:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20209,"text":"Mining, Metallurgy and Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Reduction of red bed sedimentary rocks in connection with energy metal ore formation: A case study from the Sinbad seep, Mesa County, Colorado","docAbstract":"The Paradox Basin’s Sinbad seep is a modern analog for ancient bleaching of red bed sediments by introduced alkaline, reducing brines. This bleaching, involving reductive alteration of former red beds, is essential ground preparation that enables the altered rocks to trap Cu, U, and V from later oxidized fluids, forming ore deposits. Study of Sinbad thus offers insights into these metallic mineralization processes in the Paradox and other sedimentary basins. The Sinbad seep occurs where shallow groundwater interacts with organic-rich petroleum source rocks, flows up a fault, and discharges into Salt Creek. Ratios of Na/Cl, Na/Br, and Cl/Br, plus high sulfate concentrations, indicate that the salinity of the seep water originated from dissolution of halite and gypsum during topographically driven flow of meteoric water across a diapir of the Pennsylvanian Paradox Formation, rather than from deep basinal brines. In contact with the organic-rich shales of the Paradox, these SO4-rich waters become reduced through bacterial reduction, producing H2S. The waters react with red beds of the Permian Cutler Formation, causing pervasive bleaching. The bleaching at Sinbad is characterized by iron-conservative reduction of ferric iron in diagenetic hematite and detrital ilmenite and magnetite to Fe sulfides. The ferrous iron is retained in these sulfides likely as sorbed Fe. Associated alteration includes precipitation of quartz and feldspar overgrowths, partial dissolution of detrital quartz and feldspar caused by pressure solution, formation of clay and authigenic rutile, and precipitation of carbonate and gypsum. The Fe sulfides rapidly degenerate to a mixture of jarosite and iron oxides on weathering at the surface. Among the major-oxide elements and most trace elements, there is no statistical difference between unbleached and bleached samples. The exceptions are uranium and sulfur, which are somewhat greater in bleached samples. Fission track radiography illuminates that uranium is preferentially concentrated in iron oxide cements, iron sorbed into detrital clasts, and finely disseminated iron oxide in illite cement in bleached samples. A leaching experiment suggests that uranium may be more easily available for mobilization from rocks that have undergone bleaching alteration, making them potential U sources. In addition, bleached rocks form effective traps for U, V, and some Cu mineralization.
","language":"English","publisher":"Springer","doi":"10.1007/s42461-025-01184-6","usgsCitation":"Barton, I., Thorson, J., Hall, S., Zielinski, R.A., McIntosh, J., and Kim, J., 2025, Reduction of red bed sedimentary rocks in connection with energy metal ore formation: A case study from the Sinbad seep, Mesa County, Colorado: Mining, Metallurgy and Exploration, v. 42, p. 1177-1197, https://doi.org/10.1007/s42461-025-01184-6.","productDescription":"21 p.","startPage":"1177","endPage":"1197","ipdsId":"IP-159441","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":483229,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Mesa County","otherGeospatial":"Sinbad 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Isabel","contributorId":352254,"corporation":false,"usgs":false,"family":"Barton","given":"Isabel","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":930518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorson, Jon P.","contributorId":352255,"corporation":false,"usgs":false,"family":"Thorson","given":"Jon P.","affiliations":[{"id":36466,"text":"Consulting Geologist","active":true,"usgs":false}],"preferred":false,"id":930519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Susan 0000-0002-0931-8694","orcid":"https://orcid.org/0000-0002-0931-8694","contributorId":201829,"corporation":false,"usgs":true,"family":"Hall","given":"Susan","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":930520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zielinski, Robert A. 0000-0002-4047-5129 rzielinski@usgs.gov","orcid":"https://orcid.org/0000-0002-4047-5129","contributorId":1593,"corporation":false,"usgs":true,"family":"Zielinski","given":"Robert","email":"rzielinski@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":930521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntosh, Jennifer","contributorId":352256,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":930522,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kim, Ji-Hyun","contributorId":352257,"corporation":false,"usgs":false,"family":"Kim","given":"Ji-Hyun","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":930523,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264318,"text":"70264318 - 2025 - Re-evaluating the tectonic affinity of Proterozoic crustal provinces in the Southwest USA: Detrital zircon evidence for a Laurentian source for the Yavapai and Mojave Provinces","interactions":[],"lastModifiedDate":"2025-07-09T15:57:43.400612","indexId":"70264318","displayToPublicDate":"2025-02-18T07:58:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Re-evaluating the tectonic affinity of Proterozoic crustal provinces in the Southwest USA: Detrital zircon evidence for a Laurentian source for the Yavapai and Mojave Provinces","docAbstract":"Models for crustal growth commonly involve the accretion of dominantly juvenile crust to continental margins. However, tracking the provenance and tectonic affinity of dominantly juvenile crustal provinces is challenging. This difficulty is highlighted by uncertainty over whether the Yavapai and Mojave Provinces, part of the >1300-km-wide system of Proterozoic orogens in southwestern Laurentia, (1) have similar crustal and tectonic histories and (2) if they formed on or near Laurentian, Australian, or Antarctic cratons. Here, we contribute new large-n detrital zircon U-Pb geochronology and Sm-Nd whole-rock isotope geochemistry to help constrain the provenance of the Yavapai Province and address these broader questions. Yavapai Province metasedimentary rocks from central Colorado in the southwestern USA have abundant pre-1.80 Ga detrital zircon grains, with ca. 1.85 Ga, 2.30 Ga, and 2.50−2.70 Ga peaks, and variable amounts of 1.79−1.78 Ga grains. Evolved whole-rock Sm-Nd isotopic compositions from these rocks, including 2.36−2.08 Ga model ages, also suggest mixing between 1.79 Ga and 1.78 Ga Yavapai Province arcs and early Proterozoic to Archean sources. Nearly identical pre-1.8 Ga detrital and inherited zircon age distributions suggest that the Yavapai and Mojave Provinces formed on and/or incorporated similar material. The Trans-Hudson orogen, and to a slightly lesser extent the Penokean orogen, provide the closest matches to the pre-1.80 Ga material in the Yavapai and Mojave Provinces. This similarity, coupled with a weaker resemblance to Australian and Antarctic sources, support a Laurentian affinity for the Yavapai and Mojave Provinces. We envision Paleoproterozoic arc formation on both oceanic crust and material of Laurentian affinity and multiple phases of arc-back-arc genesis, closure, and accretionary tectonism along the long-lived margin of the supercontinent Columbia (Nuna).
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37882.1","usgsCitation":"Hillenbrand, I.W., Gilmer, A.K., Premo, W.R., Williams, M.L., and Jercinovic, M.J., 2025, Re-evaluating the tectonic affinity of Proterozoic crustal provinces in the Southwest USA: Detrital zircon evidence for a Laurentian source for the Yavapai and Mojave Provinces: Geological Society of America Bulletin, v. 137, no. 7-8, p. 2965-2981, https://doi.org/10.1130/B37882.1.","productDescription":"17 p.","startPage":"2965","endPage":"2981","ipdsId":"IP-167810","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":483199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Idaho, New Mexico, Utah, Wyoming","otherGeospatial":"southwest United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.95423255032217,\n 42.82922329789568\n ],\n [\n -113.95423255032217,\n 31.615412012487866\n ],\n [\n -102.42220824721481,\n 31.615412012487866\n ],\n [\n -102.42220824721481,\n 42.82922329789568\n ],\n [\n -113.95423255032217,\n 42.82922329789568\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"137","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2025-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":930412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":930413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Premo, Wayne R. 0000-0001-9904-4801 wpremo@usgs.gov","orcid":"https://orcid.org/0000-0001-9904-4801","contributorId":1697,"corporation":false,"usgs":true,"family":"Premo","given":"Wayne","email":"wpremo@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":930414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Michael L.","contributorId":215495,"corporation":false,"usgs":false,"family":"Williams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":930415,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jercinovic, Michael J.","contributorId":316620,"corporation":false,"usgs":false,"family":"Jercinovic","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":68659,"text":"University of Massachusetts - Amherst","active":true,"usgs":false}],"preferred":false,"id":930416,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263851,"text":"70263851 - 2025 - Increased heterozygosity and body condition result from admixed translocation of the threatened Mogollon Narrow-headed Gartersnake (Thamnophis rufipunctatus)","interactions":[],"lastModifiedDate":"2025-04-17T15:32:18.845464","indexId":"70263851","displayToPublicDate":"2025-02-17T15:20:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Increased heterozygosity and body condition result from admixed translocation of the threatened Mogollon Narrow-headed Gartersnake (Thamnophis rufipunctatus)","title":"Increased heterozygosity and body condition result from admixed translocation of the threatened Mogollon Narrow-headed Gartersnake (Thamnophis rufipunctatus)","docAbstract":"Enhancing gene flow through translocations can be a useful tool in recovering small and isolated populations. However, it is not devoid of genetic risks, such as outbreeding depression in future generations, that can have negative consequences in terms of the establishment and mean fitness of the population. Studies that monitor the long-term effects of genetic rescue on populations in the wild are few, especially for snakes. We used long-term genetic monitoring and body condition indices to investigate the consequences of conservation translocation and genetic admixture in a Mogollon Narrow-headed Gartersnake (Thamnophis rufipunctatus) wild population. We compared genetic diversity and fitness metrics among the source and recipient populations to evaluate individual- and population-level fitness responses related to the conservation translocation. Our study found persistent captures with continued monitoring for over a decade post-release, and the recipient population showed lower inbreeding values and an increase in heterozygosity that was 19% higher than the two source populations. Snakes sampled in the recipient population had higher individual heterozygosity and body condition than those in the extant source and reference populations. Further, Bayesian regression models supported a significant positive relationship between heterozygosity and body condition after accounting for among-site differences, suggesting that efforts to increase heterozygosity can improve mean fitness in these populations. Our study highlights the potential benefits of conservation translocation from multiple source populations to restore the distribution and increase heterozygosity and population fitness of this threatened gartersnake. Alongside ecological restoration, translocation programs could be used to ensure both the persistence and resilience of populations throughout the species’ range.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-025-01677-3","usgsCitation":"Wood, D.A., Christman, B.L., Jennings, R., Rose, J.P., Nowak, E.M., Schofer, J., and Vandergast, A.G., 2025, Increased heterozygosity and body condition result from admixed translocation of the threatened Mogollon Narrow-headed Gartersnake (Thamnophis rufipunctatus): Conservation Genetics, v. 26, p. 403-418, https://doi.org/10.1007/s10592-025-01677-3.","productDescription":"16 p.","startPage":"403","endPage":"418","ipdsId":"IP-172385","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488336,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10592-025-01677-3","text":"Publisher Index Page"},{"id":482512,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.04554823680535,\n 33.80117748726563\n ],\n [\n -109.04554823680535,\n 33.35048803691312\n ],\n [\n -108.38767728510955,\n 33.35048803691312\n ],\n [\n -108.38767728510955,\n 33.80117748726563\n ],\n [\n -109.04554823680535,\n 33.80117748726563\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2025-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christman, Bruce L.","contributorId":207392,"corporation":false,"usgs":false,"family":"Christman","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":928677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennings, Randy D.","contributorId":351489,"corporation":false,"usgs":false,"family":"Jennings","given":"Randy D.","affiliations":[{"id":83996,"text":"Western New Mexico University","active":true,"usgs":false}],"preferred":false,"id":928678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowak, Erika M.","contributorId":207510,"corporation":false,"usgs":false,"family":"Nowak","given":"Erika","email":"","middleInitial":"M.