Low-lying, tropical, coral-reef-lined coastlines are becoming increasingly vulnerable to wave-driven flooding due to population growth, coral reef degradation, and sea-level rise. Early-warning systems (EWSs) are needed to enable coastal authorities to issue timely alerts and coordinate preparedness and evacuation measures for their coastal communities. At longer timescales, risk management and adaptation planning require robust assessments of future flooding hazard considering uncertainties. However, due to diversity in reef morphologies and complex reef hydrodynamics compared to sandy shorelines, there have been no robust analytical solutions for wave runup to allow for the development of large-scale coastal wave-driven flooding EWSs and risk assessment frameworks for reef-lined coasts. To address the need for fast, robust predictions of runup that account for the natural variability in coral reef morphologies, we constructed the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process modeling system. We developed this meta-process model using a training dataset of hydrodynamics and wave runup computed by the XBeach Non-Hydrostatic process-based hydrodynamic model for 440 combinations of water level, wave height, and wave period with 195 representative reef profiles that encompass the natural diversity in real-world fringing coral reef systems. Through this innovation, BEWARE-2 can be applied in a larger range of coastal settings than meta-models that rely on a parametric description of the coral reef geometry. In the validation stage, the BEWARE-2 modeling system produced runup results that had a relative root mean square error of 13% and relative bias of 5% relative to runup simulated by XBeach Non-Hydrostatic for a large range of oceanographic forcing conditions and for diverse reef morphologies (root mean square error and bias 0.63 and 0.26 m, respectively, relative to mean simulated wave runup of 4.85 m). Incorporating parametric modifications in the modeling system to account for variations in reef roughness and beach slope allows for systematic errors (relative bias) in BEWARE-2 predictions to be reduced by a factor of 1.5–6.5 for relatively coarse or smooth reefs and mild or steep beach slopes. This prediction provided by the BEWARE-2 modeling system is faster by 4–5 orders of magnitude than the full, process-based hydrodynamic model and could therefore be integrated into large-scale EWSs for tropical, reef-lined coasts and used for large-scale flood risk assessments.
","language":"English","publisher":"European Geosciences Union (EGU)","doi":"10.5194/nhess-24-3597-2024","usgsCitation":"McCall, R.T., Storlazzi, C.D., Roelvink, F., Pearson, S., de Goede, R., and Antolinez, J.A., 2024, Rapid simulation of wave runup on morphologically diverse, reef-lined coasts with the BEWARE-2 (Broad-range Estimator of Wave Attack in Reef Environments) meta-process model: Natural Hazards and Earth System Sciences, v. 24, p. 3597-3625, https://doi.org/10.5194/nhess-24-3597-2024.","productDescription":"29 p.","startPage":"3597","endPage":"3625","ipdsId":"IP-160501","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466824,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-24-3597-2024","text":"Publisher Index Page"},{"id":463198,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","noUsgsAuthors":false,"publicationDate":"2024-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"McCall, Robert T.","contributorId":148986,"corporation":false,"usgs":false,"family":"McCall","given":"Robert","email":"","middleInitial":"T.","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":916722,"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":916723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roelvink, Floortje","contributorId":258290,"corporation":false,"usgs":false,"family":"Roelvink","given":"Floortje","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":916724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Stuart 0000-0002-3986-4469","orcid":"https://orcid.org/0000-0002-3986-4469","contributorId":245646,"corporation":false,"usgs":false,"family":"Pearson","given":"Stuart","email":"","affiliations":[{"id":49245,"text":"Delft University of Technology; Deltares","active":true,"usgs":false}],"preferred":false,"id":916725,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Goede, Roel","contributorId":345473,"corporation":false,"usgs":false,"family":"de Goede","given":"Roel","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":916726,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Antolinez, Jose A.A.","contributorId":177510,"corporation":false,"usgs":false,"family":"Antolinez","given":"Jose","email":"","middleInitial":"A.A.","affiliations":[],"preferred":false,"id":916727,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272991,"text":"70272991 - 2024 - Concepts and evolution of urban hydrology.","interactions":[],"lastModifiedDate":"2025-12-12T16:57:20.128365","indexId":"70272991","displayToPublicDate":"2024-10-24T10:48:23","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7460,"text":"Nature Reviews Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Concepts and evolution of urban hydrology.","docAbstract":"Urbanization and climate change are exacerbating the flood risk and ecosystem degradation in urban catchments, with traditional stormwater management systems often overwhelmed. In this Review, we discuss changes in urban hydrology and approaches to stormwater management. Roughly 90% of rainfall on impervious surfaces and drainage infrastructure becomes run-off, enhancing rainfall export away from cities and leading to local water scarcity and downstream flooding and pollution. Projected increases in urban populations (68% in cities by 2050) and rainfall intensity (~12% in the 10-year and 50-year recurrence interval intensity, under 1.5 °C warming) will exacerbate these issues. Transforming stormwater systems is thus urgently needed, to mitigate flood risk and also to address community desires for environmental protection and enhanced water security. Opportunities include rain gardens and other nature-based stormwater control measures (which restore natural flows and offer other ecosystem services), smart sensor monitoring networks and real-time management (which sustain natural flow regimes, mitigate flood risk and protect ecosystem services) and stormwater harvesting (to avoid local water scarcity). Community acceptance of stormwater harvesting is as high as 96% and stormwater is a substantial resource, with volumes often exceeding demand in some parts of the world. Delivering additional transformations globally requires research into strategies to incentivize engagement and investment, and policies to guide governance of decentralized networks.
