Abundances of coldwater adapted stream fish populations are declining largely due to anthropogenic influences, including increased temperature. To persist in streams with unsuitable thermal habitat, fish must move to coldwater patches, acclimate, or adapt to water temperatures above thermal optima. Brook trout, a coldwater adapted salmonid, has previously displayed physiological plasticity and the ability for reversible thermal acclimation when reared at higher temperatures. However, because stream temperatures are not static, it is important to explore the rate at which thermal acclimation occurs to evaluate whether prior thermal experience will influence future thermal performance. To determine the temporal scale in loss of thermal acclimation as water temperatures cool, we acclimated brook trout to three thermal regimes: +0 °C (ambient; mimicking the daily average water temperature of a nearby long-term study site), as well as +2 °C and +4 °C above ambient. After 2 years of being reared under those conditions, fish from the warmer treatments were moved to a common, colder temperature (ambient). We then used critical thermal maximum to measure the loss in acclimation response of fish from each treatment over time. We found that regardless of initial acclimation temperature, thermal tolerance of warm acclimated fish decreased rapidly for 1 week, then gradually decreased, and was completely lost within 42 days. This gradual loss of acclimation may be valuable to persistence in warmer streams and will be important to include in models of the impact climate change has on brook trout and other aquatic ectotherms with significant thermal plasticity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2025.104103","usgsCitation":"O'Donnell, M., Regish, A.M., McCormick, S., and Letcher, B., 2025, How quickly do brook trout lose long-term thermal acclimation?: Journal of Thermal Biology, v. 129, 104103, 7 p., https://doi.org/10.1016/j.jtherbio.2025.104103.","productDescription":"104103, 7 p.","ipdsId":"IP-173670","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Whatley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.6617758519881,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.46221452312392\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":299019,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":932809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, S.D.","contributorId":353071,"corporation":false,"usgs":false,"family":"McCormick","given":"S.D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":932811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265472,"text":"sir20255012 - 2025 - Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022","interactions":[],"lastModifiedDate":"2025-04-16T14:15:30.417956","indexId":"sir20255012","displayToPublicDate":"2025-04-07T14:02:42","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5012","displayTitle":"Sediment Nutrient Dynamics in Selected Milwaukee Metropolitan Area Streams, Wisconsin, 2022","title":"Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022","docAbstract":"The U.S. Geological Survey and Milwaukee Metropolitan Sewerage District in Wisconsin have an ongoing partnership to monitor water quality in streams in the Milwaukee metropolitan area and to assess the effects of stream restoration on habitat and water quality. Because sediment nutrient dynamics can improve or further impair water quality, we measured sediment nitrogen and phosphorus concentrations, potential nitrogen removal, and potential phosphorus retention at 32 streams sites in the Milwaukee metropolitan area in summer 2022. Four of the sites were in rehabilitated stream reaches. Based on the results from this project, we provided a rating of good, fair, or poor for the sediment nutrient dynamics at each site.
Sediment nitrogen removal and phosphorus retention in stream reaches increased as the proportion of fine particles increased. Bioavailable nitrogen and phosphorus concentrations increased in stream reaches as particle size decreased, especially at locations with more silt and clay. Particle size typically decreased from upstream to downstream, and several of the sites with finer particles were in downstream parts of the study area, especially in the Milwaukee Estuary sites. The sites that had more fine sediment and higher bioavailable nutrients also had elevated rates of nitrification and denitrification enzyme activity, which is a measurement of the potential nitrogen removal when nitrogen and carbon do not limit the denitrifying bacteria. Additionally, sites with fine sediment typically had the highest potential to retain phosphorus as fine sediment provides many binding sites for phosphorus. The binding sites can become saturated with phosphorus, however, increasing the potential for the phosphorus to be released to stream water. Five of the 32 sampled sites were potentially saturated with phosphorus. Sites that contained more agricultural land in their drainage areas were at higher risk of having sediment that was saturated or near-saturation; however, the sites that had more agricultural land in their drainage areas also had higher nitrification rates. Results from this study indicate that stream rehabilitation projects that promote sediment deposition and accumulation of organic matter in the stream channel can increase nitrogen removal and phosphorus retention.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255012","usgsCitation":"Kreiling, R.M., Bartsch, L.A., Gierke, K.J., Perner, P.M., Fitzpatrick, F.A., and Olds, H.T., 2025, Sediment nutrient dynamics in selected Milwaukee metropolitan area streams, Wisconsin, 2022: U.S. Geological Survey Scientific Investigations Report 2025–5012, 34 p., https://doi.org/10.3133/sir20255012.","productDescription":"Report: vi, 34 p.; Data Release; Dataset","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168307","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":484256,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255012/full"},{"id":484255,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5012/images/"},{"id":484253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5012/sir20255012.pdf","text":"Report","size":"24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5012"},{"id":484258,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":484257,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14KFDFC","text":"USGS data release","linkHelpText":"Milwaukee Metropolitan Sewerage District nutrient connections project—In-stream nutrient cycling, 2022 data"},{"id":484254,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5012/sir20255012.XML"},{"id":484252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5012/coverthb.jpg"}],"country":"United States","state":"Wisconsin","city":"Milwaukee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.86648934255896,\n 43.18238733374105\n ],\n [\n -88.05617136083607,\n 43.18238733374105\n ],\n [\n -88.05617136083607,\n 42.87118189515698\n ],\n [\n -87.82769074791146,\n 42.88302863937423\n ],\n [\n -87.86648934255896,\n 43.18238733374105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Freshwater forested wetlands account for ~76% (918 M ha) of the total global wetland extent. However, freshwater forested wetlands are difficult to distinguish from upland forest due to canopy coverage, the abundance of wetland-nonwetland mosaics, seasonal hydropatterns, and fewer readily observable connections to large surface water bodies relative to marshes and other emergent habitats. Therefore, freshwater forested wetland ecosystems are often misclassified as upland forests in carbon accounting models, underestimating soil organic carbon (SOC) storage. This study highlights freshwater forested wetland SOC accounting challenges and presents SOC densities/stocks from a global literature synthesis across different freshwater forested wetland types. We reviewed 374 forested wetland articles, compiling and calculating carbon densities by depth from 90 freshwater forested wetland studies to construct a database of 334 study sites including nine countries. The median (± median absolute deviation) SOC stock was 91.2 ± 46.4 Mg C ha−1 and 235.3 ± 125.6 Mg C ha−1 in the top 30 cm and 100 cm of soil, respectively. The tidal freshwater forested wetland had highest SOC stock (341.6 ± 98.4 Mg C ha−1) in the upper 100 cm soil profile followed by rainforest (285.6 ± 75.8 Mg C ha−1), non-tidal swamps (229.3 ± 120.4 Mg C ha−1), and floodplain forested wetlands (176.6 ± 84 Mg C ha−1). Within the conterminous United States forest type groups, the Tsuga/Picea group had the highest median SOC stocks (353.6 ± 82.9 Mg ha−1) in the top 100 cm of soil followed by Quercus/Pinus (246.6 ± 82.3 Mg ha−1) and Quercus/Liquidambar/Taxodium (207.9 ± 87.7 Mg ha−1) groups, likely driven by variability in litter degradability, wetland hydroperiod, geomorphic positions, and regional climatic factors. This literature synthesis highlights SOC accounting in freshwater forested wetland carbon pools when estimating carbon stocks and fluxes. Results can be used to improve carbon modeling outcomes, as well as inform regional, national, and global management of wetland carbon resources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2025.1528440","usgsCitation":"Sapkota, Y., Berkowitz, J., Stagg, C., and Busby, R., 2025, A synthesis of freshwater forested wetland soil organic carbon storage: Frontiers in Forests and Global Change, v. 8, 1528440, 15 p., https://doi.org/10.3389/ffgc.2025.1528440.","productDescription":"1528440, 15 p.","ipdsId":"IP-176238","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2025.1528440","text":"Publisher Index