{"pageNumber":"51","pageRowStart":"1250","pageSize":"25","recordCount":184582,"records":[{"id":70269761,"text":"70269761 - 2025 - Blowing in the wind: Anemochory in blackbrush habitat of South Texas","interactions":[],"lastModifiedDate":"2025-11-20T16:43:14.129544","indexId":"70269761","displayToPublicDate":"2025-07-22T09:30:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Blowing in the wind: Anemochory in blackbrush habitat of South Texas","docAbstract":"<p><span>Wind dispersal has the potential to carry seeds long-distances and could inform the management and restoration of natural vegetation along the U.S.-Mexico Border. Plant species with the potential to disperse seeds in arid landscapes fragmented by border barrier infrastructure include foundational native, invasive, and federally endangered plant species. Wind dispersal traps constructed of cloth were set facing into the prevailing wind direction (SE) to characterize the role of wind in transporting soil particles, pebbles, plant debris, and seeds in blackbrush habitat during maximum events of wind speed (km per hour), and precipitation (cm). Shrubs, native grasses, the invasive&nbsp;</span><i>Pennisetum ciliare</i><span>&nbsp;(buffelgrass), soil particles, and pebbles dispersed in the wind, especially during maximum wind and/or precipitation events. Natural blackbrush areas supported the wind dispersal of twelve native species including grasses and woody shrubs. Sites disturbed by border infrastructure (barrier, roads, waterways) had higher seed numbers of invasive species such as&nbsp;</span><i>P. ciliare</i><span>&nbsp;captured in the wind traps. While modifications in passages through waterways and other structures have been proposed to improve the movement of organisms influenced by the barrier, the restoration of native plant species in damaged areas might further aid in the maintenance of blackbrush ecosystems by reducing invasive plant species dispersal into natural habitats.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11258-025-01527-9","usgsCitation":"Middleton, B., and Lain, E., 2025, Blowing in the wind: Anemochory in blackbrush habitat of South Texas: Plant Ecology, v. 226, p. 1057-1064, https://doi.org/10.1007/s11258-025-01527-9.","productDescription":"8 p.","startPage":"1057","endPage":"1064","ipdsId":"IP-167847","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":493240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Arroyo Morteros, Arroyo Ramirez, Cuellar tract, Lower Rio Grande Valley National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -99.86537923681847,\n              27.90301608157847\n            ],\n            [\n              -99.19865426109092,\n              26.168012208444026\n            ],\n            [\n              -97.2958075042999,\n              25.753100816726878\n            ],\n            [\n              -97.08690291521907,\n              25.9785258529746\n            ],\n            [\n              -98.88941956966367,\n              26.540145638316744\n            ],\n            [\n              -99.47996857108726,\n              27.671219788235106\n            ],\n            [\n              -99.86537923681847,\n              27.90301608157847\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"226","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206684,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":944575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lain, Emily J.","contributorId":358948,"corporation":false,"usgs":false,"family":"Lain","given":"Emily J.","affiliations":[{"id":83764,"text":"Cherokee Nation System Solutions, contracted to the U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":944576,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70269581,"text":"70269581 - 2025 - Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area","interactions":[],"lastModifiedDate":"2025-09-09T14:45:30.640888","indexId":"70269581","displayToPublicDate":"2025-07-22T08:59:45","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":"Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area","docAbstract":"<p><span>Strategies animals use to navigate human-dominated landscapes frequently mimic anti-predator responses employed by prey species. Understanding how large carnivores respond to outdoor recreation is important for conservation, particularly in protected areas with preservation mandates. Visitation to Yellowstone National Park doubled from 1980 to 2015, increasing the need to examine potential changes in behavior of grizzly bears (</span><i>Ursus arctos</i><span>) in relation to human recreation sites (trails, backcountry campsites). We developed integrated step-selection functions to explore how recreation sites influenced the movement rate and selection by male and female grizzly bears. Further, we tested whether time of day (diurnal, crepuscular, nocturnal) and restrictions to human access (i.e., restricted, unrestricted) modified bear responses and then compared behaviors based on proximity to recreation sites. Male grizzly bears used trails to travel during crepuscular and nocturnal hours and exhibited more pronounced behavior in restricted areas compared with unrestricted areas, suggesting recreation in unrestricted areas influenced the behavior of male bears. In contrast, female bears varied their movement rate and selection of trails in restricted areas much more than in unrestricted areas, suggesting females may make security tradeoffs between male bears and people. Both sexes used trails, likely as energetically efficient travel corridors; however, our analyses did not indicate that bears spent time near backcountry campsites. The sex-based differences in selection and movement patterns associated with trails and campsites suggest a single management approach for recreation may not equally benefit all bears. Recreation impacts on wildlife are complex to characterize and predict, but simultaneously modeling movement and selection provides a more comprehensive assessment of strategies animals use to navigate perceived risk.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.70068","usgsCitation":"Loggers, E., Litt, A.R., Haroldson, M., Gunther, K.A., and van Manen, F.T., 2025, Female and male grizzly bears differ in their responses to low-intensity recreation in a protected area: Journal of Wildlife Management, v. 89, no. 7, e70068, 24 p., https://doi.org/10.1002/jwmg.70068.","productDescription":"e70068, 24 p.","ipdsId":"IP-174424","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":493317,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70068","text":"Publisher Index Page"},{"id":492993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.05465697234523,\n              45.04848474160275\n            ],\n            [\n              -111.05465697234523,\n              44.132997929608706\n            ],\n            [\n              -110.00606720612153,\n              44.132997929608706\n            ],\n            [\n              -110.00606720612153,\n              45.04848474160275\n            ],\n            [\n              -111.05465697234523,\n              45.04848474160275\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"89","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Loggers, Elise","contributorId":331713,"corporation":false,"usgs":false,"family":"Loggers","given":"Elise","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":944101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Litt, Andrea R.","contributorId":208358,"corporation":false,"usgs":false,"family":"Litt","given":"Andrea","email":"","middleInitial":"R.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":944102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haroldson, Mark 0000-0002-7457-7676","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":316737,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":944103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":944104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":944105,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70270836,"text":"70270836 - 2025 - Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development","interactions":[],"lastModifiedDate":"2025-11-20T16:58:09.990917","indexId":"70270836","displayToPublicDate":"2025-07-22T07:58:36","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":"Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development","docAbstract":"<p><span>Proper development and inflation of the swim bladder is essential for swimming and foraging behavior in fish. To characterize the effects of the Brazilian oil spill that occurred between 2019 and 2020 to early life stage fish, the expression of genes involved in swim bladder development were targeted, with biochemical assays, morphology, and behavior assessed. The swim bladder was focused on due to recent findings of being a target of polycyclic aromatic hydrocarbons (PAHs)&nbsp;present in oil. Zebrafish (</span><i>Danio rerio</i><span>) were exposed to oil water accommodated fractions at concentrations measured following the spill, 1.12–71.8 total PAHs (μg-ΣPAHt L</span><sup>−1</sup><span>). Larvae exposed to 4.49 and 17.9 μg-ΣPAHt L</span><sup>−1</sup><span>&nbsp;had a downregulation in swim bladder development genes&nbsp;</span><i>hb9</i><span>,&nbsp;</span><i>sox2</i><span>,&nbsp;</span><i>has2</i><span>, and&nbsp;</span><i>elovl1a</i><span>&nbsp;at 48 hr postfertilization (hpf). Downregulation in these genes was associated with a high frequency of uninflated swim bladders at 96 and 168 hpf, with uninflated swim bladders detected in 100% of 96 to 168 hpf larvae exposed to 35.9 and 71.8 μg-ΣPAHt L</span><sup>−1</sup><span>. Superoxide dismutase and catalase levels were inhibited in larvae exposed to 1.12 and 2.24 μg-ΣPAHt L</span><sup>−1</sup><span>, respectively. There was an increase in glutathione-S-transferase and glutathione levels in exposed larvae. Average swimming speed and distance were reduced in larvae exposed to 1.12 μg-ΣPAHt L</span><sup>−1</sup><span>. This suggests that complex mixtures of PAHs from crude oil can inhibit the transcription of genes involved in swim bladder tissue development and proper swim-up behavior, which may have implications for the viability and success of developing larvae, affecting recruitment.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf184","usgsCitation":"Mariz, C.F., de Melo Alves, M.K., Magnuson, J.T., Braga de Castro, I., Silva de Andrade, F.A., Zanardi-Lamardo, E., Dias Medeiros, I., and Carvalho, P.S., 2025, Ecotoxicological effects of crude oil to early life stage Danio rerio: A molecular, morphological and behavioral approach focused on swim bladder development: Environmental Toxicology and Chemistry, v. 44, no. 11, p. 3363-3374, https://doi.org/10.1093/etojnl/vgaf184.","productDescription":"12 p.","startPage":"3363","endPage":"3374","ipdsId":"IP-172025","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":494897,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Mariz, Célio F.","contributorId":360535,"corporation":false,"usgs":false,"family":"Mariz","given":"Célio","middleInitial":"F.","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Melo Alves, Maria Karolaine","contributorId":360536,"corporation":false,"usgs":false,"family":"de Melo Alves","given":"Maria","middleInitial":"Karolaine","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":947191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braga de Castro, Italo","contributorId":360537,"corporation":false,"usgs":false,"family":"Braga de Castro","given":"Italo","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Silva de Andrade, Felix Augusto","contributorId":360538,"corporation":false,"usgs":false,"family":"Silva de Andrade","given":"Felix","middleInitial":"Augusto","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zanardi-Lamardo, Eliete","contributorId":360539,"corporation":false,"usgs":false,"family":"Zanardi-Lamardo","given":"Eliete","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dias Medeiros, Igor","contributorId":360540,"corporation":false,"usgs":false,"family":"Dias Medeiros","given":"Igor","affiliations":[{"id":86035,"text":"Federal University of São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":947195,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carvalho, Paulo S.","contributorId":360541,"corporation":false,"usgs":false,"family":"Carvalho","given":"Paulo","middleInitial":"S.","affiliations":[{"id":86032,"text":"Federal University of Pernambuco, Brazil","active":true,"usgs":false}],"preferred":false,"id":947196,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70269660,"text":"70269660 - 2025 - The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics","interactions":[],"lastModifiedDate":"2025-08-18T15:22:57.469229","indexId":"70269660","displayToPublicDate":"2025-07-22T07:45:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics","docAbstract":"Forest harvesting can lead to mercury (Hg) mobilization from soils to aquatic habitats and promote the transformation of inorganic Hg to highly neurotoxic and bioaccumulative methyl-Hg (MeHg). Multiple past studies reveal broad variation of stream water MeHg and total Hg (THg) concentrations responses to forest harvesting, which has confounded messaging to forest and resource managers. To advance beyond divergent and sometimes contradictory findings, we synthesize information for 23 previously studied catchments in North America and Fennoscandia, and compiled a uniform set of soil, landscape, and harvesting properties to identify forest management, riparian, and hillslope factors that influence responses of stream water MeHg and THg concentrations. From this synthesis, we found catchments with high soil moisture and organic soil layers > 100 cm to be at highest risk for disturbance-induced increases in MeHg formation after harvest, but not necessarily affecting concentrations of MeHg in stream waters. Instead, the combination of MeHg formation in soils along with factors that affect mobilization with runoff to streams most influenced how forest harvest affects MeHg concentrations in stream waters.