","language":"English","publisher":"Nature","doi":"10.1038/s43017-024-00599-x","usgsCitation":"Fletcher, T.D., Burns, M.J., Russell, K.L., Hamel, P., Duchesne, S., Cherqui, F., and Roy, A.H., 2024, Concepts and evolution of urban hydrology.: Nature Reviews Earth & Environment, v. 5, p. 789-801, https://doi.org/10.1038/s43017-024-00599-x.","productDescription":"13 p.","startPage":"789","endPage":"801","ipdsId":"IP-159530","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2024-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fletcher, Tim D.","contributorId":195752,"corporation":false,"usgs":false,"family":"Fletcher","given":"Tim","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":952048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Matthew J.","contributorId":146251,"corporation":false,"usgs":false,"family":"Burns","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16645,"text":"Waterway Ecosystem Research Group, School of Ecosystem and Forest Sciences, The","active":true,"usgs":false}],"preferred":false,"id":952049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, Kathryn L 0000-0002-9613-4665","orcid":"https://orcid.org/0000-0002-9613-4665","contributorId":292735,"corporation":false,"usgs":false,"family":"Russell","given":"Kathryn","email":"","middleInitial":"L","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":952050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hamel, Perrine","contributorId":146253,"corporation":false,"usgs":false,"family":"Hamel","given":"Perrine","email":"","affiliations":[{"id":16647,"text":"Natural Capital Project, Stanford University, 371 Serra Mall, Stanford, CA 94305","active":true,"usgs":false}],"preferred":false,"id":952051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duchesne, Sophie","contributorId":363817,"corporation":false,"usgs":false,"family":"Duchesne","given":"Sophie","affiliations":[{"id":25321,"text":"Institut National de la Recherche Scientifique","active":true,"usgs":false}],"preferred":false,"id":952052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cherqui, Frédéric","contributorId":363820,"corporation":false,"usgs":false,"family":"Cherqui","given":"Frédéric","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":952053,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952054,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264282,"text":"70264282 - 2024 - Effect of oxygenation and location on survival and growth of endangered Lost River Suckers in net pens","interactions":[],"lastModifiedDate":"2025-03-27T13:21:03.075344","indexId":"70264282","displayToPublicDate":"2024-10-24T09:16:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effect of oxygenation and location on survival and growth of endangered Lost River Suckers in net pens","docAbstract":"Acclimation of captively reared fishes to their release environment through soft releases and cage culture can improve survival. Recovery strategies for imperiled Lost River Suckers Deltistes luxatus includes soft releases of captive reared juveniles in net pens in Upper Klamath Lake, Oregon. However, intermittent and sometimes extreme hypoxia in the lake can reduce juvenile fish survival in net pets. To ensure juvenile fish receive adequate oxygen for growth and survival, net pens can be placed in areas of higher oxygen concentration or oxygen can be supplemented. We experimented with a low-cost oxygenation system in Upper Klamath Lake net pens and its effects on survival and growth of juvenile Lost River Suckers. Pairs of net pens, one with supplemental oxygen and one without, were located at a deep offshore site with historically higher oxygen concentration called Mid North and a shallow near shore site with historically lower oxygen concentration called Fish Banks. Survival of passive integrated transponder tagged juvenile Lost River Suckers was monitored and evaluated with Kaplan-Meier survival analyses. We measured two full water column hypoxia events at Fish Banks during the study period, but none at the Mid North site. Oxygenation decreased the number of hours oxygen concentration was less than and pH was greater than known lethal and sublethal thresholds for juvenile Lost River Suckers. For juvenile Lost River Suckers that survived the entire July to September study period, growth was faster at Mid North than Fish Banks. Additionally, there was faster growth at the oxygenated than non-oxygenated Fish Bank’s site, whereas growth was faster at the non-oxygenated than oxygenated Mid North site. Survival did not differ between Mid North net pens, and the Fish Banks oxygenated net pen had greater survival compared to the non-oxygenated Fish Banks net pen during our study. Lost River Sucker growth and survival are dependent on net pen site selection and a low-cost oxygenation system can prevent mass mortality because of summertime hypoxia in shallow freshwater ecosystems.