{"pageNumber":"45","pageRowStart":"1100","pageSize":"25","recordCount":40778,"records":[{"id":70262003,"text":"70262003 - 2025 - Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models","interactions":[],"lastModifiedDate":"2025-03-25T15:53:43.357024","indexId":"70262003","displayToPublicDate":"2025-01-07T10:32:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models","docAbstract":"<p><span>Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.20662","usgsCitation":"Krueger, K., Thompson, A., Li, Q., Radatz, A., Cooley, E., Stuntebeck, T.D., Winslow, C., Oldfield, E., and Ruark, M., 2025, Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models: Journal of Environmental Quality, v. 54, no. 2, p. 450-464, https://doi.org/10.1002/jeq2.20662.","productDescription":"15 p.","startPage":"450","endPage":"464","ipdsId":"IP-154553","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.20662","text":"Publisher Index Page"},{"id":466018,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.67253208931788,\n              46.453472239766626\n            ],\n            [\n              -96.53357725011335,\n              43.52335979339341\n            ],\n            [\n              -91.25197772229393,\n              43.462001703986346\n            ],\n            [\n              -91.04740751323666,\n              42.83358085977116\n            ],\n            [\n              -90.69567476916163,\n              42.6339355953327\n            ],\n            [\n              -88.04201458813054,\n              42.48198884581308\n            ],\n            [\n              -87.61145222121533,\n              43.8914402724194\n            ],\n            [\n              -92.82542026317009,\n              45.7061001895253\n            ],\n            [\n              -96.67253208931788,\n              46.453472239766626\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Krueger, Kelsey 0000-0002-2412-0694","orcid":"https://orcid.org/0000-0002-2412-0694","contributorId":347852,"corporation":false,"usgs":false,"family":"Krueger","given":"Kelsey","affiliations":[{"id":83262,"text":"University of Wisconsin -Madison","active":true,"usgs":false}],"preferred":false,"id":922651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":922652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Qiang","contributorId":197310,"corporation":false,"usgs":false,"family":"Li","given":"Qiang","email":"","affiliations":[],"preferred":false,"id":922653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Radatz, Amber","contributorId":217384,"corporation":false,"usgs":false,"family":"Radatz","given":"Amber","email":"","affiliations":[{"id":39612,"text":"UW Madison-Extension, UW Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooley, Eric","contributorId":151059,"corporation":false,"usgs":false,"family":"Cooley","given":"Eric","email":"","affiliations":[{"id":18174,"text":"University of Wisconsin-Extension Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winslow, Christopher J.","contributorId":347853,"corporation":false,"usgs":false,"family":"Winslow","given":"Christopher J.","affiliations":[{"id":83263,"text":"Ohio Sea Grant College Program","active":true,"usgs":false}],"preferred":false,"id":922657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oldfield, Emily 0000-0002-6181-1267","orcid":"https://orcid.org/0000-0002-6181-1267","contributorId":347854,"corporation":false,"usgs":false,"family":"Oldfield","given":"Emily","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":922658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ruark, Matthew","contributorId":151056,"corporation":false,"usgs":false,"family":"Ruark","given":"Matthew","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":922659,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70262101,"text":"70262101 - 2025 - Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire","interactions":[],"lastModifiedDate":"2025-01-14T15:40:44.912559","indexId":"70262101","displayToPublicDate":"2025-01-07T09:27:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire","docAbstract":"<p><span>Watershed sediment yield commonly increases after wildfire, often causing negative impacts to downstream infrastructure and water resources. Post-fire erosion is important to understand and quantify because it is increasingly placing water supplies, habitat, communities, and infrastructure at risk as fire regimes intensify in a warming climate. However, measurements of post-fire sediment mobilization are lacking from many regions. We measured sediment yield from a forested, heavily managed 25.4-km</span><sup>2</sup><span>&nbsp;watershed in the western Sierra Nevada, California, over 2&nbsp;years following the 2021 Caldor Fire, by repeat mapping of a reservoir where sediment accumulated from terrain with moderate to high soil burn severity. Sediment yield was less than the geochronology-derived long-term average in the first year post-fire (conservatively estimated at 21.8–28.0 t/km</span><sup>2</sup><span>), low enough to be difficult to measure with uncrewed airborne system (UAS) and bathymetric sonar survey methods that are most effective at detecting larger sedimentary signals. In the second year post-fire the sediment delivery was 1,560–2,010&nbsp;t/km</span><sup>2</sup><span>, an order of magnitude above long-term values, attributable to greater precipitation and intensive salvage logging. Hillslope erosion simulated by the Water Erosion Prediction Project (WEPP) model overestimated the measured amount by a factor of 90 in the first year and in the second year by a factor (1.9) that aligned with previously determined model performance in northern California. We encourage additional field studies, and validation of erosion models where feasible, to further expand the range of conditions informing post-fire hazard assessments and management decisions.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024EA003939","usgsCitation":"East, A.E., Logan, J.B., Dartnell, P., Dow, H.W., Lindsay, D.N., and Cavagnaro, D.B., 2025, Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire: Earth and Space Science, v. 12, no. 1, e2024EA003939, 23 p., https://doi.org/10.1029/2024EA003939.","productDescription":"e2024EA003939, 23 p.","ipdsId":"IP-168883","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024ea003939","text":"Publisher Index Page"},{"id":466216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"2021 Caldor Fire burn zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.667,\n              39\n            ],\n            [\n              -120.75,\n              39\n            ],\n            [\n              -120.75,\n              38.5\n            ],\n            [\n              -119.667,\n              38.5\n            ],\n            [\n              -119.667,\n              39\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-07","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":923095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":208208,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dow, Helen Willemien 0000-0001-6386-5560","orcid":"https://orcid.org/0000-0001-6386-5560","contributorId":299290,"corporation":false,"usgs":true,"family":"Dow","given":"Helen","email":"","middleInitial":"Willemien","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":923099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":923100,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263314,"text":"70263314 - 2025 - A landscape-scale view of soil organic matter dynamics","interactions":[],"lastModifiedDate":"2025-02-05T14:57:21.534225","indexId":"70263314","displayToPublicDate":"2025-01-07T08:53:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7460,"text":"Nature Reviews Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"A landscape-scale view of soil organic matter dynamics","docAbstract":"<p><span>Soil carbon is an important component of the terrestrial carbon cycle and could be augmented through improved soil management to mitigate climate change. However, data gaps for numerous regions and a lack of understanding of the heterogeneity of biogeochemical processes across diverse soil landscapes hinder the development of large-scale representations of soil organic matter (SOM) dynamics. In this Perspective, we outline how understanding soil formation processes and complexity at the landscape scale can inform predictions of soil organic matter (SOM) cycling and soil carbon sequestration. Long-term alterations of the soil matrix caused by weathering and soil redistribution vary across climate zones and ecosystems, but particularly with the structure of landscapes at the regional scale. Thus, oversimplified generalizations that assume that the drivers of SOM dynamics can be scaled directly from local to global regimes and vice versa leads to large uncertainties in global projections of soil C stocks. Data-driven models with enhanced coverage of underrepresented regions, particularly where soils are physicochemically distinct and environmental change is most rapid, are key to understanding C turnover and stabilization at landscape scales to better predict global soil carbon dynamics.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s43017-024-00621-2","usgsCitation":"Doetterl, S., Berhe, A., Heckman, K., Lawrence, C., Schnecker, J., Vargas, R., Vogel, C., and Wagai, R., 2025, A landscape-scale view of soil organic matter dynamics: Nature Reviews Earth & Environment, v. 6, p. 67-81, https://doi.org/10.1038/s43017-024-00621-2.","productDescription":"15 p.","startPage":"67","endPage":"81","ipdsId":"IP-165053","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":481698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Doetterl, Sebastian","contributorId":240712,"corporation":false,"usgs":false,"family":"Doetterl","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":926296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berhe, Asmeret Asefaw","contributorId":350541,"corporation":false,"usgs":false,"family":"Berhe","given":"Asmeret Asefaw","affiliations":[{"id":83765,"text":"UC Merced, CA, USA","active":true,"usgs":false}],"preferred":false,"id":926297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heckman, Katherine","contributorId":350542,"corporation":false,"usgs":false,"family":"Heckman","given":"Katherine","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":926298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Corey 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202373,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":926299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schnecker, Jörg","contributorId":350543,"corporation":false,"usgs":false,"family":"Schnecker","given":"Jörg","affiliations":[{"id":39691,"text":"University of Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":926300,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vargas, Rodrigo","contributorId":350544,"corporation":false,"usgs":false,"family":"Vargas","given":"Rodrigo","affiliations":[{"id":83766,"text":"University of Delaware, DE, USA","active":true,"usgs":false}],"preferred":false,"id":926301,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vogel, Cordula","contributorId":350545,"corporation":false,"usgs":false,"family":"Vogel","given":"Cordula","affiliations":[{"id":83767,"text":"Technical University, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":926302,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wagai, Rota","contributorId":350546,"corporation":false,"usgs":false,"family":"Wagai","given":"Rota","affiliations":[{"id":83768,"text":"National Ag. & Food Research Org., Tsukuba, Japan","active":true,"usgs":false}],"preferred":false,"id":926303,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70264076,"text":"70264076 - 2025 - Generalized Bancroft algorithm for locating earthquakes with P- and S-wave arrival times","interactions":[],"lastModifiedDate":"2025-03-26T16:04:36.884619","indexId":"70264076","displayToPublicDate":"2025-01-07T08:45:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Generalized Bancroft algorithm for locating earthquakes with P- and S-wave arrival times","docAbstract":"<p><span>Because of similarities between locating an earthquake with seismic stations and locating a Global Positioning System (GPS) receiver from satellites, the Bancroft algorithm developed for GPS processing can be used to locate earthquakes. Such an approach to earthquake location differs from the conventional method of choosing an initial or trial solution and then iteratively improving the solution until convergence. The Bancroft algorithm has the advantage of being a direct, noniterative solution but with the disadvantage of only being able to accommodate a homogeneous velocity model. An additional limitation of the standard Bancroft algorithm is that it considers arrival times in a medium with a single propagation velocity. This poses no problem for GPS processing because electromagnetic waves travel at the speed of light; however, for seismic waves it means the algorithm can be applied to collections of either&nbsp;</span><i>P</i><span>‐ or&nbsp;</span><i>S</i><span>‐wave arrival times. Here, I show how the Bancroft algorithm can be generalized to handle both&nbsp;</span><i>P</i><span>‐ and&nbsp;</span><i>S</i><span>‐wave arrival‐time measurements simultaneously. I also show how to accommodate depth‐varying&nbsp;</span><i>P</i><span>‐ and&nbsp;</span><i>S</i><span>‐wave velocity models. I apply the generalized Bancroft algorithm to microearthquakes beneath Tanaga Volcano in Alaska and compare standard locations from the widely used HYPOINVERSE location code to Bancroft locations and to the output of HYPOINVERSE when setting the trial location to the Bancroft location. I find the Bancroft locations outperform the results from the other methods for shallow earthquakes near sea level, where a quantity known as the geometric dilution of precision is large and linearized approaches such as HYPOINVERSE are expected to struggle.