Page"},{"id":484639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Sapkota, Yadav","contributorId":353419,"corporation":false,"usgs":false,"family":"Sapkota","given":"Yadav","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Jacob F.","contributorId":353422,"corporation":false,"usgs":false,"family":"Berkowitz","given":"Jacob F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":214880,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":933530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busby, Ryan R.","contributorId":353425,"corporation":false,"usgs":false,"family":"Busby","given":"Ryan R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273025,"text":"70273025 - 2025 - Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","interactions":[],"lastModifiedDate":"2025-12-15T14:46:55.827369","indexId":"70273025","displayToPublicDate":"2025-04-07T08:38:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","title":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","docAbstract":"The freshwater copepod Salmincola californiensis is an ectoparasite of Pacific salmon and trout (Oncorhynchus spp.). High levels of infection by this parasite can significantly damage gills and result in blood loss, affecting the fitness and survival of hosts, and it may hinder recovery efforts of threatened and endangered salmonids. Juvenile salmonids that rear in reservoirs have been reported to experience higher rates of infection than their stream-dwelling counterparts. To date, the relationship between reservoir environmental conditions and infection rates remains poorly understood. Here, we evaluated sampling methods designed to capture S. californiensis copepodids, the free-swimming infectious life stage of this parasitic copepod, and develop predictive models of parasite abundance in reservoirs. We used light traps to collect 675 zooplankton samples from various sites and depths in Cougar, Lookout Point, and Fall Creek reservoirs, Oregon, USA during five months in 2020. We tested several predictive models of parasite abundance using environmental covariates obtained concurrently during plankton surveys (e.g., temperature, ambient light and water clarity, reservoir plankton profiles, and water flow). Our models showed a strong influence of water temperature on abundance of copepodids, with maximum initial abundance occurring at the mean water temperature 15.2 °C. At that temperature, August abundance was estimated to be 58.6 copepodids per site in Cougar Reservoir, 43.8 copepodids per site in Fall Creek Reservoir, and 3.5 copepodids per site in Lookout Point Reservoir. Water temperature and reservoir outflow both affected population growth of copepodids: increased water temperature was associated with an increase in population growth rate while an increased reservoir outflow was associated with a decrease in population growth rate. The efficacy of our sampling method was influenced by percent of moon fullness, whether the sample site was above or below the thermocline, water temperature, and number of juvenile sculpin fishes (Cottus spp.) captured in the trap. The mean probability of detecting a single copepodid if one was present was 0.042, but detection probability increased to 0.29 under ideal trap set conditions of warmer water, location above the thermocline, and a full moon. Biologists and managers could use these methods to assess the presence and abundance of S. californiensis in other locations, or to inform reservoir operations to reduce potential salmonid infections.
","language":"English","publisher":"Peer J","doi":"10.7717/peerj.19228","usgsCitation":"Antonelli, K., Murphy, C.A., Pollock, A.M., and Arismendi, I., 2025, Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon: Aquatic Biology, v. 13, e19228, 24 p., https://doi.org/10.7717/peerj.19228.","productDescription":"e19228, 24 p.","ipdsId":"IP-172281","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497701,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.19228","text":"Publisher Index Page"},{"id":497471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"upper Willamette River reservoirs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.32050813525171,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.19989455893608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Antonelli, Kelsi","contributorId":341106,"corporation":false,"usgs":false,"family":"Antonelli","given":"Kelsi","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollock, Amanda M.M.","contributorId":363932,"corporation":false,"usgs":false,"family":"Pollock","given":"Amanda","middleInitial":"M.M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265447,"text":"70265447 - 2025 - Estimating indicators of cyanobacterial harmful algal blooms in New York State","interactions":[],"lastModifiedDate":"2025-04-07T14:54:27.747567","indexId":"70265447","displayToPublicDate":"2025-04-07T07:50:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Estimating indicators of cyanobacterial harmful algal blooms in New York State","docAbstract":"Cyanobacteria harmful algal blooms (cyanoHABs) are a global concern for aquatic ecosystem and human health. Limited funding for monitoring programs and inconsistent determination of cyanoHAB occurrence present challenges for identifying commonly effective variables for characterizing cyanoHABs and the development of generalized models. We compiled a combination of water quality measurements, lake morphology, climatology, remote sensing data, and observations of cyanoHAB occurrence across New York State and used this dataset to develop two sets of predictive models. The first model predicted chlorophyll a, a common indicator of algal biomass, and assessed the importance of variables for modeled predictions. The most important variables were then used in a second set of models to classify cyanoHAB occurrence. The irradiance attenuation coefficient (Kd), which was estimated from Secchi depth measurements, and total phosphorus were the two most important variables for predicting chlorophyll a. The second model examined several variables for their ability to classify cyanoHAB occurrence. Predicted cyanoHAB occurrence based on thresholds of chlorophyll a, Kd, or total nitrogen all had moderate agreement and were able to correctly classify approximately 70% of observed cyanoHABs. Our analysis indicated that multiple data types were important for predicting chlorophyll a statewide and that simple widely available water quality parameters could classify cyanoHABs occurrence with reasonable accuracy. Identifying variables that can be monitored with increased frequency and decreased latency to detect cyanoHAB occurrence will better inform water managers and provide valuable additional data for further refining predictive models of the likelihood of cyanoHABs occurrence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113403","usgsCitation":"Savoy, P., Gorney, R.M., and Graham, J.L., 2025, Estimating indicators of cyanobacterial harmful algal blooms in New York State: Ecological Indicators, v. 173, 113403, 11 p., https://doi.org/10.1016/j.ecolind.2025.113403.","productDescription":"113403, 11 p.","ipdsId":"IP-171481","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":488558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113403","text":"Publisher Index Page"},{"id":484244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca Michelle 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","email":"","middleInitial":"Michelle","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932742,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265471,"text":"70265471 - 2025 - Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images","interactions":[],"lastModifiedDate":"2025-04-07T15:08:27.841513","indexId":"70265471","displayToPublicDate":"2025-04-06T08:01:28","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":"Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images","docAbstract":"CubeSats provide a wealth of high-frequency observations at a meter-scale spatial resolution. However, most current methods of inferring water depth from satellite data consider only a single image. This approach is sensitive to the radiometric quality of the data acquired at that particular instant in time, which could be degraded by various confounding factors, such as sun glint or atmospheric effects. Moreover, using single images in isolation fails to exploit recent improvements in the frequency of satellite image acquisition. This study aims to leverage the dense image time series from the SuperDove constellation via an ensembling framework that helps to improve empirical (regression-based) bathymetry retrieval. Unlike previous studies that only ensembled the original spectral data, we introduce a neural network-based method that instead ensembles the water depths derived from multi-temporal imagery, provided the data are acquired under steady flow conditions. We refer to this new approach as NN-depth ensembling. First, every image is treated individually to derive multitemporal depth estimates. Then, we use another NN regressor to ensemble the temporal water depths. This step serves to automatically weight the contribution of the bathymetric estimates from each time instance to the final bathymetry product. Unlike methods that ensemble spectral data, NN-depth ensembling mitigates against propagation of uncertainties in spectral data (e.g., noise due to sun glint) to the final bathymetric product. The proposed NN-depth ensembling is applied to temporal SuperDove imagery of reaches from the American, Potomac, and Colorado rivers with depths of up to 10 m and evaluated against in situ measurements. The proposed method provided more accurate and robust bathymetry retrieval than single-image analyses and other ensembling approaches.","language":"English","publisher":"MDPI","doi":"10.3390/rs17071309","usgsCitation":"Niroumand-Jadidi, M., Legleiter, C.J., and