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-24-011","usgsCitation":"Banet, N.V., Burdick, S.M., Bart, R., Harris, A., and Krause, J.R., 2024, Effect of oxygenation and location on survival and growth of endangered Lost River Suckers in net pens: Journal of Fish and Wildlife Management, v. 15, no. 2, p. 361-379, https://doi.org/10.3996/JFWM-24-011.","productDescription":"19 p.","startPage":"361","endPage":"379","ipdsId":"IP-147662","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":488677,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-24-011","text":"Publisher Index Page"},{"id":483134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11037882919081,\n 42.591147180046164\n ],\n [\n -122.11037882919081,\n 42.205990488449686\n ],\n [\n -121.7170888205275,\n 42.205990488449686\n ],\n [\n -121.7170888205275,\n 42.591147180046164\n ],\n [\n -122.11037882919081,\n 42.591147180046164\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Banet, Nathan V 0000-0002-8537-1702","orcid":"https://orcid.org/0000-0002-8537-1702","contributorId":238015,"corporation":false,"usgs":false,"family":"Banet","given":"Nathan","email":"","middleInitial":"V","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":930252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":930253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bart, Ryan J 0000-0003-0310-0667","orcid":"https://orcid.org/0000-0003-0310-0667","contributorId":298895,"corporation":false,"usgs":false,"family":"Bart","given":"Ryan J","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":930254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":930255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krause, Jacob Richard 0000-0002-9804-2481","orcid":"https://orcid.org/0000-0002-9804-2481","contributorId":300701,"corporation":false,"usgs":true,"family":"Krause","given":"Jacob","email":"","middleInitial":"Richard","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":930256,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260109,"text":"70260109 - 2024 - Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States","interactions":[],"lastModifiedDate":"2024-11-27T15:53:46.572812","indexId":"70260109","displayToPublicDate":"2024-10-24T09:02:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States","docAbstract":"Per- and polyfluoroalkyl substances (PFAS), known colloquially as “forever chemicals”, have been associated with adverse human health effects and have contaminated drinking water supplies across the United States owing to their long-term and widespread use. People in the United States may unknowingly be drinking water that contains PFAS because of a lack of systematic analysis, particularly in domestic water supplies. We present an extreme gradient boosting model for predicting the occurrence of PFAS in groundwater at the depths of drinking water supply for the conterminous United States. Our model results indicate that 71 to 95 million people in the conterminous United States potentially rely on groundwater with detectable concentrations of PFAS for their drinking-water supplies prior to any treatment.
","language":"English","publisher":"Science","doi":"10.1126/science.ado6638","usgsCitation":"Tokranov, A.K., Ransom, K.M., Bexfield, L.M., Lindsey, B.D., Watson, E., Dupuy, D., Stackelberg, P.E., Fram, M.S., Voss, S., Kingsbury, J.A., Jurgens, B., Smalling, K., and Bradley, P., 2024, Predictions of groundwater PFAS occurrence at drinking water supply depths in the United States: Science, v. 386, no. 6723, p. 748-755, https://doi.org/10.1126/science.ado6638.","productDescription":"8 p.","startPage":"748","endPage":"755","ipdsId":"IP-157604","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf 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Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1046","displayTitle":"Lidar Estimation of Storage Capacity for Managed Water Resources Used by Desert Bighorn Sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona","title":"Lidar estimation of storage capacity for managed water resources used by Desert Bighorn Sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona","docAbstract":"In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep (Ovis canadensis mexicana) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.
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The Rappahannock Tributary Summary outlines change over time for a suite of monitored tidal water quality parameters and associated potential drivers of those trends for the period of 1985 to 2022, and provides a brief description of the current state of knowledge explaining these observed changes. Water quality parameters described include surface (above pycnocline) total nitrogen (TN), surface total phosphorus (TP), surface water temperature (WTEMP), spring (March-May) and summer (JulySeptember) surface chlorophyll a, summer bottom (below pycnocline) dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in Appendix B. Drivers discussed include physiographic watershed characteristics, changes in TN, TP, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices. Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as winddriven mixing of the water column and increase in rainfall intensity and volume, and biological factors such as phytoplankton biomass and the presence of submerged aquatic vegetation. Continuing to track water quality response and investigating these influencing factors are important steps to understanding water quality patterns and changes in the Rappahannock River. The intended audiences for this report include, but are not limited to, 1) technical managers within jurisdictions who are looking at tidal water quality data and trying to understand why patterns are occurring, 2) local watershed organizations that are trying to understand these analyses and working to connect them to their local area(s), and 3) federal, state, and academic researchers. Figure 1 presents a conceptual model highlighting these intended audiences. Our goal is for the Tributary Summary documents to be sources of readily available background for change over time in tidal water quality observed with monitoring data. The intended purpose of the Tributary Summary documents is to help answer questions related to water quality, show how landscape factors drive water quality change over time, provide support for management decisions that may alter water quality trends and living resources conditions, and highlight where there may be information or knowledge gaps.