</span></p>","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120240058","usgsCitation":"Haney, M.M., 2025, Generalized Bancroft algorithm for locating earthquakes with P- and S-wave arrival times: Bulletin of the Seismological Society of America, v. 115, no. 2, p. 367-378, https://doi.org/10.1785/0120240058.","productDescription":"12 p.","startPage":"367","endPage":"378","ipdsId":"IP-164648","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":482902,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Tanaga Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -178.29779673489296,\n              51.943189947842825\n            ],\n            [\n              -178.29779673489296,\n              51.5889322915815\n            ],\n            [\n              -177.61515092108772,\n              51.5889322915815\n            ],\n            [\n              -177.61515092108772,\n              51.943189947842825\n            ],\n            [\n              -178.29779673489296,\n              51.943189947842825\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"115","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":929686,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70262111,"text":"70262111 - 2025 - Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems","interactions":[],"lastModifiedDate":"2025-01-14T15:19:09.571057","indexId":"70262111","displayToPublicDate":"2025-01-07T08:12:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17114,"text":"Natural Hazards and Earth Systems Sciences (NHESS)","active":true,"publicationSubtype":{"id":10}},"title":"Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems","docAbstract":"Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.","language":"English","publisher":"EGU-Copernicus Publications","doi":"10.5194/nhess-25-169-2025","usgsCitation":"Mirus, B., Bogaard, T., Greco, R., and Stähli, M., 2025, Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems: Natural Hazards and Earth Systems Sciences (NHESS), v. 25, no. 1, p. 169-182, https://doi.org/10.5194/nhess-25-169-2025.","productDescription":"14 p.","startPage":"169","endPage":"182","ipdsId":"IP-159239","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":466664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-169-2025","text":"Publisher Index Page"},{"id":466212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Sitka","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -136.68999201861402,\n              58.275013995525285\n            ],\n            [\n              -136.68999201861402,\n              56.12160659807034\n            ],\n            [\n              -134.31603477353784,\n              56.12160659807034\n            ],\n            [\n              -134.31603477353784,\n              58.275013995525285\n            ],\n            [\n              -136.68999201861402,\n              58.275013995525285\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":923125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bogaard, Thom","contributorId":348180,"corporation":false,"usgs":false,"family":"Bogaard","given":"Thom","affiliations":[{"id":33885,"text":"Delft University of Technology, Netherlands","active":true,"usgs":false}],"preferred":false,"id":923126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greco, Roberto","contributorId":348181,"corporation":false,"usgs":false,"family":"Greco","given":"Roberto","affiliations":[{"id":83312,"text":"University of Campania, Italy","active":true,"usgs":false}],"preferred":false,"id":923127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stähli, Manfred","contributorId":348182,"corporation":false,"usgs":false,"family":"Stähli","given":"Manfred","affiliations":[{"id":83313,"text":"Swiss Federal Research Institute  (WSL)","active":true,"usgs":false}],"preferred":false,"id":923128,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261986,"text":"70261986 - 2025 - Understanding the influence of image enhancement on underwater object detection: A quantitative and qualitative study","interactions":[],"lastModifiedDate":"2025-01-08T15:12:36.034936","indexId":"70261986","displayToPublicDate":"2025-01-07T08:07:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the influence of image enhancement on underwater object detection: A quantitative and qualitative study","docAbstract":"Underwater image enhancement is often perceived as a disadvantageous process to object detection. We propose a novel analysis of the interactions between enhancement and detection, elaborating on the potential of enhancement to improve detection. In particular, we evaluate object detection performance for each individual image rather than across the entire set to allow a direct performance comparison of each image before and after enhancement. This approach enables the generation of unique queries to identify the outperforming and underperforming enhanced images compared to the original images. To accomplish this, we first produce enhanced image sets of the original images using recent image enhancement models. Each enhanced set is then divided into two groups: (1) images that outperform or match the performance of the original images and (2) images that underperform. Subsequently, we create mixed original-enhanced sets by replacing underperforming enhanced images with their corresponding original images. Next, we conduct a detailed analysis by evaluating all generated groups for quality and detection performance attributes. Finally, we perform an overlap analysis between the generated enhanced sets to identify cases where the enhanced images of different enhancement algorithms unanimously outperform, equally perform, or underperform the original images. Our analysis reveals that, when evaluated individually, most enhanced images achieve equal or superior performance compared to their original counterparts. The proposed method uncovers variations in detection performance that are not apparent in a whole set as opposed to a per-image evaluation because the latter reveals that only a small percentage of enhanced images cause an overall negative impact on detection. We also find that over-enhancement may lead to deteriorated object detection performance. Lastly, we note that enhanced images reveal hidden objects that were not annotated due to the low visibility of the original images.","language":"English","publisher":"MDPI","doi":"10.3390/rs17020185","usgsCitation":"Saleem, A., Awad, A., Paheding, S., Lucas, E., Havens, T., and Esselman, P., 2025, Understanding the influence of image enhancement on underwater object detection: A quantitative and qualitative study: Remote Sensing, v. 17, no. 2, 185, 17 p., https://doi.org/10.3390/rs17020185.","productDescription":"185, 17 p.","ipdsId":"IP-173511","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":466665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17020185","text":"Publisher Index Page"},{"id":465876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Saleem, Ashraf","contributorId":347827,"corporation":false,"usgs":false,"family":"Saleem","given":"Ashraf","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":922553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Awad, Ali","contributorId":347828,"corporation":false,"usgs":false,"family":"Awad","given":"Ali","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":922554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paheding, Sidike","contributorId":347829,"corporation":false,"usgs":false,"family":"Paheding","given":"Sidike","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":922555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lucas, Evan","contributorId":347830,"corporation":false,"usgs":false,"family":"Lucas","given":"Evan","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":922556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Havens, Timothy C.","contributorId":347831,"corporation":false,"usgs":false,"family":"Havens","given":"Timothy C.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":922557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esselman, Peter C. 0000-0002-0085-903X","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":204291,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":922558,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263888,"text":"70263888 - 2025 - Evaluation of the sensitivity of a federally endangered freshwater mussel (Venustaconcha trabalis) to selected chemicals","interactions":[],"lastModifiedDate":"2025-02-27T15:41:31.836746","indexId":"70263888","displayToPublicDate":"2025-01-06T09:38:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of the sensitivity of a federally endangered freshwater mussel (<i>Venustaconcha trabalis</i>) to selected chemicals","title":"Evaluation of the sensitivity of a federally endangered freshwater mussel (Venustaconcha trabalis) to selected chemicals","docAbstract":"<p><span>Protection of critically endangered species requires identification of factors limiting their survival and growth. Previous studies have demonstrated that unionid mussels are sensitive to some chemicals and the sensitivity was similar among different taxonomic families and tribes of mussels. However, common species of mussels were generally used in these previous studies; little is known about the sensitivity of endangered and threatened mussels relative to common species. The objective of this study was to evaluate the sensitivity of a critically endangered mussel (Tennessee bean,&nbsp;</span><i>Venustaconcha trabalis</i><span>) to seven chemicals with different modes of toxic action (ammonia, chloride, nitrite, potassium, cobalt, manganese, nickel) in acute 96-h exposures and to three chemicals (nitrite, cobalt, iron) in chronic 28-d exposures conducted following standard methods. A commonly tested mussel (fatmucket,&nbsp;</span><i>Lampsilis siliquoidea</i><span>) was also tested side-by-side with Tennessee bean in chronic exposures. Test chemicals were selected based on (1) chemicals of potential concern found in a review of existing data for the river where a population of Tennessee bean occurs or was historically present, (2) chemicals to which other mussels are sensitive, or (3) chemicals that had not been previously tested with mussels. Acute 50% effect concentrations (EC50s) for the seven chemicals from the Tennessee bean tests were within or close to the range of EC50s for other mussel species tested in previous studies, and chronic 20% effect concentrations for the three chemicals were similar between Tennessee bean and fatmucket, indicating the endangered species has sensitivity similar to other tested mussel species. Inclusion of the new mussel data in existing toxicity databases for freshwater organisms would rank one or more mussel species among the four most sensitive species to ammonia, chloride, potassium, and nickel in acute exposures and to nitrite, cobalt, and iron in chronic exposures.