Tapwater (TW) safety and sustainability are priorities in the United States. Per/polyfluoroalkyl substance(s) (PFAS) contamination is a growing public-health concern due to prolific use, widespread TW exposures, and mounting human-health concerns. Historically-rural, actively-urbanizing communities that rely on surficial-aquifer private wells incur elevated risks of unrecognized TW exposures, including PFAS, due to limited private-well monitoring and contaminant-source proliferation in urbanizing landscapes. Here, a broad-analytical-scope TW-assessment was conducted in a hydrologically-vulnerable, Mississippi River alluvial-island community, where PFAS contamination of the shallow-alluvial drinking-water aquifer has been documented, but more comprehensive contaminant characterization to inform decision-making is currently lacking. In 2021, we analyzed 510 organics, 34 inorganics, and 3 microbial groups in 11 residential and community locations to assess (1) TW risks beyond recognized PFAS issues, (2) day-to-day and year-to-year risk variability, and (3) suitability of the underlying sandstone aquifer as an alternative source to mitigate TW-PFAS exposures. Seventy-six organics and 25 inorganics were detected. Potential human-health risks of detected TW exposures were explored based on cumulative benchmark-based toxicity quotients (∑TQ). Elevated risks (∑TQ ≥ 1) from organic and inorganic contaminants were observed in all alluvial-aquifer-sourced synoptic samples but not in sandstone-aquifer-sourced samples. Repeated sampling at 3 sites over 52–55 h indicated limited variability in risk over the short-term. Comparable PFAS-specific ∑TQ for spatial-synoptic, short-term (3 days) temporal, and long-term (3 years quarterly) temporal samples indicated that synoptic results provided useful insight into the risks of TW-PFAS exposures at French Island over the long-term. No PFAS detections in sandstone-aquifer-sourced samples over a 3 year period indicated no PFAS-associated risk and supported the sandstone aquifer as an alternative drinking-water source to mitigate community TW-PFAS exposures. This study illustrated the importance of expanded contaminant monitoring of private-well TW, beyond known concerns (in this case, PFAS), to reduce the risks of a range of unrecognized contaminant exposures.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D5EM00005J","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Donahue, L., Gaikowski, M., Hines, R.K., Breitmeyer, S.E., Gordon, S.E., Loftin, K.A., McCleskey, R., Meppelink, S.M., and Schreiner, M., 2025, Tapwater exposures, residential risk, and mitigation in a PFAS-impacted-groundwater community: Environmental Science: Processes and Impacts, 21 p., https://doi.org/10.1039/D5EM00005J.","productDescription":"21 p.","ipdsId":"IP-142462","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":488254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1039/d5em00005j","text":"Publisher Index Page"},{"id":484592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Campbell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.3046523459501,\n 43.87386653369529\n ],\n [\n -91.3046523459501,\n 43.86407274973604\n ],\n [\n -91.28224710242334,\n 43.86407274973604\n ],\n [\n -91.28224710242334,\n 43.87386653369529\n ],\n [\n -91.3046523459501,\n 43.87386653369529\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":205651,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donahue, Lee","contributorId":353363,"corporation":false,"usgs":false,"family":"Donahue","given":"Lee","affiliations":[{"id":84381,"text":"Town of Campbell, WI","active":true,"usgs":false}],"preferred":false,"id":933352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":933353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, Randy K. 0000-0002-5135-3135 rkhines@usgs.gov","orcid":"https://orcid.org/0000-0002-5135-3135","contributorId":3340,"corporation":false,"usgs":true,"family":"Hines","given":"Randy","email":"rkhines@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":933354,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":37464,"text":"WMA - 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The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251008","collaboration":"Prepared in cooperation with the Wild Rice Watershed District","usgsCitation":"Groten, J.T., Levin, S.B., Storey, G.G., Coenen, E.N., Blount, J.D., Lund, J.W., and Brannon, D.J., 2025, Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023: U.S. Geological Survey Open-File Report 2025–1008, 38 p., https://doi.org/10.3133/ofr20251008.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154644","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":493754,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118525.htm","linkFileType":{"id":5,"text":"html"}},{"id":483763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1008/coverthb.jpg"},{"id":483764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1008"},{"id":483765,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.XML"},{"id":483766,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1008/images/"},{"id":483767,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483768,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251008/full"}],"country":"United States","state":"Minnesota","otherGeospatial":"Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97,\n 47.5833\n ],\n [\n -97,\n 47\n ],\n [\n -95.25,\n 47\n ],\n [\n -95.25,\n 47.5833\n ],\n [\n -97,\n 47.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70229","usgsCitation":"Osland, M., Bradford, J., Toth, L., Germino, M., Grace, J., Drexler, J.Z., Stagg, C.L., Grossman, E.E., Thorne, K., Romanach, S., Passeri, D., Noe, G.E., Lacy, J.R., Krauss, K., Kowalski, K., Guntenspergen, G.R., Ganju, N., Enwright, N., Carr, J., Byrd, K.B., and Buffington, K., 2025, Ecological thresholds and transformations due to climate change: The role of abiotic stress: Ecosphere, v. 16, no. 4, e70229, p., https://doi.org/10.1002/ecs2.70229.","productDescription":"e70229, p.","ipdsId":"IP-168454","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70229","text":"Publisher Index Page"},{"id":484845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":222814,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":934118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":934119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":219648,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934120,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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2025 - River floods under wetter antecedent conditions deliver coarser sediment to the coast","interactions":[],"lastModifiedDate":"2025-04-15T15:10:08.066152","indexId":"70265714","displayToPublicDate":"2025-04-13T10:05:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"River floods under wetter antecedent conditions deliver coarser sediment to the coast","docAbstract":"Increasing hydrologic volatility—more extreme rain, and larger variations between wet and dry years—has become apparent in some regions, but few data exist to determine how intensifying hydrologic extremes affect sedimentary systems. Using uniquely high-resolution records of fluvial suspended sediment and coastal morphology, we quantify sedimentary responses from a steep, 357-km2 watershed in California under extreme wet and dry hydrologic conditions. In years with multiple 2- to 10-year floods, fluvial sediment coarsened significantly as the wet season progressed, with late-season floods delivering dominantly sand-sized material to the coast. Greater and coarser sediment supply under wetter antecedent conditions affected nearshore geomorphic evolution for 4–5 years. The watershed and coastal changes we documented point to an increasing role of sediment-related hazards (flooding and hillslope erosion) and resources (nearshore accretion) as wet seasons intensify.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL115232","usgsCitation":"East, A.E., Snyder, A.G., Stevens, A.W., Warrick, J.A., Topping, D.J., Thomas, M.A., and Ritchie, A., 2025, River floods under wetter antecedent conditions deliver coarser sediment to the coast: Geophysical Research Letters, v. 52, no. 8, e2025GL115232, 10 p., https://doi.org/10.1029/2025GL115232.","productDescription":"e2025GL115232, 10 p.","ipdsId":"IP-175612","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl115232","text":"Publisher Index Page"},{"id":484583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Lorenzo River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.2795738662301,\n 37.28890656527331\n ],\n [\n -122.2795738662301,\n 36.95309077205526\n ],\n [\n -121.9584157989861,\n 36.95309077205526\n ],\n [\n -121.9584157989861,\n 37.28890656527331\n ],\n [\n -122.2795738662301,\n 37.28890656527331\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyder, Alexander G. 0000-0001-6250-4827 agsnyder@usgs.gov","orcid":"https://orcid.org/0000-0001-6250-4827","contributorId":171654,"corporation":false,"usgs":true,"family":"Snyder","given":"Alexander","email":"agsnyder@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":167736,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan","email":"jwarrick@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":933372,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":933373,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ritchie, Andrew C. 0000-0001-5826-9983","orcid":"https://orcid.org/0000-0001-5826-9983","contributorId":333630,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":933374,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267347,"text":"70267347 - 2025 - Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","interactions":[],"lastModifiedDate":"2025-05-20T15:51:41.240547","indexId":"70267347","displayToPublicDate":"2025-04-11T10:50:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21640,"text":"Toxins","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","title":"Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula)","docAbstract":"As oceans warm, harmful algal blooms (HABs) are expected to increase, including blooms of Pseudo-nitzschia, a diatom that produces domoic acid (DA), which is a potent neurotoxin. Regulatory limits for human consumption (0.075–0.1 mg/kg/day; acute exposure) exist for the Pacific razor clam; however, fisheries currently do not have regulatory limits for chronic low-level exposure to DA even though razor clams can retain DA for over a year after an algal bloom. For bivalves, exposure to marine toxins may disrupt important cellular processes, leading to concerns about effects on their overall health and potential population- and ecosystem-level impacts. Transcriptomics was used to identify differentially expressed genes in razor clams (N = 30) from Long Beach, WA, collected prior to, during, and after a DA-producing bloom. Differentially expressed genes were identified that may indicate exposure of razor clams to DA, including clams with tissue DA concentrations that fall below regulatory limits for human consumption. Targeting these genes in real-time PCR assays may provide an early warning system for routine monitoring of DA in clams. Our results suggest DA exposure is associated with physiological responses ranging from decreased immune function to the potential disruption of cell communication, including retinoic acid catabolic processes, cell adhesion, collagen fibril organization, and immune effector processes. This work may also allow us to examine potential drivers of population-level change and whether chronic lower-level exposure to DA negatively impacts razor clam function, consequently affecting individual and population health.