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The model quantifies the area of open water, partial water, and water depths on a monthly timescale during the irrigation season (April–July) from 2021–2024. This model combines previously published datasets and incorporates new measurements collected by partners. Results show that the relation between the amount of bird habitat and the extent (partial and open water) of Malheur Lake varies by bird guild. The Donner und Blitzen River supplied nearly all the surface water inflow to Malheur Lake during the analysis years, emphasizing the importance of informed management of the river. 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0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918274,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264051,"text":"70264051 - 2024 - Transfer learning with convolutional neural networks for hydrological streamline delineation","interactions":[],"lastModifiedDate":"2025-03-05T15:33:15.616325","indexId":"70264051","displayToPublicDate":"2024-10-21T08:29:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Transfer learning with convolutional neural networks for hydrological streamline delineation","docAbstract":"Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline delineation. We evaluate the performance of eleven image-based pre-trained models and a baseline model using datasets from Rowan County, North Carolina, and Covington River, Virginia in the USA. Our results demonstrate that when models are adapted to a new area, the fine-tuned ImageNet pre-trained model exhibits superior predictive accuracy, markedly higher than the models trained from scratch or those only fine-tuned on the same area. Moreover, the pre-trained model achieves better smoothness and connectivity between classified streamline channels. These findings underline the effectiveness of transfer learning in enhancing the delineation of hydrological streamlines across varied geographies, offering a scalable solution for accurate and efficient environmental modelling.
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However, less is understood about how these sources affect downgradient hydrological systems and food webs. Here, we report paired PFAS measurements in water, sediment, and aquatic biota along a hydrological gradient away from source zones contaminated by the use of legacy aqueous film-forming foam (AFFF) manufactured using electrochemical fluorination. Clustering analysis indicates that the PFAS composition characteristic of AFFF is detectable in water and fishes >8 km from the source. Concentrations of 38 targeted PFAS and extractable organofluorine (EOF) decreased in fishes downgradient of the AFFF-contaminated source zones. However, PFAS concentrations remained above consumption limits at all locations within the affected watershed. Perfluoroalkyl sulfonamide precursors accounted for approximately half of targeted PFAS in fish tissues, which explain >90% of EOF across all sampling locations. Suspect screening analyses revealed the presence of a polyfluoroketone pharmaceutical in fish species, and a fluorinated agrochemical in water that likely does not accumulate in biological tissues, suggesting the presence of diffuse sources such as septic system and agrochemical inputs throughout the watershed in addition to AFFF contamination. Based on these results, monitoring programs that consider all hydrologically connected regions within watersheds affected by large PFAS sources would help ensure public health protection.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c07016","usgsCitation":"Pickard, H.M., Ruyle, B.J., Haque, F., Logan, J.M., LeBlanc, D.R., Vojta, S., and Sunderland, E.M., 2024, Characterizing the areal extent of PFAS contamination in fish species downgradient of AFFF source zones: Environmental Science & Technology, v. 58, no. 43, p. 19440-19453, https://doi.org/10.1021/acs.est.4c07016.","productDescription":"14 p.","startPage":"19440","endPage":"19453","ipdsId":"IP-168224","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":498694,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11526379","text":"External Repository"},{"id":498583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.54,\n 41.71\n ],\n [\n -70.54,\n 41.56\n ],\n [\n -70.44,\n 41.56\n ],\n [\n -70.44,\n 41.71\n ],\n [\n -70.54,\n 41.71\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"43","noUsgsAuthors":false,"publicationDate":"2024-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pickard, Heidi M.","contributorId":365051,"corporation":false,"usgs":false,"family":"Pickard","given":"Heidi","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruyle, Bridger J.","contributorId":365053,"corporation":false,"usgs":false,"family":"Ruyle","given":"Bridger","middleInitial":"J.","affiliations":[{"id":53026,"text":"Carnegie Institute for Science","active":true,"usgs":false}],"preferred":false,"id":953642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haque, Faiz","contributorId":365056,"corporation":false,"usgs":false,"family":"Haque","given":"Faiz","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, John M.","contributorId":365058,"corporation":false,"usgs":false,"family":"Logan","given":"John","middleInitial":"M.","affiliations":[{"id":39892,"text":"Massachusetts Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":953644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vojta, Simon","contributorId":304335,"corporation":false,"usgs":false,"family":"Vojta","given":"Simon","email":"","affiliations":[{"id":66031,"text":"University of Rhode Island, Narragansett, RI, USA","active":true,"usgs":false}],"preferred":false,"id":953646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sunderland, Elsie M.","contributorId":365063,"corporation":false,"usgs":false,"family":"Sunderland","given":"Elsie","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953647,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259583,"text":"sir20245093 - 2024 - Conceptualization and simulation of groundwater flow and groundwater availability in the Boone and Roubidoux aquifers in northeastern Oklahoma, 1980–2017","interactions":[],"lastModifiedDate":"2025-12-23T21:43:15.225924","indexId":"sir20245093","displayToPublicDate":"2024-10-16T09:21:46","publicationYear":"2024","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":"2024-5093","displayTitle":"Conceptualization and Simulation of Groundwater Flow and Groundwater Availability in the Boone and Roubidoux Aquifers in Northeastern Oklahoma, 1980–2017","title":"Conceptualization and simulation of groundwater flow and groundwater availability in the Boone and Roubidoux aquifers in northeastern Oklahoma, 1980–2017","docAbstract":"Oklahoma Groundwater Law (Oklahoma Statute § 82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations to determine the maximum annual yield for the State’s groundwater basins. The Boone and Roubidoux aquifers (also known as the Springfield Plateau aquifer and Ozark aquifer, respectively) are bedrock aquifers that extend from northeastern Oklahoma into Kansas, Arkansas, and Missouri. At present (2024), the Oklahoma Water Resources Board has yet to legally issue orders for the final determination of maximum annual yields for the Boone and Roubidoux aquifers. To support determination of a maximum annual yield, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, developed a hydrogeologic framework, a conceptual groundwater-flow model, and a calibrated numerical groundwater-flow model for the Boone and Roubidoux aquifers.
