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.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-025-05848-8","collaboration":"USFWS","usgsCitation":"Cecala, K.K., Halstead, B., McGrory, J., and Maerz, J.C., 2025, Do watershed conditions or local climate play a larger role in determining regional stream salamander distributions?: Hydrobiologia, v. 852, p. 4053-4067, https://doi.org/10.1007/s10750-025-05848-8.","productDescription":"15 p.","startPage":"4053","endPage":"4067","ipdsId":"IP-114382","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":486222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina","otherGeospatial":"Upper Little Tennessee watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.2386909895219,\n 35.52532859216157\n ],\n [\n -84.25914633148402,\n 34.38251830455587\n ],\n [\n -82.90909376196274,\n 34.37126510334987\n ],\n [\n -82.90909376196274,\n 35.52532859216157\n ],\n [\n -84.2386909895219,\n 35.52532859216157\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"852","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Cecala, Kristen K.","contributorId":171762,"corporation":false,"usgs":false,"family":"Cecala","given":"Kristen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":937824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGrory, James S.","contributorId":355637,"corporation":false,"usgs":false,"family":"McGrory","given":"James S.","affiliations":[{"id":84785,"text":"University of the South","active":true,"usgs":false}],"preferred":false,"id":937826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maerz, John C.","contributorId":341635,"corporation":false,"usgs":false,"family":"Maerz","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":937827,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265930,"text":"70265930 - 2025 - A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach","interactions":[],"lastModifiedDate":"2025-04-22T15:33:21.230287","indexId":"70265930","displayToPublicDate":"2025-03-28T10:31:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach","docAbstract":"The thermal structure of the continental crust plays a critical role in understanding its elastic and rheologic properties as well as its dynamic processes. Thermal parameter data sets on continental scales have been used to constrain the crustal thermal structure, including both the direct (e.g. temperature, heat flux and heat conductivity measured at the surface) and indirect (e.g. seismically derived Mohorovičić discontinuity (Moho) temperature, geomagnetically derived Curie depth) observations. In this study, we present a new continental scale crustal heat generation model with additional information from seismologically inferred crustal composition. Together with previous direct and indirect thermal parameter data sets in the conterminous United States, we use the new crustal heat generation model to construct a 3-D crustal temperature model under a newly developed Bayesian framework. Specifically, we first derive profiles of crustal heat generation based on an empirical geochemical relationship at 1683 locations where seismologically derived crustal composition information is available. Then for each of these locations, the average heat generation values in the upper, middle and lower crust are combined with other thermal parameters through a Markov Chain Monte-Carlo inversion for a conductive, vertically smooth temperature profile. The results, posterior distributions of temperature profiles, are used to generate a 3-D crustal thermal model with the uncertainties systematically assessed. The new temperature model overall exhibits similar patterns to that from the U.S. Geological Survey National Crustal Model, but also reduces possible biases and the model's dependence on a single thermal parameter.
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Weisen","contributorId":353597,"corporation":false,"usgs":false,"family":"Shen","given":"Weisen","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":934054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934055,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268306,"text":"70268306 - 2025 - Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach","interactions":[],"lastModifiedDate":"2025-06-20T15:18:04.082324","indexId":"70268306","displayToPublicDate":"2025-03-28T10:11:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach","docAbstract":"Climate change is affecting coastal ecosystems worldwide as water temperatures increase, hydrologic regimes change, and sea levels rise. Consequently, estuaries risk declines in ecosystem functioning due to increasing temperatures and other hydrologic factors. Characterizing and predicting estuarine water temperature are challenging because these systems are highly dynamic. Statistical models have been used to accurately assess air temperature-water temperature relationships in lakes and streams but have not been effectively applied to tidally influenced ecosystems like estuaries. We used 6 years of continuous monitoring data from the Nisqually River Delta in Puget Sound, Washington, U.S.A., to parameterize and run a non-linear statistical model and generate spatially explicit model predictions. Our goal was to examine spatiotemporal patterns in estuarine water temperature and thermal refugia given current estimates of climactic change. The performance of the parameterized