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":928680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schofer, Justin","contributorId":351490,"corporation":false,"usgs":false,"family":"Schofer","given":"Justin","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":928681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928682,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70266086,"text":"70266086 - 2025 - Application of transcriptomics concentration-response modeling for prioritization of contaminants detected in tributaries of the North American Great Lakes","interactions":[],"lastModifiedDate":"2025-05-12T15:47:36.606655","indexId":"70266086","displayToPublicDate":"2025-02-17T10:08:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Application of transcriptomics concentration-response modeling for prioritization of contaminants detected in tributaries of the North American Great Lakes","docAbstract":"As part of the Great Lakes Restoration Initiative, chemical monitoring and surveillance efforts have detected approximately 330 chemicals in surface water of Great Lakes tributaries. There were 140 chemicals for which no empirical toxicity data were available. The aim of this study was to generate transcriptomic points of departure (tPODs) for 10 of these compounds and demonstrate how they could be applied in a screening-level prioritization. Organisms representing three trophic levels of the aquatic food web (Pimephales promelas, Daphnia magna, and Raphidocelis subcapitata) were exposed for 24 hr to a half-log dilution series of nominal exposure concentrations typically ranging from 66.7–0.021 µM of each chemical. In addition to observations of apical effects (e.g., survival and morphology), whole body transcriptomic responses (tPODs) to each chemical were evaluated with targeted analysis using TempO-seq for P. promelas and D. magna and nontargeted RNA-seq for R. subcapitata. The tPODs ranged from 0.18–10.8 µM for P. promelas and 0.32–29 µM for D. magna, with the most potent of the chemicals tested being fipronil carboxamide for both species. For R. subcapitata, the tPODs ranged from 0.04–1.77 µM, with gabapentin as the most potent chemical tested. Empirically derived tPODs from these data-poor chemicals were compared with concentrations detected in the Great Lakes basin. Environmental concentrations were less than the tPODs except for R. subcapitata and 3,4-dichlorophenyl isocyanate. Similarly, tPODs from previously tested data-rich chemicals were compared with environmental concentrations, in which case tPODs from several chemicals overlapped environmental concentrations. This work demonstrates the potential utility of emerging ecological high-throughput transcriptomics assays to support screening and prioritization of data-poor environmental contaminants.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf050","usgsCitation":"Jenna Cavallin, Kendra Bush, Corsi, S., DeCicco, L., Kevin Flynn, Alex Kasparek, Monique Hazimi, Erin Maloney, Peter Schuman, and Daniel Villeneuve, 2025, Application of transcriptomics concentration-response modeling for prioritization of contaminants detected in tributaries of the North American Great Lakes: Environmental Toxicology and Chemistry, v. 44, no. 5, p. 1310-1321, https://doi.org/10.1093/etojnl/vgaf050.","productDescription":"12 p.","startPage":"1310","endPage":"1321","ipdsId":"IP-167135","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":484984,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenna Cavallin","contributorId":353840,"corporation":false,"usgs":false,"family":"Jenna Cavallin","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":934549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendra Bush","contributorId":353841,"corporation":false,"usgs":false,"family":"Kendra Bush","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":934550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeCicco, Laura 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":215381,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kevin Flynn","contributorId":353846,"corporation":false,"usgs":false,"family":"Kevin Flynn","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":934553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alex Kasparek","contributorId":353847,"corporation":false,"usgs":false,"family":"Alex Kasparek","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":934554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monique Hazimi","contributorId":353850,"corporation":false,"usgs":false,"family":"Monique Hazimi","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":934555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erin Maloney","contributorId":353852,"corporation":false,"usgs":false,"family":"Erin Maloney","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":934556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peter Schuman","contributorId":353856,"corporation":false,"usgs":false,"family":"Peter Schuman","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":934557,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daniel