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5c02787","usgsCitation":"Eklof, K., de Wit, H.A., Eckley, C.S., Eagles-Smith, C., Eggert, S.L., Mackereth, R., Skyllberg, U., Ukonmaanaho, L., Verta, M., Allan, C.J., Emilson, E., Kidd, K.A., Mitchell, C., Munthe, J., Sallantaus, T., Segersten, J., Bravo, A., Kolka, R., McCarter, C., Porvari, P., Ring, E., Sebestyen, S., Sikstrom, U., and Zetterberg, T., 2025, The effects of forest harvesting on total and methylmercury concentrations in surface waters depend on harvest practices and physical site characteristics: Environmental Science and Technology, v. 59, no. 30, p. 15944-15955, https://doi.org/10.1021/acs.est.5c02787.","productDescription":"12 p.","startPage":"15944","endPage":"15955","ipdsId":"IP-174865","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493100,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493299,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5c02787","text":"Publisher Index Page"}],"country":"Canada, Finland, Norway, Sweden, United States","volume":"59","issue":"30","noUsgsAuthors":false,"publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Eklof, Karin","contributorId":358850,"corporation":false,"usgs":false,"family":"Eklof","given":"Karin","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":944306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Wit, Heleen A. 0000-0001-5646-5390","orcid":"https://orcid.org/0000-0001-5646-5390","contributorId":332803,"corporation":false,"usgs":false,"family":"de Wit","given":"Heleen","email":"","middleInitial":"A.","affiliations":[{"id":13695,"text":"Norwegian Institute for Water Research","active":true,"usgs":false}],"preferred":false,"id":944307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eckley, Chris S. 0000-0002-6986-4451","orcid":"https://orcid.org/0000-0002-6986-4451","contributorId":246031,"corporation":false,"usgs":false,"family":"Eckley","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":944308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eggert, Susan L.","contributorId":191489,"corporation":false,"usgs":false,"family":"Eggert","given":"Susan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":944310,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mackereth, Robert W.","contributorId":358852,"corporation":false,"usgs":false,"family":"Mackereth","given":"Robert W.","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":944311,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skyllberg, Ulf","contributorId":358855,"corporation":false,"usgs":false,"family":"Skyllberg","given":"Ulf","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":944312,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ukonmaanaho, Liisa","contributorId":358857,"corporation":false,"usgs":false,"family":"Ukonmaanaho","given":"Liisa","affiliations":[{"id":40380,"text":"Natural Resources Institute Finland","active":true,"usgs":false}],"preferred":false,"id":944313,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Verta, Matti","contributorId":358858,"corporation":false,"usgs":false,"family":"Verta","given":"Matti","affiliations":[{"id":40382,"text":"Finnish Environment Institute","active":true,"usgs":false}],"preferred":false,"id":944314,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Allan, Craig J","contributorId":339868,"corporation":false,"usgs":false,"family":"Allan","given":"Craig","email":"","middleInitial":"J","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":944315,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Emilson, Erik J.S.","contributorId":358862,"corporation":false,"usgs":false,"family":"Emilson","given":"Erik J.S.","affiliations":[{"id":85691,"text":"Natural Resources Canada, Great Lakes Forestry Centre","active":true,"usgs":false}],"preferred":false,"id":944316,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kidd, Karen A.","contributorId":201554,"corporation":false,"usgs":false,"family":"Kidd","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":25502,"text":"McMaster University","active":true,"usgs":false}],"preferred":false,"id":944317,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mitchell, Carl P.J.","contributorId":358865,"corporation":false,"usgs":false,"family":"Mitchell","given":"Carl P.J.","affiliations":[{"id":7044,"text":"University of 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,{"id":70269399,"text":"sir20255044 - 2025 - Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia","interactions":[],"lastModifiedDate":"2026-02-03T14:29:52.898888","indexId":"sir20255044","displayToPublicDate":"2025-07-21T15:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5044","displayTitle":"Factors Affecting the Distribution of Water-Bearing Fractures in the Bedrock Aquifers of West Virginia","title":"Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia","docAbstract":"<p>Bedrock aquifers cover 23,601 square miles within the State of West Virginia and comprise 97.4 percent of the surficial area within the State; the remaining 2.6 percent (621 square miles) consists of alluvial sand-and-gravel and glacial outwash aquifers bordering the State’s major rivers. While West Virginia’s alluvial aquifers have been studied extensively, bedrock aquifers have only been characterized for studies completed in a few areas in Jefferson, McDowell, and Monroe Counties. Bedrock aquifers are water supplies for public supply, agriculture, industry, and residential homeowner use. In this study, the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management, provides a statewide assessment of the occurrence and distribution of fractures within bedrock aquifers of the State and the various topographic, physiographic, and lithologic influences controlling the occurrence and distribution of bedrock fractures. The results of this study provide an increased understanding of the distribution of fractures in bedrock aquifers in West Virginia and help to verify trends that have been suspected for many years but were never well documented or verified by data.</p><p>The results confirmed that the density of fractures and those that were determined to be water bearing decrease significantly with depth. A statistically significant difference in the density of fractures was observed at a depth of 215 feet for wells in the Appalachian Plateaus Physiographic Province’s and in the Valley and Ridge Physiographic Province’s aquifers; a higher density of fractures and water-bearing fractures were above a depth of 215 feet than below that depth. This is an important consideration when drilling wells for residential, commercial, industrial, or agricultural water supply.</p><p>Abandoned underground coal mines are commonly believed to form large pools of water in the interconnected mine entries in abandoned room and pillar coal mines. Such pools of water can and do exist in abandoned underground coal mines, but many mines lack open entries and are held up by overburden strata and pillars that can collapse and form aquifers comprised of vast interconnected rubble zones (gob), especially in older mines.</p><p>Data assessed for this study showed that shale-corrected values of effective porosity for limestone aquifers in West Virginia had a median value of 2 percent and an average value of 4 percent and generally are mineralized with low effective porosity. Argillaceous or sandy limestone has a median shale-corrected porosity of 4 percent and an average shale-corrected porosity of 5 percent. The median and average shale-corrected porosity of sandstone aquifers was estimated to be 14 percent, but the median shale-corrected porosity for argillaceous or calcareous sandstone was 5 percent and the average shale-corrected porosity for argillaceous or calcareous sandstone was 6 percent. Even though shale has a relatively high total sonic porosity compared to other lithologies, shale and siltstone had relatively low shale-corrected porosity, ranging from 0 to 2 percent.</p><p>Well yields were previously documented to be highest in valley settings, lowest on hilltops, and intermediate on hillsides. Transmissivity data provided by this study confirm this general pattern within the Appalachian Plateaus Province; however, the Valley and Ridge Province does not follow this pattern. While still lowest on hilltop settings, the highest well yields were in hillside settings. The trend for the Valley and Ridge Province was likely skewed because of 9 high-yield wells specifically targeting deeper thin limestone units, such as the Tonoloway and Helderberg Limestones, at depths with transmissivity in excess of 2,000 feet squared per day in Mineral County, West Virginia, or targeting karst aquifers in Berkeley, Jefferson, or Greenbrier Counties, West Virginia.</p><p>Finally, water-bearing fractures have been hypothesized to comprise a small number of all fractures within a typical bedrock well in West Virginia. Data collected for this study support this theory. A total of 3,403 fractures were identified during this study; 3,151 (92.6 percent) of those fractures are low-transmissive, and only 252 (7.4 percent) fractures are water-bearing. Even though a well may contain many fractures, less than 8 percent are considered water-bearing fractures.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255044","isbn":"978-1-4113-4608-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection Division of Water and Waste Management","usgsCitation":"Kozar, M.D., McAdoo, M.A., Austin, S.H., and Wright, C.A., 2025, Factors affecting the distribution of water-bearing fractures in the bedrock aquifers of West Virginia: U.S. Geological Survey Scientific Investigations Report 2025–5044, 66 p., https://doi.org/10.3133/sir20255044.","productDescription":"x, 66 p.","numberOfPages":"66","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-167322","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":499045,"rank":7,"type":{"id":36,"text":"NGMDB Index 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Virginia\",\"nation\":\"USA  \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/virginia-and-west-virginia-water-science-center\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Factors Affecting Distribution of Water-Bearing Fractures</li><li>Selected Areas of Specific Investigation</li><li>Conclusion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-07-21","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":943660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAdoo, Mitchell A. 0000-0002-3895-0816 mmcadoo@usgs.gov","orcid":"https://orcid.org/0000-0002-3895-0816","contributorId":200287,"corporation":false,"usgs":true,"family":"McAdoo","given":"Mitchell","email":"mmcadoo@usgs.gov","middleInitial":"A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":943661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":943662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, Carson A. 0009-0005-7567-5453","orcid":"https://orcid.org/0009-0005-7567-5453","contributorId":352325,"corporation":false,"usgs":true,"family":"Wright","given":"Carson A.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":943663,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70270742,"text":"70270742 - 2025 - A flexible conservation and connectivity tool to inform stream conservation prioritization","interactions":[],"lastModifiedDate":"2026-01-05T16:37:21.451935","indexId":"70270742","displayToPublicDate":"2025-07-21T10:13:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"A flexible conservation and connectivity tool to inform stream conservation prioritization","docAbstract":"<p><span>Healthy stream networks rely on diverse fish assemblages and the mobility of fish between habitats to maintain ecosystem structure and function. Anthropogenic structures that impede fish movement (e.g., roads, dams) disrupt life cycles of migratory fishes and isolate fish populations making them more sensitive to environmental stressors. Growing interest in barrier removal is driven by the recognition that restoring fish passage improves ecosystem health and resilience at multiple trophic levels, but identifying which streams should be reconnected and which barriers to remove remains an unresolved issue. Using the state of Missouri (USA) stream network, we developed an interactive decision support tool designed to help natural resource managers identify a shortlist of stream reaches to prioritize for reconnection, barrier removal, and habitat restoration. Our aquatic connectivity decision support tool, which we call AquaConn, is aimed at managers seeking to improve connectivity within and between existing conservation areas, particularly in wadeable streams. AquaConn provides a flexible platform that allows managers to consider entire assemblages of fish or individual species across local or more regional spatial scales. While AquaConn (</span><a class=\"link link-uri openInAnotherWindow\" rel=\"noopener\" href=\"https://bit.ly/4kQgXK8\" target=\"_blank\" data-google-interstitial=\"false\" data-mce-href=\"https://bit.ly/4kQgXK8\">https://bit.ly/4kQgXK8</a><span>) was built for the state of Missouri, our approach and framework can be replicated in any geographical region that has adequate fish assemblage data.