","language":"English","publisher":"MDPI","doi":"10.3390/toxins17040194","usgsCitation":"Bowen, L., Waters-Dynes, S.C., Ballachey, B., Coletti, H., Forster, Z., Li, J., and Jenner, B., 2025, Transcriptomics as an early warning of domoic acid exposure in Pacific razor clams (Siliqua patula): Toxins, v. 17, no. 4, 194, 21 p., https://doi.org/10.3390/toxins17040194.","productDescription":"194, 21 p.","ipdsId":"IP-175527","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490137,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/toxins17040194","text":"Publisher Index Page"},{"id":486224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waters-Dynes, Shannon C. 0000-0002-9707-4684 swaters@usgs.gov","orcid":"https://orcid.org/0000-0002-9707-4684","contributorId":5826,"corporation":false,"usgs":true,"family":"Waters-Dynes","given":"Shannon","email":"swaters@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballachey, Brenda 0000-0003-1855-9171","orcid":"https://orcid.org/0000-0003-1855-9171","contributorId":264735,"corporation":false,"usgs":false,"family":"Ballachey","given":"Brenda","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":937819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coletti, Heather","contributorId":258849,"corporation":false,"usgs":false,"family":"Coletti","given":"Heather","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":937820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Forster, Zachary","contributorId":355634,"corporation":false,"usgs":false,"family":"Forster","given":"Zachary","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":937821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Ji","contributorId":22916,"corporation":false,"usgs":true,"family":"Li","given":"Ji","email":"","affiliations":[],"preferred":false,"id":937822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jenner, Bradley","contributorId":355636,"corporation":false,"usgs":false,"family":"Jenner","given":"Bradley","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":937823,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70273122,"text":"70273122 - 2025 - Multi-Scale Graph Learning for anti-sparse downscaling","interactions":[],"lastModifiedDate":"2025-12-16T16:51:11.338092","indexId":"70273122","displayToPublicDate":"2025-04-11T10:46:24","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Multi-Scale Graph Learning for anti-sparse downscaling","docAbstract":"Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e., fine scales, ≤ 1 km) enables precise interventions to maintain water quality and protect aquatic habitats. Although spatiotemporal models have made substantial progress in spatially coarse time series modeling, challenges persist in predicting at fine spatial scales due to the lack of data at that scale. To address the problem of insufficient fine-scale data, we propose a Multi-Scale Graph Learning (MSGL) method. This method employs a multi-task learning framework where coarse-scale graph learning, bolstered by larger datasets, simultaneously enhances fine-scale graph learning. Although existing multi-scale or multi-resolution methods integrate data from different spatial scales, they often overlook the spatial correspondences across graph structures at various scales. To address this, our MSGL introduces an additional learning task, cross-scale interpolation learning, which leverages the hydrological connectedness of stream locations across coarse- and fine-scale graphs to establish cross-scale connections, thereby enhancing overall model performance. Furthermore, we have broken free from the mindset that multi-scale learning is limited to synchronous training by proposing an Asynchronous Multi-Scale Graph Learning method (ASYNC-MSGL). Extensive experiments demonstrate the state-of-the-art performance of our method for anti-sparse downscaling of daily stream temperatures in the Delaware River Basin, USA, highlighting its potential utility for water resources monitoring and management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the AAAI conference on artificial intelligence","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Association for the Advancement of Artificial Intelligence","doi":"10.1609/aaai.v39i27.35014","usgsCitation":"Fan, Y., Yu, R., Barclay, J.R., Appling, A.P., Sun, Y., Xie, Y., and Jia, X., 2025, Multi-Scale Graph Learning for anti-sparse downscaling, in Proceedings of the AAAI conference on artificial intelligence, v. 39, no. 27, p. 27969-27977, https://doi.org/10.1609/aaai.v39i27.35014.","productDescription":"9 p.","startPage":"27969","endPage":"27977","ipdsId":"IP-167502","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":497731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1609/aaai.v39i27.35014","text":"Publisher Index Page"},{"id":497583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"27","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Yingda","contributorId":352470,"corporation":false,"usgs":false,"family":"Fan","given":"Yingda","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Runlong 0000-0003-4080-2377","orcid":"https://orcid.org/0000-0003-4080-2377","contributorId":352471,"corporation":false,"usgs":false,"family":"Yu","given":"Runlong","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":952394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Yiming","contributorId":352472,"corporation":false,"usgs":false,"family":"Sun","given":"Yiming","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":952396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":952397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266250,"text":"70266250 - 2025 - Detection of Giardia and Cryptosporidium in surface water of a subarctic city","interactions":[],"lastModifiedDate":"2025-05-02T14:34:36.525786","indexId":"70266250","displayToPublicDate":"2025-04-11T09:31:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16699,"text":"Food and Waterborne Parasitology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Detection of Giardia and Cryptosporidium in surface water of a subarctic city","title":"Detection of Giardia and Cryptosporidium in surface water of a subarctic city","docAbstract":"Giardia and Cryptosporidium spp. are globally distributed protozoan parasites that can cause gastrointestinal disease in humans and animals. These zoonotic parasites and their ecological relationships have been understudied in Alaska and elsewhere, despite being identified as priority zoonotic pathogens. We aimed to detect and characterize Giardia and Cryptosporidium spp. in waterbodies within Anchorage, Alaska, USA using two methods, including the Environmental Protection Agency (EPA) Method 1623 that relies on microscopy and a molecular detection approach. The molecular approach was ultimately unsuccessful and therefore only data obtained using Method 1623 are presented. Giardia or Cryptosporidium spp. was detected from nine of 15 urban streams and lakes sampled (60%), six of which were positive for both parasites (40%). Fewer than 10 cysts or oocysts were detected in 10 L of surface water. Further research to characterize Giardia and Cryptosporidium beyond the genus level would help elucidate the zoonotic potential and ecology of these parasites within the region and more broadly in Alaska.