Bovolo, F., 2025, Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images: Remote Sensing, v. 17, no. 7, 1309, 19 p., https://doi.org/10.3390/rs17071309.","productDescription":"1309, 19 p.","ipdsId":"IP-149931","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17071309","text":"Publisher Index Page"},{"id":484247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Niroumand-Jadidi, Milad 0000-0002-9432-3032","orcid":"https://orcid.org/0000-0002-9432-3032","contributorId":292943,"corporation":false,"usgs":false,"family":"Niroumand-Jadidi","given":"Milad","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":932783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":932784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bovolo, Francesca 0000-0003-3104-7656","orcid":"https://orcid.org/0000-0003-3104-7656","contributorId":292944,"corporation":false,"usgs":false,"family":"Bovolo","given":"Francesca","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":932785,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272682,"text":"70272682 - 2025 - Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","interactions":[],"lastModifiedDate":"2025-12-04T16:46:03.167798","indexId":"70272682","displayToPublicDate":"2025-04-05T10:43:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18010,"text":"JGR Machine Learning and Computation","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","docAbstract":"Borehole nuclear magnetic resonance (bNMR) data are typically used to infer in situ hydrologic properties. Partial water content as a function of pore size is estimated by fitting the measured NMR response to a multi-exponential T2 distribution, and the sum of estimated T2 amplitudes equals the total volumetric water content. From these estimated parameters, several empirical relationships are commonly used to infer hydraulic conductivity from the NMR-estimated water content and T2 distribution. Often, parameters are estimated through deterministic inversion methods that produce a single best-fit estimate, but do not reflect uncertainties in model parameters. Here, a Bayesian Markov chain Monte Carlo (McMC) approach for analyzing bNMR data is developed that allows for comprehensive uncertainty quantification of NMR parameters and derived hydrologic properties. The underlying model that describes the T2 distribution is defined by a set of spline interpolation points. The number of interpolation points is allowed to vary in a trans-dimensional algorithm that naturally favors simple models with fewer interpolation points, allowing the data to inform the necessary level of model complexity. Additionally, data error is estimated as an unknown parameter. Analysis of the ensemble of models output from the McMC algorithm provides useful details on the range of plausible T2 distributions that can fit a measured bNMR decay curve, as well as uncertainty estimates of total water content. The ensemble of NMR parameters can also be propagated through commonly used relationships to produce uncertainty estimates on derived parameters such as bound/capillary/mobile water content or hydraulic conductivity.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JH000461","usgsCitation":"Minsley, B.J., Phillips, S.N., and James, S.R., 2025, Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data: JGR Machine Learning and Computation, v. 2, no. 2, e2024JH000461, 15 p., https://doi.org/10.1029/2024JH000461.","productDescription":"e2024JH000461, 15 p.","ipdsId":"IP-171454","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jh000461","text":"Publisher Index Page"},{"id":497066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephanie N. 0000-0002-2022-7726","orcid":"https://orcid.org/0000-0002-2022-7726","contributorId":214857,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":951327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265767,"text":"70265767 - 2025 - The North American greenhouse gas budget: Emissions, removals, and integration for CO2, CH4, and N2O (2010–2019): Results From the Second REgional Carbon Cycle Assessment and Processes Study (RECCAP2)","interactions":[],"lastModifiedDate":"2025-04-15T14:57:11.227014","indexId":"70265767","displayToPublicDate":"2025-04-05T09:46:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The North American greenhouse gas budget: Emissions, removals, and integration for CO2, CH4, and N2O (2010–2019): Results From the Second REgional Carbon Cycle Assessment and Processes Study (RECCAP2)","title":"The North American greenhouse gas budget: Emissions, removals, and integration for CO2, CH4, and N2O (2010–2019): Results From the Second REgional Carbon Cycle Assessment and Processes Study (RECCAP2)","docAbstract":"Accurate accounting of greenhouse-gas (GHG) emissions and removals is central to tracking progress toward climate mitigation and for monitoring potential climate-change feedbacks. GHG budgeting and reporting can follow either the Intergovernmental Panel on Climate Change methodologies for National Greenhouse Gas Inventory (NGHGI) reporting or use atmospheric-based “top-down” (TD) inversions or process-based “bottom-up” (BU) approaches. To help understand and reconcile these approaches, the Second REgional Carbon Cycle Assessment and Processes study (RECCAP2) was established to quantify GHG emissions and removals for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), for ten-land and five-ocean regions for 2010–2019. Here, we present the results for the North American land region (Canada, the United States, Mexico, Central America and the Caribbean). For 2010–2019, the NGHGI reported total net-GHG emissions of 7,270 TgCO2-eq yr−1 compared to TD estimates of 6,132 ± 1,846 TgCO2-eq yr−1 and BU estimates of 9,060 ± 898 TgCO2-eq yr−1. Reconciling differences between the NGHGI, TD and BU approaches depended on (a) accounting for lateral fluxes of CO2 along the land-ocean-aquatic continuum (LOAC) and trade, (b) correcting land-use CO2 emissions for the loss-of-additional-sink capacity (LASC), (c) avoiding double counting of inland water CH4 emissions, and (d) adjusting area estimates to match the NGHGI definition of the managed-land proxy. Uncertainties remain from inland-water CO2 evasion, the conversion of nitrogen fertilizers to N2O, and from less-frequent NGHGI reporting from non-Annex-1 countries. The RECCAP2 framework plays a key role in reconciling independent GHG-reporting methodologies to support policy commitments while providing insights into biogeochemical processes and responses to climate change.
","language":"English","publisher":"Wiley","doi":"10.1029/2024GB008310","usgsCitation":"Poulter, B., Murray-Tortarolo, G., Hayes, D.J., Ciais, P., Andrew, R., Bastos, A., Byrne, B., Butman, D., Canadell, J., Chatterjee, A., Domke, G., Feldman, A.F., Foster, K., Hunka, N., Jackson, R., kurz, W.A., Lindquist, A., Liu, M., Luijkx, I., Mialon, A., Michalak, A., Miller, J., Obermeier, W., Pan, N., Randerson, J.T., Raymond, P.A., Regnier, P., Resplandy, L., Rocher-Ros, G., Rodriquez-Fernandez, N., Rosentreter, J.A., Salazar-Neira, J., Tank, S.E., Tan, H., Vargas, R., Villalobos, Y., Wang, J.A., Wei, X., Wickland, K., Williams , C., Windham-Myers, L., Woodall, C.W., Ying, Q., and Zhang, Z., 2025, The North American greenhouse gas budget: Emissions, removals, and integration for CO2, CH4, and N2O (2010–2019): Results From the Second REgional Carbon Cycle Assessment and Processes Study (RECCAP2): Global Biogeochemical Cycles, v. 39, no. 4, e2024GB008310, 31 p., https://doi.org/10.1029/2024GB008310.","productDescription":"e2024GB008310, 31 p.","ipdsId":"IP-169508","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gb008310","text":"Publisher Index Page"},{"id":484577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Poulter, Benjamin","contributorId":330088,"corporation":false,"usgs":false,"family":"Poulter","given":"Benjamin","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":933436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray-Tortarolo, Guillermo","contributorId":296446,"corporation":false,"usgs":false,"family":"Murray-Tortarolo","given":"Guillermo","email":"","affiliations":[{"id":64038,"text":"Instituto de Investigaciones en Ecosistemas y Sustentabilidad. 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This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides significant volumes of agricultural products not just for California but the entire United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface water and groundwater resources in the valley. This has resulted in water management challenges in the Salinas Valley that are predominantly related to distribution of water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. To deal with the distribution issue, historically water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface water supplies are insufficient. Availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand on groundwater and surface water resources throughout the Salinas Valley has resulted in undesirable effects of unsustainable water use, such as surface water depletion, groundwater level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface water and groundwater resources. To meet water demands and reduce undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and a variable climate. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resource Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley Hydrogeologic system called the Salinas Valley System Model. The Salinas Valley Geologic Framework was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The Salinas Valley Watershed Model simulates the entire Salinas River watershed. Monthly surface water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.