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1093/fshmag/vuaf064","usgsCitation":"Winikoff, S.G., Paukert, C., Sievert, N., and Rogosch, J.S., 2025, A flexible conservation and connectivity tool to inform stream conservation prioritization: Fisheries, v. 50, no. 12, p. 527-537, https://doi.org/10.1093/fshmag/vuaf064.","productDescription":"11 p.","startPage":"527","endPage":"537","ipdsId":"IP-169145","costCenters":[{"id":198,"text":"Coop Res Unit 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,{"id":70274005,"text":"70274005 - 2025 - Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","interactions":[],"lastModifiedDate":"2026-02-20T16:11:51.850785","indexId":"70274005","displayToPublicDate":"2025-07-21T10:05:49","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":"Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species","docAbstract":"<p><span>Knowledge of animal-movement patterns is a crucial component in identifying areas with high potential for human–wildlife conflict and in prioritizing associated management actions. Electrical energy infrastructure is a major source of mortality for animals worldwide, with millions of birds colliding with or being electrocuted by power lines and power-pole infrastructure each year. Movement, habitat use, and the spatial distribution of electrocution risk can vary with age, but studies of younger age classes are often hampered because these groups are difficult to observe and lack well-defined home ranges. To identify movement patterns and high-use areas of bald eagles in Arizona, USA, we analyzed global positioning system (GPS) telemetry data collected from 13 immature bald eagles (</span><i>Haliaeetus leucocephalus</i><span>) across Arizona between 2017 and 2023. We built multi-scale, integrated step-selection functions that evaluated eagle responses to a suite of environmental covariates. We then used these models to simulate eagle movement and predict habitat use within and surrounding Maricopa County, which contains both the Phoenix Metropolitan Area and the plurality of bald eagle breeding areas in Arizona. We provide a use case for how these simulated movements could be used by resource managers to identify high-risk areas for electrocution. Eagles avoided urban areas and selected steeper slopes, more pronounced ridges, and areas with greater water and wetland land cover. Predicted habitat use by bald eagles was greatest near waterbodies and along ridges and steep slopes, and indicated where power infrastructure may pose greater electrocution risk. We show how integrated step-selection analyses and movement path simulation may be used for subadult animals lacking stable home ranges to predict high-use areas and identify locations with greater potential for negative human–wildlife interactions.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70061","usgsCitation":"Cappello, C. ., Jacobson, K.V., Driscoll, J.T., McCarty, K.M., Bauder, J.M., 2025, Using integrated step-selection analyses to map high-risk electrocution areas for a highly mobile species: Journal of Wildlife Management, v. 89, no. 7, e70061, 19 p., https://doi.org/10.1002/jwmg.70061.","productDescription":"e70061, 19 p.","ipdsId":"IP-178672","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.5,\n              34.1\n            ],\n            [\n              -113.5,\n              32.5\n            ],\n            [\n              -111,\n              32.5\n            ],\n            [\n              -111,\n              34.1\n            ],\n            [\n              -113.5,\n              34.1\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"89","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Cappello, Caroline   D.","contributorId":366625,"corporation":false,"usgs":false,"family":"Cappello","given":"Caroline","middleInitial":"  D.","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":956103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobson, Kenneth V.","contributorId":366626,"corporation":false,"usgs":false,"family":"Jacobson","given":"Kenneth","middleInitial":"V.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, James T.","contributorId":366627,"corporation":false,"usgs":false,"family":"Driscoll","given":"James","middleInitial":"T.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Kyle M.","contributorId":366629,"corporation":false,"usgs":false,"family":"McCarty","given":"Kyle","middleInitial":"M.","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273993,"text":"70273993 - 2025 - Shared leadership can promote success in collaborative research networks in ecology","interactions":[],"lastModifiedDate":"2026-02-24T14:55:18.949074","indexId":"70273993","displayToPublicDate":"2025-07-21T09:03:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Shared leadership can promote success in collaborative research networks in ecology","docAbstract":"<p>1. While collaborative science is becoming the norm in ecology, many ecologists participating in collaborations are less aware of the body of research that studies the processes by which collaborative teams organize and communicate.</p><p>2. Here, we discuss how we successfully used a shared leadership model in the Dry Rivers Research Coordination Network. We discuss how this model promote dour success in different stages of the project, using the Tuckman model of team development: forming, storming, norming, performing and adjourning.</p><p>3. Shared leadership in the forming phase helped us recruit a diverse membership from different scientific disciplines. In the storming and norming phases, shared leadership was especially useful in ensuring that all voices were heard in establishing group norms that promoted adhesion among and investment by RCN members. Shared leadership in the performing phase was crucial in providing opportunities for early career members to lead projects, and in the adjourning phase we reflected upon our entire collaboration to identify that shared leadership was crucial to our success, generating the thesis for this commentary.</p><p>4. It is our hope that others may find this discussion of our experience in implementing a shared leadership model useful in developing their own fruitful collaborations.</p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.70109","usgsCitation":"Allen, D.C., Burgin, A.J., Seybold, E.C., Dodds, W.K., Busch, M.H., Bergstrom, A., Krabbenhoft, C.A., Boersma, K.S., Stegen, J.C., Olden, J.D., Atkinson, C.L., Jones, C.N., Datry, T., Godsey, S.E., Shogren, A.J., Walters, A.W., Plont, S., Walker, R.H., Shanafield, M., Mims, M.C., Price, A.N., Smith, C.R., You, Y., Bogan, M.T., Burrows, R.M., Messager, M.L., Stubbington, R., Zimmer, M.A., 2025, Shared leadership can promote success in collaborative research networks in ecology: Functional Ecology, 9 p., https://doi.org/10.1111/1365-2435.70109.","productDescription":"9 p.","ipdsId":"IP-176946","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500600,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.70109","text":"Publisher Index Page"},{"id":500414,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Daniel C. 0000-0002-0451-0564","orcid":"https://orcid.org/0000-0002-0451-0564","contributorId":225169,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","middleInitial":"C.","affiliations":[{"id":41064,"text":"Department of Biology, University of Oklahoma, Norman OK, 73019","active":true,"usgs":false}],"preferred":false,"id":956032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgin, Amy 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Tech","active":true,"usgs":false}],"preferred":false,"id":956051,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Price, Adam N.","contributorId":366565,"corporation":false,"usgs":false,"family":"Price","given":"Adam","middleInitial":"N.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":956052,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Smith, Chelsea R.","contributorId":366567,"corporation":false,"usgs":false,"family":"Smith","given":"Chelsea","middleInitial":"R.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":956053,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"You, Yaqi","contributorId":366570,"corporation":false,"usgs":false,"family":"You","given":"Yaqi","affiliations":[{"id":87494,"text":"The State University of New York College of Environmental Science and 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,{"id":70269443,"text":"70269443 - 2025 - Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA","interactions":[],"lastModifiedDate":"2025-07-23T14:32:38.22027","indexId":"70269443","displayToPublicDate":"2025-07-20T09:28:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA","docAbstract":"<p><span>Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with known bioaccumulative and toxic effects in aquatic ecosystems. This study assessed site-specific differences in PFAS contamination in fish from Ashumet Pond, Sudbury River, and Great Herring Pond (reference site) in Massachusetts. Fish from Ashumet Pond exhibited the highest PFAS concentrations, particularly perfluorooctane sulfonate (PFOS), which exceeded levels in plasma almost 650 times those at the reference site. Principal component analysis identified distinct PFAS profiles at each site, reflecting localized contamination sources. Temporal analysis at Ashumet Pond revealed a substantial increase in plasma PFOS and perfluorodecanoic acid (PFDA) from 2020 to 2022. Tissue distribution analyses showed the highest PFAS concentrations in plasma, followed by liver and muscle, consistent with PFAS binding affinity for blood proteins. Species-specific differences in PFAS bioaccumulation were observed, with largemouth bass (</span><i>Micropterus nigricans</i><span>) exhibiting higher body burdens than banded killifish (</span><i>Diaphanus fundulus</i><span>), likely due to trophic position and dietary exposure. Histopathological assessments and gene transcript analyses revealed associations between PFAS exposure and inflammatory responses, oxidative stress, endocrine disruption, and immune-related pathways, with the most pronounced molecular effects observed at the downstream site of the Sudbury River. This study underscores the importance of understanding site-specific contamination sources, exposure pathways, and biological effects of PFAS in fish. These findings would benefit from additional research on sediment contamination, temporal analyses at each site, trophic transfer, and transcriptomic analyses across multiple organs to further elucidate PFAS toxicity mechanisms and guide remediation efforts.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquatox.2025.107499","usgsCitation":"Walsh, H.L., Blazer, V., Lord, E., Hurley, S.T., and LeBlanc, D.R., 2025, Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA: Aquatic Toxicology, v. 287, 107499, 17 p., https://doi.org/10.1016/j.aquatox.2025.107499.","productDescription":"107499, 17 p.","ipdsId":"IP-179883","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":497990,"rank":0,"type":{"id":40,"text":"Open Access 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Emma","contributorId":358438,"corporation":false,"usgs":false,"family":"Lord","given":"Emma","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":943757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurley, Stephen T.","contributorId":138980,"corporation":false,"usgs":false,"family":"Hurley","given":"Stephen","email":"","middleInitial":"T.","affiliations":[{"id":12605,"text":"Mass Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":943758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943759,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70269620,"text":"70269620 - 2025 - Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA","interactions":[],"lastModifiedDate":"2025-07-28T14:17:21.049353","indexId":"70269620","displayToPublicDate":"2025-07-20T09:10:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA","docAbstract":"<p><span>The ecological importance of springs in semiarid regions is far greater than their small size and sparse distribution, yet little is known about the hydrologic functioning of these systems. During 2016–22, 261 springs were visited in the volcanic terrane of eastern Oregon and northern Nevada. When conditions were suitable, measurements of discharge, water temperature, and specific conductance were made, and samples for the analysis of carbon-14, tritium, and water stable isotopes (WSI) were collected. A subset of 60 springs was revisited during different seasons in the same year and during the dry season in multiple years to evaluate variability in discharge, chemistry, and groundwater age. Specific conductance and WSI varied considerably among springs across the study area but were unexpectedly stable across seasons and years at individual springs. Seasonal and interannual variability in spring discharge was related to the residence time of the discharging groundwater. Springs discharging older groundwater (10</span><sup>3</sup><span>–10</span><sup>4</sup><span>&nbsp;years) had significantly less variability in their discharge compared to springs discharging younger groundwater (10</span><sup>0</sup><span>–10</span><sup>1</sup><span>&nbsp;years). Variability among springs discharging younger groundwater included cessation of late-summer discharge at 18&nbsp;% of the repeat-visit springs. A logistic regression model predicted the age of discharging spring water with 89&nbsp;% accuracy using only the spring latitude, longitude, elevation, and δ</span><sup>2</sup><span>H value. This study framework provides a simple, inexpensive, and robust method to provisionally assess the hydrologic behavior of springs having little or no prior information in understudied, semiarid regions across the globe.