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fawpar.2025.e00262","usgsCitation":"Ahlstrom, C., Carey, M.P., Menning, D.M., O’Donnell, J.A., and Ramey, A.M., 2025, Detection of Giardia and Cryptosporidium in surface water of a subarctic city: Food and Waterborne Parasitology, v. 39, e00262, 6 p., https://doi.org/10.1016/j.fawpar.2025.e00262.","productDescription":"e00262, 6 p.","ipdsId":"IP-173920","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":487921,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fawpar.2025.e00262","text":"Publisher Index Page"},{"id":485323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.71809212582164,\n 61.26288495513296\n ],\n [\n -150.13097003492274,\n 61.26288495513296\n ],\n [\n -150.13097003492274,\n 61.05787266884491\n ],\n [\n -149.71809212582164,\n 61.05787266884491\n ],\n [\n -149.71809212582164,\n 61.26288495513296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":935084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":935085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menning, Damian M. 0000-0003-3547-3062 dmenning@usgs.gov","orcid":"https://orcid.org/0000-0003-3547-3062","contributorId":205131,"corporation":false,"usgs":true,"family":"Menning","given":"Damian","email":"dmenning@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":935086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":935087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":935088,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265768,"text":"70265768 - 2025 - Development of a genotyping-in-thousands by sequencing (GT-seq) panel for identifying individuals and estimating relatedness among Alaska black bears (Ursus americanus)","interactions":[],"lastModifiedDate":"2025-04-15T14:34:50.502337","indexId":"70265768","displayToPublicDate":"2025-04-11T09:30:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Development of a genotyping-in-thousands by sequencing (GT-seq) panel for identifying individuals and estimating relatedness among Alaska black bears (Ursus americanus)","title":"Development of a genotyping-in-thousands by sequencing (GT-seq) panel for identifying individuals and estimating relatedness among Alaska black bears (Ursus americanus)","docAbstract":"The management and conservation of large mammals, such as black bears (Ursus americanus), have long been informed by genetic estimates of population size and individual dispersal. Amplicon sequencing methods, also known as ‘genotyping-in-thousands-by sequencing’ (GT-seq), now enable the efficient and cost-effective genotyping of hundreds of loci and individuals in the same sequencing run. Here, we develop a GT-seq panel for individual identification and kinship inference in Alaska black bears. Using genomic data from restriction site-associated DNA sequencing of hunter-harvested bears from Southcentral Alaska (n = 85), we identified 170 microhaplotype and single nucleotide polymorphism (SNP) loci that were highly heterozygous in local populations. To enable sexing of individuals, we also included a previously published sex-linked locus in the GT-seq panel. We empirically validated the GT-seq panel using samples collected at different spatial scales. These samples included tissues (n = 82) obtained from bears within a small geographic area in Anchorage, Alaska, which were likely to be relatives as well as the hunter-harvested samples collected from geographically widespread locations throughout Southcentral Alaska. Empirical validation indicated high genotyping success and genotype reproducibility across replicate subsamples. Computer simulations demonstrated that the GT-seq panel had ample statistical power for distinguishing distinct individuals and first-order relatives (parent-offspring and full-sibling pairs) from unrelated individuals. As a final proof of concept, the panel was used to identify individual bears and close kin sampled from urban and wild habitats in Anchorage, Alaska. We anticipate that the GT-seq panel will be a useful genomic resource for the monitoring and management of Alaska black bear populations.ons.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71273","usgsCitation":"Petrou, E., Brandt, C., Spivey, T., Gruenthal, K., Mckeeman, C.M., Farley, S.D., Battle, D., Stantorf, C., and Ramey, A.M., 2025, Development of a genotyping-in-thousands by sequencing (GT-seq) panel for identifying individuals and estimating relatedness among Alaska black bears (Ursus americanus): Ecology and Evolution, v. 15, no. 4, e71273, 13 p., https://doi.org/10.1002/ece3.71273.","productDescription":"e71273, 13 p.","ipdsId":"IP-173133","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":488245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71273","text":"Publisher Index Page"},{"id":484575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -144.37908579144883,\n 60.1880549532429\n ],\n [\n -145.33789769841525,\n 61.28084387847426\n ],\n [\n -147.5603688778254,\n 61.761383856172614\n ],\n [\n -150.36520049953535,\n 61.47257901289217\n ],\n [\n -151.5611076733203,\n 60.44966814671875\n ],\n [\n -152.16087869317707,\n 59.10929453238546\n ],\n [\n -150.57556260378138,\n 59.05220379442184\n ],\n [\n -144.37908579144883,\n 60.1880549532429\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrou, Eleni Leto 0000-0001-7811-9288","orcid":"https://orcid.org/0000-0001-7811-9288","contributorId":334653,"corporation":false,"usgs":true,"family":"Petrou","given":"Eleni Leto","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":933480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Colette D.","contributorId":353400,"corporation":false,"usgs":false,"family":"Brandt","given":"Colette D.","affiliations":[{"id":84395,"text":"Department of the Air Force","active":true,"usgs":false}],"preferred":false,"id":933481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spivey, Timothy J.","contributorId":353401,"corporation":false,"usgs":false,"family":"Spivey","given":"Timothy J.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gruenthal, Kristen M.","contributorId":353402,"corporation":false,"usgs":false,"family":"Gruenthal","given":"Kristen M.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mckeeman, Cherie Marie 0000-0001-9868-2502","orcid":"https://orcid.org/0000-0001-9868-2502","contributorId":334651,"corporation":false,"usgs":true,"family":"Mckeeman","given":"Cherie","email":"","middleInitial":"Marie","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":933484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farley, Sean D.","contributorId":340801,"corporation":false,"usgs":false,"family":"Farley","given":"Sean","email":"","middleInitial":"D.","affiliations":[{"id":81667,"text":"Alaska Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":933485,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Battle, David","contributorId":353403,"corporation":false,"usgs":false,"family":"Battle","given":"David","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933486,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stantorf, Cory","contributorId":353404,"corporation":false,"usgs":false,"family":"Stantorf","given":"Cory","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933487,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":933488,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70265519,"text":"ofr20251005 - 2025 - Managing for tomorrow—A climate adaptation decision framework","interactions":[],"lastModifiedDate":"2025-08-07T20:50:42.059957","indexId":"ofr20251005","displayToPublicDate":"2025-04-11T06:43:43","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1005","displayTitle":"Managing for Tomorrow—A Climate Adaptation Decision Framework","title":"Managing for tomorrow—A climate adaptation decision framework","docAbstract":"Climate change presents new and compounding challenges to natural resource management. With changing climate patterns, managers are confronted with difficult decisions on how to minimize climate effects on habitats, infrastructure, and wildlife populations. To support climate adaptation decision making, we first conceptualized an approach that integrates the principles of the resist–accept–direct framework, climate scenario planning, and decision analysis into a general framework to support adaptation planning. This framework was implemented and refined by working with three National Wildlife Refuge System refuges within the Midwest Region. The objectives of this report are to describe the climate adaptation decision framework and provide guidance for how to apply the framework to support transparent, consistent, and decision-focused adaptation planning. We include a workbook to support the application of each step of the framework as well as lessons learned from our experiences developing the framework. The climate adaptation decision framework has wide applicability to aid adaptation planning within natural resource management and underscores the important role of engaging interest groups in climate adaptation decisions.