model was similar to that of non-linear stream temperature models (NSE = 0.76; RMSE = 2.34 °C). Scenarios incorporating forecasted high-emission air temperatures through the year 2100 (+ 7 °C) predicted a corresponding 3.55 ± 0.63 °C increase in average water temperatures; however, moderate and high rates of sea-level rise offset temperature increases by 3–20% and substantially reduced the amount of time temperatures exceeded the thermal stress threshold of 20 °C for juvenile salmon. These findings demonstrate how the effects of one climate stressor (sea-level rise) may offset another (temperature increases) to maintain thermal refugia for coldwater fishes. Similar exercises may allow managers to explore mitigation options like the planting of riparian vegetation or modified flooding regimes to further offset rising water temperatures.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01510-7","usgsCitation":"Davis, M.J., Woo, I., and De La Cruz, S.E., 2025, Estuarine tidal cycles may preserve thermal refugia as global temperatures increase: Estuaries and Coasts, v. 48, 90, 19 p., https://doi.org/10.1007/s12237-025-01510-7.","productDescription":"90, 19 p.","ipdsId":"IP-129413","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta, Puget Sound, Salish Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.55330830655157,\n 48.98716401827198\n ],\n [\n -123.55330830655157,\n 47.20224465518157\n ],\n [\n -121.87955279406418,\n 47.20224465518157\n ],\n [\n -121.87955279406418,\n 48.98716401827198\n ],\n [\n -123.55330830655157,\n 48.98716401827198\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938186,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268307,"text":"70268307 - 2025 - Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments","interactions":[],"lastModifiedDate":"2025-06-20T14:02:06.25149","indexId":"70268307","displayToPublicDate":"2025-03-28T08:57:34","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":"Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments","docAbstract":"Coastal erosion, intensified by sea level rise, poses significant threats to coastal communities in Hawaiʻi and similar island communities. This study projects long-term shoreline change on the Hawaiian Island of O‘ahu using the data-assimilated CoSMoS-COAST shoreline change model. CoSMoS-COAST models four key shoreline processes: (1) Alongshore transport, (2) Recession due to sea level rise, (3) Cross-shore transport due to waves, and (4) Residual processes represented by a linear trend term. This study marks the first application of CoSMoS-COAST for an oceanic equatorial island with narrow beaches and a dynamic wave climate. The model is informed with a novel combination of shoreline data derived from high-resolution imagery from Planet, Sentinel-2, and Landsat satellites, wave-climate hindcasts specific to Hawai‘i, and regional beach-slope surveys. On a dynamic northern Oʻahu beach, the model achieved a root mean square error of 9.4 m between observations and model output. CoSMoS-COAST predicts that 81% of O‘ahu’s sandy beach coastline could experience beach loss by 2100; with 39.8% of this loss happening by 2030. This represents an increase, 43.3%, in net landward shoreline change compared to previous erosion forecasts, for 0.3 m of sea level rise (2050). Additionally, dynamic processes such as cross-shore equilibrium processes and alongshore sediment transport, play a large contribution to gross shoreline change within the next decade, particularly on O ‘ahu’s north and west shores. In the long term, we find that recession due to sea level rise and residual processes dominate, but dynamic, wave-driven processes (longshore and cross-shore transport) still account for 34% of shoreline change between present and 2100. We assert dynamic, wave-driven processes are a crucial addition for accurate modeling of island sandy beach environments. These findings have implications for O‘ahu’s coastal planning and development, suggesting updates to shoreline policies that rely upon erosion forecasting, and highlights the importance of incorporating wave and alongshore transport in erosion models for other Pacific islands.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-95074-y","usgsCitation":"Moskvichev, R., Mikkelsen, A., Anderson, T., Vitousek, S., Joel Nicolow, and Fletcher, C., 2025, Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments: Scientific Reports, v. 15, 10794, 23 p., https://doi.org/10.1038/s41598-025-95074-y.","productDescription":"10794, 23 p.","ipdsId":"IP-176072","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-95074-y","text":"Publisher Index Page"},{"id":491019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.97415529522343,\n 21.740805505081653\n ],\n [\n -158.15139260242358,\n 21.600579083024826\n ],\n [\n -158.2903083296884,\n 21.599465629948895\n ],\n [\n -158.24240635476954,\n 21.479162346928234\n ],\n [\n -158.11187347311537,\n 21.27955194162557\n ],\n [\n -157.87475869726666,\n 21.277320121849456\n ],\n [\n -157.78853514241246,\n 21.229327812614713\n ],\n [\n -157.6687802051152,\n 21.253883970723265\n ],\n [\n -157.62447087831504,\n 21.30744683110042\n ],\n [\n -157.70231158755843,\n 21.41228417679669\n ],\n [\n -157.71069443316924,\n 21.478047962139442\n ],\n [\n -157.79811553739634,\n 21.456873031193922\n ],\n [\n -157.82446162360165,\n 21.49476283830066\n ],\n [\n -157.8172763273639,\n 