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133922","usgsCitation":"Johnson, H.M., 2025, Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA: Journal of Hydrology, v. 662, no. Part A, 133922, 13 p., https://doi.org/10.1016/j.jhydrol.2025.133922.","productDescription":"133922, 13 p.","ipdsId":"IP-123085","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":493312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133922","text":"Publisher Index Page"},{"id":492994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.31311680484953,\n              41.99539074875983\n            ],\n            [\n              -120.0068581722988,\n              41.99391273807197\n            ],\n            [\n              -119.90145747408332,\n              41.992434693061426\n            ],\n            [\n              -119.84179670150823,\n              41.66048803137227\n            ],\n            [\n              -118.9246520186846,\n              41.65959449142923\n            ],\n            [\n              -118.93301194332504,\n              41.98445357532694\n            ],\n            [\n              -117.02491929749873,\n              42.016929659002585\n            ],\n            [\n              -117.01355889504242,\n              43.86708893750037\n            ],\n            [\n              -116.91131527293696,\n              44.17343283492443\n            ],\n            [\n              -117.20668573679785,\n              44.30365776197061\n            ],\n            [\n              -117.26349474591721,\n              44.58751884415352\n            ],\n            [\n              -117.18671855238352,\n              44.79442609102742\n            ],\n            [\n              -117.77146876695777,\n              44.926186190521406\n            ],\n            [\n              -117.91090405154984,\n              44.91839177439985\n            ],\n            [\n              -117.97144831985975,\n              44.63186629043838\n            ],\n            [\n              -118.6664325411721,\n              44.37656025661704\n            ],\n            [\n              -119.868869617017,\n              44.396170474914186\n            ],\n            [\n              -121.12677954373844,\n              44.318586844969104\n            ],\n            [\n              -121.51042244069035,\n              42.944368334976076\n            ],\n            [\n              -121.28368996303429,\n              42.40400912273424\n            ],\n            [\n              -120.73802661060382,\n              42.42707264631977\n            ],\n            [\n              -120.26821317970226,\n              41.99741467441126\n            ],\n            [\n              -120.31311680484953,\n              41.99539074875983\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"662","issue":"Part A","noUsgsAuthors":false,"publicationDate":"2025-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Henry M. 0000-0002-7571-4994 hjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":869,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"hjohnson@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944189,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70269455,"text":"70269455 - 2025 - A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","interactions":[],"lastModifiedDate":"2025-07-23T14:18:18.596644","indexId":"70269455","displayToPublicDate":"2025-07-19T09:12:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","docAbstract":"<p><span>Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub-watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5-m stream sub-reach across 426 sub-watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub-watersheds that contained training data and decreased to 0.67 for sub-watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040478","usgsCitation":"Burnett, J., Jaeger, K.L., Johnson, S.L., Wondzell, S., Dunham, J., Barker, M., Heaston, E.D., Chelgren, N., Wing, M., Staab, B., and Brown, M., 2025, A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation: Water Resources Research, v. 61, no. 7, e2025WR040478, 29 p., https://doi.org/10.1029/2025WR040478.","productDescription":"e2025WR040478, 29 p.","ipdsId":"IP-166720","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040478","text":"Publisher Index Page"},{"id":492763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Coast Range, Cascades, Klamath Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.57426256802401,\n              42.38410052088969\n            ],\n            [\n              -121.21373758117394,\n              45.28963738462886\n            ],\n            [\n              -121.54860532807825,\n              45.699012143249206\n            ],\n            [\n              -122.42689354437806,\n              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   }\n  ]\n}","volume":"61","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Burnett, Jonathan D.","contributorId":358463,"corporation":false,"usgs":false,"family":"Burnett","given":"Jonathan D.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Sherri L 0000-0002-4223-3465","orcid":"https://orcid.org/0000-0002-4223-3465","contributorId":192210,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":943797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wondzell, Steven M. 0000-0002-5182-5796","orcid":"https://orcid.org/0000-0002-5182-5796","contributorId":337143,"corporation":false,"usgs":false,"family":"Wondzell","given":"Steven M.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":943798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barker, Matthew Irwin 0000-0002-5286-4930","orcid":"https://orcid.org/0000-0002-5286-4930","contributorId":358465,"corporation":false,"usgs":true,"family":"Barker","given":"Matthew Irwin","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaston, Emily Dawn 0000-0002-3949-391X","orcid":"https://orcid.org/0000-0002-3949-391X","contributorId":290618,"corporation":false,"usgs":true,"family":"Heaston","given":"Emily","email":"","middleInitial":"Dawn","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":943802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wing, Michael G.","contributorId":358467,"corporation":false,"usgs":false,"family":"Wing","given":"Michael G.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943803,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Staab, Brian","contributorId":358469,"corporation":false,"usgs":false,"family":"Staab","given":"Brian","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943804,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brown, Michael E.","contributorId":358471,"corporation":false,"usgs":false,"family":"Brown","given":"Michael E.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":943805,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70268790,"text":"sir20255054 - 2025 - Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2026-02-03T14:29:12.653472","indexId":"sir20255054","displayToPublicDate":"2025-07-18T13:39:29","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5054","displayTitle":"Hydrogeologic Framework and Conceptual Model of the Red River Alluvial Aquifer East of Lake Texoma, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","docAbstract":"<p>The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. At present (2025), the Oklahoma Water Resources Board has not established a maximum annual yield for the Red River alluvial aquifer east of Lake Texoma. To support the evaluation and determination of a maximum annual yield, a hydrogeologic framework and conceptual groundwater-flow model were developed to assess groundwater availability in the Red River alluvial aquifer east of Lake Texoma.</p><p>The scope of this hydrologic investigation is the alluvium and terrace containing the Red River alluvial aquifer in Oklahoma between Lake Texoma, the Texas State line, and the Arkansas State line, an extent referred to in this report as “the eastern part of the Red River alluvial aquifer.” Parts of the alluvium and terrace extent in Arkansas and Texas are included in some analyses to address hydrologic influences from outside the aquifer’s boundaries in Oklahoma.</p><p>The eastern part of the Red River alluvial aquifer in southeastern Oklahoma consists of approximately 401,280&nbsp;acres of Quaternary alluvium and terrace deposits associated with the Red River and its major tributaries. Mean annual recharge to the aquifer for the 1980–2022 study period was estimated to be 8.62 inches per year, or 17.98&nbsp;percent of the mean annual precipitation over the same period (47.94&nbsp;inches). This mean annual recharge rate is equivalent to an inflow of approximately 288,250 acre-feet per year for the eastern part of the Red River alluvial aquifer. Recharge estimated using the Soil-Water-Balance code accounts for 98.7 percent of the conceptual-model inflows to the eastern part of the Red River alluvial aquifer. Saturated-zone evapotranspiration accounts for 11.9 percent and net streambed seepage accounts for 87.4 percent of the outflows in the conceptual model.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255054","issn":"2328-0328","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Codner, C., Gammill, N.C., Dale, I.A., Morris, A.S., Kirby, E.A., Graves, G.M., Fetkovich, E.J., Wagner, D.L., Sanford, J.E., and Baciocco, C.A., 2025, Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022: U.S. Geological Survey Scientific Investigations Report 2025–5054, 46 p., https://doi.org/10.3133/sir20255054.","productDescription":"Report: x, 46 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-149879","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":494153,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118693.htm","linkFileType":{"id":5,"text":"html"}},{"id":491682,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1KUH5DS","text":"USGS Data Release","linkHelpText":"- Soil-Water-Balance model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022"},{"id":491681,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5054/sir20255054.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5054 XML"},{"id":491680,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255054/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5054 HTML"},{"id":491677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5054/coverthb.jpg"},{"id":491678,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5054/images"},{"id":491679,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5054/sir20255054.pdf","size":"19.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5054"}],"country":"United States","state":"Arkansas, Oklahoma, Texas","otherGeospatial":"Red River alluvial aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.6,\n              34.25\n            ],\n            [\n              -96.6,\n              33.45\n            ],\n            [\n              -94,\n              33.45\n            ],\n            [\n              -94,\n              34.25\n            ],\n            [\n              -96.6,\n              34.25\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/ot-water\" href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane<br>Austin, TX 78754–4501<br></p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-olk-copy-source=\"MailCompose\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology of the Eastern Part of the Red River Alluvial Aquifer</li><li>Hydrogeologic Framework</li><li>Conceptual Groundwater-Flow Model and Water Budget</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-07-18","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Codner, Chloe 0009-0009-6577-8706","orcid":"https://orcid.org/0009-0009-6577-8706","contributorId":352321,"corporation":false,"usgs":true,"family":"Codner","given":"Chloe","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gammill, Nicole C. 0000-0003-3037-2668","orcid":"https://orcid.org/0000-0003-3037-2668","contributorId":328664,"corporation":false,"usgs":false,"family":"Gammill","given":"Nicole C.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":941983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dale, Isaac A. 0000-0003-0844-0193","orcid":"https://orcid.org/0000-0003-0844-0193","contributorId":352322,"corporation":false,"usgs":true,"family":"Dale","given":"Isaac A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morris, Amy S. 0000-0002-9847-5607","orcid":"https://orcid.org/0000-0002-9847-5607","contributorId":352415,"corporation":false,"usgs":true,"family":"Morris","given":"Amy S.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirby, Ethan A. 0000-0001-7521-5477","orcid":"https://orcid.org/0000-0001-7521-5477","contributorId":352416,"corporation":false,"usgs":true,"family":"Kirby","given":"Ethan A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graves, Grant M. 0000-0002-4010-3253 ggraves@usgs.gov","orcid":"https://orcid.org/0000-0002-4010-3253","contributorId":177760,"corporation":false,"usgs":true,"family":"Graves","given":"Grant","email":"ggraves@usgs.gov","middleInitial":"M.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fetkovich, Evin J. 0000-0002-8899-8543","orcid":"https://orcid.org/0000-0002-8899-8543","contributorId":328666,"corporation":false,"usgs":true,"family":"Fetkovich","given":"Evin","email":"","middleInitial":"J.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941988,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagner, Derrick L. 0000-0002-9291-7785","orcid":"https://orcid.org/0000-0002-9291-7785","contributorId":345145,"corporation":false,"usgs":false,"family":"Wagner","given":"Derrick","email":"","middleInitial":"L.","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":true,"id":941989,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanford, Jon E.","contributorId":177763,"corporation":false,"usgs":false,"family":"Sanford","given":"Jon","email":"","middleInitial":"E.","affiliations":[{"id":18135,"text":"Oklahoma Water Resources Board","active":true,"usgs":false}],"preferred":false,"id":941990,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Baciocco, Colin A. 0000-0002-9548-9077","orcid":"https://orcid.org/0000-0002-9548-9077","contributorId":352323,"corporation":false,"usgs":true,"family":"Baciocco","given":"Colin A.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941991,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70271168,"text":"70271168 - 2025 - Long-term dynamics of earthquake swarms in the Yellowstone caldera","interactions":[],"lastModifiedDate":"2025-09-02T15:35:23.98053","indexId":"70271168","displayToPublicDate":"2025-07-18T09:51:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Long-term dynamics of earthquake swarms in the Yellowstone caldera","docAbstract":"<p><span>The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adv6484","usgsCitation":"Florez, M., Li, B.Q., Shelly, D.R., Angulo, M., and Sanabria-Gomez, J., 2025, Long-term dynamics of earthquake swarms in the Yellowstone caldera: Science Advances, v. 11, no. 29, eadv6484, 10 p., https://doi.org/10.1126/sciadv.adv6484.","productDescription":"eadv6484, 10 p.","ipdsId":"IP-175431","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":495178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adv6484","text":"Publisher Index Page"},{"id":495121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone Caldera","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.2,\n              44.85\n            ],\n            [\n              -111.2,\n              44.1\n            ],\n            [\n              -110.2,\n              44.1\n            ],\n            [\n              -110.2,\n              44.85\n            ],\n            [\n              -111.2,\n              44.85\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","issue":"29","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Florez, Manuel","contributorId":360774,"corporation":false,"usgs":false,"family":"Florez","given":"Manuel","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Bing Q.","contributorId":360823,"corporation":false,"usgs":false,"family":"Li","given":"Bing","middleInitial":"Q.","affiliations":[],"preferred":false,"id":947633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":947634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angulo, Mia","contributorId":360775,"corporation":false,"usgs":false,"family":"Angulo","given":"Mia","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanabria-Gomez, Jose","contributorId":360776,"corporation":false,"usgs":false,"family":"Sanabria-Gomez","given":"Jose","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70269434,"text":"70269434 - 2025 - Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","interactions":[],"lastModifiedDate":"2025-08-18T15:15:37.43118","indexId":"70269434","displayToPublicDate":"2025-07-18T09:35:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","docAbstract":"<div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">The management of invasive Silver Carp<span>&nbsp;</span><i>Hypophthalmichthys molitrix</i><span>&nbsp;</span>in the Tennessee River basin focuses on removal, and there is interest in extending removal efforts to the tailwater environments of high-head locks and dams along the Tennessee River, such as Kentucky Dam. We used acoustic telemetry data from Silver Carp to understand important ecological associations underlying their residence in the Kentucky Dam tailwater, measured by daily fish counts and mean residence time.