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\"}}]}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km2) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m2) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points (n=870) during active mapping and accuracy assessment points (n=216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones.
The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251010","usgsCitation":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Stone, K., Silva, I., Martinez, T., Peralto, C., Levine, A.S., Stow, D., and Maloney, J., 2025, Benthic Habitat Map of Olowalu Reef, Maui, Hawaii—Geomorphological Structure, Biological Cover, and Geologic Zonation Determined with Spectral, Lidar, and Acoustic Data: U.S. Geological Survey Open-File Report 2025–1010, 32 p., https://doi.org/10.3133/ofr20251010.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-152179","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":493749,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118524.htm","linkFileType":{"id":5,"text":"html"}},{"id":484394,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ICJ7CF","text":"USGS Data Release","description":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Silva, I., Stone, K., Martinez, T., and Peralto, C., 2025, Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui: U.S. Geological Survey data release, https://doi.org/10.5066/P9ICJ7CF.","linkHelpText":"Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui"},{"id":484407,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1010/covrthb.jpg"},{"id":484408,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1010/ofr20251010.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui, Olowalu Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.66330945257621,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.84439182546096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
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No abstract available.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pcbi.1012898","usgsCitation":"Gimenez, O., Royle, A., Kéry, M., and Nater, C., 2025, Ten quick tips to get you started with Bayesian statistics: PLOS Computational Biology, v. 21, no. 4, e1012898, 13 p., https://doi.org/10.1371/journal.pcbi.1012898.","productDescription":"e1012898, 13 p.","ipdsId":"IP-171789","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1012898","text":"Publisher Index Page"},{"id":484683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Gimenez, Olivier","contributorId":352825,"corporation":false,"usgs":false,"family":"Gimenez","given":"Olivier","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":932138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":932139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kéry, Marc","contributorId":310340,"corporation":false,"usgs":false,"family":"Kéry","given":"Marc","affiliations":[{"id":67146,"text":"Swiss Ornithological Institute","active":true,"usgs":false}],"preferred":false,"id":932140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nater, Chloé","contributorId":352826,"corporation":false,"usgs":false,"family":"Nater","given":"Chloé","affiliations":[{"id":33046,"text":"Norwegian Institute for Nature Research","active":true,"usgs":false}],"preferred":false,"id":932141,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267196,"text":"70267196 - 2025 - Behavioral responses of Silver Carp to underwater acoustic deterrent sounds","interactions":[],"lastModifiedDate":"2025-05-16T15:55:02.452881","indexId":"70267196","displayToPublicDate":"2025-04-10T10:51:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Behavioral responses of Silver Carp to underwater acoustic deterrent sounds","docAbstract":"Invasive carps continue to spread across the Mississippi River basin, posing significant ecological risk. Identifying technologies to slow their dispersal is critical. The use of sound has been proposed as a method to modify the behavior of Silver Carp Hypophthalmichthys molitrix, offering a nonstructural deterrent strategy.
Silver Carp implanted with acoustic transmitters were released into earthen ponds equipped with telemetry arrays. The fish were exposed to a 30-min playback of three underwater sounds (chirp saw, chirp square, and 100-hp boat motor). Movement trajectories were analyzed using a two-state hidden Markov model to estimate the effects of environmental and experimental variables on fish behavior.
The results of the hidden Markov model supported two behavioral states. State 1 was characterized by longer step lengths (distance between positions) and greater directional persistence in turning angle (change in direction between two intervals), indicative of heighted activity. State 2 was defined by shorter step lengths and less directional persistence, suggesting reduced activity. Silver Carp that were exposed to the chirp square sound had an increased likelihood of entering state 1, whereas the 100-hp boat motor sound promoted transitions to state 2.
Underwater sounds distinctly influenced the movement of Silver Carp in earthen ponds. The chirp square sound elicited heightened activity levels, demonstrating potential for use in acoustic deterrent applications. However, the response of Silver Carp to these sounds may be influenced by the size of the study environment or the absence of natural drivers of fish behavior, such as food or reproduction. This study contributes to the development of nonstructural, species-specific deterrent systems by identifying sounds that influence the behavior of invasive carps. The application of sound-based methods may play a critical role in integrated pest management strategies for invasive carps, potentially limiting their spread while minimizing effects on native species.
Infrastructure along the U.S.-Mexico Border may not be equally permeable to all types of insect pollinators with potential implications for pollen and gene flow between plant populations. Pollinators were observed on their approach to two types of border barriers (slatted and cemented) along the U.S.-Mexico Border from March 2023 to January 2024. Near the barrier, four insect behaviors were observed including 1) flying over the barrier, 2) crossing through the slats of the barrier, 3) not crossing the barrier, or 4) flying parallel to the barrier without crossing. Overall, 90.2% of the pollinators crossed the barrier. Butterflies were most often observed flying over the barrier (86.8%) or sometimes moving through the slats in the barrier (6.8%). It was more common for moths to crawl through the slats than to fly over the barrier based on the occurrence model. On windy days, both butterflies and moths sometimes flew parallel to the barrier without crossing (1.2% and 27.3%, respectively), although moth crossing behavior was not related to the abundance model. Butterfly abundance increased in higher temperatures and decreased in higher wind speeds. Other insect pollinators were also observed (bee, skipper, wasp) but their crossing behavior was not significantly related to the model. Because pollinators support endangered plant species, strategies to facilitate their barrier crossing could support plant conservation in South Texas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113421","usgsCitation":"Middleton, B., 2025, Insect pollinator crossing of international border barriers along the U.S.-Mexico border: Ecological Indicators, v. 174, 113421, 6 p., https://doi.org/10.1016/j.ecolind.2025.113421.","productDescription":"113421, 6 p.","ipdsId":"IP-168032","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113421","text":"Publisher Index Page"},{"id":484840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"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 -98.55875994836624,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.271404139036903\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.13781819292579,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.51105231424154\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"174","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934236,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70265692,"text":"70265692 - 2025 - Identifying preferential flow from soil moisture time series: Review of methodologies","interactions":[],"lastModifiedDate":"2025-04-14T16:18:34.093186","indexId":"70265692","displayToPublicDate":"2025-04-10T09:14:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Identifying preferential flow from soil moisture time series: Review of methodologies","docAbstract":"Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially-distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods, to highlight important information for readers who want to identify PF from soil moisture data, and to inform those who aim to develop new methods or improve existing ones.","language":"English","publisher":"Soil Science Society of America","doi":"10.1002/vzj2.70017","usgsCitation":"Nimmo, J.R., Wiekenkamp, I., Araki, R., Groh, J., Singh, N., Crompton, O., Wyatt, B., Ajami, H., Gimenez, D., Hirmas, D., Sullivan, P., and Sprenger, M., 2025, Identifying preferential flow from soil moisture time series: Review of methodologies: Vadose Zone Journal, v. 24, no. 2, e70017, 25 p., https://doi.org/10.1002/vzj2.70017.","productDescription":"e70017, 25 p.","ipdsId":"IP-175711","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/vzj2.70017","text":"Publisher Index Page"},{"id":484511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":933270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiekenkamp, Inge","contributorId":353318,"corporation":false,"usgs":false,"family":"Wiekenkamp","given":"Inge","affiliations":[{"id":52961,"text":"GFZ Potsdam","active":true,"usgs":false}],"preferred":false,"id":933271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Araki, Ryoko","contributorId":353321,"corporation":false,"usgs":false,"family":"Araki","given":"Ryoko","affiliations":[{"id":84355,"text":"San Diego State