21.53152880555119\n ],\n [\n -157.97415529522343,\n 21.740805505081653\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Moskvichev, Richelle","contributorId":357155,"corporation":false,"usgs":false,"family":"Moskvichev","given":"Richelle","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikkelsen, Anna","contributorId":357158,"corporation":false,"usgs":false,"family":"Mikkelsen","given":"Anna","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Tiffany","contributorId":357161,"corporation":false,"usgs":false,"family":"Anderson","given":"Tiffany","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joel Nicolow","contributorId":357164,"corporation":false,"usgs":false,"family":"Joel Nicolow","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fletcher, Charles","contributorId":357167,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940773,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265535,"text":"70265535 - 2025 - A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model","interactions":[{"subject":{"id":70265535,"text":"70265535 - 2025 - A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model","indexId":"70265535","publicationYear":"2025","noYear":false,"title":"A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model"},"predicate":"SUPERSEDED_BY","object":{"id":70272242,"text":"70272242 - 2025 - Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model","indexId":"70272242","publicationYear":"2025","noYear":false,"title":"Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model"},"id":1}],"supersededBy":{"id":70272242,"text":"70272242 - 2025 - Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model","indexId":"70272242","publicationYear":"2025","noYear":false,"title":"Technical note: A low-cost approach to monitoring relative streamflow dynamics in small headwater streams using time lapse imagery and a deep learning model"},"lastModifiedDate":"2025-11-24T17:09:06.905617","indexId":"70265535","displayToPublicDate":"2025-03-28T08:41:30","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":20900,"text":"EGUSphere","active":true,"publicationSubtype":{"id":32}},"title":"A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model","docAbstract":"Despite their ubiquity and importance as freshwater habitat, small headwater streams are under monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position. A person then annotates pairs of images, in each case indicating which image has more apparent streamflow or indicating equal flow if no difference is discernible. A deep learning modelling framework called Streamflow Rank Estimation (SRE) is then trained on the annotated image pairs and applied to rank all images from highest to lowest apparent streamflow. From this result a relative hydrograph can be derived. We found that our modelled relative hydrograph dynamics matched the observed hydrograph dynamics well for 11 cameras at 8 streamflow sites in western Massachusetts. Higher performance was observed during the annotation period (median Kendall’s Tau rank correlation 0.75 with range 0.6–0.83) than after it (median Kendall’s Tau 0.59 with range 0.34 – 0.74). We found that annotation performance was generally consistent across the eleven camera sites and two individual annotators and was positively correlated with streamflow variability at a site. A scaling simulation determined that model performance improvements were limited after 1,000 annotation pairs. Our model’s estimates of relative flow, while not equivalent to absolute flow, may still be useful for many applications, such as ecological modelling and calculating event-based hydrological statistics (e.g., the number of out-of-bank floods). We anticipate this method will be a valuable tool to extend existing stream monitoring networks and provide new insights on dynamic headwater systems.
","language":"English","publisher":"EGUSphere","doi":"10.5194/egusphere-2025-1186","usgsCitation":"Goodling, P.J., Fair, J.H., Gupta, A., Walker, J.D., Dubreuil, T., Hayden, M.J., and Letcher, B., 2025, A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model: EGUSphere, preprint posted March 28, 2025, https://doi.org/10.5194/egusphere-2025-1186.","productDescription":"26 p.","ipdsId":"IP-171724","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488204,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/egusphere-2025-1186","text":"Publisher Index Page"},{"id":484489,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fair, Jennifer H. 0000-0002-9902-1893","orcid":"https://orcid.org/0000-0002-9902-1893","contributorId":245941,"corporation":false,"usgs":true,"family":"Fair","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gupta, Amrita 0000-0003-2643-5865","orcid":"https://orcid.org/0000-0003-2643-5865","contributorId":264600,"corporation":false,"usgs":false,"family":"Gupta","given":"Amrita","email":"","affiliations":[{"id":54512,"text":"Georgia Institute of Techniology","active":true,"usgs":false}],"preferred":false,"id":932972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walker, Jeffrey D. 0000-0003-1923-6550","orcid":"https://orcid.org/0000-0003-1923-6550","contributorId":244114,"corporation":false,"usgs":false,"family":"Walker","given":"Jeffrey","middleInitial":"D.","affiliations":[{"id":48839,"text":"Walker Environmental Research LLC","active":true,"usgs":false}],"preferred":false,"id":932973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubreuil, Todd 