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The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS) streamflow data with satellite-based glacier volume change estimates to quantify how glacier mass loss subsidized streamflow over the 2000–2019 period for 116 glacierized basins. We examine interannual variability in that subsidy at three USGS-monitored glaciers to explore the ability of the subsidy to buffer streamflow derived solely from precipitation. We found the relative importance of percent glacier cover on streamflow magnitude increases in drier basins. In the driest basins, glaciers produced 40 times greater percent glacier mass loss subsidies to streamflow for the percent glacier cover compared to the wettest basins. While the subsidy from glacier mass loss buffers interannual variability in streamflow to varying degrees, it can also increase streamflow variability. Smaller amounts of percent glacier cover are needed to produce summer-melt-dominated seasonal flow regimes in drier basins than in wetter basins. Decreasing glacier cover will eventually decrease summer streamflow, increasing spring streamflow in drier basins, and attenuating seasonality with increasing spring and autumnal streamflow in wetter basins. Quantifying the downstream effects of continued glacier mass loss without the computational expense of a hydrological model is broadly applicable in this changing climate.
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Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":938483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rick, Brianna 0000-0002-0516-7577","orcid":"https://orcid.org/0000-0002-0516-7577","contributorId":350547,"corporation":false,"usgs":false,"family":"Rick","given":"Brianna","affiliations":[{"id":83769,"text":"USGS Alaska Climate Adaptation Center","active":true,"usgs":false}],"preferred":false,"id":938484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":938485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":938486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264653,"text":"70264653 - 2025 - Pediment formation and subsequent erosion in Gale crater: Clues to the climate history of Mars","interactions":[],"lastModifiedDate":"2025-03-18T15:05:40.972943","indexId":"70264653","displayToPublicDate":"2025-04-04T07:53:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Pediment formation and subsequent erosion in Gale crater: Clues to the climate history of Mars","docAbstract":"Evidence of paleo-rivers, fans, deltas, lakes, and channel networks across Mars has prompted much debate about what climate conditions would permit the formation of these surface water derived features. Pediments, gently sloping erosional surfaces of low relief developed in bedrock, have also been identified on Mars. On Earth, these erosional landforms, often thought to be created by overland flow and shallow channelized runoff, are typically capped by fluvial sediments, and thus in exceptionally arid regions, pediments are interpreted to record past wet periods. Here we document the Greenheugh pediment in Gale crater, exploiting the observational capability of the Curiosity rover. The absence of a fluvial cap suggests that the pediment was likely cut by wind erosion, not fluvial processes. The pediment was then buried by an aeolian deposit (Stimson sandstone) that mantled the lower footslopes of Aeolis Mons (informally known as Mt. Sharp). This burial terminated active wind erosion, preserving the pediment surface (as an angular unconformity). Groundwater was present prior-to, during, and shortly after Stimson deposition, perhaps contributing to lithification and certainly to early diagenesis. Post lithification, wind erosion first cut canyons in the northern most footslopes (north of Vera Rubin ridge). Unlithified gravels were deposited in these canyons, likely due to runoff from Mt. Sharp. Boulder-rich fluvial and debris flow deposits built a > 70 m thick sequence (Gediz Vallis ridge) on the southern Greenheugh pediment. Continued wind erosion left elevated patches of gravel on the northern footslopes, and exposure age dating shows that erosion essentially ceased before 1 Ga (but possibly much earlier). Erosion to the south led to emergence of Vera Rubin ridge, retreat of the Greenheugh pediment, and the formation of Glen Torridon valley. Hence, this footslope environment of Mt. Sharp records climate-driven periods of wind erosion, aeolian deposition (and groundwater activity), surface runoff and sediment deposition, followed by further significant wind erosion that declined to present very slow rates. This likely occurred during the late Hesperian and possibly into the Amazonian.
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However, the ability to accurately quantify fR at scale has been limited. In this study we produced annual maps of fR for farmland in Maryland, USA using WorldView-3 (WV3) imagery paired with on-farm photographs (n = 895) classified to fR using SamplePoint software. Univariate linear regressions were used to compare photograph fR to WV3 crop residue indices including: 1) Shortwave Infrared Normalized Difference Residue Index (SINDRI), 2) Shortwave Infrared Difference Residue Index (SIDRI), 3) Normalized Difference Tillage Index (NDTI), and 4) Shortwave Infrared Angle Index (SWIRA). SINDRI and SIDRI are based on narrow bands capable of measuring lignocellulose absorption features. NDTI and SWIRA are based on Landsat-comparable broad bands. Our findings demonstrated that SINDRI outperformed other indices in fR estimation in terms of coefficient of determination (R2 = 0.869) and root mean square error (RMSE = 0.111), when R2 and RMSE were averaged across six individual years. For a univariate analysis combining five years of high-quality WV3 imagery, SINDRI again exhibited the highest fR estimation performance (R2 = 0.795; RMSE = 0.141), suggesting that SINDRI can map fR accurately with a singular relationship, potentially reducing the need for labor-intensive ground data collection. For broad-band indices, a multiple linear regression analysis that included a Water Index (WI) and Normalized Difference Vegetation Index (NDVI) as additional predictors increased the accuracy of fR estimation significantly, particularly for SWIRA (R2 = 0.767; RMSE = 0.144), but also NDTI (R2 = 0.654; RMSE = 0.174). Our findings suggest that while indices computed from narrow-band imagery are most accurate for fR estimation, SWIRA has the potential to improve fR estimation compared to NDTI, especially when used in conjunction with WI and NDVI. An index suite of SWIRA, WI, and NDVI can be computed with Landsat 4–9 imagery, providing a more accurate record of global fR dating back to 1982.
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In acute (96-hr) toxicity tests with aquatic larvae of the mayfly Neocloeon triangulifer, 6PPDQ did not cause mortalities at the highest test concentration, which was just below the limit of solubility. In toxicity tests with 4-HDPA, a calculated 96-hr median lethal concentration of 339 µg/L is above environmentally relevant concentrations. However, in toxicity tests with 6PPD, there was evidence that the degradation of this tire wear compound produced unknown TPs that caused mortalities in exposed mayfly larvae. Additional work could identify other TPs of 6PPD that could be a hazard to aquatic invertebrates exposed to tire wear compounds transported into surface waters from transportation corridors.