U","active":true,"usgs":false}],"preferred":false,"id":933272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Groh, Jannis","contributorId":353322,"corporation":false,"usgs":false,"family":"Groh","given":"Jannis","affiliations":[{"id":84358,"text":"Agrosphere Institute, Jülich, Germany","active":true,"usgs":false}],"preferred":false,"id":933273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Nitin","contributorId":353323,"corporation":false,"usgs":false,"family":"Singh","given":"Nitin","affiliations":[{"id":84359,"text":"Auburn U","active":true,"usgs":false}],"preferred":false,"id":933274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crompton, Octavia","contributorId":353324,"corporation":false,"usgs":false,"family":"Crompton","given":"Octavia","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":933275,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wyatt, Briana","contributorId":353325,"corporation":false,"usgs":false,"family":"Wyatt","given":"Briana","affiliations":[{"id":84360,"text":"Texas A&M U","active":true,"usgs":false}],"preferred":false,"id":933276,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ajami, Hoori 0000-0001-6883-7630","orcid":"https://orcid.org/0000-0001-6883-7630","contributorId":303806,"corporation":false,"usgs":false,"family":"Ajami","given":"Hoori","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":933277,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gimenez, Daniel","contributorId":353326,"corporation":false,"usgs":false,"family":"Gimenez","given":"Daniel","affiliations":[{"id":84361,"text":"Rutgers U","active":true,"usgs":false}],"preferred":false,"id":933278,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hirmas, Daniel","contributorId":353327,"corporation":false,"usgs":false,"family":"Hirmas","given":"Daniel","affiliations":[{"id":49949,"text":"Texas Tech U","active":true,"usgs":false}],"preferred":false,"id":933279,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sullivan, Pamela","contributorId":190446,"corporation":false,"usgs":false,"family":"Sullivan","given":"Pamela","affiliations":[],"preferred":false,"id":933280,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sprenger, Matthias 0000-0003-1221-2767","orcid":"https://orcid.org/0000-0003-1221-2767","contributorId":344277,"corporation":false,"usgs":false,"family":"Sprenger","given":"Matthias","email":"","affiliations":[{"id":82324,"text":"Lawrence Berkley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":933281,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70266197,"text":"70266197 - 2025 - Seasonal stratification drives bioaccumulation of pelagic mercury sources in eutrophic lakes","interactions":[],"lastModifiedDate":"2025-05-12T15:49:36.887814","indexId":"70266197","displayToPublicDate":"2025-04-10T08:26:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10071,"text":"Environmental Science and Technology Water","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal stratification drives bioaccumulation of pelagic mercury sources in eutrophic lakes","docAbstract":"Increased lake eutrophication, influenced by changing climate and land use, alters aquatic cycling and bioaccumulation of mercury (Hg). Additionally, seasonally dynamic lake circulation and plankton community composition can confound our ability to predict changes in biological Hg concentrations and sources. To assess temporal variation, we examined seasonal total Hg (THg) and methylmercury (MeHg) concentrations and stable isotope values in seston, waters, sediments, and fish from two adjacent urban eutrophic lakes in Madison, Wisconsin. In Lake Monona, surface sediment THg concentrations were elevated due to comparably higher urbanization and historical industrial inputs, whereas Lake Mendota sediments had lower concentrations corresponding with largely agricultural and suburban surrounding watershed. Surface water THg and MeHg were similar between lakes and seasonally dynamic, but water profiles exhibited elevated concentrations in the meta- and hypolimnion, highlighting water column MeHg production. Seston MeHg concentrations were often highest at shoulder seasons, possibly owing to metalimnetic MeHg delivery, but also differences in biomass and water clarity. The ∆199Hg and δ202Hg values in seston were similar between lakes, despite differing sediment THg concentrations and values, suggesting a shared bioaccumulated source of MeHg. Measurement of MeHg stable isotopes further elucidated that seston and fish predominantly bioaccumulated pelagic-sourced MeHg.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsestwater.5c00028","usgsCitation":"Armstrong, G.J., Janssen, S.E., Lepak, R.F., Rosera, T., Peterson, B.D., Cushing, S., Tate, M., and Hurley, J.W., 2025, Seasonal stratification drives bioaccumulation of pelagic mercury sources in eutrophic lakes: Environmental Science and Technology Water, v. 5, no. 5, p. 2444-2454, https://doi.org/10.1021/acsestwater.5c00028.","productDescription":"11 p.","startPage":"2444","endPage":"2454","ipdsId":"IP-168185","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":490115,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.5c00028","text":"Publisher Index Page"},{"id":485207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lake Mendota, Lake Monona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.48912579234224,\n 43.156751915482516\n ],\n [\n -89.48912579234224,\n 43.044667453665085\n ],\n [\n -89.32306507311453,\n 43.044667453665085\n ],\n [\n -89.32306507311453,\n 43.156751915482516\n ],\n [\n -89.48912579234224,\n 43.156751915482516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Armstrong, Grace Jane 0009-0009-8132-9011","orcid":"https://orcid.org/0009-0009-8132-9011","contributorId":332127,"corporation":false,"usgs":true,"family":"Armstrong","given":"Grace","email":"","middleInitial":"Jane","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah Elizabeth 0000-0002-5723-1112","orcid":"https://orcid.org/0000-0002-5723-1112","contributorId":261232,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah","email":"","middleInitial":"Elizabeth","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lepak, Ryan F. rlepak@usgs.gov","contributorId":5784,"corporation":false,"usgs":true,"family":"Lepak","given":"Ryan","email":"rlepak@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":934889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosera, Tylor 0000-0002-3611-4654","orcid":"https://orcid.org/0000-0002-3611-4654","contributorId":221507,"corporation":false,"usgs":true,"family":"Rosera","given":"Tylor","email":"","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":934891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cushing, Samia T.","contributorId":353978,"corporation":false,"usgs":false,"family":"Cushing","given":"Samia T.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":934892,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tate, Michael 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":216029,"corporation":false,"usgs":true,"family":"Tate","given":"Michael","email":"mttate@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934893,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hurley, James W.","contributorId":23659,"corporation":false,"usgs":true,"family":"Hurley","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":934894,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70265538,"text":"70265538 - 2025 - Costs of land treatments on public lands in the western United States","interactions":[],"lastModifiedDate":"2025-04-14T15:22:33.402206","indexId":"70265538","displayToPublicDate":"2025-04-10T08:05:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Costs of land treatments on public lands in the western United States","docAbstract":"Public land managers often conduct rehabilitation and restoration actions to achieve desired conditions or specific natural resource objectives. These “land treatments” include a variety of techniques, such as biomass removal or manipulation, seeding, and herbicide application. Limited information exists on the costs of conducting many common types of land treatments, but such information can be paired with treatment effectiveness data to prioritize application of limited resources where they may have the greatest benefit and improve efficiency. Here, we investigated cost information recorded in the Land Treatment Digital Library, a catalog of legacy land treatment information on public lands managed by the U.S. Department of the Interior's Bureau of Land Management. Based on 1,701 treatment records across eleven western U.S. states, we developed empirical per-acre cost estimates for representative land treatments in eight categories: three seeding categories (aerial seeding, drill seeding, and seedling planting), prescribed burning, soil disturbance, soil stabilization, vegetation disturbance, and weed control. We evaluated spatio-temporal factors that may be associated with variation in treatment costs and found strong evidence for nonlinear decreases in per-acre costs as treatment areas increased and that per-acre treatment costs have increased in real terms in recent decades. We also found evidence that per-acre costs for drill seeding, prescribed burns, and soil stabilization increased with the average slope of the terrain of a treated area and that per-acre costs for prescribed burns, seedling planting, and soil stabilization were influenced by distance to urban areas or major roads. These results can inform planning, prioritization, and assessment of common land treatments on public lands in the western United States, in particular supporting greater consideration of costs and cost effectiveness.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2025.03.004","usgsCitation":"Meldrum, J., Huber, C., Monroe, A., Tarbox, B.C., Jeffries, M.I., Pilliod, D., and Aldridge, C.L., 2025, Costs of land treatments on public lands in the western United States: Rangeland Ecology & Management, v. 100, p. 99-110, https://doi.org/10.1016/j.rama.2025.03.004.","productDescription":"12 p.","startPage":"99","endPage":"110","ipdsId":"IP-167666","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2025.03.004","text":"Publisher Index Page"},{"id":484501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tarbox, Bryan C. 0000-0001-5040-3949","orcid":"https://orcid.org/0000-0001-5040-3949","contributorId":288930,"corporation":false,"usgs":true,"family":"Tarbox","given":"Bryan","email":"","middleInitial":"C.