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">We used time-series-informed regression models, variance partitioning, and cross-correlation function analysis to associate six predictors, including lock and dam operations (total, spill gate, and turbine discharge and number of lockages), hydrology (tailwater elevation), and water temperature, with two measures of Silver Carp residency (daily counts and mean residence time).</p></div><div class=\" sec\"><div class=\"title\">Results</div><p class=\"chapter-para\">We found that spill-induced hydrology (total discharge + spill discharge + tailwater elevation) was negatively associated with daily counts but not with residence time, whereas temperature was positively associated with counts and negatively associated with residence times. Variance partitioning indicated that nearly all the variance in counts and residence times was jointly explained by temporal effects, lock and dam operations (discharge, tailwater elevation, and lockages), and temperature. The cross-correlations indicated that the counts were lagged by all predictors, sometimes up to 5 d, whereas residence times were lagged by both total and spill discharge and number of lockages.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">We found that discharge and water temperature were principally associated with residency of Silver Carp in the Kentucky Dam tailwater. However, these associations were entirely temporally constrained, which can affect how strongly and how quickly Silver Carp respond to changing environmental conditions across different time scales. Managers can leverage these associations to plan removal periods where daily tailwater conditions/dam operations are favorable to invasive carp residence (e.g., &gt;10°C and &lt;2,500 m<sup>3</sup>/s) and adjust fishing effort to optimize removal rates in response to changing conditions.</p></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1093/najfmt/vqaf043","usgsCitation":"Budnick, W., Mosel, K., Tompkins, J., Knights, B., Vallazza, J.M., Brey, M.K., and Fritts, A.K., 2025, Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam: North American Journal of Fisheries Management, v. 45, no. 4, p. 603-615, https://doi.org/10.1093/najfmt/vqaf043.","productDescription":"13 p.","startPage":"603","endPage":"615","ipdsId":"IP-170612","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":492729,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493788,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/najfmt/vqaf043","text":"Publisher Index Page"}],"country":"United States","otherGeospatial":"Kentucky Lock and Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.28591202257577,\n              37.020643272966964\n            ],\n            [\n              -88.28591202257577,\n              37.00847830627373\n            ],\n            [\n              -88.25449320818063,\n              37.00847830627373\n            ],\n            [\n              -88.25449320818063,\n              37.020643272966964\n            ],\n            [\n              -88.28591202257577,\n              37.020643272966964\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Budnick, William R 0000-0001-9288-6782","orcid":"https://orcid.org/0000-0001-9288-6782","contributorId":355213,"corporation":false,"usgs":false,"family":"Budnick","given":"William R","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":943737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosel, Kyle 0000-0002-9885-6960","orcid":"https://orcid.org/0000-0002-9885-6960","contributorId":317887,"corporation":false,"usgs":true,"family":"Mosel","given":"Kyle","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tompkins, Joshua","contributorId":317888,"corporation":false,"usgs":false,"family":"Tompkins","given":"Joshua","email":"","affiliations":[{"id":53972,"text":"Kentucky Department of Fish and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":943739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent 0000-0001-8526-8468","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":304124,"corporation":false,"usgs":false,"family":"Knights","given":"Brent","affiliations":[{"id":65975,"text":"UMESC Retired","active":true,"usgs":false}],"preferred":false,"id":943740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943741,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943742,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943743,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70269462,"text":"70269462 - 2025 - Perfluorodecanesulfonate (PFDS) induces innate immune toxicity through the NF-κB pathway in early life stage zebrafish","interactions":[],"lastModifiedDate":"2025-07-23T14:21:55.644849","indexId":"70269462","displayToPublicDate":"2025-07-18T09:18:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Perfluorodecanesulfonate (PFDS) induces innate immune toxicity through the NF-κB pathway in early life stage zebrafish","docAbstract":"<p><span>Perfluorodecanesulfonate (PFDS), a long-chain polyfluoroalkyl substance (PFAS), is widely detected in aquatic environments and increasingly recognized for its environmental persistence and bioaccumulative potential; however, its immunotoxicity remains poorly understood in aquatic biota. In this study, early life stage zebrafish (</span><i>Danio rerio</i><span>) were exposed to environmentally relevant concentrations of PFDS and PFOS for 120&nbsp;h to better characterize the adverse effects of PFDS on aquatic organisms. Additionally, the toxicological differences between PFDS and PFOS at the same exposure concentrations were compared, as PFDS is a known substitute for PFOS. PFDS bioaccumulated in zebrafish larvae at environmentally relevant concentrations, which disrupted immune function by altering the number of macrophages and neutrophils, inducing oxidative stress, and dysregulating immune markers such as interleukins and immunoglobulins. Mechanistically, PFDS activated the nuclear factor kappa B (NF-κB) signaling pathway, driving pro-inflammatory cytokine expression and immune dysfunction. Furthermore, the use of a NF-κB morpholino knockdown confirmed the role of the NF-κB pathway in mediating PFDS-induced immunotoxicity. These findings provide the first comprehensive evidence of PFDS-induced immunotoxicity being mediated through NF-κB activation, offering novel insights into the ecological risks of long-chain perfluorosulfonic acids. Notably, PFDS exhibited a stronger immunotoxic response relative to PFOS, indicating that its adverse effects may be more severe. Overall, these findings provide valuable insights for the ecological risk assessment of PFDS and the toxic potential that unregulated PFAS can have to aquatic systems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2025.109688","usgsCitation":"Zhou, C., Cheng, W., Xuan, R., Kang, X., Wang, J., Magnuson, J.T., Li, J., Fang, D., and Qiu, W., 2025, Perfluorodecanesulfonate (PFDS) induces innate immune toxicity through the NF-κB pathway in early life stage zebrafish: Environment International, v. 202, 109688, 11 p., https://doi.org/10.1016/j.envint.2025.109688.","productDescription":"109688, 11 p.","ipdsId":"IP-177554","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":492881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envint.2025.109688","text":"Publisher Index Page"},{"id":492764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"202","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Chengwei","contributorId":358479,"corporation":false,"usgs":false,"family":"Zhou","given":"Chengwei","affiliations":[{"id":85627,"text":"The First Affiliated Hospital of Ningbo University, China","active":true,"usgs":false}],"preferred":false,"id":943817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheng, Wei","contributorId":251787,"corporation":false,"usgs":false,"family":"Cheng","given":"Wei","email":"","affiliations":[{"id":50399,"text":"JISAO, NOAA","active":true,"usgs":false}],"preferred":false,"id":943818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xuan, Rongrong","contributorId":329834,"corporation":false,"usgs":false,"family":"Xuan","given":"Rongrong","email":"","affiliations":[{"id":78725,"text":"Ningbo University","active":true,"usgs":false}],"preferred":false,"id":943819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Xinyuan","contributorId":347340,"corporation":false,"usgs":false,"family":"Kang","given":"Xinyuan","email":"","affiliations":[{"id":83142,"text":"Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, Shenzhen, China","active":true,"usgs":false}],"preferred":false,"id":943820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jiazhen","contributorId":329836,"corporation":false,"usgs":false,"family":"Wang","given":"Jiazhen","email":"","affiliations":[{"id":78727,"text":"Southern University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":943821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":943822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Jialin","contributorId":348835,"corporation":false,"usgs":false,"family":"Li","given":"Jialin","affiliations":[{"id":80248,"text":"Ningbo University, China","active":true,"usgs":false}],"preferred":false,"id":943823,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fang, Di","contributorId":348832,"corporation":false,"usgs":false,"family":"Fang","given":"Di","affiliations":[{"id":80251,"text":"Southern University of Science and Technology, China","active":true,"usgs":false}],"preferred":false,"id":943824,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Qiu, Wenhui","contributorId":334797,"corporation":false,"usgs":false,"family":"Qiu","given":"Wenhui","email":"","affiliations":[{"id":80251,"text":"Southern University of Science and Technology, China","active":true,"usgs":false}],"preferred":false,"id":943825,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70269369,"text":"70269369 - 2025 - Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements","interactions":[],"lastModifiedDate":"2025-07-21T14:18:05.475685","indexId":"70269369","displayToPublicDate":"2025-07-18T09:05:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13783,"text":"Environmental Science & Policy","active":true,"publicationSubtype":{"id":10}},"title":"Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements","docAbstract":"<p><span>Inland fish and fisheries are globally important to environmental function and human services, yet their persistent lack of recognition in global agreements, especially multilateral environmental agreements (MEAs), may hinder progress towards biodiversity conservation and human well-being. The connection between inland fish, fisheries, and their ecosystems means that addressing the needs of fish directly offers opportunities to meet multiple global commitments and provide indicators of progress towards many global goals. In this perspective, we highlight opportunities to better integrate inland fish and fisheries into MEAs, specifically the Convention on Biological Diversity (CBD), Convention on Wetlands (commonly known as the Ramsar Convention), Convention on Conservation of Migratory Species (CMS), Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), and World Heritage Convention (WHC). Greater attention on inland fish and fisheries through MEAs could help ensure more holistic planning, investment, and conservation of these important fish and fisheries, their biodiversity, the essential resources they provision, and the environments they inhabit.