0000-0003-0189-4336","orcid":"https://orcid.org/0000-0003-0189-4336","contributorId":217872,"corporation":false,"usgs":true,"family":"Dubreuil","given":"Todd","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932974,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayden, Michael J. 0000-0002-9010-6831","orcid":"https://orcid.org/0000-0002-9010-6831","contributorId":291388,"corporation":false,"usgs":true,"family":"Hayden","given":"Michael","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":932975,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":932976,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266766,"text":"70266766 - 2025 - Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams","interactions":[],"lastModifiedDate":"2025-05-29T13:10:29.985307","indexId":"70266766","displayToPublicDate":"2025-03-28T07:46:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams","docAbstract":"Microplastics, per- and polyfluoroalkyl substances (PFAS), antibiotic resistance genes (ARGs), pharmaceuticals and personal care products (PPCPs), and pesticides may lead to unintended environmental contamination through many pathways in multiple matrices. This statewide, multi-matrix study of contaminants of global concern (CGCs) in agricultural streams across Iowa (United States) is the first to examine multiple CGCs in water, bed sediment, and fish to understand their occurrence in small streams located in regions of intense agriculture activity. Iowa plays a pivotal role in agriculture, with more than 85% of Iowa’s landscape devoted to agriculture making it an ideal location for determining the prevalence of CGCs to provide critical baseline exposure data. Fifteen sites were sampled across a range of predominant land uses (e.g., poultry, swine); all sites had detections of microplastics in all matrices. Concentrations of PFAS varied but were detected in water and sediment; all fish had detections of perfluorooctanesulfonate (PFOS), a type of PFAS. More than 50% of water and bed sediment samples had detections of ARGs. The most frequently detected PPCP was metformin. No sites had a cumulative exposure activity ratio greater than 1.0 for chemical exposures; 13 sites were above the 0.001 precautionary threshold. Toxicity quotients calculated using Aquatic Life Benchmarks were below the 0.1 moderate risk threshold for chemical exposures for all but one site. For fish, all sites exceeded the moderate and high-risk thresholds proposed for microplastic particles for food dilution (both chronic and acute exposures) and all sites exceeded the microplastic moderate threshold proposed for chronic tissue translocation, and two sites exceeded the threshold for acute tissue translocation.","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D4EM00753K","usgsCitation":"Meppelink, S.M., Kolpin, D., LeFevre, G., Cwiertny, D., Givens, C.E., Green, L., Hubbard, L.E., Iwanowicz, L.R., Lane, R.F., Mianecki, A., O’Shea, P.S., Raines, C.D., Scott, J., Thompson, D., Wilson, M.C., and Gray, J.L., 2025, Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams: Environmental Science: Processes & Impacts, v. 27, p. 1401-1422, https://doi.org/10.1039/D4EM00753K.","productDescription":"22 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0000-0003-1568-4073","orcid":"https://orcid.org/0000-0003-1568-4073","contributorId":353174,"corporation":false,"usgs":false,"family":"Scott","given":"John W.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":936726,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thompson, Darrin A. 0000-0002-6398-1067","orcid":"https://orcid.org/0000-0002-6398-1067","contributorId":353177,"corporation":false,"usgs":false,"family":"Thompson","given":"Darrin A.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":936727,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wilson, Michaelah C. 0000-0001-7052-9506","orcid":"https://orcid.org/0000-0001-7052-9506","contributorId":229469,"corporation":false,"usgs":true,"family":"Wilson","given":"Michaelah","email":"","middleInitial":"C.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":936728,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":205658,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":936729,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70264905,"text":"fs20253012 - 2025 - A partnership between the USGS and the Klamath Tribes to apply structured decision making for chronic wasting disease management","interactions":[],"lastModifiedDate":"2025-08-07T20:25:45.598265","indexId":"fs20253012","displayToPublicDate":"2025-03-27T14:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3012","displayTitle":"A Partnership Between the USGS and the Klamath Tribes to Apply Structured Decision Making for Chronic Wasting Disease Management","title":"A partnership between the USGS and the Klamath Tribes to apply structured decision making for chronic wasting disease management","docAbstract":"Project Overview: The Klamath Tribes (TKT) are the Klamath, Modoc, and Yahooskin Paiute peoples, and are the first peoples of the land, having lived in ancestral lands of Oregon and California since time immemorial. Members of TKT have rights to hunt, fish, trap, and gather, including the harvest of mule deer (Odocoileus hemionus) and elk (Cervus canadensis nelsoni) within the 1.19 million acres of their Reserved Treaty Rights Area.