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jeffries, Michelle I. 0000-0003-1146-1331","orcid":"https://orcid.org/0000-0003-1146-1331","contributorId":202734,"corporation":false,"usgs":true,"family":"Jeffries","given":"Michelle","middleInitial":"I.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":932981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pilliod, David 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":218009,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":932982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":932983,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268494,"text":"70268494 - 2025 - Source and longevity of streambed sediment and phosphorus retention in a lake-plain tributary of the Maumee River","interactions":[],"lastModifiedDate":"2025-06-27T15:08:21.348892","indexId":"70268494","displayToPublicDate":"2025-04-10T08:02:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Source and longevity of streambed sediment and phosphorus retention in a lake-plain tributary of the Maumee River","docAbstract":"We described abundance and source of soft, fine-grained, streambed sediment and associated phosphorus (sed-P) during summer low flow in Little Flatrock Creek (LFR), a channelized tributary of the Maumee River and western Lake Erie. Reach-level assessments compared streambed-sediment storage to streambank erosion. Streambed sediment was fingerprinted and analyzed for sed-P and the potential for P de/sorption between the water column and streambed sediment. The ratio of two fallout radionuclides apportioned “new sediment” in streambed storage. Basin-wide streambed-sediment storage exceeded both annual streambank erosion and the annual suspended-sediment load. Streambed sediment was generally a mix of streambank and cropland sources and each equaled or exceeded abundance of new streambed sediment, indicating accumulation of sediment from both sources during the current agricultural cycle. The implication is that this mix of new and old sediment, and legacy P, takes multiple events and seasons to be transported downstream. Streambed sediment had the potential to adsorb dissolved P (DP) from the water column, with sed-P stored in the silt + clay fraction similar to the annual particulate-P (total-dissolved) load transported with suspended sediment, but with lower concentrations than cropland- and streambank-sourced sediment. This indicates supplementation of water-column DP as sediment settles to the bottom and a lag between land and channel management and in-channel P availability. Storage of fine-grained sediment and sed-P in this lake-plain/bed basin is distinct from another Maumee headwater tributary with glacial-moraine controlled geomorphology. The implication is that streambank erosion, in-channel sediment accumulation, and the resultant total-dissolved-sediment P spiral differ based on geomorphic setting and drainage history.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2025.102575","usgsCitation":"Williamson, T.N., Fitzpatrick, F., Karwan, D.L., Kreiling, R., Blount, J.D., and Hoefling, D., 2025, Source and longevity of streambed sediment and phosphorus retention in a lake-plain tributary of the Maumee River: Journal of Great Lakes Research, v. 51, no. 3, 102575, 15 p., https://doi.org/10.1016/j.jglr.2025.102575.","productDescription":"102575, 15 p.","ipdsId":"IP-164999","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":500570,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2025.102575","text":"Publisher Index Page"},{"id":491529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana, Michigan, Ohio","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.0894114295611,\n 42.07777840323945\n ],\n [\n -85.0894114295611,\n 41.06596068951595\n ],\n [\n -84.12029299352434,\n 41.06596068951595\n ],\n [\n -84.12029299352434,\n 42.07777840323945\n ],\n [\n -85.0894114295611,\n 42.07777840323945\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209588,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":941511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kreiling, Rebecca 0000-0002-9295-4156 rkreiling@usgs.gov","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":147679,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","email":"rkreiling@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":941569,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941512,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoefling, Dayle Jordan 0000-0002-2004-3142","orcid":"https://orcid.org/0000-0002-2004-3142","contributorId":304442,"corporation":false,"usgs":true,"family":"Hoefling","given":"Dayle Jordan","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941513,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265711,"text":"70265711 - 2025 - Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","interactions":[],"lastModifiedDate":"2025-04-15T15:03:17.346697","indexId":"70265711","displayToPublicDate":"2025-04-10T07:58:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","docAbstract":"The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNdi = ‐2.2 ± 0.8) and zircon Lu-Hf (εHfi = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHfi in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2025.108060","usgsCitation":"Benson, E.K., Watts, K., and Hillenbrand, I.W., 2025, Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California: LITHOS, v. 508-509, 108060, 18 p., https://doi.org/10.1016/j.lithos.2025.108060.","productDescription":"108060, 18 p.","ipdsId":"IP-173126","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.lithos.2025.108060","text":"Publisher Index Page"},{"id":484582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.29333455287775,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 36.19312110709426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"508-509","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265433,"text":"fs20243051 - 2025 - Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023","interactions":[],"lastModifiedDate":"2025-08-07T20:41:25.073086","indexId":"fs20243051","displayToPublicDate":"2025-04-09T11:40:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3051","displayTitle":"Assessment of Undiscovered Oil and Gas Resources of the Los Angeles Basin Province, 2023","title":"Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 61 million barrels of oil and 240 billion cubic feet of gas in the Los Angeles Basin Province.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243051","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Tennyson, M.E., Mercier, T.J., Le, P.A., Cicero, A.D., Drake, R.M., II, Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., and Timm, K.K., 2025, Assessment of undiscovered oil and gas resources of the Los Angeles Basin Province, 2023: U.S. Geological Survey Fact Sheet 2024–3051, 4 p., https://doi.org/10.3133/fs20243051.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-157105","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":493748,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118519.htm","linkFileType":{"id":5,"text":"html"}},{"id":484350,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3051/images"},{"id":484349,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P148FWYT","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Los Angeles Basin Province: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":484393,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243051/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3051"},{"id":484351,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3051/fs20243051.xml"},{"id":484194,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3051/coverthb.jpg"},{"id":484195,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3051/fs20243051.pdf","text":"Report","size":"720 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3051"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.46009478730042,\n 33.23344855361785\n ],\n [\n -117.32296349710847,\n 34.45004669658452\n ],\n [\n -118.16445095964868,\n 34.54765057900826\n ],\n [\n -118.9934719412617,\n 34.38834329310062\n ],\n [\n -119.62926246851423,\n 34.37291032933257\n ],\n [\n -120.4458169692015,\n 34.44490648556631\n ],\n [\n -120.67021362587857,\n 34.45004669658452\n ],\n [\n -119.3736996095206,\n 34.151392287418204\n ],\n [\n -118.6007777920766,\n 33.84650135234095\n ],\n [\n -118.17691744057491,\n 33.58207150936819\n ],\n [\n -117.46009478730042,\n 33.23344855361785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