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsci.2025.104089","usgsCitation":"Lynch, A.J., Bartley, D., Beard, Borba, G., Cooke, S., Cowx, I., Elliott, V., Embke, H., Gondwe, E., Hogan, Z., Low, J., Madden, J., Phang, S.C., Rice, E., Sievert, N., Stokes, G.L., Akwany, L., Allison, E.H., Arlinghaus, R., Arthur, R.I., Atkore, V., Badhon, M., Baigun, C., Brooks, J., Castello, L., Chanthalounnavong, S., Chea, S., Chhorn, S., Cooperman, M.S., Crisafi, K., Dalton, J., Doughty, C., Earl, J., Emam, W., Flitcroft, R.L., Gundermann, D., Hansen, H.H., Harrison, I., Hughes, K., Kangur, K., Lawrence, T., Lyach, R., Myers, B., Muthiah, M., Quyen, N., Nguyen, V., Nyboer, E.A., Olden, J., Paukert, C.P., Piczak, M.L., Quintana, Y., Quyen, V., Akintola, S., Shrestha, R., Uon, S., Uy, S., and VanWynen, C., 2025, Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements: Environmental Science & Policy, v. 171, 104089, 12 p., https://doi.org/10.1016/j.envsci.2025.104089.","productDescription":"104089, 12 p.","ipdsId":"IP-168310","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":492614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":943543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartley, Devin","contributorId":166934,"corporation":false,"usgs":false,"family":"Bartley","given":"Devin","affiliations":[],"preferred":false,"id":943544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, Jr. 0000-0003-2632-2350 dbeard@usgs.gov","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":169459,"corporation":false,"usgs":true,"family":"Beard","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":943545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borba, Gabriel","contributorId":358334,"corporation":false,"usgs":false,"family":"Borba","given":"Gabriel","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":943546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooke, Steven J.","contributorId":340990,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":943547,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cowx, Ian G.","contributorId":341626,"corporation":false,"usgs":false,"family":"Cowx","given":"Ian G.","affiliations":[{"id":81763,"text":"Fisheries Institute at the University of Hull","active":true,"usgs":false}],"preferred":false,"id":943548,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Elliott, Vittoria 0000-0001-8230-489X","orcid":"https://orcid.org/0000-0001-8230-489X","contributorId":216206,"corporation":false,"usgs":false,"family":"Elliott","given":"Vittoria","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":943549,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":358337,"corporation":false,"usgs":true,"family":"Embke","given":"Holly Susan","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":943550,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gondwe, Edith","contributorId":268048,"corporation":false,"usgs":false,"family":"Gondwe","given":"Edith","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":943551,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hogan, Zeb","contributorId":341632,"corporation":false,"usgs":false,"family":"Hogan","given":"Zeb","affiliations":[{"id":37455,"text":"University of 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Numerous studies have investigated spatial patterns and habitat use of large carnivores in human-modified landscapes, but little research has examined their activity rhythms. We compiled Global Positioning System data (2004–2022) for 139 brown bears&nbsp;</span><i>Ursus arctos</i><span>&nbsp;from six populations across Europe, representing a human-modified landscape, and the Greater Yellowstone Ecosystem, U.S.A., representing a landscape with limited human impact, which we used to calculate hourly movement rates as an activity proxy. Using a Bayesian approach to model the temporal autocorrelation of activity data, we tested if the extent of nocturnality in brown bears is modulated by intensity of human encroachment, accounting for primary productivity and maximum ambient temperature. All bear populations exhibited a predominantly bimodal, crepuscular pattern of activity, although Yellowstone bears were proportionally more crepuscular and diurnal. Whereas the effect of primary productivity was variable, all European populations became more nocturnal in response to higher human encroachment and reduced diurnal and crepuscular activity at higher summer temperatures, decreasing overall diel activity levels. Yellowstone bears displayed the greatest shift towards nocturnality among all populations in response to increasing human encroachment, and increased nocturnal activity to compensate for lower diurnal and crepuscular activity at higher summer temperatures. Our research indicates that European bears in human-modified landscapes may be reaching a limit in the behavioral plasticity they can manifest in their activity patterns, being already constrained into increased nocturnality. 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,{"id":70269707,"text":"70269707 - 2025 - Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","interactions":[],"lastModifiedDate":"2025-07-30T15:06:19.598148","indexId":"70269707","displayToPublicDate":"2025-07-18T07:58:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22155,"text":"Smart Agricultural Technology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","docAbstract":"<p><span>Cover crops play a critical role in providing agroecological services such as improving soil health, reducing erosion and nitrogen loss, and suppressing weeds, which are closely tied to their performance such as accumulated biomass. This study evaluated the Active Canopy Sensor (ACS) -214, an active proximal sensing device equipped with its own light-emitting red and near-infrared spectral reflectance sensors, a time-of-flight laser, and an ultrasonic sensor, for estimating winter cover crop biomass across 13 U.S. states from 2020 to 2024. We assessed 11 species from three functional groups – grasses (</span><i>n</i><span>&nbsp;= 797), legumes (</span><i>n</i><span>&nbsp;= 264), and brassicas (</span><i>n</i><span>&nbsp;= 181) – using Random Forest (RF) models and four cross-validation strategies. The ACS-214 showed moderate to strong prediction accuracy for grasses (</span><i>R<sup>2</sup></i><span>&nbsp;= 0.51 – 0.64) and legumes (</span><i>R<sup>2</sup></i><span>&nbsp;= 0.44 – 0.76), though performance declined in leave-one-region-out analyses (</span><i>R<sup>2</sup></i><span>&nbsp;= 0.06 – 0.46), indicating limited spatial generalizability. Brassica models had low prediction accuracy for all models (</span><i>R<sup>2</sup></i><span>&nbsp;&lt; 0.30), likely due to flowering and patchy growth. Biomass prediction breakpoints were observed at ∼3000 kg ha</span><sup>−1</sup><span>&nbsp;for legumes and ∼4000 kg ha</span><sup>−1</sup><span>&nbsp;for grasses. We also evaluated the effectiveness of using ACS-214 data to train Sentinel-2 satellite imagery for estimating grass cover crop biomass using withheld, out of bag data from 2023 to 2024. Sentinel-2 RF models trained with ACS-214 data showed good agreement with field-sampled (</span><i>R<sup>2</sup></i><span>&nbsp;= 0.58 – 0.61) and ACS-214-estimated biomass (</span><i>R<sup>2</sup></i><span>&nbsp;= 0.70). While Sentinel-2 offers scalability, the ACS-214 enables finer-resolution biomass mapping and better accounts for within-field variability, making it an effective tool for localized management and monitoring. These findings support the integration of proximal and satellite sensing approaches to enhance cover crop biomass estimation and agroecological assessment.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.atech.2025.101201","usgsCitation":"Jennewein, J., Davis, B., Seehaver-Eagan, S., Nicolette, J., Pittman, J., Hively, W.D., Goldsmith, A., Hidalgo, C., Reberg-Horton, C., and Mirsky, S., 2025, Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions: Smart Agricultural Technology, v. 12, 101201, 22 p., https://doi.org/10.1016/j.atech.2025.101201.","productDescription":"101201, 22 p.","ipdsId":"IP-179201","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":493304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atech.2025.101201","text":"Publisher Index Page"},{"id":493188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Indiana, Iowa, Kansas, Maryland, Missouri, North Carolina, Ohio, New Hampshire, Vermont, Virginia, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.92714553560637,\n              43.58854319693313\n            ],\n            [\n              -95.89232587289348,\n              37.62183341552925\n            ],\n            [\n              -89.95992461869106,\n              37.07043638610585\n            ],\n            [\n              -88.56407871751861,\n              30.53924077937387\n            ],\n            [\n              -87.95786849494071,\n              30.079081766107564\n            ],\n            [\n              -79.28622937957765,\n              30.005749406912585\n            ],\n            [\n              -71.27060896702632,\n              45.07860396784778\n            ],\n            [\n              -86.55806437204849,\n              45.188229262227445\n            ],\n            [\n              -91.6664764308591,\n              46.72848518852835\n            ],\n            [\n              -96.92714553560637,\n              43.58854319693313\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":944485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Brian W. 0000-0003-0714-5133","orcid":"https://orcid.org/0000-0003-0714-5133","contributorId":358921,"corporation":false,"usgs":false,"family":"Davis","given":"Brian W.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seehaver-Eagan, S. 0009-0002-1048-9623","orcid":"https://orcid.org/0009-0002-1048-9623","contributorId":358924,"corporation":false,"usgs":false,"family":"Seehaver-Eagan","given":"S.","affiliations":[{"id":85715,"text":"North Carolina State University (NCSU)","active":true,"usgs":false}],"preferred":false,"id":944487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicolette, J. 0000-0002-8904-2391","orcid":"https://orcid.org/0000-0002-8904-2391","contributorId":358925,"corporation":false,"usgs":false,"family":"Nicolette","given":"J.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pittman, J.","contributorId":358926,"corporation":false,"usgs":false,"family":"Pittman","given":"J.","affiliations":[{"id":85718,"text":"BAER","active":true,"usgs":false}],"preferred":false,"id":944489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldsmith, Avi","contributorId":358927,"corporation":false,"usgs":false,"family":"Goldsmith","given":"Avi","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":944491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hidalgo, C. 0009-0007-2566-5198","orcid":"https://orcid.org/0009-0007-2566-5198","contributorId":358928,"corporation":false,"usgs":false,"family":"Hidalgo","given":"C.","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":944492,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reberg-Horton, C. 0000-0001-5002-106X","orcid":"https://orcid.org/0000-0001-5002-106X","contributorId":358929,"corporation":false,"usgs":false,"family":"Reberg-Horton","given":"C.","affiliations":[{"id":85719,"text":"NSCU","active":true,"usgs":false}],"preferred":false,"id":944493,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mirsky, S.B.","contributorId":357633,"corporation":false,"usgs":false,"family":"Mirsky","given":"S.B.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":944494,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70269291,"text":"sir20255056 - 2025 - Selected special conditions affecting peak streamflow and extreme floods in Alaska through water year 2022","interactions":[],"lastModifiedDate":"2026-02-03T14:28:42.124178","indexId":"sir20255056","displayToPublicDate":"2025-07-17T14:22:08","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5056","displayTitle":"Selected Special Conditions Affecting Peak Streamflow and Extreme Floods in Alaska Through Water Year 2022","title":"Selected special conditions affecting peak streamflow and extreme floods in Alaska through water year 2022","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Alaska Department of Transportation and Public Facilities, inventoried selected special conditions for annual peak flows and identified extreme floods at streamgages in Alaska through water year 2022 to facilitate hydrologic analysis. Special conditions identified from U.S. Geological Survey gaging records and basin characteristics included regulation and diversion, urbanization, indeterminate drainage areas, drainage areas less than the minimum used in regional analyses, glacial lake outburst floods, other outburst floods, and snowmelt floods. For peak flows that occurred during calendar years 1980–2019, an atmospheric river dataset was used to identify atmospheric river presence or absence on the dates peak flows occurred. Extreme floods (defined as peak flows exceeding the 1-percent annual exceedance probability flood magnitude or an empirical measure of relative magnitude using Creager’s coefficient C) were identified and associated with flood-generating mechanisms using the other inventoried special conditions and other information.</p><p>The gaging record contained glacial lake outburst floods at 15 streamgages and other types of outburst floods at 10 streamgages. Non-outburst peak flows in Alaska resulted from a mixture of rainfall and melt-based flood-generating mechanisms in all but the most rain-dominated seasonal flow regime. Melt-based flood-generating mechanisms included snowmelt, high-elevation snow and ice melt, or rain-on-snow events. Atmospheric rivers were common in Alaska and conterminous basins in Canada, occurring in that region on 67 percent of the days in the calendar year 1980–2019 period. Atmospheric rivers were more common on the days of peak flows and even more common on the days of non-outburst extreme floods. The percentage of days when an atmospheric river was present increased to 78 percent for the days of peak flows in that period and to 83 percent for the days of non-outburst extreme floods in that period. Of 149 extreme floods in the gaging record, 38 were generated by outburst floods. Of the non-outburst extreme floods, 72 percent were generated by rainfall and 26 percent were generated by melt-based processes or a combination of rainfall and melt-based processes. Flood-generating mechanisms could not be determined for the final 2 percent of the non-outburst extreme floods because the month and day of the peak flows were unknown and no other information was available. Secondary factors strongly associated with extreme floods included antecedent rain and streamflow conditions and warm storm conditions that produced rain instead of snow or generated snowmelt.