","language":"English","publisher":"Society for Environmental Toxicology and Chemistry","doi":"10.1093/etojnl/vgaf062","usgsCitation":"Soucek, D.J., Dorman, R.A., Steevens, J.A., Yargeau, V., Pineda, M., Bennett, E., and Metcalfe, C., 2025, Acute Toxicity of 4-hydroxydiphenylamine (4-HDPA) and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPDQ), transformation products of 6PPD, to early instars of the mayfly, Neocloeon triangulifer: Environmental Toxicology & Chemistry, v. 44, no. 5, p. 1369-1377, https://doi.org/10.1093/etojnl/vgaf062.","productDescription":"9 p.","startPage":"1369","endPage":"1377","ipdsId":"IP-172245","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":486240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Ontario","city":"Toronto","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.42368046700955,\n 44.11997206927657\n ],\n [\n -80.42368046700955,\n 43.47787968657278\n ],\n [\n -78.48291547339888,\n 43.47787968657278\n ],\n [\n -78.48291547339888,\n 44.11997206927657\n ],\n [\n -80.42368046700955,\n 44.11997206927657\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Soucek, David J. 0000-0002-7741-0193 drieckssoucek@usgs.gov","orcid":"https://orcid.org/0000-0002-7741-0193","contributorId":295408,"corporation":false,"usgs":true,"family":"Soucek","given":"David","email":"drieckssoucek@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorman, Rebecca A. 0000-0002-5748-7046","orcid":"https://orcid.org/0000-0002-5748-7046","contributorId":28522,"corporation":false,"usgs":true,"family":"Dorman","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yargeau, Viviane","contributorId":352224,"corporation":false,"usgs":false,"family":"Yargeau","given":"Viviane","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":937811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pineda, Marco","contributorId":352225,"corporation":false,"usgs":false,"family":"Pineda","given":"Marco","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":937812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennett, Erin","contributorId":352226,"corporation":false,"usgs":false,"family":"Bennett","given":"Erin","affiliations":[{"id":36679,"text":"Trent University","active":true,"usgs":false}],"preferred":false,"id":937813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Metcalfe, Chris","contributorId":152693,"corporation":false,"usgs":false,"family":"Metcalfe","given":"Chris","email":"","affiliations":[],"preferred":false,"id":937814,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267349,"text":"70267349 - 2025 - Nature-based solutions could offset coastal squeeze of tidal wetlands from sea-level rise on the U.S. Pacific coast","interactions":[],"lastModifiedDate":"2025-05-20T15:33:25.995043","indexId":"70267349","displayToPublicDate":"2025-04-03T10:24:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Nature-based solutions could offset coastal squeeze of tidal wetlands from sea-level rise on the U.S. Pacific coast","docAbstract":"In this study, we explored the opportunities for tidal wetland landward migration in response to sea-level rise on the Pacific Coast of the United States. By employing a systematic spatial approach, we quantified the available space for wetland migration with sea-level rise across 61 estuarine drainage areas. Although many of the existing tidal wetlands are small patches, our analyses show that 63% of the estuaries lacked the landward migration space needed to replace current tidal wetland extent, thereby threatening a wide range of protected species and ecosystem services. Developed lands and steep topography represent common barriers to migration along the Pacific coast, especially in central and southern California. The available wetland migration space consists primarily of agriculture, pasture, and freshwater wetlands, with most of the area available for migration occurring in just a few watersheds. In most watersheds tidal wetland migration would only occur with human intervention or facilitation. The greatest amount of area available for wetland migration was in the San Francisco Bay-Delta and Columbia River estuaries, together accounting for 58% of all available migration space on the Pacific Coast. Nature-based solutions to reduce tidal wetland loss from sea-level rise can include restoration in suitable areas, removal of barriers to tidal wetland migration, and elevation building approaches. Tidal wetland restoration opportunities could increase area by 59%, underscoring it as a plausible approach to prevent tidal wetland loss in those estuaries and a viable Nature-based solution. 54% of estuaries building elevations of existing tidal wetlands may be the most feasible approach needed. Our analyses illustrate the importance of management efforts that use Nature-based approaches to prevent tidal wetland ecosystem and species loss over the coming decades from sea-level rise.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-93437-z","usgsCitation":"Thorne, K., Buffington, K., Osland, M., Chivoiu, B., Grace, J., Enwright, N., and Guntenspergen, G.R., 2025, Nature-based solutions could offset coastal squeeze of tidal wetlands from sea-level rise on the U.S. Pacific coast: Scientific Reports, v. 15, 11443, 12 p., https://doi.org/10.1038/s41598-025-93437-z.","productDescription":"11443, 12 p.","ipdsId":"IP-164443","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-93437-z","text":"Publisher Index Page"},{"id":486221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Pacific Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.16831375659916,\n 32.529659744934875\n ],\n [\n -115.72548020849868,\n 32.68811119997032\n ],\n [\n -116.72029735902163,\n 34.78387252818949\n ],\n [\n -120.34090280190134,\n 36.54193564982417\n ],\n [\n -120.9472907013008,\n 38.759310670914516\n ],\n [\n -123.54701176882111,\n 41.966192999636405\n ],\n [\n -123.20188620835336,\n 43.16328889810765\n ],\n [\n -120.38724503464049,\n 46.08031374669787\n ],\n [\n -120.91587844138245,\n 48.93382512190934\n ],\n [\n -123.29079358659652,\n 49.1104823673754\n ],\n [\n -122.8174496679051,\n 48.242818948542606\n ],\n [\n -124.98213074652709,\n 48.33598274699136\n ],\n [\n -125.98264717009208,\n 41.29683005590644\n ],\n [\n -123.75248879506864,\n 36.62077412853161\n ],\n [\n -120.9684573791725,\n 34.06055979823492\n ],\n [\n -118.6027512944191,\n 32.23098898839369\n ],\n [\n -117.16831375659916,\n 32.529659744934875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":219805,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":937830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chivoiu, Bogdan 0000-0002-4568-3496","orcid":"https://orcid.org/0000-0002-4568-3496","contributorId":222660,"corporation":false,"usgs":true,"family":"Chivoiu","given":"Bogdan","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":937953,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":206247,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":937831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":201678,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":937832,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":937833,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70265463,"text":"70265463 - 2025 - Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico","interactions":[],"lastModifiedDate":"2025-04-07T15:00:09.063332","indexId":"70265463","displayToPublicDate":"2025-04-03T09:53:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico","docAbstract":"Coastal resilience has become a pressing global issue due to the growing vulnerability of coastlines to the effects of climate change. Nature-based solutions have emerged as a promising approach to coastal protection to not only enhance coastal resilience, but also restore critical ecosystems. Coral reef restoration has the potential to provide ecosystem services benefits; however, there are still key uncertainties in linking restoration design to reductions in coastal flood hazard under current and future climate conditions. In this study, we applied one-dimensional and two-dimensional numerical coastal engineering models, calibrated and validated using field data, to evaluate the effectiveness of coral restoration scenarios on coastal waves, water levels, and flooding along the coast of San Juan, Puerto Rico, U.S.A. Model results indicate a small reduction in maximum water levels under the proposed restoration scenarios. This underscores the importance of these endeavors, not only for ecological preservation but also for preventing further reef deterioration. Such preservation is essential for mitigating the increased coastal risks anticipated in the future. Results from this study provide information to guide policymakers and coastal managers in making informed decisions on viable restoration project design options. By systematically evaluating how restoration location impacts coastal flood hazards, communities can develop and implement proactive strategies to mitigate flood-related risk. In addition, by restoring coral reefs, communities can contribute to environmental preservation while ensuring sustainable development and protection of coastal environments.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2025.1528460","usgsCitation":"Familkhalili, R., Storlazzi, C.D., Nemeth, M., and Viehman, S., 2025, Assessing the effect of coral reef restoration location on coastal flood hazard along the San Juan Coastline, Puerto Rico: Frontiers in Marine Science, v. 12, 1528460, 11 p., https://doi.org/10.3389/fmars.2025.1528460.","productDescription":"1528460, 11 p.","ipdsId":"IP-169548","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488566,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2025.1528460","text":"Publisher Index Page"},{"id":484246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, San Juan coastline","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.08782395132914,\n 18.480815260981046\n ],\n [\n -66.09096383189711,\n 18.45217867401871\n ],\n [\n -65.96850848974445,\n 18.42720367145678\n ],\n [\n -65.96005496513799,\n 18.468673931779904\n ],\n [\n -66.08782395132914,\n 18.480815260981046\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2025-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Familkhalili, Ramin","contributorId":353052,"corporation":false,"usgs":false,"family":"Familkhalili","given":"Ramin","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":932772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nemeth, Michael","contributorId":353056,"corporation":false,"usgs":false,"family":"Nemeth","given":"Michael","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viehman, Shay","contributorId":353053,"corporation":false,"usgs":false,"family":"Viehman","given":"Shay","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":932771,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269263,"text":"70269263 - 2025 - Are we heading towards a global decrease in coregonine catches?","interactions":[],"lastModifiedDate":"2025-07-17T13:58:47.8889","indexId":"70269263","displayToPublicDate":"2025-04-03T08:54:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17451,"text":"International Journal of Limnology","active":true,"publicationSubtype":{"id":10}},"title":"Are we heading towards a global decrease in coregonine catches?","docAbstract":"Coregonines have specific ecological needs, making them potentially very vulnerable to changes in lake conditions. A contemporary concern is that many lakes worldwide are experiencing environmental changes due to anthropogenic pressure and climate warming. Here, we compiled long-term data of coregonine catches from 27 lakes from three continents in the northern hemisphere. Declines in catch were observed in 67% of the lakes during the first two decades of the 21st century, with a significant trend (p-value<0.05) in 44% of the cases. An analysis to determine whether trends are globally linked to environmental conditions and specific lake attributes was carried out on 26 lakes for the period 2000–2019. Several local declines in catches had already been documented in the literature and are likely to be due to local forcing such as nutrients, species invasions and changes in fishing practices. Nevertheless, on a global scale, our results indicate that lakes, which exhibited a significant decrease in catch were larger and more nutrient-poor than other lakes. The rate of change in catches appeared to be related to the trophic state of the lake. The specific effect of warming is difficult to determine during the studied period. When warming occurred outside the period of egg incubation, decreasing trends were more frequently observed in nutrient-poor than in mesotrophic lakes. In conclusion, our findings suggest that achieving oligo- or ultraoligotrophic conditions, as required in developed countries to control phytoplankton blooms and enhance water quality, could pose significant challenges for future management of coregonine fisheries.