We investigated how visitors to federal, state, and local parks and protected areas (PPAs) respond to weather and air quality conditions in the Pacific Northwest (PNW), United States. Specifically, we modeled the relationship between weekly visitation and mean weekly minimum and maximum temperature, precipitation, Air Quality Index (AQI), and particulate matter 2.5 concentration (PM2.5, often used as an indicator of wildfire smoke) during an extended peak visitation season from 2017 to 2021 in 91 PNW PPAs. We used mobile device data from StreetLight Data Inc. to estimate weekly vehicular visitation. Our findings indicate that increasing precipitation corresponded with decreased weekly visitation to all three types of PPAs and rising minimum temperatures corresponded with increased visitation. We found that rising maximum temperatures corresponded with increased visitation in federal and local PPAs, but corresponded with decreased visitation in local PPAs once temperatures reach a maximum threshold. We did not observe a maximum threshold effect in federal or state settings. Further, we found that the effect of air quality and smoke on visitation varies based on the metric used: increased PM2.5 concentrations (possibly indicating the presence of wildfire smoke) in federal and local PPAs corresponded with decreased visitation, while increased AQI in federal PPAs corresponded with increased visitation. These findings indicate that visitors may respond differently to different types of air pollution. Our results have implications for adapting peak- and shoulder- season visitor use management to current and future climate change within and beyond PPAs of the PNW.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pclm.0000537","usgsCitation":"Minehart, K., D'Antonio, A., and Wilkins, E.J., 2025, The mountains are calling, but will visitors go? 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\"}}]}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Minehart, Kira 0009-0006-6007-0782","orcid":"https://orcid.org/0009-0006-6007-0782","contributorId":353124,"corporation":false,"usgs":false,"family":"Minehart","given":"Kira","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Antonio, Ashley","contributorId":353127,"corporation":false,"usgs":false,"family":"D'Antonio","given":"Ashley","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkins, Emily J. 0000-0003-3055-4808","orcid":"https://orcid.org/0000-0003-3055-4808","contributorId":328409,"corporation":false,"usgs":true,"family":"Wilkins","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":933008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265511,"text":"sir20255026 - 2025 - Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey","interactions":[],"lastModifiedDate":"2025-08-07T20:39:55.109963","indexId":"sir20255026","displayToPublicDate":"2025-04-09T10:00:00","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":"2025-5026","displayTitle":"Time of Travel of Releases From Lake Wallenpaupack to the U.S. Geological Survey’s Streamgage Monitoring Location on the Delaware River at Montague, New Jersey","title":"Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey","docAbstract":"In 2016, the U.S. Geological Survey (USGS) carried out a hydraulic study within the upper Delaware River Basin for the purpose of determining the time of travel for water releases from the Brookfield Renewable U.S. hydroelectric plant at Lake Wallenpaupack, Pennsylvania, to reach the USGS streamgage located on the Delaware River at Montague, New Jersey (site number 01438500). From September 19 to October 14, 2016, Brookfield Renewable initiated repeated releases of approximately 650 cubic feet per second (ft3/s) and 1,440 ft3/s. Hydraulic signals from the releases were tracked at nine key locations between Lake Wallenpaupack and the USGS streamgage at Montague, New Jersey (01438500). Gage height data were recorded at streamgages at major confluences of the Lackawaxen and Delaware Rivers, Mongaup and Delaware Rivers, and the Neversink and Delaware Rivers. The time of travel to the USGS streamgage at Montague, New Jersey, was determined to be 1,185 minutes during the approximately 650 ft3/s releases and 960 minutes during the approximately 1,440 ft3/s releases. Elevated streamflow between Lake Wallenpaupack and the Montague streamgage from runoff events prior to the dam releases was found to decrease calculated time of travel identified during the study. The results from this study can be used as a guide to estimate time of travel while considering the water level of downstream streamflow, the volume of water being released, and other outside influences, such as precipitation and snowmelt.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255026","collaboration":"Prepared in cooperation with the Office of the Delaware River Master","usgsCitation":"Polcino, J., Trainor, J.J., and Collenburg, J.V., 2025, Time of travel of releases from Lake Wallenpaupack to the U.S. Geological Survey’s streamgage monitoring location on the Delaware River at Montague, New Jersey: U.S. Geological Survey Scientific Investigations Report 2025–5026, 20 p., https://doi.org/10.3133/sir20255026.","productDescription":"vii, 20 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-150895","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":484348,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5026/images/"},{"id":484347,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5026/sir20255026.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5026 XML"},{"id":484346,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255026/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5026 HTML"},{"id":484345,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5026/sir20255026.pdf","text":"Report","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5026 PDF"},{"id":484344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5026/coverthb.jpg"},{"id":493747,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118518.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River, Lake Wallenpaupack","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.28276534144987,\n 41.608544510962616\n ],\n [\n -75.28276534144987,\n 41.13145977502657\n ],\n [\n -74.30523052576332,\n 41.13145977502657\n ],\n [\n -74.30523052576332,\n 41.608544510962616\n ],\n [\n -75.28276534144987,\n 41.608544510962616\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The impoundment of Lake Conroe in 1973 created an important water resource for greater Houston, Texas. The U.S. Geological Survey, in cooperation with the San Jacinto River Authority, analyzed water-quality data collected from 1974 to 2021 at upreservoir, mid-reservoir, and downreservoir sites in Lake Conroe. Water-column and seasonal variability of selected water-quality constituents (physiochemical properties, major ions, nutrients, and trace metals) were assessed, as well as thermal stratification. Water-quality trends were evaluated for 1974–2021 and 1993–2021.
Near-surface water (1–3 feet below the water surface) was warmer and contained higher dissolved-oxygen concentrations compared to near-bottom water (2–3 feet above the reservoir bottom). Dissolved-oxygen concentrations were lowest in summer and highest in winter. Specific conductance was higher near the bottom and varied seasonally, being lowest in winter and highest in summer. Values of pH were generally higher at the surface, with some variability between sites and seasons. Water transparency was higher downreservoir and seasonally lowest in summer.
Major-ion concentrations varied minimally within the water column and seasonally, except for sulfate, which was higher in winter and lower in summer. Most nutrient and trace metal concentrations were highest near the bottom during summer, notably at deeper sites. Thermal stratification in Lake Conroe begins in spring and peaks in summer and was limited to the deeper parts of the reservoir. The seasonal variability observed in dissolved constituent concentrations was driven by thermal stratification. Trend analyses for 1974–2021 indicated positive trends in water temperature, dissolved oxygen, pH, potassium, sodium, and silica. Negative trends were detected for calcium and magnesium near the reservoir bottom. During 1993–2021, positive trends were detected for near-surface dissolved-oxygen concentration, specific conductance, pH, all major ions excluding sulfate, and near-surface ammonia plus organic nitrogen concentration. Negative trends were determined for ammonia, iron, and manganese concentrations. Water transparency generally decreased over time.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"We present major and trace element whole-rock geochemistry of 94 samples from the Bronson Hill arc (BHA) and Connecticut Valley–Gaspé trough (CVGT). These data, when combined with recent zircon U-Pb geochronology and a reexamination of existing whole-rock geochemistry, enable a new analysis of the tectonic history of the ancient Laurentian-Ganderian margin in the northern Appalachians of New England, USA, and southeastern Canada. The whole-rock geochemical data from the Ordovician BHA in western New Hampshire indicate that metamorphosed extrusive and intrusive rocks share the same temporally variable geochemical fingerprint. Mafic and felsic rocks form a bimodal distribution and plot as island arc magmas on geochemical discrimination diagrams. Approximately 80% of mafic greenstone and amphibolite samples plot as island arc tholeiites with a subset of samples that trend toward a more within-plate basalt geochemical signature. Where ages are known, older felsic rocks (ca. 475–460 Ma) in the BHA tend to be more sodic and less potassic than their younger (ca. 460–445 Ma) counterparts, and the geochemical results trend from volcanic arc granites toward syn-collisional granites through time. Prior to recent geochronology, it was thought that an age gap existed between the island arc magmas and the syn collisional granites. This led to the separation of felsic plutons into the predominantly older trondhjemitic magmas assigned to the Ammonoosuc Volcanics and a younger suite of granites designated as the Oliverian Plutonic Suite. This age gap was thought to represent a flip in subduction polarity which would also account for observed changes in pluton chemistry. With the addition of more recent U-Pb isotopic age data, we now know there is a continuum of ages, and a polarity flip is no longer required. When the isotopic ages are combined with the new geochemical data presented here, they suggest that as the BHA approached and collided with Laurentia ca. 455 Ma, continental material was assimilated into the magma, and there was a transition from trondhjemite to granodiorite and granite magmas in felsic rocks and from island arc tholeiite toward more alkali-rich basalt with a continental signature in mafic magmas. The similarities in whole-rock and trace element geochemistry, rock type, and range of isotopic ages from the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic Suite, suggest they originated from the same magma source and were part of one evolving island arc system that persisted throughout the Ordovician, and the need to separate the Oliverian Plutonic Suite from the Ammonoosuc Volcanics is not necessary.