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae092","usgsCitation":"Wang, N., Ivey, C.D., Cleveland, D.M., Kunz, J.L., Schapansky, R., Lane, T.W., and Barnhart, M., 2025, Evaluation of the sensitivity of a federally endangered freshwater mussel (Venustaconcha trabalis) to selected chemicals: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgae092.","ipdsId":"IP-170240","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":487701,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae092","text":"Publisher Index Page"},{"id":482561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":928913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schapansky, Rebecca","contributorId":351559,"corporation":false,"usgs":false,"family":"Schapansky","given":"Rebecca","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":928914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, Timothy W.","contributorId":333081,"corporation":false,"usgs":false,"family":"Lane","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":79722,"text":"Virginia Department of Wildlife Resoures","active":true,"usgs":false}],"preferred":false,"id":928915,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnhart, M. Christopher","contributorId":189301,"corporation":false,"usgs":false,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":928916,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70263985,"text":"70263985 - 2025 - Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets","interactions":[],"lastModifiedDate":"2025-05-13T15:57:02.42202","indexId":"70263985","displayToPublicDate":"2025-01-06T09:16:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20195,"text":"Applied Computing and Geosciences.","active":true,"publicationSubtype":{"id":10}},"title":"Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets","docAbstract":"<p><span>Coastal marsh wetlands experience variations in vertical gains and losses through time, which have allowed them to infill relict topography and record variations in drivers. The stratigraphic unit associated with the development of the marsh also reflects the long-term importance of key ecosystem services supplied by the marsh environment, including carbon storage and storm mitigation. Mapping these coastal wetland sediments and the marsh unit thickness is challenging as traditional coastal geophysical tools are not easily deployable (acoustic methods) or are unreliable in saline-soil environments (e.g., ground-penetrating radar), leaving core-based methods the most viable mapping method. In the present study, we utilized prior information on the geologic architecture of the region to select spatial and physical metrics that likely persisted throughout evolution of the marsh during the late Holocene. We then assessed the individual and collective power of these metrics to predict marsh thickness observed from cores. Employing regressive predictive models powered by these data, we improve the quantification of marsh thickness for a coastal fringing marsh within the Grand Bay estuary in Mississippi and Alabama (USA). The information gained from this approach yields improved estimates of the carbon stocks in this environment. Additionally, the stored sediment masses reflect the past, and potential future, persistence of the Grand Bay marsh under historical and present marsh-estuarine sediment exchange fluxes. Such improvements to both the sediment budget of recent marsh stratigraphic units and the spatial extent provide new resources for comparison with large-scale landscape models, the latter of which may be used, when validated, to predict future change and ecosystem transformations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.acags.2024.100215","usgsCitation":"Smith, C., Bernier, J., Ellis, A.M., and Smith, K., 2025, Predictive regressive models of recent marsh sediment thickness improve the quantification of coastal marsh sediment budgets: Applied Computing and Geosciences., v. 25, 100215, 12 p., https://doi.org/10.1016/j.acags.2024.100215.","productDescription":"100215, 12 p.","ipdsId":"IP-168346","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":490116,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.acags.2024.100215","text":"Publisher Index Page"},{"id":482794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama. Mississippi","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.28354140678013,\n              30.419771757548105\n            ],\n            [\n              -88.46387852940934,\n              30.419771757548105\n            ],\n            [\n              -88.46387852940934,\n              30.31160215154773\n            ],\n            [\n              -88.28354140678013,\n              30.31160215154773\n            ],\n            [\n              -88.28354140678013,\n              30.419771757548105\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":929422,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263830,"text":"70263830 - 2025 - Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries","interactions":[],"lastModifiedDate":"2025-02-25T15:13:12.08078","indexId":"70263830","displayToPublicDate":"2025-01-06T09:07:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries","docAbstract":"<p><span>Ongoing anthropogenic activities and analytical advancements yield continuously expanding lists of environmental contaminants. This represents a challenge to environmental managers, who must prioritize chemicals for management actions (e.g., restriction, regulation, remediation) but are often hindered by resource limitations. To help facilitate prioritization efforts, this study presents several strategies for deriving environmental hazard concentrations using publicly accessible data and open-source computational tools. Using a Great Lakes tributaries aquatic monitoring dataset as a case study, environmental hazard concentrations were obtained or derived for 334 organic chemicals. These concentrations were based on (1) current water quality guidelines; (2) apical screening values; (3) apical and (4) nonapical effect concentrations from the ECOTOXicology Knowledgebase; (5) in vitro effect concentrations from the ToxCast database; (6) cytotoxic burst concentrations collated from the Comptox Dashboard; (7) “estimated screening values” derived from modeled or estimated data and available from various regulatory and nonregulatory agencies; (8) pharmaceutical potency estimates from the MaPPFAST database; and (9) quantitative structure-activity relationship (QSAR)–derived acute toxicity estimates. Environmental fate data included aquatic half-lives and bioconcentration factors collated from the Comptox Dashboard or estimated using QSARs. To identify patterns that could be used for characterization, availability of ecotoxicological concentrations and environmental fate data were evaluated. Furthermore, exceedances of hazard concentrations were evaluated and compared across diverse ecotoxicological data types. Altogether, by providing detailed methodology and practical examples generated with real monitoring data, this study demonstrated that these hazard concentration derivation strategies can be efficiently and effectively used with large, complex datasets and identified critical considerations for future prioritization efforts.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae002","usgsCitation":"Maloney, E., Corsi, S., Pronschinske, M.A., DeCicco, L.A., Nott, M.A., Frisch, J.R., Fuller, N.W., Baldwin, A.K., Kimbrough, K., Edwards, M., Hummel, S.L., Vinas, N., and Villeneuve, D.L., 2025, Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgae002.","ipdsId":"IP-160548","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":482440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -92.34029884659675,\n              47.04791584502874\n            ],\n            [\n              -92.94697875735348,\n              46.500335857975415\n            ],\n            [\n              -89.09023264044944,\n              46.12147932567862\n            ],\n            [\n              -88.83134021093606,\n              42.93561346003102\n            ],\n            [\n              -87.2083584997993,\n              41.22934429547493\n            ],\n            [\n              -80.96760820419331,\n              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M.","affiliations":[{"id":34699,"text":"University of Minnesota-Duluth","active":true,"usgs":false}],"preferred":false,"id":928560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pronschinske, Matthew A. 0000-0001-9787-4545 mpronschinske@usgs.gov","orcid":"https://orcid.org/0000-0001-9787-4545","contributorId":295961,"corporation":false,"usgs":true,"family":"Pronschinske","given":"Matthew","email":"mpronschinske@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frisch, John R.","contributorId":171761,"corporation":false,"usgs":false,"family":"Frisch","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":928565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fuller, Neil W.","contributorId":335522,"corporation":false,"usgs":false,"family":"Fuller","given":"Neil","email":"","middleInitial":"W.","affiliations":[{"id":13212,"text":"Southern Illinois University","active":true,"usgs":false}],"preferred":false,"id":928566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":928567,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kimbrough, Kimani","contributorId":296970,"corporation":false,"usgs":false,"family":"Kimbrough","given":"Kimani","affiliations":[],"preferred":false,"id":928568,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Edwards, Michael","contributorId":351473,"corporation":false,"usgs":false,"family":"Edwards","given":"Michael","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric 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0000-0003-2801-0203","orcid":"https://orcid.org/0000-0003-2801-0203","contributorId":197436,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":928572,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70262012,"text":"70262012 - 2025 - Automating physics-based models to estimate thermoelectric-power water use","interactions":[],"lastModifiedDate":"2025-01-10T17:08:02.343623","indexId":"70262012","displayToPublicDate":"2025-01-05T11:02:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Automating physics-based models to estimate thermoelectric-power water use","docAbstract":"<p><span>Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341&nbsp;TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106265","usgsCitation":"Harris, M.A., Diehl, T.H., Gorman Sanisaca, L.E., Galanter, A.E., Lombard, M.A., Skinner, K.D., Chamberlin, C.A., McCarthy, B.A., Niswonger, R.G., Stewart, J.S., and Valseth, K., 2025, Automating physics-based models to estimate thermoelectric-power water use: Environmental Modelling and Software, v. 185, 106265, 16 p., https://doi.org/10.1016/j.envsoft.2024.106265.","productDescription":"106265, 16 p.","ipdsId":"IP-156740","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":466666,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106265","text":"Publisher Index Page"},{"id":466004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skinner, Kenneth D. 0000-0003-1774-6565","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":204388,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922695,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chamberlin, Catherine A. 0000-0002-1307-4784","orcid":"https://orcid.org/0000-0002-1307-4784","contributorId":331334,"corporation":false,"usgs":true,"family":"Chamberlin","given":"Catherine","email":"","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922696,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCarthy, Brendan A. 0000-0003-4993-021X","orcid":"https://orcid.org/0000-0003-4993-021X","contributorId":221009,"corporation":false,"usgs":true,"family":"McCarthy","given":"Brendan","email":"","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922697,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - 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,{"id":70262294,"text":"70262294 - 2025 - Exposure to the Polychlorinated biphenyl mixture Aroclor 1254 elicits neurological and cardiac developmental effects in early life stage zebrafish (Danio rerio)","interactions":[],"lastModifiedDate":"2025-01-16T16:19:08.483483","indexId":"70262294","displayToPublicDate":"2025-01-03T10:16:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exposure to the Polychlorinated biphenyl mixture Aroclor 1254 elicits neurological and cardiac developmental effects in early life stage zebrafish (<i>Danio rerio</i>)","title":"Exposure to the Polychlorinated biphenyl mixture Aroclor 1254 elicits neurological and cardiac developmental effects in early life stage zebrafish (Danio rerio)","docAbstract":"<p><span>The goal of this study was to compare the bioaccumulation of the PCB mixture Aroclor 1254 in zebrafish to cardiac and neurologic outcomes. The establishment of effect concentrations (ECs) for cardiac and neurotoxic effects of PCBs in early life stage fish is challenging due to a lack of measured PCB concentrations in test media (e.g., fish tissue), the lack of standard exposure methods, and the propensity of PCBs to adsorb to test glassware and materials resulting in discrepancies in ECs from different studies with similar endpoints. Reporting tissue concentrations in test organisms will allow for standardization across different tests and thus may improve estimations of effect thresholds. Early life stage zebrafish (</span><i>Danio rerio</i><span>) are a common environmental toxicological model well represented within the literature, making them ideal for comparisons across multiple studies. Embryos were exposed at 6&nbsp;h post fertilization (hpf) to aqueous Aroclor 1254 for 96&nbsp;h with or without renewal in addition to a PCB 126 positive control for cardiotoxicity. PCB concentrations were measured in both exposure solutions and tissue samples. Measured concentrations of Aroclor 1254 in test solutions ranged from 8.7% to 870% of nominal concentrations. Heart rate, pericardial edema, and neurological endpoints (eye tremors) were measured in 102 hpf larvae. Pericardial edema was not present in Aroclor 1254-treated zebrafish but was observed in those exposed to PCB-126. Concentration-dependent bradycardia was observed in zebrafish exposed to Aroclor 1254 and PCB-126. Similarly, a concentration-dependent increase in eye tremor behavior was observed in embryos exposed to Aroclor 1254. Data produced by this study demonstrate novel toxicological effects of Aroclor 1254 and highlight the importance of measuring PCBs in both exposure and receptor media.