","language":"English","publisher":"EDP Sciences","doi":"10.1051/limn/2025003","usgsCitation":"Anneville, O., Alric, B., Chang, C., Baer, J., Bourinet, F., Brinker, A., Bunnell, D.B., Goulon, C., Holmgren, K., Hsieh, C., Janjua, Y., Kao, Y., Kangur, K., Sandstrom, A., Silow, E.A., and Zhu, X., 2025, Are we heading towards a global decrease in coregonine catches?: International Journal of Limnology, v. 61, 6, 19 p., https://doi.org/10.1051/limn/2025003.","productDescription":"6, 19 p.","ipdsId":"IP-165207","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":498674,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-05020364","text":"External 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exposure to onshore oil and gas wastewater: What we need to know to protect human health","docAbstract":"Produced water is a chemically complex waste stream generated during oil and gas development. Roughly four trillion liters were generated onshore in the United States in 2021 (ALL Consulting, 2022, https://www.gwpc.org/wp-content/uploads/2021/09/2021_Produced_Water_Volumes.pdf). Efforts are underway to expand historic uses of produced water to offset freshwater needs in water-stressed regions, avoid induced seismic activity associated with its disposal, and extract commodities. Understanding the potential exposures from current and proposed produced water uses and management practices can help to inform health-protective practices. This review summarizes what is known about potential human exposure to produced water from onshore oil and gas development in the United States. We synthesize 236 publications to create a conceptual model of potential human exposure that illustrates the current state of scientific inquiry and knowledge. Exposure to produced water can occur following its release to the environment through spills or leaks during its handling and management. Exposure can also arise from authorized releases, including permitted discharges to surface water, crop irrigation, and road treatment. Knowledge gaps include understanding the variable composition and toxicity of produced water released to the environment, the performance of treatment methods, migration pathways through the environment that can result in human exposure, and the significance of the exposures for human and ecosystem health. Reducing these uncertainties may help in realizing the benefits of produced water use while simultaneously protecting human health.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GH001263","usgsCitation":"Ariana, A., Cozzarelli, I.M., Danforth, C., McDevitt, B., Rosofsky, A., and Vorhees, D., 2025, Pathways for potential exposure to onshore oil and gas wastewater: What we need to know to protect human health: Environmental Health Perspectives, v. 9, no. 4, e2024GH001263, 21 p., https://doi.org/10.1029/2024GH001263.","productDescription":"e2024GH001263, 21 p.","ipdsId":"IP-166041","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":490099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gh001263","text":"Publisher Index Page"},{"id":484765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vorhees, Donna","contributorId":353546,"corporation":false,"usgs":false,"family":"Vorhees","given":"Donna","affiliations":[{"id":84430,"text":"Health Effects Institute Energy, Boston, MA, USA","active":true,"usgs":false}],"preferred":false,"id":933810,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265224,"text":"70265224 - 2025 - Spatiotemporal patterns in urban nutrient and suspended sediment loads and stream response to watershed management implementation","interactions":[],"lastModifiedDate":"2025-04-04T13:09:53.455294","indexId":"70265224","displayToPublicDate":"2025-04-01T09:53:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal patterns in urban nutrient and suspended sediment loads and stream response to watershed management implementation","docAbstract":"In recent years, local governments have invested heavily in management practices to reduce nutrient and sediment loads. These practices provide localities with nutrient and sediment regulatory reduction credits; however, their effects on water quality are poorly understood at the watershed scale. Long-term watershed-scale monitoring is essential for assessing progress toward water-quality goals, yet it has historically been lacking in urban watersheds. Since 2007, Fairfax County, Virginia, has partnered with the US Geological Survey to monitor and evaluate water-quality conditions in 20 small urban streams. This study assessed nutrient and suspended sediment loads, trends in concentration, and trends in load. Trends in load are affected by streamflow-induced variability that must be removed through a process called “flow-normalization;” however, existing methods have neither been applied to small urban watersheds nor to loads computed on a sub-daily timestep. In this study, four such methods also were assessed, and an adaptation of the weighted regressions on time, discharge, and season approach was found to be most effective. Loads, concentrations, and trends in load were spatially and temporally variable. Differences were attributed to physical watershed features such as geology, soils, and channel geomorphology, as well as urban sources such as turfgrass fertilization and septic infrastructure. Most notably, flow-normalized suspended sediment, nitrogen, and phosphorus loads decreased in two watersheds with completed stream restorations and increased in those with few implemented practices.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-13917-7","usgsCitation":"Porter, A.J., 2025, Spatiotemporal patterns in urban nutrient and suspended sediment loads and stream response to watershed management implementation: Environmental Monitoring and Assessment, v. 197, 497, 26 p., https://doi.org/10.1007/s10661-025-13917-7.","productDescription":"497, 26 p.","ipdsId":"IP-171869","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":490092,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-13917-7","text":"Publisher Index Page"},{"id":484134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","county":"Fairfax 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Aaron J. 0000-0002-0781-3309","orcid":"https://orcid.org/0000-0002-0781-3309","contributorId":239980,"corporation":false,"usgs":true,"family":"Porter","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932527,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70268100,"text":"70268100 - 2025 - Lake Ontario August gillnet survey and Lake Trout assessment, 2024","interactions":[],"lastModifiedDate":"2025-06-13T14:41:20.146762","indexId":"70268100","displayToPublicDate":"2025-04-01T09:28:54","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lake Ontario August gillnet survey and Lake Trout assessment, 2024","docAbstract":"Lake Ontario Lake Trout (Salvelinus namaycush) rehabilitation has been assessed with fishery independent surveys to evaluate program benchmarks and compare observations with management objectives since 1983. These surveys provide information on the abundance, strain composition, and performance of stocked Lake Trout, as well as information on levels of natural recruitment, and Sea Lamprey (Petromyzon marinus) wounding rates. In 2024, the gillnet survey occurred in United States (US) and Canadian waters marking the first lake-wide Lake Trout assessment since 2008. Lake Trout catch per unit effort (CPUE) was higher in US than Canadian waters. Recaptures of stocked fish with coded wire tags occurred mostly in US waters, and were composed of the following strains: Lake Champlain, Seneca Lake, Superior Klondike Reef, and Huron Parry Sound. Percentage of naturally produced Lake Trout in US waters continued to be relatively low for mature and immature fish. Interestingly, the percentage of naturally produced Lake Trout was higher in Canadian waters, despite lower total numbers of Lake Trout caught. Sea Lamprey wounding rates on Lake Trout > 432 mm in 2024 were above management targets in US and Canadian waters. Overall, the 2024 survey results suggest that Lake Trout indicators continue to meet some of the management objectives and show spatial differences in overall abundance and the proportion of stocked vs wild fish between the US and Canadian stocks.