Villeneuve","contributorId":353857,"corporation":false,"usgs":false,"family":"Daniel Villeneuve","affiliations":[],"preferred":false,"id":934558,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70264973,"text":"70264973 - 2025 - Reevaluating the depositional model of the Cenomanian–Turonian Bridge Creek Limestone Member near Pueblo, Colorado, U.S.A.: Roles of changing sedimentation rate on the formation of limestone–marl bedding couplets","interactions":[],"lastModifiedDate":"2025-03-27T15:05:02.687084","indexId":"70264973","displayToPublicDate":"2025-02-17T09:57:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2451,"text":"Journal of Sedimentary Research","onlineIssn":"1938-3681","printIssn":"1527-1404","active":true,"publicationSubtype":{"id":10}},"title":"Reevaluating the depositional model of the Cenomanian–Turonian Bridge Creek Limestone Member near Pueblo, Colorado, U.S.A.: Roles of changing sedimentation rate on the formation of limestone–marl bedding couplets","docAbstract":"Although interbedded limestone–marl couplets in many hemipelagic and pelagic deposits have been commonly attributed to orbital-driven climate cycles, the driving mechanisms of these couplets remain largely controversial. This situation arises from the fact that detailed sedimentologic and petrographic facies characteristics of these fine-grained deposits have rarely been examined closely. In this study we conduct an integrated sedimentologic and petrographic analysis to disentangle causes of the limestone–marl bedding couplets in the Cenomanian–Turonian Bridge Creek Limestone Member (BCL) of the Greenhorn Formation using cores and outcrop near Pueblo, Colorado. By integrating existing geochemical datasets, each of the three general lithologies in the BCL including limestone, marl, and calcareous mudstone can be divided into two facies, a more bioturbated vs. a more laminated facies, in addition to bentonite beds. The variability in sedimentary, bioturbation, and petrographic characteristics of different sedimentary facies types, as well as constraints from the existing orbital time scale, in the BCL indicate changes in sediment accumulation rate or the amount of time recorded by different facies—the limestone, marl, and calcareous facies are interpreted to reflect increasing sedimentation rate. The sedimentary and petrographic facies variations, including but not limited to lithological alternations, in the BCL are interpreted to result from the combined influence of various processes such as bottom currents, bioturbation, early diagenesis, and episodic volcanic input, with some of the above-mentioned processes likely modulated by short-term relative changes in sea level. Results of this study highlight the need for detailed sedimentologic and petrographic studies and consideration of short-term changes in sedimentation rate to fully resolve the causes of the apparent limestone–marl bedding couplets and reliably reconstruct short-term changes in depositional and environmental conditions from the BCL and other similar successions.
","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/jsr.2024.121","usgsCitation":"Zhiyang Li, and Flaum, J.A., 2025, Reevaluating the depositional model of the Cenomanian–Turonian Bridge Creek Limestone Member near Pueblo, Colorado, U.S.A.: Roles of changing sedimentation rate on the formation of limestone–marl bedding couplets: Journal of Sedimentary Research, v. 95, no. 1, p. 186-208, https://doi.org/10.2110/jsr.2024.121.","productDescription":"23 p.","startPage":"186","endPage":"208","ipdsId":"IP-164103","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":483944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Pueblo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.30769287342653,\n 38.43186764103851\n ],\n [\n -105.18611920603225,\n 38.43186764103851\n ],\n [\n -105.18611920603225,\n 38.04895114213508\n ],\n [\n -104.30769287342653,\n 38.04895114213508\n ],\n [\n -104.30769287342653,\n 38.43186764103851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"95","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhiyang Li","contributorId":352824,"corporation":false,"usgs":false,"family":"Zhiyang Li","affiliations":[{"id":84293,"text":"Texas A&M International University","active":true,"usgs":false}],"preferred":false,"id":932135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flaum, Jason A. 0000-0003-1251-1142","orcid":"https://orcid.org/0000-0003-1251-1142","contributorId":300809,"corporation":false,"usgs":true,"family":"Flaum","given":"Jason","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":932136,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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