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2024.144023","usgsCitation":"Green, C., Morris, J.M., Magnuson, J.T., Leads, R., Lay, C., Gielazyn, M., Rosman, L., Schlenk, D., and Roberts, A., 2025, Exposure to the Polychlorinated biphenyl mixture Aroclor 1254 elicits neurological and cardiac developmental effects in early life stage zebrafish (Danio rerio): Chemosphere, v. 371, 144023, 11 p., https://doi.org/10.1016/j.chemosphere.2024.144023.","productDescription":"144023, 11 p.","ipdsId":"IP-167313","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":489892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2024.144023","text":"Publisher Index Page"},{"id":466637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"371","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Corey A.","contributorId":348784,"corporation":false,"usgs":false,"family":"Green","given":"Corey A.","affiliations":[{"id":83408,"text":"Eastern New Mexico University","active":true,"usgs":false}],"preferred":false,"id":923760,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Jeffrey M.","contributorId":172778,"corporation":false,"usgs":false,"family":"Morris","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":923761,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":923762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leads, Rachel","contributorId":348785,"corporation":false,"usgs":false,"family":"Leads","given":"Rachel","affiliations":[{"id":34637,"text":"University of North Texas","active":true,"usgs":false}],"preferred":false,"id":923763,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lay, Claire R.","contributorId":348786,"corporation":false,"usgs":false,"family":"Lay","given":"Claire R.","affiliations":[{"id":83409,"text":"Abt Global","active":true,"usgs":false}],"preferred":false,"id":923764,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gielazyn, Michel","contributorId":348787,"corporation":false,"usgs":false,"family":"Gielazyn","given":"Michel","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":923765,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosman, Lisa","contributorId":348788,"corporation":false,"usgs":false,"family":"Rosman","given":"Lisa","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":923766,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schlenk, Daniel","contributorId":221106,"corporation":false,"usgs":false,"family":"Schlenk","given":"Daniel","email":"","affiliations":[{"id":12655,"text":"University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":923767,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roberts, Aaron P.","contributorId":348789,"corporation":false,"usgs":false,"family":"Roberts","given":"Aaron P.","affiliations":[{"id":34637,"text":"University of North Texas","active":true,"usgs":false}],"preferred":false,"id":923768,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70261993,"text":"70261993 - 2025 - Linking fire, food webs, and fish in stream ecosystems","interactions":[],"lastModifiedDate":"2025-01-08T15:20:30.750552","indexId":"70261993","displayToPublicDate":"2025-01-03T08:13:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Linking fire, food webs, and fish in stream ecosystems","docAbstract":"As wildfire regimes shift, resource managers are concerned about potential threats to aquatic ecosystems and the species they support, especially fishes. However, predicting fish responses can be challenging because wildfires affect aquatic ecosystems via multiple pathways. Application of whole-ecosystem approaches, such as food web modeling, can act as heuristic tools that offer valuable insights that account for these different mechanisms. We applied a dynamic food web simulation model that mechanistically linked stream trophic dynamics to the myriad effects that wildfires can have on aquatic and riparian ecosystems at a local stream reach-scale. We simulated how wildfires of different severity may influence short- (months to years) and long-term (years to decades) periphyton, aquatic invertebrate, and fish biomass dynamics in forested headwater streams of the western Pacific Northwest (USA). In many cases, wildfire increased modeled periphyton, invertebrate, and fish biomass over both short- and long-time periods. However, modeled responses varied extensively in their direction (that is, positive or negative), magnitude, and duration depending on fire severity, time since fire, and trophic level. The shapes of these response trajectories were especially sensitive to predicted wildfire effects on water temperature, canopy cover, riparian shading, and instream turbidity. Model simulations suggest a single fire could result in a wide range of aquatic ecosystem responses, especially in watersheds with mixed burn severity. Our analysis highlights the utility of whole-ecosystem approaches, like food web modeling, as heuristic tools for improving our understanding of the mechanisms linking fire, food webs, and fish and for identifying contexts where fires could have deleterious impacts on fishes.","language":"English","publisher":"Springer Nature","doi":"10.1007/s10021-024-00955-4","usgsCitation":"Roon, D.A., Bellmore, J.R., Benjamin, J.R., Robinne, F., Flitcroft, R.L., Compton, J.E., Ebersole, J.L., Dunham, J., and Bladon, K.D., 2025, Linking fire, food webs, and fish in stream ecosystems: Ecosystems, v. 28, 1, 22 p., https://doi.org/10.1007/s10021-024-00955-4.","productDescription":"1, 22 p.","ipdsId":"IP-164295","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":466667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10021-024-00955-4","text":"Publisher Index 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 \"}}]}","volume":"28","noUsgsAuthors":false,"publicationDate":"2025-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Roon, David A.","contributorId":267257,"corporation":false,"usgs":false,"family":"Roon","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":27847,"text":"Department of Fisheries and Wildlife, Oregon State University, Corvallis, Oregon","active":true,"usgs":false}],"preferred":false,"id":922588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellmore, J. Ryan","contributorId":271034,"corporation":false,"usgs":false,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[{"id":56260,"text":"U.S. Forest Service, Pacific Northwest Research Station, 11175 Auke Lake Way, Juneau, Alaska, 99801","active":true,"usgs":false}],"preferred":false,"id":922589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":922590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robinne, François-Nicolas 0000-0002-0554-7668","orcid":"https://orcid.org/0000-0002-0554-7668","contributorId":347847,"corporation":false,"usgs":false,"family":"Robinne","given":"François-Nicolas","affiliations":[{"id":83261,"text":"Pacific Salmon Foundation","active":true,"usgs":false}],"preferred":false,"id":922591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flitcroft, Rebecca L. 0000-0003-3341-996X","orcid":"https://orcid.org/0000-0003-3341-996X","contributorId":172180,"corporation":false,"usgs":false,"family":"Flitcroft","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":922592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Compton, Jana E. 0000-0001-9833-8664","orcid":"https://orcid.org/0000-0001-9833-8664","contributorId":242876,"corporation":false,"usgs":false,"family":"Compton","given":"Jana","middleInitial":"E.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":922593,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ebersole, Joseph L.","contributorId":146938,"corporation":false,"usgs":false,"family":"Ebersole","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":922594,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":922595,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bladon, Kevin D. 0000-0002-4182-6883","orcid":"https://orcid.org/0000-0002-4182-6883","contributorId":264447,"corporation":false,"usgs":false,"family":"Bladon","given":"Kevin","email":"","middleInitial":"D.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":922596,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70263812,"text":"70263812 - 2025 - Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf","interactions":[],"lastModifiedDate":"2025-02-25T15:21:59.92779","indexId":"70263812","displayToPublicDate":"2025-01-03T08:12:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf","docAbstract":"<p>Red snapper (<i>Lutjanus campechanus</i>) is an iconic marine fish species along the southeast United States coast. Despite its ecological and economic importance, surprisingly little is known about red snapper biology and habitat use on the southeast United States Atlantic continental shelf (SEUS). We used data from a long-term baited trap and video survey (2011–2022), as well as from remotely operated vehicle (ROV) sampling (2021–2023), to quantify temporal changes in relative abundance, patterns of spatial distribution, and habitat use of red snapper in the SEUS. Using generalized additive models, we showed that red snapper increased in relative abundance from 2011 to 2022 by 960% in traps and 1,141% in video samples. Red snapper relative abundance was highest in mid-shelf waters off the east coast of Florida, Georgia, and, to a lesser extent, off the Outer Banks of North Carolina; red snapper were less common off southern North Carolina and South Carolina. Highest relative abundance of red snapper occurred in locations with a moderate amount of natural structured habitat and high seafloor complexity and were never observed at randomly selected ROV stations (n = 197) lacking structured habitat. These results increase our understanding of the spatial and temporal distribution of red snapper, improve our knowledge of red snapper habitat use, and can be used when scaling local density estimates to the entire SEUS.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107200","usgsCitation":"Bacheler, N., Patterson III, W., Tarnecki, J., Shertzer, K., Buckel, J., Hostetter, N.J., Pacifici, K., Zulian, V., and Bubley, W., 2025, Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf: Fisheries Research, v. 281, 107200, 13 p., https://doi.org/10.1016/j.fishres.2024.107200.","productDescription":"107200, 13 p.","ipdsId":"IP-160875","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":486926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2024.107200","text":"Publisher Index Page"},{"id":482442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","otherGeospatial":"southeastern United States Atlantic continental shelf","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -79.92593395494507,\n              33.15275092248328\n            ],\n            [\n              -81.99045643689327,\n              31.10056957805797\n            ],\n            [\n              -80.87712766876851,\n              28.48701241069105\n            ],\n            [\n              -80.3042465673629,\n              31.325404220996276\n            ],\n            [\n              -76.71024593975332,\n              34.122762076854926\n            ],\n            [\n              -76.22924401859534,\n              35.13912357508609\n            ],\n            [\n              -79.92593395494507,\n              33.15275092248328\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.13968222172028,\n              19.755747085043822\n            ],\n            [\n              -155.13968222172028,\n              19.69242312727401\n            ],\n            [\n              -155.07419576383438,\n              19.69242312727401\n            ],\n            [\n              -155.07419576383438,\n              19.755747085043822\n            ],\n            [\n              -155.13968222172028,\n              19.755747085043822\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"281","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bacheler, Nathan M.","contributorId":351435,"corporation":false,"usgs":false,"family":"Bacheler","given":"Nathan M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patterson III, William F.","contributorId":351436,"corporation":false,"usgs":false,"family":"Patterson III","given":"William F.