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"O’Malley, B., Minihkeim, S.P., Mitchinson, O.M., Stahl, S.D., Weidel, B., Connerton, M., Goretzke, J., Sunderland, L., Bloomfield, E., Farrell, C., and Gorsky, D., 2025, Lake Ontario August gillnet survey and Lake Trout assessment, 2024, 15 p.","productDescription":"15 p.","ipdsId":"IP-175455","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":490704,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://glfc.org/publication-media-search.php","linkFileType":{"id":5,"text":"html"}},{"id":490707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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0009-0002-0248-4523","orcid":"https://orcid.org/0009-0002-0248-4523","contributorId":339870,"corporation":false,"usgs":true,"family":"Stahl","given":"Scott","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":940206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":940207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connerton, Michael 0000-0001-5400-4347","orcid":"https://orcid.org/0000-0001-5400-4347","contributorId":302344,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":940208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goretzke, Jessica","contributorId":268339,"corporation":false,"usgs":false,"family":"Goretzke","given":"Jessica","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":940209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sunderland, Lucus","contributorId":356826,"corporation":false,"usgs":false,"family":"Sunderland","given":"Lucus","affiliations":[{"id":85250,"text":"OMNR","active":true,"usgs":false}],"preferred":false,"id":940210,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bloomfield, Emma","contributorId":353232,"corporation":false,"usgs":false,"family":"Bloomfield","given":"Emma","affiliations":[{"id":12864,"text":"OMNRF","active":true,"usgs":false}],"preferred":false,"id":940211,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Farrell, Collin","contributorId":339871,"corporation":false,"usgs":false,"family":"Farrell","given":"Collin","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":940212,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gorsky, Dimitry","contributorId":251650,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":940213,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70265056,"text":"70265056 - 2025 - Uncertainty reduction for subaerial landslide-tsunami hazards","interactions":[],"lastModifiedDate":"2025-04-01T15:08:00.852625","indexId":"70265056","displayToPublicDate":"2025-04-01T08:03:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty reduction for subaerial landslide-tsunami hazards","docAbstract":"Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JF007906","usgsCitation":"Barnhart, K.R., George, D.L., Collins, A.L., Schaefer, L.N., and Staley, D.M., 2025, Uncertainty reduction for subaerial landslide-tsunami hazards: Journal of Geophysical Research: Earth Surface, v. 130, no. 4, e2024JF007906, 33 p., https://doi.org/10.1029/2024JF007906.","productDescription":"e2024JF007906, 33 p.","ipdsId":"IP-167063","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":488660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jf007906","text":"Publisher Index Page"},{"id":484066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.7784819894945,\n 61.26414641973446\n ],\n [\n -148.7784819894945,\n 59.85768506370988\n ],\n [\n -145.67415454216552,\n 59.85768506370988\n ],\n [\n -145.67415454216552,\n 61.26414641973446\n ],\n [\n -148.7784819894945,\n 61.26414641973446\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":932433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Andrew L. 0000-0003-4751-7333","orcid":"https://orcid.org/0000-0003-4751-7333","contributorId":332093,"corporation":false,"usgs":true,"family":"Collins","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268133,"text":"70268133 - 2025 - Per- and polyfluoroalkyl substances (PFAS) mass flux and mass balance at an aqueous film-forming foam release site in semiarid eastern New Mexico, USA","interactions":[],"lastModifiedDate":"2025-06-13T15:50:56.988751","indexId":"70268133","displayToPublicDate":"2025-03-31T10:41:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Per- and polyfluoroalkyl substances (PFAS) mass flux and mass balance at an aqueous film-forming foam release site in semiarid eastern New Mexico, USA","docAbstract":"Passive flux meters (PFMs) directly measure groundwater chemistry mass flux and Darcy flux, providing insight into contaminant source-zone architecture and transport properties. This study uses PFMs to characterize PFAS flux in groundwater at a semiarid site with a thick (greater than 90-m) unsaturated zone where groundwater has been contaminated with per- and polyfluoroalkyl substances (PFAS) related to the use of aqueous film-forming foam (AFFF) for fire training and fire suppression. PFAS mass discharge (PFAS mass flux integrated over a control plane) in groundwater downgradient from several PFAS release areas is calculated using PFM results. In groundwater downgradient from fire-training areas, total PFAS mass discharge (summed across 14 compounds) was estimated to be between 6.0 and 31 g per day in 2020 and between 5.9 and 23 g per day in 2021. Site-specific documentation, generic information on AFFF properties, and literature values of PFAS concentration in AFFF are used to estimate site-specific PFAS-application rates at fire-training areas. These PFAS-application rates are compared to groundwater PFAS-discharge rates. Results suggest that transformation processes (exact pathways unknown) have led to increased discharge of measured PFAS in groundwater relative to initial AFFF formulations. The mass balance approach has broad applicability as a high-level approach that can provide insight into PFAS transport at AFFF sites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104550","usgsCitation":"Gray, E., Potteiger, S., Brannon, T., Norton, S., Cho, J., and Annable, M., 2025, Per- and polyfluoroalkyl substances (PFAS) mass flux and mass balance at an aqueous film-forming foam release site in semiarid eastern New Mexico, USA: Journal of Contaminant Hydrology, v. 272, 104550, 11 p., https://doi.org/10.1016/j.jconhyd.2025.104550.","productDescription":"104550, 11 p.","ipdsId":"IP-160587","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":491002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2025.104550","text":"Publisher Index Page"},{"id":490714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Cannon Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.33908374205211,\n 34.41604524683224\n ],\n [\n -103.33908374205211,\n 34.359881732275326\n ],\n [\n -103.29149858549228,\n 34.359881732275326\n ],\n [\n -103.29149858549228,\n 34.41604524683224\n ],\n [\n -103.33908374205211,\n 34.41604524683224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"272","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, Erin Louise 0000-0002-3945-6393","orcid":"https://orcid.org/0000-0002-3945-6393","contributorId":295317,"corporation":false,"usgs":true,"family":"Gray","given":"Erin Louise","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Potteiger, Samuel Edwin 0009-0006-3293-7246","orcid":"https://orcid.org/0009-0006-3293-7246","contributorId":339925,"corporation":false,"usgs":true,"family":"Potteiger","given":"Samuel Edwin","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brannon, Trevor Dylan 0009-0005-6030-8140","orcid":"https://orcid.org/0009-0005-6030-8140","contributorId":344656,"corporation":false,"usgs":true,"family":"Brannon","given":"Trevor Dylan","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norton, Stuart Bryan 0000-0002-4870-7481","orcid":"https://orcid.org/0000-0002-4870-7481","contributorId":295316,"corporation":false,"usgs":true,"family":"Norton","given":"Stuart Bryan","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cho, Jay","contributorId":239518,"corporation":false,"usgs":false,"family":"Cho","given":"Jay","email":"","affiliations":[{"id":47898,"text":"BSEE","active":true,"usgs":false}],"preferred":false,"id":940316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Annable, Michael D. 0000-0002-8736-9411","orcid":"https://orcid.org/0000-0002-8736-9411","contributorId":356873,"corporation":false,"usgs":false,"family":"Annable","given":"Michael D.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":940317,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265450,"text":"70265450 - 2025 - Patterns of water-extractable soil organic matter in the US Great Plains: Insights from the Haas Soil Archive","interactions":[],"lastModifiedDate":"2025-04-07T15:11:28.29755","indexId":"70265450","displayToPublicDate":"2025-03-31T10:01:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18722,"text":"Agrosystems, Geosciences & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of water-extractable soil organic matter in the US Great Plains: Insights from the Haas Soil Archive","docAbstract":"Novel approaches that are fast and sensitive are needed to evaluate soil change and integrate soil ecosystem properties. Carbon (C) and nitrogen (N) extracted from soil with water are associated with plant nutrients and microbial activity but information about change over time in the US Great Plains is sparse. We used cool (20°C) and hot (80°C) water extracts from historic (1947) and contemporary (2018) soil samples collected at Moccasin, MT; Akron, CO; and Big Spring, TX; to examine changes to labile C and N and optical properties after 71 years of dryland cropping. Concentrations of C and N extracted with cool water decreased between 1947 and 2018 in surface (0–15.2 cm) samples from Moccasin, by 52% and 35%, and Big Spring, by 37% and 32%, but remained unchanged at Akron. Conversely, net (hot−cool) extractable C did not change at Moccasin or Big Spring but increased at Akron by 26%. Net extractable N decreased at Moccasin by 22% but did not change elsewhere. Sequential principal component analysis and stepwise discriminant analysis identified three important optical properties. Values of SUVA254 (where SUVA254 is the specific ultraviolet absorbance at 254 nm) in extracts did not change at Moccasin between 1947 and 2018 but increased at Akron, indicating increased aromaticity. Conversely, SUVA254 decreased at Big Spring. Values for Sag350–400 (where Sag350–400 is the slope from a nonlinear fit of an exponential function to the absorption spectrum over the wavelength range from 350 to 400 nm), inversely related to extract molecular weight and aromaticity, decreased at Moccasin but not elsewhere. The proportion of recalcitrant to labile compounds, C:T (where C:T is the ratio of fluorescence intensity from Peak C [ex340/em440] to Peak T [ex275/em340]), increased in extracts from all sites but especially at Akron. Together, these methods provided insights into soil change while conserving samples.