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255056","collaboration":"Prepared in cooperation with Alaska Department of Transportation and Public Facilities","usgsCitation":"Curran, J.H., 2025, Selected special conditions affecting peak streamflow and extreme floods in Alaska through water year 2022: U.S. Geological Survey Scientific Investigations Report 2025–5056, 41 p., https://doi.org/10.3133/sir20255056.","productDescription":"Report: viii, 41 p.; 5 Data Releases","onlineOnly":"Y","ipdsId":"IP-169678","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":499049,"rank":11,"type":{"id":36,"text":"NGMDB Index 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href=\"mailto:dc_ak@usgs.gov\" data-mce-href=\"mailto:dc_ak@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska, 99508</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Description of Study Area</li><li>Data Collection and Compilation Methods</li><li>Results of Inventories of Special Conditions for Peak Flows</li><li>Results of Assessment of Flood-Generating Mechanisms for Extreme Floods</li><li>Discussion—Applications for Hydrologic Analysis</li><li>Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2025-07-17","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Curran, Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":943366,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70270761,"text":"70270761 - 2025 - Warmer Is deadlier: A meta‐analysis reveals increasing temperatures accentuate disease effects on fisheries hosts","interactions":[],"lastModifiedDate":"2025-08-22T15:32:47.12575","indexId":"70270761","displayToPublicDate":"2025-07-17T10:24:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22179,"text":"Ecological Letters","active":true,"publicationSubtype":{"id":10}},"title":"Warmer Is deadlier: A meta‐analysis reveals increasing temperatures accentuate disease effects on fisheries hosts","docAbstract":"<p><span>Rapid warming could drastically alter host–parasite relationships, which is especially important for fisheries crucial to human nutrition and economic livelihoods, yet we lack a synthetic understanding of how warming influences parasite-induced mortality in these systems. We conducted a meta-analysis using 266 effect sizes from 52 empirical papers on harvested aquatic species and determined the relationship between parasite-induced host mortality and temperature and how this relationship was altered by host, parasite, and study design traits. Overall, higher temperatures increased parasite-induced host mortality; however, the magnitude of this relationship varied. Hosts from the order Salmoniformes experienced a greater increase in parasite-induced mortality with temperature than the average response to temperature across fish orders. Opportunistic parasites were associated with a greater increase in infected host mortality with temperature than the average across parasite strategies, while bacterial parasites were associated with lower infected host mortality as temperature increased than the average across parasite types. Thus, parasites will generally increase host mortality as the environment warms; however, this effect will vary among systems.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.70156","usgsCitation":"Tomamichel, M.M., Lowe, K.I., Arnold, K.M., Frischer, M.E., Irwin, B., Osenberg, C.W., Hall, R.J., and Byers, J.E., 2025, Warmer Is deadlier: A meta‐analysis reveals increasing temperatures accentuate disease effects on fisheries hosts: Ecological Letters, v. 28, no. 7, e70156, 14 p., https://doi.org/10.1111/ele.70156.","productDescription":"e70156, 14 p.","ipdsId":"IP-159658","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495041,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ele.70156","text":"External Repository"},{"id":494524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tomamichel, M. M.","contributorId":360384,"corporation":false,"usgs":false,"family":"Tomamichel","given":"M.","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, K. I.","contributorId":360387,"corporation":false,"usgs":false,"family":"Lowe","given":"K.","middleInitial":"I.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, K. M.H.","contributorId":360390,"corporation":false,"usgs":false,"family":"Arnold","given":"K.","middleInitial":"M.H.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frischer, M. E.","contributorId":360392,"corporation":false,"usgs":false,"family":"Frischer","given":"M.","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irwin, Brian J. 0000-0002-0666-2641","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":280043,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":947009,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osenberg, C. W.","contributorId":360396,"corporation":false,"usgs":false,"family":"Osenberg","given":"C.","middleInitial":"W.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, R. J.","contributorId":360398,"corporation":false,"usgs":false,"family":"Hall","given":"R.","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947011,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byers, J. E.","contributorId":360402,"corporation":false,"usgs":false,"family":"Byers","given":"J.","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947012,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70269321,"text":"70269321 - 2025 - Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation","interactions":[],"lastModifiedDate":"2025-11-18T16:58:07.522222","indexId":"70269321","displayToPublicDate":"2025-07-17T09:08:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation","docAbstract":"<p><span>The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaf087","usgsCitation":"Weiss, M., Holland, A., D’Amato, A.W., Deegan, L.A., Farmer, W., Hoving, C., Karmalkar, A., Latzka, A.W., Magee, M., McIntyre, P.B., Morelli, T.L., Notaro, M., Olmstead, N., Palmer, R., Pau, N., Renfrew, R., Ribic, C., Sheppard, J., Staudinger, M., Zuckerberg, B., and Bradley, B.A., 2025, Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation: BioScience, v. 75, no. 10, p. 842-855, https://doi.org/10.1093/biosci/biaf087.","productDescription":"14 p.","startPage":"842","endPage":"855","ipdsId":"IP-169492","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":492532,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiss, Marissa","contributorId":167459,"corporation":false,"usgs":false,"family":"Weiss","given":"Marissa","email":"","affiliations":[{"id":24712,"text":"Harvard Forest","active":true,"usgs":false}],"preferred":false,"id":943442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, Addie Rose","contributorId":355367,"corporation":false,"usgs":false,"family":"Holland","given":"Addie Rose","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":943443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":943444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deegan, Linda A.","contributorId":34094,"corporation":false,"usgs":false,"family":"Deegan","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. 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Massachusetts","active":true,"usgs":false}],"preferred":false,"id":943462,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70269608,"text":"70269608 - 2025 - New insights into gas-driven phase segregation in andesitic enclaves from Mt. Mazama (Crater Lake), USA","interactions":[],"lastModifiedDate":"2025-07-28T14:58:44.447972","indexId":"70269608","displayToPublicDate":"2025-07-17T07:52:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"New insights into gas-driven phase segregation in andesitic enclaves from Mt. Mazama (Crater Lake), USA","docAbstract":"A key process in active magmatic systems is the “recharge” of deep-sourced mafic magma into cooler, more evolved, and crystal-rich shallow reservoirs; recharge may be the cause of, or response to, eruptive activity. Although compositional evidence for recharge has been extensively documented, physical models of recharge are limited, particularly processes that\nseparate exsolving volatiles and melts from rapidly growing crystals. To improve constraints on phase separation behaviors, we re-examine andesitic enclaves in silicic andesite lava flows of Mt. Mazama (Crater Lake), USA, that provided early evidence of gas-driven filter pressing (Bacon, 1986). 2D and 3D imaging shows that enclaves have a sample-spanning crystal\nframework that is disrupted by melt patches, indicating that initially deformable crystal networks were subject to early phase reorganization. Small enclaves are poorly vesicular and require early gas loss. Large enclaves have porous cores with angular (diktytaxitic) voids that are well-connected in 3D and denser rinds with isolated pores. Large enclave rinds have similar bulk\ncompositions to small enclaves but their less evolved cores require ~ 20% melt removal. In the large enclave, diktytaxitic core textures and gas fingering structures at the core–rind boundary suggest relatively slow late-stage outward gas migration. Both scaling arguments and evidence of outward gas/melt migration require a resistant rind. Rind formation is best explained by differential cooling and demonstrates the importance of thermal gradients for gas-driven filter pressing. A corollary is a limited time scale of recharge, enclave formation, and vesiculation to produce diktytaxitic textures, suggesting that recharge was (near) synchronous with eruption.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01855-8","usgsCitation":"Oppenheimer, J., Cashman, K., Rust, A.C., Bacon, C.R., Lindoo, A., and Dobson, K., 2025, New insights into gas-driven phase segregation in andesitic enclaves from Mt. Mazama (Crater Lake), USA: Bulletin of Volcanology, v. 87, no. 65, 65, 19 p., https://doi.org/10.1007/s00445-025-01855-8.","productDescription":"65, 19 p.","ipdsId":"IP-172926","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":494436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01855-8","text":"Publisher Index Page"},{"id":493002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake, Mt. Mazama","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.18090601540398,\n              42.98586629991806\n            ],\n            [\n              -122.18090601540398,\n              42.895897881682174\n            ],\n            [\n              -122.0345881300828,\n              42.895897881682174\n            ],\n            [\n              -122.0345881300828,\n              42.98586629991806\n            ],\n            [\n              -122.18090601540398,\n              42.98586629991806\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oppenheimer, Julie","contributorId":358795,"corporation":false,"usgs":false,"family":"Oppenheimer","given":"Julie","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":944172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Katharine V.","contributorId":40097,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine V.","affiliations":[],"preferred":false,"id":944173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rust, Alison C.","contributorId":196700,"corporation":false,"usgs":false,"family":"Rust","given":"Alison","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":944174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":944175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindoo, Amanda","contributorId":344833,"corporation":false,"usgs":false,"family":"Lindoo","given":"Amanda","email":"","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":944176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dobson, Katherine J.","contributorId":358798,"corporation":false,"usgs":false,"family":"Dobson","given":"Katherine J.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":944177,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70271993,"text":"70271993 - 2025 - Global terrestrial nitrogen fixation and its modification by agriculture","interactions":[],"lastModifiedDate":"2025-09-30T15:37:10.058045","indexId":"70271993","displayToPublicDate":"2025-07-16T10:32:34","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":"Global terrestrial nitrogen fixation and its modification by agriculture","docAbstract":"<p><span>Biological nitrogen fixation (BNF) is the largest natural source of new nitrogen (N) that supports terrestrial productivity</span><sup>1,2</sup><span>, yet estimates of global terrestrial BNF remain highly uncertain</span><sup>3,4</sup><span>. Here we show that this uncertainty is partly because of sampling bias, as&nbsp;field BNF measurements in natural terrestrial ecosystems occur where N fixers are 17 times more prevalent than their mean abundances worldwide. To correct this bias, we develop new estimates of global terrestrial BNF by upscaling field BNF measurements using spatially explicit abundances of all major biogeochemical N-fixing niches. We find that natural biomes sustain lower BNF, 65 (52–77) Tg N yr</span><sup>−1</sup><span>, than previous empirical bottom-up estimates</span><sup>3,4</sup><span>, with most BNF occurring in tropical forests and drylands. We also find high agricultural BNF in croplands and cultivated pastures, 56 (54–58) Tg N yr</span><sup>−1</sup><span>. Agricultural BNF has increased terrestrial BNF by 64% and total terrestrial N inputs from all sources by 60% over pre-industrial levels. Our results indicate that BNF may impose stronger constraints on the carbon sink in natural terrestrial biomes and represent a larger source of agricultural N than is generally considered in analyses of the global N cycle</span><sup>5,6</sup><span>, with implications for proposed safe operating limits for N use</span><sup>7,8</sup><span>.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41586-025-09201-w","usgsCitation":"Reis Ely, C., Perakis, S.S., Cleveland, C., Menge, D., Reed, S.C., Taylor, B., Batterman, S., Clark, C.M., Crews, T., Dynarski, K.A., Gei, M., Gundale, M., Herridge, D., Jovan, S.E., Kou-Giesbrecht, S., Peoples, M., Piipponen, J., Rodriguez-Caballero, E., Salmon, V., Soper, F.M., Staccone, A., Weber, B., Williams, C., and Wurzburger, N., 2025, Global terrestrial nitrogen fixation and its modification by agriculture: Nature, v. 643, p. 705-711, https://doi.org/10.1038/s41586-025-09201-w.","productDescription":"7 p.","startPage":"705","endPage":"711","ipdsId":"IP-163219","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":496330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-025-09201-w","text":"Publisher Index Page"},{"id":496266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"643","noUsgsAuthors":false,"publicationDate":"2025-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Reis Ely, Carla R. 0000-0002-9657-8071","orcid":"https://orcid.org/0000-0002-9657-8071","contributorId":353554,"corporation":false,"usgs":false,"family":"Reis Ely","given":"Carla R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":949633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":949634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Cory C. 0000-0002-8804-4248","orcid":"https://orcid.org/0000-0002-8804-4248","contributorId":353556,"corporation":false,"usgs":false,"family":"Cleveland","given":"Cory C.