Three types of groundwater-availability scenarios were simulated by using the calibrated numerical model. These scenarios were used to (1) estimate equal-proportionate-share groundwater withdrawal rates (groundwater withdrawal applied equally over the aquifer), (2) quantify the potential effects of projected groundwater withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought. For the Boone aquifer, equal-proportionate-share groundwater withdrawal rates were 1.10, 0.98, and 0.96 acre-feet per acre per year for the 20-, 40-, and 50-year scenarios, respectively. For the Roubidoux aquifer, equal-proportionate-share groundwater withdrawal rates were 1.76, 1.34, and 1.25 acre-feet per acre per year for the 20-, 40-, and 50-year simulations, respectively. For the 50-year scenarios, stream seepage was minimally affected. Over the 10-year drought scenario, groundwater storage in the Boone and Roubidoux aquifers decreased by 660,451 acre-feet (6.7 percent) and 508,472 acre-feet (1.0 percent), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245093","issn":"2328-0328","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Trevisan, A.R., Russell, C.A., Lockmiller, H.A., Wagner, D.L., Correll, J.S., and Knierim, K.J., 2024, Conceptualization and simulation of groundwater flow and groundwater availability in the Boone and Roubidoux aquifers in northeastern Oklahoma, 1980–2017: U.S. Geological Survey Scientific Investigations Report 2024–5093, 105 p., https://doi.org/10.3133/sir20245093.","productDescription":"Report: xiv, 105 p.; Data Release","numberOfPages":"124","onlineOnly":"Y","ipdsId":"IP-142594","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":462876,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245093/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5093 HTML"},{"id":462875,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5093/sir20245093.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5093 XML"},{"id":462874,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5093/sir20245093.pdf","size":"38.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5093"},{"id":462873,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5093/images"},{"id":462872,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5093/coverthb.jpg"},{"id":462877,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KWWUAV","text":"USGS Data Release","linkHelpText":"- MODFLOW-NWT model used for the simulation of groundwater flow and analysis of groundwater availability in the Boone and Roubidoux aquifers in northeastern Oklahoma, 1980–2017"},{"id":497943,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117647.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oklahoma","otherGeospatial":"Boone and Roubidoux aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.61835569487307,\n 37.340465151367\n ],\n [\n -95.61835569487307,\n 34.999403485947965\n ],\n [\n -93.99237913237286,\n 34.999403485947965\n ],\n [\n -93.99237913237286,\n 37.340465151367\n ],\n [\n -95.61835569487307,\n 37.340465151367\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
For additional information, visit
https://www.usgs.gov/centers/ot-water
Contact Us- USGS Publications Warehouse
","tableOfContents":"Knowledge of snow and firn-density change is needed to use elevation-change measurements to estimate glacier mass change. Additionally, firn-density evolution on glaciers is closely connected to meltwater percolation, refreezing and runoff, which are key processes for glacier mass balance and hydrology. Since 2016, the U.S. Geological Survey Benchmark Glacier Project has recovered firn cores from a site on Wolverine Glacier in Alaska's Kenai Mountains. We use annual horizons in repeat cores to track firn densification and meltwater retention over seasonal and interannual timescales, and we use density measurements to quantify how the firn air content (FAC) changes through time. The results suggest the firn is densifying due primarily to compaction rather than refreezing. Liquid-water retention in the firn is transient, likely due to gravity-fed drainage and irreducible-water-content decreases that accompany decreasing porosity. We show that the uncertainty (±60 kg m−3) in the commonly used volume-to-mass conversion factor of 850 kg m−3 is an underestimation when glacier-wide FAC variability exceeds 12% of the glacier-averaged height change. Our results demonstrate how direct measurements of firn properties on mountain glaciers can be used to better quantify the uncertainty in geodetic volume-to-mass conversions.