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarnecki, Joseph H.","contributorId":351437,"corporation":false,"usgs":false,"family":"Tarnecki","given":"Joseph H.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shertzer, Kyle W.","contributorId":351439,"corporation":false,"usgs":false,"family":"Shertzer","given":"Kyle W.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckel, Jeffrey A.","contributorId":351441,"corporation":false,"usgs":false,"family":"Buckel","given":"Jeffrey A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":928519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pacifici, Krishna","contributorId":351444,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zulian, Viviane","contributorId":351446,"corporation":false,"usgs":false,"family":"Zulian","given":"Viviane","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928521,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bubley, Walter J.","contributorId":351447,"corporation":false,"usgs":false,"family":"Bubley","given":"Walter J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":928522,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70261922,"text":"70261922 - 2025 - Evaluating a simulation-based wildfire burn probability map for the conterminous US","interactions":[],"lastModifiedDate":"2025-01-03T15:33:59.530102","indexId":"70261922","displayToPublicDate":"2025-01-02T09:26:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating a simulation-based wildfire burn probability map for the conterminous US","docAbstract":"<div class=\"section\"><strong>Background</strong><p id=\"d6e305\">Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography and ignition locations, and BP maps are key components of wildfire risk assessments.</p></div><div class=\"section\"><strong>Aims</strong><p id=\"d6e310\">Few studies have compared BP maps with real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous US based on the large fire simulation model FSim.</p></div><div class=\"section\"><strong>Methods</strong><p id=\"d6e315\">We compared BP with observed wildfires from 2016 to 2022 across 128 regions representing similar fire regimes (‘pyromes’). We evaluated the distribution of burned areas across BP values, and compared burned area distributions among fire size classes.</p></div><div class=\"section\"><strong>Key results</strong><p id=\"d6e320\">Across all pyromes, mean BP was moderately correlated with observed burned area. An average of 71% of burned area occurred in higher-BP classes, vs 79% expected. BP underpredicted burned area in the Mountain West, especially for extremely large fires.</p></div><div class=\"section\"><strong>Conclusions</strong><p id=\"d6e325\">The FSim BP map was useful for estimating subsequent wildfire hazard, but may have underestimated burned areas where input data did not reflect recent climate change, vegetation change or human ignition patterns.</p></div><div class=\"section\"><strong>Implications</strong><p id=\"d6e330\">Our evaluations indicate that caution is needed when relying on simulation-based BP maps to inform management decisions. Our results also highlight potential opportunities to improve model estimates.</p></div>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF23196","usgsCitation":"Carlson, A.R., Hawbaker, T., Bair, L., Hoffman, C., Meldrum, J., Baggett, L., and Steblein, P.F., 2025, Evaluating a simulation-based wildfire burn probability map for the conterminous US: International Journal of Wildland Fire, v. 34, no. 1, WF23196, 16 p., https://doi.org/10.1071/WF23196.","productDescription":"WF23196, 16 p.","ipdsId":"IP-158988","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":489096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70261980,"text":"70261980 - 2025 - Advancing the science of headwater streamflow for global water protection","interactions":[],"lastModifiedDate":"2025-01-27T16:46:01.883887","indexId":"70261980","displayToPublicDate":"2025-01-02T08:54:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Advancing the science of headwater streamflow for global water protection","docAbstract":"<p><span>The protection of headwater streams faces increasing challenges, exemplified by limited global recognition of headwater contributions to watershed resiliency and a recent US Supreme Court decision limiting federal safeguards. Despite accounting for ~77% of global river networks, the lack of adequate headwaters protections is caused, in part, by limited information on their extent and functions—in particular, their flow regimes, which form the foundation for decision-making regarding their protection. Yet, headwater streamflow is challenging to comprehensively measure and model; it is highly variable and sensitive to changes in land use, management and climate. Modelling headwater streamflow to quantify its cumulative contributions to downstream river networks requires an integrative understanding across local hillslope and channel (that is, watershed) processes. Here we begin to address this challenge by proposing a consistent definition for headwater systems and streams, evaluating how headwater streamflow is characterized and advocating for closing gaps in headwater streamflow data collection, modelling and synthesis.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00351-1","usgsCitation":"Golden, H.E., Christiensen, J., McMillan, H., Kelleher, C.A., Lane, C., Husic, A., Li, L., Ward, A., Hammond, J., Seybold, E.C., Jaeger, K.L., Zimmer, M.A., Sando, R., Jones, C., Segura, C., Mahoney, D.T., Price, A.N., and Chang, F., 2025, Advancing the science of headwater streamflow for global water protection: Nature Water, v. 3, p. 16-26, https://doi.org/10.1038/s44221-024-00351-1.","productDescription":"11 p.","startPage":"16","endPage":"26","ipdsId":"IP-161519","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science 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Nathan","contributorId":295982,"corporation":false,"usgs":false,"family":"Jones","given":"C. Nathan","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":922520,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Segura, Catalina","contributorId":192222,"corporation":false,"usgs":false,"family":"Segura","given":"Catalina","email":"","affiliations":[],"preferred":false,"id":922523,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Mahoney, D. Tyler 0000-0003-0523-508X","orcid":"https://orcid.org/0000-0003-0523-508X","contributorId":304419,"corporation":false,"usgs":false,"family":"Mahoney","given":"D.","email":"","middleInitial":"Tyler","affiliations":[{"id":66062,"text":"University of Louisville","active":true,"usgs":false}],"preferred":false,"id":922525,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Price, Adam N. 0000-0002-7211-4758","orcid":"https://orcid.org/0000-0002-7211-4758","contributorId":295971,"corporation":false,"usgs":false,"family":"Price","given":"Adam","email":"","middleInitial":"N.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":922522,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Chang, Frederick","contributorId":347820,"corporation":false,"usgs":false,"family":"Chang","given":"Frederick","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":922526,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70267414,"text":"70267414 - 2025 - Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal","interactions":[],"lastModifiedDate":"2025-05-23T15:38:31.239395","indexId":"70267414","displayToPublicDate":"2025-01-01T10:31:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19856,"text":"Laurentian","active":true,"publicationSubtype":{"id":10}},"title":"Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal","docAbstract":"<p><span>The Sandusky River, Ohio, USA, has experienced more than a century of alterations, including dam implementation and removal, causing a cascade of habitat changes. The physical changes in the river led to establishment of several invasive species. Ten hoop-net sampling sites, spaced about 500 m apart were established in the river to monitor fish assemblage and their habitat preferences. Four 10-d sampling events were completed from April through October 2021. Ordination analyses were used to assess fish-assemblage structure seasonably, species-habitat relationships, and life-history strategies of 31 species. Generalized linear mixed-effects models were used to assess temporal factors that may drive diversity and community assemblage. Models indicated increased species richness after removal of the dam. Presence and proportion of catch data were compared to Ohio Environmental Protection Agency 2009 pre-dam-removal data to further assess changes in fish assemblage. Several species, especially catostomids, have begun to use the habitat downstream of the former dam, altering fish assemblage throughout the river. We expect shifts in assemblage structure to persist, making continued monitoring essential for understanding how non-native and recreationally important species continue to respond to dam removal.</span></p>","language":"English","publisher":"Great Lakes Fishery Commission","doi":"10.70227/GDZU9409","usgsCitation":"Schulz, K., Acre, M.R., Mueller, A.T., Wamboldt, J.J., Broaddus, D., Hessler, T., Wilson, T., Mapes, R., Amberg, J., and Calfee, R.D., 2025, Fish-assemblage evaluation in the lower Sandusky River, Ohio, following dam removal: Laurentian, 2025-01, 26 p., https://doi.org/10.70227/GDZU9409.","productDescription":"2025-01, 26 p.","ipdsId":"IP-151712","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":498245,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.70227/gdzu9409","text":"Publisher Index Page"},{"id":486517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Sandusky River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.00181931823779,\n              41.45338855338082\n            ],\n            [\n              -83.09113294485806,\n              41.45338855338082\n            ],\n            [\n              -83.09113294485806,\n              41.411024886695174\n            ],\n            [\n              -83.00181931823779,\n              41.411024886695174\n            ],\n            [\n              -83.00181931823779,\n              41.45338855338082\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationDate":"2025-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulz, Kailee Amanda 0000-0002-0998-7951","orcid":"https://orcid.org/0000-0002-0998-7951","contributorId":339886,"corporation":false,"usgs":true,"family":"Schulz","given":"Kailee Amanda","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":938141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Andrew T. 0000-0001-8566-8023","orcid":"https://orcid.org/0000-0001-8566-8023","contributorId":238278,"corporation":false,"usgs":true,"family":"Mueller","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wamboldt, James J. 0000-0003-3043-5198","orcid":"https://orcid.org/0000-0003-3043-5198","contributorId":219060,"corporation":false,"usgs":true,"family":"Wamboldt","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":938144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Broaddus, Dustin 0000-0002-3160-0477","orcid":"https://orcid.org/0000-0002-3160-0477","contributorId":331134,"corporation":false,"usgs":true,"family":"Broaddus","given":"Dustin","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hessler, Tyler","contributorId":352222,"corporation":false,"usgs":false,"family":"Hessler","given":"Tyler","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":938146,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson, Tammy Michelle 0000-0001-8570-6069","orcid":"https://orcid.org/0000-0001-8570-6069","contributorId":339888,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy Michelle","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938147,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mapes, Robert L.","contributorId":339890,"corporation":false,"usgs":false,"family":"Mapes","given":"Robert L.