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":949635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":949636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":217604,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949637,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Benton 0000-0002-9834-9192","orcid":"https://orcid.org/0000-0002-9834-9192","contributorId":245071,"corporation":false,"usgs":false,"family":"Taylor","given":"Benton","email":"","affiliations":[{"id":49081,"text":"Smithsonian Environmental Research Center, Edgewater, MD, 21037 USA","active":true,"usgs":false}],"preferred":false,"id":949638,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Batterman, Sarah A. 0000-0002-7703-9873","orcid":"https://orcid.org/0000-0002-7703-9873","contributorId":353558,"corporation":false,"usgs":false,"family":"Batterman","given":"Sarah A.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":949639,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clark, Christopher M.","contributorId":361916,"corporation":false,"usgs":false,"family":"Clark","given":"Christopher","middleInitial":"M.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":949640,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Crews, Timothy E. 0000-0003-4764-341X","orcid":"https://orcid.org/0000-0003-4764-341X","contributorId":353560,"corporation":false,"usgs":false,"family":"Crews","given":"Timothy E.","affiliations":[{"id":64924,"text":"The Land Institute","active":true,"usgs":false}],"preferred":false,"id":949641,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dynarski, Katherine A 0000-0001-5101-9666","orcid":"https://orcid.org/0000-0001-5101-9666","contributorId":225403,"corporation":false,"usgs":false,"family":"Dynarski","given":"Katherine","email":"","middleInitial":"A","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":949642,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gei, Maga G. 0000-0003-0775-4916","orcid":"https://orcid.org/0000-0003-0775-4916","contributorId":353562,"corporation":false,"usgs":false,"family":"Gei","given":"Maga G.","affiliations":[{"id":64927,"text":"Association for Tropical Biology and Conservation","active":true,"usgs":false}],"preferred":false,"id":949643,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gundale, Michael J. 0000-0003-2447-609X","orcid":"https://orcid.org/0000-0003-2447-609X","contributorId":353564,"corporation":false,"usgs":false,"family":"Gundale","given":"Michael J.","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":949644,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Herridge, David F. 0000-0002-0423-2517","orcid":"https://orcid.org/0000-0002-0423-2517","contributorId":353569,"corporation":false,"usgs":false,"family":"Herridge","given":"David F.","affiliations":[{"id":38381,"text":"University of New England","active":true,"usgs":false}],"preferred":false,"id":949645,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Jovan, Sarah E. 0000-0001-7860-4005","orcid":"https://orcid.org/0000-0001-7860-4005","contributorId":361180,"corporation":false,"usgs":false,"family":"Jovan","given":"Sarah","middleInitial":"E.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":949646,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kou-Giesbrecht, Sian 0000-0002-4086-0561","orcid":"https://orcid.org/0000-0002-4086-0561","contributorId":261258,"corporation":false,"usgs":false,"family":"Kou-Giesbrecht","given":"Sian","email":"","affiliations":[{"id":52786,"text":"Columbia U","active":true,"usgs":false}],"preferred":false,"id":949647,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Peoples, Mark B. 0000-0001-6060-3290","orcid":"https://orcid.org/0000-0001-6060-3290","contributorId":353566,"corporation":false,"usgs":false,"family":"Peoples","given":"Mark B.","affiliations":[{"id":84434,"text":"CSIRO Agriculture and Food","active":true,"usgs":false}],"preferred":false,"id":949648,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Piipponen, Johannes","contributorId":353571,"corporation":false,"usgs":false,"family":"Piipponen","given":"Johannes","affiliations":[{"id":84437,"text":"Aalto University","active":true,"usgs":false}],"preferred":false,"id":949649,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":949650,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Salmon, Verity G. 0000-0002-2188-551X","orcid":"https://orcid.org/0000-0002-2188-551X","contributorId":353567,"corporation":false,"usgs":false,"family":"Salmon","given":"Verity G.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":949651,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Soper, Fiona M. 0000-0002-9910-9377","orcid":"https://orcid.org/0000-0002-9910-9377","contributorId":361183,"corporation":false,"usgs":false,"family":"Soper","given":"Fiona","middleInitial":"M.","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":949652,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Staccone, Anika P. 0000-0002-2558-8715","orcid":"https://orcid.org/0000-0002-2558-8715","contributorId":353568,"corporation":false,"usgs":false,"family":"Staccone","given":"Anika P.","affiliations":[{"id":84436,"text":"Earthshot Labs","active":true,"usgs":false}],"preferred":false,"id":949653,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Weber, Bettina","contributorId":196800,"corporation":false,"usgs":false,"family":"Weber","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":949654,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Williams, Christopher A. 0000-0002-8819-6786","orcid":"https://orcid.org/0000-0002-8819-6786","contributorId":353572,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher A.","affiliations":[{"id":24788,"text":"Clark University","active":true,"usgs":false}],"preferred":false,"id":949655,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wurzburger, Nina","contributorId":299676,"corporation":false,"usgs":false,"family":"Wurzburger","given":"Nina","email":"","affiliations":[{"id":27235,"text":"U Georgia","active":true,"usgs":false}],"preferred":false,"id":949656,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70273007,"text":"70273007 - 2025 - Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system","interactions":[],"lastModifiedDate":"2025-12-12T16:23:39.187411","indexId":"70273007","displayToPublicDate":"2025-07-16T10:18:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system","docAbstract":"<p><span>Predation establishes risk, which can indirectly influence prey behavior and ecology. We evaluated the influence of Mexican gray wolves (</span><i>Canis lupus baileyi</i><span>) on habitat selection and spatiotemporal predator avoidance strategies of elk (</span><i>Cervus canadensis</i><span>). We fit 866 adult female elk with GPS collars across areas of varying wolf densities within the Mexican wolf experimental population area of eastern Arizona and western New Mexico between 2019−2021. Using step-selection functions we examined relative intensity of elk use in relation to landscape attributes, estimated predator/prey diel activity, and measures of risk. Risk metrics included predicted wolf presence, habitat openness, and predicted risky places modeled from attributes of locations where wolves killed elk. Wolf activity varied across seasons and increased midday and night in fall and monsoon seasons. Relative use by elk was best explained by incorporating an interaction between diel period and predicted risky places across all seasons. Elk utilized risky places more in times of nutritional deficit associated with high energetic demands of the third trimester pregnancy and lactation and when forage quality was best, during spring and monsoon season. Particularly, use of risky places increased at less risky times in areas with more established wolf presence, suggesting use of risky places varied relative to exposure to Mexican wolves. These behaviors highlight the importance of temporal avoidance when predators and prey are highly mobile and largely overlap in space. Our research suggests temporally responding to predictable and relatively static environmental characteristics associated with encounter and kill rates may better balance energetic trade-offs than anticipating changes in wolf activity or spatially avoiding areas with higher wolf presence. Thus, elk appear to be more willing to take chances and mitigate cursorial predation risk with a more immediate, reactive approach and make proactive trade-offs during the seasons they can best increase fitness.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2025.1613904","usgsCitation":"Thompson, C.J., Tatman, N.M., Farley, Z.J., Boyle, S.T., Greenleaf, A.R., and Cain, J.W., 2025, Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system: Frontiers in Ecology and Evolution, v. 13, 1613904, 17 p., https://doi.org/10.3389/fevo.2025.1613904.","productDescription":"1613904, 17 p.","ipdsId":"IP-178445","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":497705,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2025.1613904","text":"Publisher Index Page"},{"id":497479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.32284903489135,\n              35.0948138550403\n            ],\n            [\n              -111.32284903489135,\n              32.96688100110357\n            ],\n            [\n              -106.60492292551181,\n              32.96688100110357\n            ],\n            [\n              -106.60492292551181,\n              35.0948138550403\n            ],\n            [\n              -111.32284903489135,\n              35.0948138550403\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Cara J.","contributorId":363878,"corporation":false,"usgs":false,"family":"Thompson","given":"Cara","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tatman, Nicole M.","contributorId":363881,"corporation":false,"usgs":false,"family":"Tatman","given":"Nicole","middleInitial":"M.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":952086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farley, Zachary J.","contributorId":363884,"corporation":false,"usgs":false,"family":"Farley","given":"Zachary","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyle, Scott T.","contributorId":363887,"corporation":false,"usgs":false,"family":"Boyle","given":"Scott","middleInitial":"T.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greenleaf, Allison R.","contributorId":363890,"corporation":false,"usgs":false,"family":"Greenleaf","given":"Allison","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":952089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cain, James W. 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,{"id":70269252,"text":"70269252 - 2025 - Using community-reported data to understand how boat speed affects marine wildlife: An example with the Florida manatee","interactions":[],"lastModifiedDate":"2025-07-17T14:30:00.754874","indexId":"70269252","displayToPublicDate":"2025-07-16T09:26:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Using community-reported data to understand how boat speed affects marine wildlife: An example with the Florida manatee","docAbstract":"<ol class=\"\"><li>Boat collisions are a known and increasing threat to many marine wildlife populations. The Florida manatee<span>&nbsp;</span><i>Trichechus manatus latirostris</i><span>&nbsp;</span>is a key example of a species with high boat-related mortality, whose long-term viability and population are limited by human activities in shared habitats. The goal of this work was to quantify the probability of lethal injury to Florida manatees using community-reported data on collisions with boats. We test the hypothesis that higher boat speeds increase the probability of lethal injury to manatees. Empirical data to test this hypothesis are collected opportunistically, with low sample sizes and uncertainty in reported boat speed.</li><li>We fit a logistic regression model using Bayesian inference with Markov Chain Monte Carlo to community-reported collision data. We also present results for two errors-in-variables modelling approaches that account for uncertainty in boat speeds reported as qualitative values. The first uses a multiple imputation approach, whereas the second uses Bayesian estimation with informed priors. We evaluated issues related to quasi-separation, sample size, and measurement errors using simulated data.</li><li>The models predicted that the probability of lethal injury increased at greater strike speed. However, the small number of records with low boat speed or where the injury was considered non-lethal contributed to uncertainty around this functional relationship. Although the relationships were consistent among models, the uncertainty was greater for the errors-in-variables models.</li><li><i>Practical implication</i>. When combined with information on manatee and boat abundance and behaviour, the results of this analysis can be used to predict the number of deadly collisions, test alternative management scenarios and inform speed zone regulations. We also identify ways to improve data reporting to reduce uncertainty in the effect of boat speed on lethal injury to marine wildlife. This type of analysis can be applied to any marine animal where records of collisions with boats are kept.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1002/2688-8319.70058","usgsCitation":"Combs-Hintze, B., Hostetler, J.A., Calleson, C., Basset, B., Ainsworth, C., and Martin, J., 2025, Using community-reported data to understand how boat speed affects marine wildlife: An example with the Florida manatee: Ecological Solutions and Evidence, v. 6, no. 3, e70058, 11 p., https://doi.org/10.1002/2688-8319.70058.","productDescription":"e70058, 11 p.","ipdsId":"IP-158968","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2688-8319.70058","text":"Publisher Index Page"},{"id":492418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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