Grassland birds are under threat worldwide due to loss of habitat to agriculture. Prairie strips are a new agricultural conservation practice composed of linear strips of reconstructed diverse, native, herbaceous, perennial vegetation designed to promote land sharing among agriculture and biodiversity, while also addressing soil and water conservation goals. We evaluated bird community response to establishment of prairie strips on commercial row-crop fields (corn [(Zea mays] and soybean [Glycine max]) in Iowa, USA compared to controls fields without prairie strips, from 2015 to 2020. We found a 2.94-fold higher density of grassland birds on fields with prairie strips compared to control fields, and a 1.87-fold higher density of birds overall. Time since prairie strip establishment was a significant predictor of grassland bird density, with significant increases between years 1 and 2 and years 3 and 4. Species with the strongest positive response to prairie strips were Red-winged Blackbird (Agelaius phoeniceus), Common Yellowthroat (Geothlypis trichas), Western Meadowlark (Sturnella neglecta) and two species of greatest conservation need: Dickcissel (Spiza americana) and Eastern Meadowlark (Sturnella magna). Diversity measures (e.g., Shannon’s and Simpson’s indices) did not differ between fields with prairie strips versus those without. Prairie strips provide quality breeding habitat for a suite of species, including grassland species and those of conservation concern. While improving several bird community measures, prairie strips do not provide habitat for area-sensitive grassland birds. Larger grassland patches are needed, potentially managed as land-sparing reserves, to achieve overall biodiversity goals in agricultural landscapes.
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\"}}]}","volume":"374","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Giese, Jordan C.","contributorId":343192,"corporation":false,"usgs":false,"family":"Giese","given":"Jordan","email":"","middleInitial":"C.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":910663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schulte, Lisa A.","contributorId":177987,"corporation":false,"usgs":false,"family":"Schulte","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":910664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910665,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260381,"text":"70260381 - 2024 - An assessment of N, P, Fe, Zn, Ni and Mo limitation on suspended nutrient diffusing substrates in nearshore areas of Lake Michigan and Lake Erie","interactions":[],"lastModifiedDate":"2024-10-31T11:44:01.543101","indexId":"70260381","displayToPublicDate":"2024-10-15T06:39:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3897,"text":"Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of N, P, Fe, Zn, Ni and Mo limitation on suspended nutrient diffusing substrates in nearshore areas of Lake Michigan and Lake Erie","docAbstract":"In large lakes, metal availability sometimes limits the acquisition of nutrients (nitrogen, N and phosphorus, P) in offshore waters that are relatively isolated from tributaries and sediments. We hypothesize that metals may also be important within harmful algal blooms (HABs). HABs occur where nutrient loads are elevated, but bioassays often indicate that phytoplankton in HABs are N or P limited. Nutrient limitation may be exacerbated by corresponding limitations in several metals (i.e. nickel - Ni, molybdenum - Mo, zinc - Zn, and iron - Fe) that facilitate uptake and transformation of oxidized and organic forms of nutrients, such as urea, nitrate and organic phosphorus. The cyanotoxin microcystin has been hypothesized to have a role in metal management, so metal demand may also influence the toxicity of HABs. Here, we used nutrient diffusing substrates to measure how N, P, Ni, Mo, Zn and Fe amendments influenced the growth and toxicity of periphyton. Periphyton was grown suspended in 10 nearshore sites in Lake Michigan and Lake Erie (5 with and 5 without perennial HABs). Outside of blooms, we found no evidence for metal limitation or co-limitation. However, evidence for metal co-limitation was observed in two HABs sites (Zn in Green Bay and Zn, Mo, Ni and Fe in Sandusky Bay). N, P and Zn amendments all stimulated microcystin content in Maumee Bay. These data indicate that nutrient limitation occurs even within blooms, and the availability of metals may have an influence on growth, community composition and toxicity.
The global prevalence of mercury (Hg) contamination and its complex biogeochemical cycling has resulted in elevated Hg concentrations in biota in remote and pristine environments. However, there is uncertainty in the relative importance of Hg deposition and landscape factors that control Hg cycling and bioaccumulation. To address this, we measured total mercury (THg) concentrations in 1344 fish across 60 subalpine lakes from 12 national parks (NPs). These parks represent three distinct high-elevation regions across the western U.S.: Cascades and Olympic Peninsula, Sierra Nevada and Great Basin, and Rocky Mountains. Within these regions, three NPs (Mount Rainier, Yosemite, and Rocky Mountain) were intensively studied representatives of each region. This study aimed to (1) assess the magnitude of mercury contamination in a collection of remote, small catchment lakes; (2) quantify the variability of fish THg concentrations among and within parks; and (3) test the relative importance of Hg inputs in comparison to landscape characteristics on lake-specific fish THg concentrations. The spatial variability in fish THg concentrations was 2.6-fold higher than variation in deposition to watersheds, suggesting that factors other than Hg delivery are important determinants of Hg accumulation in these environments. Spatially, fish THg concentrations (ng/g ww ± standard error) were lower in the Rockies (46.2 ± 5.0) and Sierra (56.5 ± 5.8) compared to the Cascades (67.8 ± 6.1). Additionally, fish THg concentrations increased with increasing conifer forest cover (Intensive parks: P < 0.0001, R2 = 0.43; All parks: P = 0.0001, R2 = 0.23) but were not correlated with wet Hg deposition across the catchment. These findings suggest that forest composition is likely an important aspect of Hg delivery to lake food webs, and although the mechanisms are unclear, could be tied to some combination of forest influences on catchment organic carbon and increased surface