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":938148,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":938149,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938150,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70268834,"text":"70268834 - 2025 - Statistical review of systematic reconnaissance flight (SRF) surveys (2008-2023) for monitoring American alligator (Alligator mississippiensis) nests in Everglades National Park","interactions":[],"lastModifiedDate":"2025-07-08T15:19:30.719881","indexId":"70268834","displayToPublicDate":"2025-01-01T10:15:28","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Statistical review of systematic reconnaissance flight (SRF) surveys (2008-2023) for monitoring American alligator (Alligator mississippiensis) nests in Everglades National Park","docAbstract":"<p>We reviewed current (2008-2023) protocols for monitoring American alligator nests in Everglades National Park (ENP) using a qualitative statistical review framework that emphasizes connecting measurable objectives with evaluation of survey design elements. Our review outlined the statistical assumptions that, if severely violated, would prevent defensible inferences from being drawn regarding the three alligator nesting metrics monitored in ENP’s systematic reconnaissance flight (SRF) surveys: nest effort (number of nests), nest distribution, and nest fate. After evaluating the current survey and inference methods, we offer potential adjustments or augmentations to the design and models currently used to better account for potential error sources and align the stated objectives with statistical inferences.</p>","language":"English","publisher":"National Park Service","doi":"10.36967/2307861","usgsCitation":"Rieber, C., Irvine, K., Dean, T., McCaffrey, K., Parry, M., and Strickland, B.A., 2025, Statistical review of systematic reconnaissance flight (SRF) surveys (2008-2023) for monitoring American alligator (Alligator mississippiensis) nests in Everglades National Park, 41 p., https://doi.org/10.36967/2307861.","productDescription":"41 p.","ipdsId":"IP-172357","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":491800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.21727403045963,\n              25.795899732767708\n            ],\n            [\n              -81.21727403045963,\n              25.13941607702479\n            ],\n            [\n              -80.31670690774011,\n              25.13941607702479\n            ],\n            [\n              -80.31670690774011,\n              25.795899732767708\n            ],\n            [\n              -81.21727403045963,\n              25.795899732767708\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rieber, Camille Julia 0009-0009-8680-3237","orcid":"https://orcid.org/0009-0009-8680-3237","contributorId":357712,"corporation":false,"usgs":true,"family":"Rieber","given":"Camille Julia","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":942275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":221555,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":942276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dean, Tylan","contributorId":301064,"corporation":false,"usgs":false,"family":"Dean","given":"Tylan","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCaffrey, Kelly","contributorId":357713,"corporation":false,"usgs":false,"family":"McCaffrey","given":"Kelly","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parry, Mark","contributorId":175457,"corporation":false,"usgs":false,"family":"Parry","given":"Mark","email":"","affiliations":[],"preferred":false,"id":942279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Strickland, Bradley A.","contributorId":177343,"corporation":false,"usgs":false,"family":"Strickland","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":942280,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70261473,"text":"70261473 - 2025 - The progression of basaltic–rhyolitic melt storage at Yellowstone Caldera","interactions":[],"lastModifiedDate":"2025-01-14T16:14:26.059072","indexId":"70261473","displayToPublicDate":"2025-01-01T10:08:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"The progression of basaltic–rhyolitic melt storage at Yellowstone Caldera","docAbstract":"<p><span>Yellowstone Caldera is one of the largest volcanic systems on Earth, hosting three major caldera-forming eruptions in the past two million years, interspersed with periods of less explosive, smaller-volume eruptions</span><sup><a id=\"ref-link-section-d1654952e503\" title=\"Christiansen, R. L. The Quaternary and Pliocene Yellowstone Plateau Volcanic Field of Wyoming, Idaho, and Montana Vol. 729 (US Department of the Interior, US Geological Survey, 2001).\" href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR1\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 1\" data-mce-href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR1\">1</a></sup><span>. Caldera-forming eruptions at Yellowstone are sourced by rhyolitic melts stored within the mid- to upper crust. Seismic tomography studies have suggested that a broad region of rhyolitic melt extends beneath Yellowstone Caldera, with an estimated melt volume that is one to four times greater than the eruptive volume of the largest past caldera-forming eruption, and an estimated melt fraction of 6–28 per cent</span><sup><a id=\"ref-link-section-d1654952e507\" title=\"Jiang, C., Schmandt, B., Farrell, J., Lin, F.-C. &amp; Ward, K. M. Seismically anisotropic magma reservoirs underlying silicic calderas. Geology 46, 727–730 (2018).\" href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR2\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" data-mce-href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR2\">2</a>,<a id=\"ref-link-section-d1654952e507_1\" title=\"Wu, S.-M., Huang, H.-H., Lin, F.-C., Farrell, J. &amp; Schmandt, B. Extreme seismic anisotropy indicates shallow accumulation of magmatic sills beneath Yellowstone Caldera. Earth Planet. Sci. Lett. 616, 118244 (2023).\" href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR3\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" data-mce-href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR3\">3</a>,<a id=\"ref-link-section-d1654952e507_2\" title=\"Maguire, R. et al. Magma accumulation at depths of prior rhyolite storage beneath Yellowstone Caldera. Science 378, 1001–1004 (2022).\" href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR4\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" data-mce-href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR4\">4</a>,<a id=\"ref-link-section-d1654952e510\" title=\"Huang, H. H. et al. The Yellowstone magmatic system from the mantle plume to the upper crust. Science 348, 773–776 (2015).\" href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR5\" data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 5\" data-mce-href=\"https://www.nature.com/articles/s41586-024-08286-z#ref-CR5\">5</a></sup><span>. Seismic velocity is strongly influenced by temperature, pressure and melt; however, magnetotelluric data are primarily sensitive to the presence of melt, making these data ideal for constraining volcanic systems. Here we utilize magnetotelluric data to model the resistivity structure of Yellowstone Caldera’s crustal magma reservoir and constrain the region’s potential for producing major volcanic eruptions. We find that rhyolitic melts are stored in segregated regions beneath the caldera with low melt fractions, indicating that the reservoirs are not eruptible. Typically, these regions have melt volumes equivalent to small-volume post-caldera Yellowstone eruptions. The largest region of rhyolitic melt storage, concentrated beneath northeast Yellowstone Caldera, has a storage volume similar to the eruptive volume of Yellowstone’s smallest caldera-forming eruption. We identify regions of basalt migrating from the lower crust, merging with and supplying heat to the northeast region of rhyolitic melt storage. On the basis of our analysis, we suggest that the locus of future rhyolitic volcanism has shifted to northeast Yellowstone Caldera.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41586-024-08286-z","usgsCitation":"Bennington, N.L., Schultz, A., Bedrosian, P.A., Bowles-Martinez, E., Lynn, K.J., Stelten, M.E., Tu, X., and Thurber, C., 2025, The progression of basaltic–rhyolitic melt storage at Yellowstone Caldera: Nature, v. 637, p. 97-102, https://doi.org/10.1038/s41586-024-08286-z.","productDescription":"6 p.","startPage":"97","endPage":"102","ipdsId":"IP-168140","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone Caldera","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.8,\n              45.2\n            ],\n            [\n              -111.8,\n              43.9\n            ],\n            [\n              -109.8,\n              43.9\n            ],\n            [\n              -109.8,\n              45.2\n            ],\n            [\n              -111.8,\n              45.2\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"637","noUsgsAuthors":false,"publicationDate":"2025-01-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Bennington, Ninfa Lucia 0000-0003-3230-6744","orcid":"https://orcid.org/0000-0003-3230-6744","contributorId":346226,"corporation":false,"usgs":true,"family":"Bennington","given":"Ninfa","email":"","middleInitial":"Lucia","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, Adam","contributorId":347045,"corporation":false,"usgs":false,"family":"Schultz","given":"Adam","affiliations":[{"id":12961,"text":"College of Earth, Ocean, and Atmospheric Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":920677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowles-Martinez, Esteban","contributorId":347046,"corporation":false,"usgs":false,"family":"Bowles-Martinez","given":"Esteban","affiliations":[{"id":12961,"text":"College of Earth, Ocean, and Atmospheric Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":920678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920679,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920680,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tu, Xiaolei","contributorId":347047,"corporation":false,"usgs":false,"family":"Tu","given":"Xiaolei","affiliations":[{"id":12961,"text":"College of Earth, Ocean, and Atmospheric Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":920681,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thurber, Clifford","contributorId":347048,"corporation":false,"usgs":false,"family":"Thurber","given":"Clifford","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":920682,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70263713,"text":"70263713 - 2025 - Sex differences in migration routes and non-breeding areas of a declining shorebird","interactions":[],"lastModifiedDate":"2025-02-20T15:40:42.561015","indexId":"70263713","displayToPublicDate":"2025-01-01T09:36:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Sex differences in migration routes and non-breeding areas of a declining shorebird","docAbstract":"<p><span>Migratory birds face different threats and pressures across their annual cycle, and understanding the impact of these factors on individuals is critical to the conservation of avian populations. Individuals from the same breeding population may share the same non-breeding areas, and thus experience similar conditions, or they may travel to different habitats or regions during migration and the stationary non-breeding period. Marbled Godwits (</span><i>Limosa fedoa</i><span>) breeding in the Northern Great Plains, which have experienced steep population declines, are thought to spend the non-breeding period primarily on the Pacific Coast of the United States and Mexico. However, little is known about migratory routes, stopover sites, and non-breeding locations of specific breeding populations, nor whether individuals from the same breeding population remain together throughout the year. We deployed satellite transmitters on four mated pairs of godwits breeding in southern Alberta, Canada, with individuals tracked over a mean of 2.2 annual cycles (range 0.6–5.6, excluding one unit that stopped transmitting immediately following deployment). Counter to our expectations, females and males separated completely following breeding, with females traveling to non-breeding areas along the coast of California, United States, and males stopping over at Great Salt Lake, Utah, United States, and spending the non-breeding period in Baja California Sur, Mexico, a distance of ~1300 km from their mates. Despite spending nine months apart, individuals from this breeding population have previously been shown to have high mate fidelity. Interestingly, individuals mostly used protected areas during the non-breeding period, in contrast to the human-modified agricultural landscapes that make up the majority of their breeding grounds. Despite a small sample size, our results suggest a strong pattern of differential migration based on sex, with implications for the specific environmental conditions, and potentially threats, faced by female and male godwits across the annual cycle.