Anthropogenic changes threaten the well-being of mule deer and elk and of the Tribes that rely on them. Today, these species are a primary protein source for TKT. They are traded within TKT and among other Tribes and provide materials for cultural and sacred items such as regalia. However, mule deer numbers have been declining across the western states for the past several decades because of multiple stressors, including persistent and frequent drought and wildfires, habitat loss and degradation, vehicle mortality, and increasing barriers to migratory movements between summer and winter ranges. The migratory movements of mule deer, which allow deer to access the best available seasonal habitats, put them at risk of another potential stressor—infection with chronic wasting disease (CWD). Chronic wasting disease is a fatal prion disease of deer that has been detected in 36 U.S. states. It was detected in free-ranging mule deer in northern Idaho in 2021, prompting the Tribes to initiate a planning process for CWD surveillance, prevention, and response measures to preserve and protect the deer and elk within the Reserved Treaty Rights Area.
In 2023, the Klamath Tribes Natural Resources Department began to develop their CWD plan by incorporating preliminary input provided by the Klamath Indian Game Commission (KIGC) and working with scientists from the U.S. Geological Survey (USGS). This collaborative effort includes the application of structured decision making and the development of mathematical models to analyze potential CWD management strategies. The result will be a transparent assessment that incorporates TKT values throughout the process and can inform place-based management of the cultural, natural, and physical resources upon which the Tribes depend. In addition, this process may provide opportunities for broader coordination by natural resource management agencies to work together to ensure the long-term health and sustainability of deer and elk populations within the Reserved Treaty Rights Area and throughout the state of Oregon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253012","collaboration":"Prepared in Cooperation with the Klamath Tribes Natural Resources Department","usgsCitation":"McEachran, M.C., Guntly-Yancey, K.M., Berl, R.E.W., Gentry, D., Runge, M.C., White, C., and Cook, J.D., 2025, A partnership between the USGS and the Klamath Tribes to apply structured decision making for chronic wasting disease management: U.S. Geological Survey Fact Sheet 2025–3012, 4 p., https://doi.org/10.3133/fs20253012.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-169589","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":493738,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118503.htm","linkFileType":{"id":5,"text":"html"}},{"id":483890,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3012/fs20253012.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3012 XML"},{"id":483888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3012/fs20253012.pdf","text":"Report","size":"12.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3012 PDF"},{"id":483891,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3012/images/"},{"id":483887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3012/coverthb.jpg"},{"id":483889,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253012/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3012 HTML"}],"country":"United States","state":"Oregon","otherGeospatial":"Klamath Tribes reserved treaty rights area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.27104164386708,\n 43.25\n ],\n [\n -122.27104164386708,\n 42\n ],\n [\n -120.75,\n 42\n ],\n [\n -120.75,\n 43.25\n ],\n [\n -122.27104164386708,\n 43.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Eastern Ecological Science Center
U.S. Geological Survey
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Total phosphorus (TP) concentrations and loads in the Boise River near Parma, Idaho, were examined to identify changes by month over a 19-year period from water year 2003 through water year 2021 and to evaluate the performance of three common water-quality models. Mean annual TP concentrations and loads were estimated to have reduced by approximately 60 percent over the study period. Mean annual TP concentrations were reduced from 0.42 milligrams per liter in 2003 to 0.18 milligrams per liter in 2021. Mean annual TP loads were reduced from 816 kilograms per day in 2003 to 302 kilograms per day in 2021. Mean annual concentrations and loads reduced by approximately 3 percent per year with the largest changes occurring in the non-irrigation season of October through April. The TP load remained highest in May across the model period while peak concentration shifted from January to March.