area for dry Hg deposition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.176936","usgsCitation":"Flanagan-Pritz, C.M., Johnson, B.L., Willacker, J., Kennedy, C.M., Daniele, N., and Eagles-Smith, C., 2024, Forest cover influences fish mercury concentrations in national parks of the western U.S.: Science of the Total Environment, v. 955, 176936, 10 p., https://doi.org/10.1016/j.scitotenv.2024.176936.","productDescription":"176936, 10 p.","ipdsId":"IP-167506","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":493324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.176936","text":"Publisher Index Page"},{"id":493107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.90372169965117,\n 48.83924487815952\n ],\n [\n -124.90372169965117,\n 35.409036548087556\n ],\n [\n -104.74017350711692,\n 35.409036548087556\n ],\n [\n -104.74017350711692,\n 48.83924487815952\n ],\n [\n -124.90372169965117,\n 48.83924487815952\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"955","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flanagan-Pritz, Colleen M.","contributorId":301093,"corporation":false,"usgs":false,"family":"Flanagan-Pritz","given":"Colleen","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":944351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Branden L. 0000-0002-8018-6452 branden_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-8018-6452","contributorId":257446,"corporation":false,"usgs":true,"family":"Johnson","given":"Branden","email":"branden_johnson@usgs.gov","middleInitial":"L.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":221744,"corporation":false,"usgs":true,"family":"Willacker","given":"James","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Christopher M.","contributorId":346473,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":944354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniele, Ninette R.","contributorId":358885,"corporation":false,"usgs":false,"family":"Daniele","given":"Ninette R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":944355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":944356,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262444,"text":"70262444 - 2024 - Hatch timing of largemouth bass: Implications for recruitment at the northern edge of their native range","interactions":[],"lastModifiedDate":"2025-01-21T15:07:55.662733","indexId":"70262444","displayToPublicDate":"2024-10-14T09:19:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hatch timing of largemouth bass: Implications for recruitment at the northern edge of their native range","docAbstract":"Climate-related shifts in hatch timing could mean that age-0 largemouth bass Micropterus salmoides in north temperate lakes reach larger sizes and experience higher survival, which may contribute to increased prevalence of this species in many lakes. However, information on age-0 largemouth bass life history is lacking for these lakes. We estimated hatch dates, daily growth rates (DGR), and length-based probability of piscivory of age-0 largemouth bass in Wisconsin lakes to: (1) provide baseline data on early life history; (2) compare hatch timing between years with different spring temperature regimes, and (3) project how shifts in hatch timing might influence total length (TL) distributions of age-0 bass if mean DGR remained constant. Most age-0 largemouth bass (>90%) collected from ten Wisconsin lakes (N = 746) hatched between 23 May and 24 June during 2012 and 2013 and did not switch to piscivory during their first summer. Prevalence of positive correlations (16 of 24 lake-year pairings) between TL in and age indicates hatch timing may influence TLs attained by age-0 largemouth bass in August in some lake-years. Mean daily water temperatures in May 2012 were 3.1 °C warmer than in May 2013 for the five of the six lakes where hatch dates were estimated in both years. On average, earliest and median hatch dates for age-0 largemouth bass in these six lakes were 10–11 d earlier in 2012 than in 2013 and hatch duration was approximately 8 d longer in 2012. Despite differences in hatch timing, mean DGR was relatively consistent (range = 0.61–0.74 mm/d) between lakes and years. Simple simulations suggest that earlier hatch dates could result in more age-0 largemouth bass reaching TLs associated with piscivory and overwinter survival by the end of their first summer if growth rates did not change, which could translate to higher recruitment.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2024.2403360","usgsCitation":"Coppola, G., Kelling, C., Dembkowski, D., and Isermann, D.A., 2024, Hatch timing of largemouth bass: Implications for recruitment at the northern edge of their native range: Journal of Freshwater Ecology, v. 39, no. 1, 2403360, 17 p., https://doi.org/10.1080/02705060.2024.2403360.","productDescription":"2403360, 17 p.","ipdsId":"IP-155075","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481056,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2024.2403360","text":"Publisher Index Page"},{"id":480743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"39","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Coppola, Giancarlo","contributorId":349329,"corporation":false,"usgs":false,"family":"Coppola","given":"Giancarlo","affiliations":[{"id":83472,"text":"University of Wisconsin–Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelling, Craig J.","contributorId":349330,"corporation":false,"usgs":false,"family":"Kelling","given":"Craig J.","affiliations":[{"id":83472,"text":"University of Wisconsin–Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dembkowski, Daniel J.","contributorId":349331,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":83472,"text":"University of Wisconsin–Stevens Point","active":true,"usgs":false}],"preferred":false,"id":924226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924227,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261950,"text":"70261950 - 2024 - Lake temperature and morphometry shape the thermal composition of recreational fishing catch","interactions":[],"lastModifiedDate":"2025-01-06T15:12:52.812213","indexId":"70261950","displayToPublicDate":"2024-10-11T09:06:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Lake temperature and morphometry shape the thermal composition of recreational fishing catch","docAbstract":"Managing freshwater fisheries in warming lakes is challenging because climate change impacts anglers, fish, and their interactions.