</span></p>","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ACE-02785-200102","usgsCitation":"McKellar, A.E., Gratto-Trevor, C.L., and Tibbitts, T., 2025, Sex differences in migration routes and non-breeding areas of a declining shorebird: Avian Conservation and Ecology, v. 20, no. 1, 2, 12 p., https://doi.org/10.5751/ACE-02785-200102.","productDescription":"2, 12 p.","ipdsId":"IP-169987","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":489861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02785-200102","text":"Publisher Index Page"},{"id":482272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.47009688253796,\n              51.647756647734525\n            ],\n            [\n              -125.25783924890335,\n              51.647756647734525\n            ],\n            [\n              -125.25783924890335,\n              26.731178692950436\n            ],\n            [\n              -110.47009688253796,\n              26.731178692950436\n            ],\n            [\n              -110.47009688253796,\n              51.647756647734525\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKellar, Ann E.","contributorId":340997,"corporation":false,"usgs":false,"family":"McKellar","given":"Ann","email":"","middleInitial":"E.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":927928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gratto-Trevor, Cheri L","contributorId":270109,"corporation":false,"usgs":false,"family":"Gratto-Trevor","given":"Cheri","email":"","middleInitial":"L","affiliations":[{"id":48188,"text":"Environment Canada","active":true,"usgs":false}],"preferred":false,"id":927929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tibbitts, T. Lee 0000-0002-0290-7592","orcid":"https://orcid.org/0000-0002-0290-7592","contributorId":224104,"corporation":false,"usgs":true,"family":"Tibbitts","given":"T. Lee","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":927930,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70269033,"text":"70269033 - 2025 - Predictability and behavior of water transfers across basin boundaries","interactions":[],"lastModifiedDate":"2025-07-15T15:23:21.548418","indexId":"70269033","displayToPublicDate":"2024-12-31T10:12:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Predictability and behavior of water transfers across basin boundaries","docAbstract":"<p><span>Inter-basin water transfers (IBTs) are important components of water balances of basins, and they can have substantial impact on regional water availability. Flow information is often not available at locations with known IBTs, which is a drawback in several published IBT databases. Few, if any, studies examine whether IBT flow behavior can be generalized, and if these behaviors can be predicted at undocumented locations or known IBT locations with no flow information. In this study, we employ a clustering method based on image matching to identify similar classes of flow behavior of IBTs. Machine learning models are used to assess how well IBT flow characteristics (e.g., average flow) associated with these behaviors can be predicted. These evaluations of IBTs are done for two regions in the United States. Three primary classes of IBTs (seasonal, nonseasonal/not mixed, and seasonal/mixed) are identified across the two regions analyzed. The IBT flow characteristics are accurately predicted in the northeast region. In the Colorado region, however, only the flow characteristics related to timing were accurately predicted. These results indicate that the proposed modeling framework can be used to identify generalizable IBT flow characteristics. This framework is shown to predict flow characteristics with a reasonable amount of accuracy to undocumented locations and improves previously published IBT databases by backfilling flow information to locations with a known IBT presence.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13250","usgsCitation":"Eng, K., Medalie, L., Skinner, K.D., Ivahnenko, T., Heilman, J.A., and Smith, J.D., 2025, Predictability and behavior of water transfers across basin boundaries: Journal of the American Water Resources Association, v. 61, e13250, 15 p., https://doi.org/10.1111/1752-1688.13250.","productDescription":"e13250, 15 p.","ipdsId":"IP-147952","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":497991,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13250","text":"Publisher Index Page"},{"id":492245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Delaware, Kansas, Maryland, Massachusetts, Nebraska, New Jersey, New Mexico, New York, Ohio, Oklahoma, Pennsylvania, Utah, Vermont, Virginia, West Virginia, Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.75734409961451,\n              45.09868924907843\n            ],\n            [\n              -80.97443752275147,\n              45.09868924907843\n            ],\n            [\n              -80.97443752275147,\n              38.117403832345445\n            ],\n            [\n              -72.75734409961451,\n              38.117403832345445\n            ],\n            [\n              -72.75734409961451,\n              45.09868924907843\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.52129035595209,\n              41.629774044376546\n            ],\n            [\n              -110.52129035595209,\n              35.490831922925224\n            ],\n            [\n              -100.9978185470249,\n              35.490831922925224\n            ],\n            [\n              -100.9978185470249,\n              41.629774044376546\n            ],\n            [\n              -110.52129035595209,\n              41.629774044376546\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"61","noUsgsAuthors":false,"publicationDate":"2024-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":942990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medalie, Laura 0000-0002-2440-2149","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":258234,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skinner, Kenneth D. 0000-0003-1774-6565","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":204388,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ivahnenko, Tamara 0000-0002-1124-7688","orcid":"https://orcid.org/0000-0002-1124-7688","contributorId":344276,"corporation":false,"usgs":false,"family":"Ivahnenko","given":"Tamara","affiliations":[{"id":34498,"text":"USGS retiree","active":true,"usgs":false}],"preferred":false,"id":942993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heilman, Julian A. 0000-0002-2987-4057 jahr@usgs.gov","orcid":"https://orcid.org/0000-0002-2987-4057","contributorId":202192,"corporation":false,"usgs":true,"family":"Heilman","given":"Julian","email":"jahr@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":942994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Jared David 0000-0003-3124-8255","orcid":"https://orcid.org/0000-0003-3124-8255","contributorId":329716,"corporation":false,"usgs":true,"family":"Smith","given":"Jared","email":"","middleInitial":"David","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":942995,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70262583,"text":"70262583 - 2025 - Ensemble methods for parameter estimation of WRF-Hydro","interactions":[],"lastModifiedDate":"2025-01-21T17:12:52.004655","indexId":"70262583","displayToPublicDate":"2024-12-30T11:07:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble methods for parameter estimation of WRF-Hydro","docAbstract":"<p><span>The WRF-Hydro hydrological model has been used in many applications in the past with some level of history matching in the majority of these studies. In this study, we use the iterative Ensemble Smoother (iES), a powerful parameter estimation methodology implemented in the open-source PEST++ software. The iES provides an ensemble solution with an uncertainty bound instead of a single best estimate which has been the common approach in the previous WRF-Hydro studies. We discuss the importance of accounting for observation noise which results in a wider spread in the model solution. We investigate the impact of constructing objective functions by differentially weighting the observations to tune the model response toward model outputs appropriate for a specific application. Results confirm the necessity of differentially weighting the observations before calculation of the objective function as the optimization algorithm struggles with calculating parameter updates with uniform weighting. We also show that we achieve better model performance in terms of verification metrics with higher emphasis on the high flow events, when the objective function is tuned toward an application where the extreme events are of importance. We then investigate the impact of estimating more parameters, in particular we estimate a larger number of snow parameters. Results show a large improvement in the model performance. In summary, our study demonstrates the efficacy of employing iES alongside differential weighting of observations, highlighting its potential to enhance hydrological model parameter estimation.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR038048","usgsCitation":"RafieeiNasab, A., Fienen, M., Omani, N., Srivastava, I., and Dugger, A., 2025, Ensemble methods for parameter estimation of WRF-Hydro: Water Resources Research, v. 61, no. 1, e2024WR038048, 32 p., https://doi.org/10.1029/2024WR038048.","productDescription":"e2024WR038048, 32 p.","ipdsId":"IP-172257","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":481033,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr038048","text":"Publisher Index Page"},{"id":480841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"RafieeiNasab, Arezoo","contributorId":349704,"corporation":false,"usgs":false,"family":"RafieeiNasab","given":"Arezoo","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":924612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Omani, Nina","contributorId":349705,"corporation":false,"usgs":false,"family":"Omani","given":"Nina","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":924614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Srivastava, Ishita","contributorId":349706,"corporation":false,"usgs":false,"family":"Srivastava","given":"Ishita","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":924615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Aubrey","contributorId":349707,"corporation":false,"usgs":false,"family":"Dugger","given":"Aubrey","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":924616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70261990,"text":"70261990 - 2025 - Integrating Sr isotopes, microchemistry, and genetics to reconstruct Salmonidae species and life history","interactions":[],"lastModifiedDate":"2025-01-08T15:17:33.385758","indexId":"70261990","displayToPublicDate":"2024-12-30T09:12:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":881,"text":"Archaeometry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Integrating Sr isotopes, microchemistry, and genetics to reconstruct <i>Salmonidae</i> species and life history","title":"Integrating Sr isotopes, microchemistry, and genetics to reconstruct Salmonidae species and life history","docAbstract":"<p><span>Recent approaches to fisheries research emphasize the importance of the coproduction of knowledge in building resilient and culturally mindful fisheries management frameworks. Despite widespread recognition of the need for Indigenous knowledge and historical reference points as baseline data, archaeological data are rarely included in conservation biology research designs. Here we propose a novel multiproxy method to learn from former fisheries stewards by generating archaeological data on past salmonid population parameters. We used a newly developed, high throughput qPCR (HT-qPCR) chip, originally designed for environmental DNA (eDNA), for species identification of archaeological salmonid vertebrae. We combine this with the laser ablation split-stream (LASS) approach to identify ocean-migration versus freshwater residency. We test this multidisciplinary approach using both contemporary and archaeological salmonid samples and new radiocarbon dates from the Tronsdal Site on the Skagit River, Washington State, USA. This is a useful approach for extracting information about&nbsp;</span><i>Salmonidae</i><span>&nbsp;species and life history diversity from archaeological remains to reconstruct historic baselines for several population parameters in anadromous species with long periods of freshwater residency. The approach outlined in this paper may be particularly useful for research investigating past fisheries dynamics, offering hundreds to thousands of years of temporal depth for modern fisheries management, harvest policies, restoration ecology, and conservation biology.