Most magmatism in the BHA ceased ca. 440 Ma. Following the Taconic orogeny, Silurian basin development was widespread along the length of the Laurentian-Ganderian suture. In New England and Québec, this resulted in the formation of the CVGT. The BHA and the CVGT are generally studied separately: the BHA in the context of arc-continent collision during the Taconic orogeny, and the CVGT as it relates to post-orogenic extension or the distal effects of the Salinic disturbance. When viewed collectively, the igneous geochemistry of the BHA and CVGT reveals an overlap between the waning stages of Taconic orogenesis and the onset of Silurian to Devonian basin development in the northern Appalachians. Metamorphosed bimodal volcanic and intrusive rocks are present in the CVGT (ca. 434–407 Ma) and Silurian cover sequence, which unconformably overlies the BHA. Mafic rocks in the CVGT are mostly tholeiitic basalts with a subset of alkali basalt in the Waits River Formation. Tectonic discrimination diagrams show that the mafic rocks are a mix of mid-ocean ridge basalt to within-plate basalt. The felsic rocks in the CVGT are mostly metamorphosed volcanic rocks that vary from island arc granite to within-plate granite. The geochemical signature of the CVGT is consistent with a post-collisional intra-arc basin, where slab breakoff or crustal attenuation played a key role before transitioning to a deepening foreland basin at the beginning of the Acadian orogeny.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02768.1","usgsCitation":"Valley, P.M., Walsh, G., Merschat, A.J., and McAleer, R.J., 2025, Geochemical and tectonic evolution of the Ordovician Bronson Hill arc and Silurian and Devonian Connecticut Valley–Gaspé trough: Eastern Vermont and western New Hampshire, USA: Geosphere, v. 21, no. 3, p. 418-445, https://doi.org/10.1130/GES02768.1.","productDescription":"28 p.","startPage":"418","endPage":"445","ipdsId":"IP-158690","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":490653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02768.1","text":"Publisher Index Page"},{"id":489369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.625,\n 43.75\n ],\n [\n -72.625,\n 43.125\n ],\n [\n -72.125,\n 43.125\n ],\n [\n -72.125,\n 43.75\n ],\n [\n -72.625,\n 43.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Valley, Peter M. 0000-0002-9957-0403 pvalley@usgs.gov","orcid":"https://orcid.org/0000-0002-9957-0403","contributorId":4809,"corporation":false,"usgs":true,"family":"Valley","given":"Peter","email":"pvalley@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":938935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Gregory J. 0000-0003-4264-8836","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":265307,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":938936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merschat, Arthur J. 0000-0002-9314-4067 amerschat@usgs.gov","orcid":"https://orcid.org/0000-0002-9314-4067","contributorId":4556,"corporation":false,"usgs":true,"family":"Merschat","given":"Arthur","email":"amerschat@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":938937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":938938,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265600,"text":"70265600 - 2025 - Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","interactions":[],"lastModifiedDate":"2025-11-18T16:42:55.698486","indexId":"70265600","displayToPublicDate":"2025-04-09T08:20:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5984,"text":"Reviews in Fisheries Science and Aquaculture","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","title":"Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation","docAbstract":"ulturally, economically, and nutritionally valuable inland fisheries face many new challenges on top of chronic disturbances. In the upper midwestern United States, declines in cool- and coldwater fisheries have been observed, including ogaa/walleye Sander vitreus. In response to population declines, agencies have implemented rehabilitation efforts, and the frequency and intensity of efforts have increased recently given declines. Evaluating intervention outcomes is critical for institutional learning and to understand strategy effectiveness, but is difficult to do when multiple interventions are applied concurrently and in the absence of replication or controls. This review documents walleye rehabilitation efforts in the upper Midwest U.S., where a rehabilitation effort was defined as a coordinated effort with the stated intention to restore a self-sustaining population such that it required limited-to-no further intervention. We discuss: (1) strategies used; (2) similarities and differences in metrics of success; (3) factors leading to success; and (4) recommendations that may increase future successful rehabilitation. Strategies included harvest regulation changes, stocking, fish community manipulations, habitat enhancement, and partner discussions. Overall, evaluations of environmental, habitat, and fish community factors causing walleye population declines were not included in most rehabilitation plans before implementation. This review highlights an increased need for ecosystem-based fisheries management principles and cultivating ecological conditions that favor walleye as a potential path for future rehabilitation plans. Lessons drawn from rehabilitation plans are applicable to global inland fisheries to inform the conservation of declining fish populations.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23308249.2025.2487714","usgsCitation":"Embke, H.S., Feiner, Z.S., Hansen, G., Mrnak, J., Rounds, C., Sass, G., Shaw, S., and Shultz, A.D., 2025, Healing ogaa (walleye Sander vitreus) waters: Lessons and future directions for inland fisheries rehabilitation: Reviews in Fisheries Science and Aquaculture, v. 33, no. 4, p. 579-597, https://doi.org/10.1080/23308249.2025.2487714.","productDescription":"19 p.","startPage":"579","endPage":"597","ipdsId":"IP-158666","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":484503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":933074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feiner, Zachary S.","contributorId":342575,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary","email":"","middleInitial":"S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":933075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen","contributorId":174810,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":933076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mrnak, Joseph T.","contributorId":348717,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joseph T.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":933077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rounds, Christopher I.","contributorId":349471,"corporation":false,"usgs":false,"family":"Rounds","given":"Christopher I.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":933078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sass, Greg G.","contributorId":244466,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":933079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaw, Stephanie L.","contributorId":342852,"corporation":false,"usgs":false,"family":"Shaw","given":"Stephanie L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":933080,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shultz, Aaron D.","contributorId":303739,"corporation":false,"usgs":false,"family":"Shultz","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16233,"text":"Great Lakes Indian Fish and Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":933081,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271313,"text":"70271313 - 2025 - Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","interactions":[],"lastModifiedDate":"2025-09-04T15:13:46.061817","indexId":"70271313","displayToPublicDate":"2025-04-09T08:06:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","docAbstract":"The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.
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