High-frequency TP data collected with an automated sampler every 49 hours enabled detailed model performance evaluation of the Load Estimator (LOADEST), Weighted Regressions on Time, Discharge, and Season (WRTDS), and WRTDS method with Kalman filtering (WRTDS_K) water-quality models generated with near-monthly data. All three models were generally able to reproduce the observed concentrations, with the largest errors occurring in the spring when observed concentrations were most variable. Annual TP loads varied by up to 27 percent, or approximately 128,000 kilograms, between the three models calibrated on monthly data. In this system with highly variable concentrations, we note that performance metrics for WRTDS_K based on monthly calibration data masked serious errors that were only revealed by comparing results against higher frequency (49-hour) autosampler data. This emphasizes the value of high frequency validation data to quantify uncertainty in water-quality models when applied to systems where concentrations change rapidly. Lastly, we identify that hydraulic routing may be a valuable addition to discharge, season, and time in water-quality modeling for systems with significant human intervention in natural hydro-biogeochemical processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245110","collaboration":"Prepared in cooperation with the City of Boise","programNote":"National Water Quality Program","usgsCitation":"King, T.V., and Yoder, A.M., 2025, A trend analysis and model comparison of total phosphorus concentrations and loads in the Boise River near Parma, southwestern Idaho, water years 2003–21: U.S. Geological Survey Scientific Investigations Report 2024–5110, 41 p., https://doi.org/10.3133/sir20245110.","productDescription":"Report: vi, 41p.; Data Release","onlineOnly":"Y","ipdsId":"IP-140444","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":493739,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118504.htm","linkFileType":{"id":5,"text":"html"}},{"id":483669,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5110/sir20245110.XML"},{"id":483668,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5110/images"},{"id":483667,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98DMTAN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality modeling results of total phosphorus for the lower Boise River near Parma, Idaho 2002 - 2021"},{"id":483666,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245110/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5110"},{"id":483665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5110/sir20245110.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5110"},{"id":483664,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5110/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Parma","otherGeospatial":"Boise River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.25,\n 44\n ],\n [\n -117.25,\n 43\n ],\n [\n -115.75,\n 43\n ],\n [\n -115.75,\n 44\n ],\n [\n -117.25,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4250
This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-4 (LISS–4) sensor. It is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resouresat-2 and 2A carry the Advanced Wide Field Sensor, Linear Imaging Self Scanning-3, and LISS–4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about the Indian Space Research Organisation’s satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium at https://calval.cr.usgs.gov/apps/compendium/ and from the manufacturer at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performances of the Resourcesat-2A LISS–4 sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had mean offsets in the range of −0.118 to 0.024 pixel in easting and −0.053 to 0.022 pixel in northing with root mean square error values from 0.067 to 0.230 pixel in easting and from 0.087 to 0.2 pixel in northing. The exterior geometric performance had offsets in the range of 2.55 to 7.85 meters (m) in easting and −6.15 to 11.15 m in northing with root mean square error values in the range of 2.6 to 8.2 m in easting and 6.35 to 11.8 m in northing compared to the U.S. Department of Agriculture National Agriculture Imagery Program and WorldView-3 orthoimages. The measured radiometric performance had offsets from 0.003 to 0.024 and slopes from 0.736 to 0.952, and spatial performance was in the range of 1.633 to 1.903 pixels for the full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.0529 to 0.0952.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030U","usgsCitation":"Shrestha, M., Sampath, A., Kim, M., Park, S., and Clauson, J., 2025, System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor, chap. U of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 16 p., https://doi.org/10.3133/ofr20211030U.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170098","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":483933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/u/coverthb.jpg"},{"id":483934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/u/ofr20211030u.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-U"},{"id":483935,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/u/ofr20211030u.XML"},{"id":483936,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/u/images/"},{"id":483938,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030U/full"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The Atlantic Sturgeon Acipenser oxyrinchus is a wide-ranging, long-lived diadromous fish that is endangered in most of its range. Our objective was to develop and apply long-term, detection-corrected indices of relative abundance for juvenile and adult Atlantic Sturgeon in the Hudson River, New York, United States, to support population monitoring and stock assessment.
We used long-term gill-net catches to estimate relative abundances of juvenile and adult Atlantic Sturgeon while accounting for imperfect detection within an N-mixture modeling framework. We validated the model framework using a simulation–estimation framework based on mean parameter estimates from the adult Atlantic Sturgeon relative abundance index.
Simulation testing indicated that absolute abundance estimates may be biased low due to poor characterization of detection probabilities. However, model estimates of relative abundance tracked simulated abundance trends well. Juvenile relative abundance estimates followed similar trends as raw gill-net catches but were less variable among years when corrected for detection probability. Relative abundance of juveniles increased from 2004 to 2015 prior to declining through 2022, with little evidence for change between the start and end of the survey. Detection-corrected indices for adult sturgeon indicated a consistent increase in relative abundance that was not readily apparent in raw catch indices.
Detection-corrected catch indices can provide improved characterization of Atlantic Sturgeon relative abundance dynamics over raw gill-net catches through use of N-mixture models. The approach has broad applicability to data types that are commonly collected for understanding population trends in stock assessment. Estimation of absolute abundance and other population demographics germane to management would benefit from alternative or auxiliary data collected through approaches such as side-scan sonar or acoustic telemetry, which are increasingly common for monitoring sturgeon populations.