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/arcm.13058","usgsCitation":"Salerno, R., Murdoch, R., Taylor Wilcox, Elmore, J., Hegg, J., Austin, C.S., LeMoine, M., Luckhurst, J., Fraik, A., and Molly Carney, 2025, Integrating Sr isotopes, microchemistry, and genetics to reconstruct Salmonidae species and life history: Archaeometry, https://doi.org/10.1111/arcm.13058.","ipdsId":"IP-163914","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":466671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/arcm.13058","text":"Publisher Index Page"},{"id":465877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2024-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Salerno, Ross Anthony 0000-0002-0053-5668","orcid":"https://orcid.org/0000-0002-0053-5668","contributorId":347832,"corporation":false,"usgs":true,"family":"Salerno","given":"Ross Anthony","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":922565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murdoch, Remi 0009-0004-2039-0795","orcid":"https://orcid.org/0009-0004-2039-0795","contributorId":347833,"corporation":false,"usgs":false,"family":"Murdoch","given":"Remi","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":922566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor Wilcox","contributorId":347835,"corporation":false,"usgs":false,"family":"Taylor Wilcox","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":922568,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elmore, Joanna 0000-0002-2851-6290","orcid":"https://orcid.org/0000-0002-2851-6290","contributorId":347834,"corporation":false,"usgs":false,"family":"Elmore","given":"Joanna","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":922567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hegg, Jens 0000-0003-0125-9287","orcid":"https://orcid.org/0000-0003-0125-9287","contributorId":347836,"corporation":false,"usgs":false,"family":"Hegg","given":"Jens","affiliations":[{"id":83257,"text":"Gonzaga University","active":true,"usgs":false}],"preferred":false,"id":922569,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Austin, Catherine S 0000-0003-4245-8266","orcid":"https://orcid.org/0000-0003-4245-8266","contributorId":316293,"corporation":false,"usgs":false,"family":"Austin","given":"Catherine","email":"","middleInitial":"S","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":922570,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeMoine, Michael","contributorId":300286,"corporation":false,"usgs":false,"family":"LeMoine","given":"Michael","email":"","affiliations":[{"id":65066,"text":"Skagit River Systems Cooperative","active":true,"usgs":false}],"preferred":false,"id":922571,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Luckhurst, Jade","contributorId":347838,"corporation":false,"usgs":false,"family":"Luckhurst","given":"Jade","affiliations":[{"id":83258,"text":"Skagit River System Cooperative","active":true,"usgs":false}],"preferred":false,"id":922572,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fraik, Alexandra 0000-0002-9285-1173","orcid":"https://orcid.org/0000-0002-9285-1173","contributorId":347839,"corporation":false,"usgs":false,"family":"Fraik","given":"Alexandra","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":922573,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Molly Carney 0000-0003-1535-7363","orcid":"https://orcid.org/0000-0003-1535-7363","contributorId":347840,"corporation":false,"usgs":false,"family":"Molly Carney","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":922574,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70261863,"text":"70261863 - 2025 - Shifts in marsh erosion, migration, and wave exposure over nearly two centuries of sea-level rise in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2025-05-13T15:58:12.378691","indexId":"70261863","displayToPublicDate":"2024-12-30T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19865,"text":"Estuarine Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Shifts in marsh erosion, migration, and wave exposure over nearly two centuries of sea-level rise in the Gulf of Mexico","docAbstract":"<p><span>Coastal wetlands are economically important ecosystems, but are at risk to erosion from waves, storms, and sea level rise. However, marshes can persist under rising sea level through vertical accretion and migration into adjacent higher-elevation habitats. We measured rates of marsh shoreline change and migration and compared the results for historical and modern periods in a largely undeveloped and marine-dominated estuary within the Mississippi-Alabama coast of the Northern Gulf of Mexico. Mean shoreline change rate for the modern (post-1957) period was higher than historical rates (pre-1957) at −1.55&nbsp;±&nbsp;0.11&nbsp;m yr</span><sup>−1</sup><span>&nbsp;and -0.84&nbsp;±&nbsp;0.07&nbsp;m yr</span><sup>−1</sup><span>, respectively. Shoreline change rates were highest in regions where exposure to wind-driven waves increased due to barrier island migration and land loss. Marsh migration (modern 1.25&nbsp;±&nbsp;0.37&nbsp;m yr</span><sup>−1</sup><span>&nbsp;and historical 1.01&nbsp;±&nbsp;0.13&nbsp;m yr</span><sup>−1</sup><span>) occurred at similar rates as shoreline erosion except for the highest erosive shorelines, leading to an overall 15% marsh loss. Upland-to-marsh conversion occurred in forested areas and may have been encouraged by changes in management practices. In the Grand Bay estuary, our data show that marsh migration is not occurring at sufficient rates to compensate for marsh loss, resulting in overall loss in marsh habitat. Overall, migration may allow marsh to persist under rising sea levels but can lead to an overall reduction in forested or freshwater habitats if steep slopes or other barriers prevent their migration.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2024.109106","usgsCitation":"Smith, K., Terrano, J.F., Jenkins, R., Pitchford, J.L., Passeri, D., and Smith, C., 2025, Shifts in marsh erosion, migration, and wave exposure over nearly two centuries of sea-level rise in the Gulf of Mexico: Estuarine Coastal and Shelf Science, v. 313, 109106, 14 p., https://doi.org/10.1016/j.ecss.2024.109106.","productDescription":"109106, 14 p.","ipdsId":"IP-158052","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488386,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2024.109106","text":"Publisher Index Page"},{"id":465577,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.87381287579537,\n              30.63451483614469\n            ],\n            [\n              -88.87381287579537,\n              30.24759264551828\n            ],\n            [\n              -88.04948746031226,\n              30.24759264551828\n            ],\n            [\n              -88.04948746031226,\n              30.63451483614469\n            ],\n            [\n              -88.87381287579537,\n              30.63451483614469\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"313","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":922077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrano, Joseph F. 0000-0003-3060-7682 jterrano@usgs.gov","orcid":"https://orcid.org/0000-0003-3060-7682","contributorId":173263,"corporation":false,"usgs":true,"family":"Terrano","given":"Joseph","email":"jterrano@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":922078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Robert L. 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,{"id":70269529,"text":"70269529 - 2025 - Potential 2050 distributions of World Terrestrial Ecosystems from projections of changes in World Climate Regions and Global Land Cover","interactions":[],"lastModifiedDate":"2025-07-25T14:24:26.715073","indexId":"70269529","displayToPublicDate":"2024-12-24T09:17:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Potential 2050 distributions of World Terrestrial Ecosystems from projections of changes in World Climate Regions and Global Land Cover","docAbstract":"<p><span>The urgency to address ecosystem loss is paramount, as both land use change and climate change will continue to rapidly alter and degrade natural ecosystems and reduce the many services they provide. To support conservation actions that mitigate impacts from these dual threats, we have developed potential World Terrestrial Ecosystem (WTE) distributions for 2050 following IPCC best practice guidelines. This projection of ecosystem distributions builds on the previously released 2015 WTEs, a snapshot of the distribution and conservation status of 431 terrestrial ecosystem types defined as distinct combinations of 18 global climate regions, 4 global landform classes, and 8 global vegetation/land cover classes. Extending that work herein, we modeled the potential 2050 WTE distributions based on projections of five CMIP6 general circulation models (GCMs) and one global land cover change model, determined for three shared socioeconomic pathway (SSP) scenarios. The climate region modeling included projections for 2050 for both mean annual temperature and mean annual aridity. Model agreement for changes to WTEs was generally high, particularly for temperature projections. Widespread changes in ecosystem classes due to shifts in climate settings and/or land cover between 2015 and 2050 were projected, with both the magnitude and specific geography of projected change largely governed by the SSP scenario. For the three SSP scenarios (sustainable development, regional rivalry, and fossil-fueled development), geographic changes in climate setting (temperature, aridity, or both) and/or changes in vegetation/land cover are projected for 29 %, 36 %, and 39 % of Earth’s terrestrial surface, respectively. These changes occur in areas where 31 %, 36 %, and 41 % of the global population lives. Projected changes in ecosystem distributions related to temperature change are approximately an order of magnitude greater than for aridity change. By offering insight into potential ecosystem changes, this new resource is intended to facilitate conservation planning and priority setting aimed at improved conservation of biodiversity and ecosystem services.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2024.e03370","usgsCitation":"Sayre, R., Frye, C., Breyer, S., Roehrdanz, P., Elsen, P., Butler, K., Brown, C., Cress, J., Karagulle, D., Martin, M.T., Sangermano, F., Smyth, R., Sohl, T., Wolff, N., Wright, D., and Wu, Z., 2025, Potential 2050 distributions of World Terrestrial Ecosystems from projections of changes in World Climate Regions and Global Land Cover: Global Ecology and Conservation, v. 57, e03370, 20 p., https://doi.org/10.1016/j.gecco.2024.e03370.","productDescription":"e03370, 20 p.","ipdsId":"IP-170996","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science 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,{"id":70265978,"text":"70265978 - 2025 - Identifying lakes critical to the westward spread and establishment of zebra mussels","interactions":[],"lastModifiedDate":"2025-04-23T14:57:30.214434","indexId":"70265978","displayToPublicDate":"2024-12-20T09:39:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying lakes critical to the westward spread and establishment of zebra mussels","docAbstract":"<p><span>Damaging aquatic invasive species, such as the zebra mussel (</span><i>Dreissena polymorpha),</i><span>&nbsp;pose an ongoing concern for potential introduction and establishment in the western United States. Our study applied habitat suitability indices and network analysis to identify lakes critical to the continued westward spread and establishment of zebra mussels from a key invasion front in Texas. We created multiple networks consisting of lake nodes and connecting roadway edges. Each network represented the potential connectivity of lakes for recreational users depending on the distance boaters were likely to travel. We evaluated three networks with different maximum edge lengths based on boater movement surveys: 363-km, 125-km, and 51-km. Via graph analysis, we identified lakes critical to mussel spread by acting as hubs, stepping stones, or cutpoints in each network. Water quality-based habitat suitability indices classified most lakes in the study area as moderate to high suitability. In all networks, hubs were concentrated in northeastern Texas. At the lowest maximum edge lengths, stepping stones were also concentrated in the northeast, but could be found in the western portions of the study area as maximum travel distance increased. No cutpoints were found in the 363-km maximum edge length network, indicating a highly connected network with the potential for further western spread facilitated by stepping stones in western Texas and New Mexico. Identifying critical lakes using network analysis and habitat suitability indices provides a predictive tool for resource managers to guide the allocation of limited time and resources for management actions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110931","usgsCitation":"Creamer, D., Rogosch, J.S., Patino, R., and McGarrity, M., 2025, Identifying lakes critical to the westward spread and establishment of zebra mussels: Biological Conservation, v. 302, 110931, 12 p., https://doi.org/10.1016/j.biocon.2024.110931.","productDescription":"110931, 12 p.","ipdsId":"IP-164052","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2024.110931","text":"Publisher Index 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