We integrated recent models of current and future lake temperatures with recreational fisheries catch data from 587 lakes in three north-central U.S. states (Michigan, Minnesota, and Wisconsin) to evaluate how the thermal composition of recreational fisheries catch varied as a function of temperature, ice coverage, and lake morphometry.
We found that warmwater catch share (WCS), defined as the proportion of fish in recreational angling catch that belonged to the warmwater thermal guild (final temperature preferendum [FTP] > 25°C), increased with average annual lake surface temperature and decreased with survey ice coverage. However, we also found that WCS decreased with increased lake area and depth. Using mid-century (2040–2060) water temperature and ice projections while holding all other variables constant, we predicted that WCS will likely increase as the climate warms but that significant thermal heterogeneity will persist.
Lakes that are large (>100 ha) and deep (>10 m) and those with cooler (<3700 annual growing degree-days) predicted future temperatures will likely hold thermal refugia for coolwater (FTP = 19–25°C) and coldwater (FTP < 19°C) fish even as average lake temperatures rise, creating the potential for management actions to resist the shift from coolwater to warmwater fisheries. Managers of smaller and more rapidly warming lakes may want to consider strategies that accept or direct emerging warmwater fishing opportunities. We suggest that the most viable path to climate adaptation in landscapes of diverse lakes may be to resist warmwater shifts where possible and to accept or direct the rise of warmwater fishing opportunities where necessary.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10481","usgsCitation":"Wszola, L.S., Sievert, N., Lynch, A.J., Embke, H.S., Kaz, A.L., Robertson, M., Midway, S., and Paukert, C.P., 2024, Lake temperature and morphometry shape the thermal composition of recreational fishing catch: Transactions of the American Fisheries Society, v. 153, no. 6, p. 746-762, https://doi.org/10.1002/tafs.10481.","productDescription":"13 p.","startPage":"746","endPage":"762","ipdsId":"IP-154515","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":500789,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/oceanography_coastal_pubs/1055","text":"External Repository"},{"id":465669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Minnesota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-90.418136,46.566094],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192],[-90.614589,42.508053],[-91.078097,42.806526],[-91.177728,43.118733],[-91.062562,43.243165],[-91.217706,43.50055],[-96.453049,43.500415],[-96.452948,45.268925],[-96.835451,45.586129],[-96.587093,45.816445],[-96.559271,46.058272],[-96.789572,46.639079],[-96.851293,47.589264],[-97.139497,48.153108],[-97.108655,48.691484],[-97.238387,48.982631],[-95.153711,48.998903],[-95.153314,49.384358],[-94.974286,49.367738],[-94.555835,48.716207],[-93.741843,48.517347],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.735927,47.624343],[-92.058888,46.809938],[-92.025789,46.710839],[-91.781928,46.697604],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.418136,46.566094]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Michigan\",\"nation\":\"USA \"}}]}","volume":"153","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Wszola, Lyndsie S.","contributorId":205135,"corporation":false,"usgs":false,"family":"Wszola","given":"Lyndsie","email":"","middleInitial":"S.","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":922381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sievert, Nicholas A. 0000-0003-3160-7596","orcid":"https://orcid.org/0000-0003-3160-7596","contributorId":177341,"corporation":false,"usgs":false,"family":"Sievert","given":"Nicholas A.","affiliations":[],"preferred":false,"id":922382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":922383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":922384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaz, Anna L.","contributorId":339462,"corporation":false,"usgs":false,"family":"Kaz","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":922385,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Matthew D.","contributorId":347760,"corporation":false,"usgs":false,"family":"Robertson","given":"Matthew D.","affiliations":[{"id":26965,"text":"Memorial University of Newfoundland","active":true,"usgs":false}],"preferred":false,"id":922386,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Midway, Stephen R.","contributorId":244467,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":922387,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922388,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70259699,"text":"70259699 - 2024 - Reducing wastewater nitrogen loading by >90% with carbon-amended septic systems: A field demonstration in Barnstable (Cape Cod), Massachusetts","interactions":[],"lastModifiedDate":"2024-10-19T13:50:54.703043","indexId":"70259699","displayToPublicDate":"2024-10-11T08:46:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Reducing wastewater nitrogen loading by >90% with carbon-amended septic systems: A field demonstration in Barnstable (Cape Cod), Massachusetts","docAbstract":"Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a watershed. We compare the predictive performance of space- and time-unaware Random Forest models and space- and time-aware Recurrent Graph Convolution Neural Network models (KGE: 0.67 and 0.64, respectively) and use explainable artificial intelligence methods to interpret model predictions and understand salinization drivers. These models are applied to the Delaware River Basin, a developed watershed with diverse land uses that experiences anthropogenic salinization from winter deicer applications. These models capture seasonality for the winter first flush of deicers, and the streams with elevated predictions correspond well with indicators of deicer application. This result suggests that these models can be used to identify potential salinity-impaired streams for winter best management practices. Daily salinity predictions are driven primarily by land cover (urbanization) trends that may represent anthropogenic salinization processes and weather at time scales up to three months. Such modeling approaches are likely transferable to other watersheds and can be applied to further understand salinization risks and drivers.