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America","doi":"10.1002/agg2.70060","usgsCitation":"Halvorson, J., Hansen, A., Stewart, C., and Liebig, M., 2025, Patterns of water-extractable soil organic matter in the US Great Plains: Insights from the Haas Soil Archive: Agrosystems, Geosciences & Environment, v. 8, no. 2, e70060, 19 p., https://doi.org/10.1002/agg2.70060.","productDescription":"e70060, 19 p.","ipdsId":"IP-169442","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488588,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/agg2.70060","text":"Publisher Index Page"},{"id":484248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Wyoming","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.71690230492678,\n 49.00767217377904\n ],\n [\n -114.52047194344055,\n 48.96620820388196\n ],\n [\n -108.02761104444338,\n 43.431362102036616\n ],\n [\n -105.46908622364728,\n 41.157349572572656\n ],\n [\n -104.7642331125596,\n 38.60534381629034\n ],\n [\n -105.05752733002399,\n 31.53015238806853\n ],\n [\n -101.92451560611104,\n 29.673791965164952\n ],\n [\n -99.21248896868579,\n 29.64451686827489\n ],\n [\n -95.39792325146101,\n 36.09005746704193\n ],\n [\n -95.97673584844566,\n 39.785455700995584\n ],\n [\n -97.38163970337908,\n 43.351886514816215\n ],\n [\n -99.71690230492678,\n 49.00767217377904\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Halvorson, Jonathan J. 0000-0001-5201-3928","orcid":"https://orcid.org/0000-0001-5201-3928","contributorId":349396,"corporation":false,"usgs":false,"family":"Halvorson","given":"Jonathan J.","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":932743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Angela 0000-0003-0938-7611 anhansen@usgs.gov","orcid":"https://orcid.org/0000-0003-0938-7611","contributorId":171551,"corporation":false,"usgs":true,"family":"Hansen","given":"Angela","email":"anhansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Catherine E. 0000-0003-1216-0450","orcid":"https://orcid.org/0000-0003-1216-0450","contributorId":349399,"corporation":false,"usgs":false,"family":"Stewart","given":"Catherine E.","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":932745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liebig, Mark A. 0000-0002-2716-3665","orcid":"https://orcid.org/0000-0002-2716-3665","contributorId":349397,"corporation":false,"usgs":false,"family":"Liebig","given":"Mark A.","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":932746,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270325,"text":"70270325 - 2025 - The effects of breeding status on common raven movement, home range, and habitat selection","interactions":[],"lastModifiedDate":"2025-08-14T14:21:36.529864","indexId":"70270325","displayToPublicDate":"2025-03-31T09:18:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"The effects of breeding status on common raven movement, home range, and habitat selection","docAbstract":"Anthropogenic infrastructure has contributed to increasing common raven (Corvus corax) abundance across the Great Basin region of the United States, particularly in sagebrush ecosystems, where high raven densities are correlated with reduced sage-grouse (Centrocercus urophasianus) nest survival. Our understanding of how raven reproductive behavior affects sage-grouse nest predation is limited, especially considering their overlapping breeding seasons. Understanding differences in space use and resource selection between breeding and non-breeding ravens could help identify high-use areas and corresponding predation risk for sage-grouse nests. We analyzed space use and resource selection of breeding (n = 13) and non-breeding (n = 32) global positioning system (GPS)-marked ravens in Nevada, USA (2017–2022) during the breeding season (1 March–31 June). We compared home-range size, core area size, step lengths, and resource selection within a Bayesian framework with inference made by comparing Bayesian credible intervals (CRI). We generated home range and core area estimates using autocorrelated kernel density methods. We did not find a difference in home range size between breeding (469.33 km2, 95% CRI = 228.79–709.45 km2) and non-breeding (525.26 km2, 95% CRI = 410.71–654.10 km2) ravens. However, breeding ravens had smaller core areas (10.77 km2, 95% CRI = 3.16–35.78 km2) and shorter step lengths (1,160.33 m/hr, 95% CRI = 1,087.78–1,277.17 m/hr) than non-breeding ravens (core area = 279.50 km2, 95% CRI = 206.77–363.72 km2; step length = 1,953.74 m/hr, 95% CRI = 1,898.42–2,009.56 m/hr). Ravens in both breeding classes selected high normalized difference vegetation index (NDVI) and low annual grass and shrub cover, but non-breeding ravens showed stronger selection for low annual grass and shrub cover areas. We found strong differences in selection between breeding classes for 6 of our 9 covariates: distance to road, solar radiation, distance to natural water, distance to forest edge, percent annual grass cover, and percent shrub cover. Non-breeding ravens concentrated activity near forest edges, natural water sources, and anthropogenic features, whereas breeding ravens focused activity close to their nests. Our findings suggest that raven management could be more effective if it targeted areas with high NDVI and low annual grass and shrub cover, especially in anthropogenically modified landscapes and near forest edges, and prevented raven nest establishment near prey populations of concern.
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In 2024, the Lake Superior fish community was sampled with daytime bottom and surface trawls at 72 nearshore locations in June and 36 offshore locations in July. Nearshore bottom trawls collected 22,190 fish represented by 27 species or morphotypes. The number of species collected at each location ranged from 1 to 12, with a median of 5.5 species. Estimated fish biomass at individual locations ranged from <0.1 to 62.9 kg per ha with a lakewide mean of 3.7 kg per ha. Offshore bottom trawls collected 33,634 fish represented by 12 species or morphotypes. Estimated fish biomass at individual locations ranged from 0.6 to 25.8 kg per ha with a lakewide mean of 8.3 kg per ha, which was the second highest for the period-of-record. Lakewide average densities (fish per ha) of age-1 fish were 1 per ha for Bloater, 5 per ha for Cisco, 1 per ha for Lake Whitefish, 60 per ha for Rainbow Smelt, and 19 per ha for Kiyi. Surface trawling collected 5,177 larval Coregonus individuals which was the third fewest Coregonus larvae collected in a whole lake survey since the larval fish survey began in 2014. Nearshore mean larval Coregonus densities were 176 fish per ha in June 2024 and offshore densities were 7 fish per ha in July 2024. June and July surface water temperatures were near the warmest for the period-of-record.
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Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Do watershed conditions or local climate play a larger role in determining regional stream salamander distributions?","docAbstract":"Anthropogenic influences like land use and climate variability interact with natural heterogeneity to influence the persistence of stream salamanders. Using occupancy modeling in the southern Appalachian Mountains, we investigated the influence of land use, climate, and physical context (e.g., drainage area, elevation) on stream salamander occupancy, noting species, and life stage specific responses. Our results illustrate that forest loss is a better predictor of salamander occupancy than physical context (elevation) or climate. Across the gradients in this dataset, precipitation did not have a significant influence on salamander occupancy, potentially due to the observed narrow, wet gradient. Temperature had little effect on Eurycea wilderae occupancy; however, temperature negatively affected adult but not larval Desmognathus amphileucus occupancy. Spatial thermal variability in this study was larger than projected increases due to climate change, suggesting that local mechanisms (e.g., behavior or physiological plasticity) may facilitate salamander resilience to climate change. However, the negative effects of forest loss coupled with rising temperatures (e.g., increased solar radiation, warmer stream runoff) underscore the importance of riparian forests in mitigating climate stressors. Preserving forest cover is critical for maintaining stream salamander populations and may offer opportunities for maintaining resilience in the face of additional stressors like rising temperatures or drought.
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