Critical minerals are commodities essential to modern industrial and strategic technologies and are highly vulnerable to supply chain disruption. The Critical Minerals Mapping Initiative (CMMI) is a collaboration among the U.S. Geological Survey (USGS), the Geological Survey of Canada, and Geoscience Australia that aims to deepen global understanding of where critical minerals are located. A key output of this initiative is the Critical Minerals in Ores (CMiO) database that is advancing our collective understanding of critical minerals distributions. For instance, publicly available data on the concentrations of many critical minerals are sparse because these commodities can only be produced in small, yet essential, quantities compared to the primary commodities like copper and zinc. The CMiO database helps bridge this gap by offering high-quality, multielement geochemical data from a wide variety of critical mineral-bearing deposits around the world. Importantly, it uses a novel consensus deposit environment, group, and type classification scheme developed by the agencies that allows comparisons among ore deposits from different regions. The CMiO database contains geochemical data for more than 20,000 samples from more than 100 deposit types comprising 10 deposit environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253002","collaboration":"Prepared in collaboration with the Geological Survey of Canada and Geoscience Australia","programNote":"Mineral Resources Program","usgsCitation":"Case, G.N.D., Graham, G.E., Lawley, C.J.M., Bastrakov, E., Huston, D.L., Hofstra, A.H., Lisitsin, V., Hawkins, S.G., and Wang, B., 2025, Critical Minerals in Ores (CMiO) database (ver. 1.2, May 2025): U.S. Geological Survey Fact Sheet 2025–3002, 2 p., https://doi.org/10.3133/fs20253002.","productDescription":"Report: 2 p.; Dataset","onlineOnly":"N","ipdsId":"IP-172113","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":493736,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118563.htm","text":"Version 1.1","linkFileType":{"id":5,"text":"html"}},{"id":485219,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2025/3002/versionHist.txt","size":"4.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2025-3002 version history"},{"id":483999,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3002"},{"id":483900,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.xml"},{"id":483899,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3002/images"},{"id":483682,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pid.geoscience.gov.au/dataset/ga/145496","text":"Critical Minerals in Ores - geochemistry database"},{"id":483671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.pdf","text":"Report","size":"5.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3002"},{"id":483670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3002/coverthb3.jpg"},{"id":498997,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118502.htm","text":"Version 1.0","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0: March 26, 2025; Version 1.1: April 30, 2025; Version 1.2: May 22, 2025","contact":"Program Coordinator, Mineral Resources Program
U.S. Geological Survey
913 National Center
Reston, VA 20192
A previous study evaluating restoration success of Paddlefish Polyodon spathula suggested that excessive turbidity in lakes and rivers may inhibit foraging by juveniles prior to the development of the rostrum. Although a Paddlefish's rostrum, which contains electroreceptors, helps the fish to locate zooplankton prey, the prerostrum stage lacks many of these electroreceptors, potentially affecting foraging in highly turbid waters. To evaluate this hypothesis, we conducted a series of laboratory experiments in small aquaria by varying the level of turbidity measured as Secchi tube depth: >95 (clear tap water), 40, 20, 10, or 5 cm.
For each foraging trial, approximately 300 zooplankton were added to the aquaria, followed by three postlarval Paddlefish, which were allowed to feed on the zooplankton for approximately 18 h. After the 18-h period, Paddlefish were removed and dissected and the zooplankton in the gut were counted to quantify foraging success.
From three experimental trials, we observed statistically significant nonlinear relationships for two trials, which included the largest fish tested. The smallest Paddlefish size-class showed no significant trend in foraging among turbidity treatments. However, the subsequent trials, which contained larger Paddlefish, both showed unimodal responses, with the highest foraging observed at moderate (30–50-cm Secchi tube depth) turbidity levels.
High turbidity and excessively clear water both appear to affect foraging by juvenile Paddlefish before the rostrum is fully developed, depending on fish size. Understanding this relationship can further influence management and restoration projects directed at this species.
Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse (Centrocercus urophasianus) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70022","usgsCitation":"Wann, G.T., Whipple, A.L., Orning, E.K., McLachlan, M.M., Beck, J.L., Coates, P., Conway, C.J., Dinkins, J.B., Johnston, A.N., Hagen, C., Makela, P., Naugle, D., Schroeder, M.A., Sedinger, J.S., Walker, B.L., Williams, P.J., Inman, R.D., and Aldridge, C.L., 2025, Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications: Journal of Wildlife Management, v. 89, no. 5, e70022, 33 p., https://doi.org/10.1002/jwmg.70022.","productDescription":"e70022, 33 p.","ipdsId":"IP-154951","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488629,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70022","text":"Publisher Index Page"},{"id":484325,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.85259667955762,\n 49.62627448300293\n ],\n [\n -123.85259667955762,\n 33.76025294128375\n ],\n [\n -104.85728560371575,\n 33.76025294128375\n ],\n [\n -104.85728560371575,\n 49.62627448300293\n ],\n [\n -123.85259667955762,\n 49.62627448300293\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 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Refuge","active":true,"usgs":false}],"preferred":false,"id":932845,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":932846,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":932847,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70268950,"text":"70268950 - 2025 - Social composition of soft‐release groups is correlated with survival of translocated gopher tortoises","interactions":[],"lastModifiedDate":"2025-07-11T15:08:06.152682","indexId":"70268950","displayToPublicDate":"2025-03-26T08:03:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16872,"text":"The Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Social composition of soft‐release groups is correlated with survival of translocated gopher tortoises","docAbstract":"The social structure of translocated animal populations can have important effects on the survival and reproduction of translocated individuals for both solitary and social species. The gopher tortoise (Gopherus polyphemus) is a reptile of conservation concern that is currently experiencing high levels of mitigation translocation in Florida, USA. Individuals live in aggregations of burrows with frequent agonistic, courtship, and burrow-sharing interactions between residents. Given that exposure to many unfamiliar individuals may increase the frequency of aggressive interactions and social stress following translocation, we predicted that tortoises with greater numbers of familiar individuals co-translocated from the same origin site would have higher survival after translocation. To test this, we updated a recently published survival analysis of 2,822 translocated tortoises and 502 identified carcasses from a translocation site in the western Florida panhandle from 2006–2022. After controlling for simultaneous effects of soft-release enclosure identity, release season, release density, region of origin, sex, and size, adding the number of potentially familiar individuals improved model fit and showed increasing the number of familiars reduced the probability of being found dead. This effect was modulated by release density, being apparent only when density was high, suggesting a role for social interactions. This effect was also present only in the first few years after release, prior to the removal of soft-release enclosures preventing dispersal, and was similar in magnitude to previously identified effects of density, release season, and region of origin. We suggest that this effect may result from reduced aggressive interactions or social stress for tortoises with a greater number of familiar individuals in their release enclosures but cannot rule out the possibility of reduced novel pathogen exposure for individuals released with a greater number of individuals from the same source site or other factors that may be confounded with the size of translocated groups. Designing and implementing mitigation translocations to account for social composition of gopher tortoise groups could improve survival in release enclosures.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70020","usgsCitation":"Loope, K., Cozad, R., Breakfield, D., Aresco, M., and Hunter, E.A., 2025, Social composition of soft‐release groups is correlated with survival of translocated gopher tortoises: The Journal of Wildlife Management, v. 89, no. 5, e70020, 14 p., https://doi.org/10.1002/jwmg.70020.","productDescription":"e70020, 14 p.","ipdsId":"IP-169542","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":492475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70020","text":"Publisher Index Page"},{"id":492133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.75224246079063,\n 30.992257366593762\n ],\n [\n -87.75224246079063,\n 29.82890590815998\n ],\n [\n -84.30370034537961,\n 29.82890590815998\n ],\n [\n -84.30370034537961,\n 30.992257366593762\n ],\n [\n -87.75224246079063,\n 30.992257366593762\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Loope, Kevin J.","contributorId":357851,"corporation":false,"usgs":false,"family":"Loope","given":"Kevin J.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":942703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cozad, Rebecca A.","contributorId":357853,"corporation":false,"usgs":false,"family":"Cozad","given":"Rebecca A.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":942704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breakfield, Derek. B.","contributorId":357855,"corporation":false,"usgs":false,"family":"Breakfield","given":"Derek. B.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":942705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aresco, Matthew J.","contributorId":357857,"corporation":false,"usgs":false,"family":"Aresco","given":"Matthew J.","affiliations":[{"id":81935,"text":"Nokuse","active":true,"usgs":false}],"preferred":false,"id":942706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":942707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266844,"text":"70266844 - 2025 - Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands","interactions":[],"lastModifiedDate":"2025-05-13T15:09:17.143776","indexId":"70266844","displayToPublicDate":"2025-03-26T07:59:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands","docAbstract":"1. Decomposition controls the release of carbon and nutrients from decaying plant litter into soils or the atmosphere. In most biomes decomposition rates can be accurately predicted with simple mathematical models, but these models have long under-predicted decomposition in globally- extensive drylands.
2. We posit that the exposed surface conditions characteristic of drylands makes litter decomposition uniquely subject to microsite-specific environmental controls and spatially-variable microbial communities. As such, decomposition in dryland ecosystems – which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability – is a prime example of a macrosystems process that can be addressed by merging field data with new predictive models operating across a hierarchical continuum of spatial scales and process resolutions.
3. A macrosystems approach offers promise to reconcile model-measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g., shrub sub-canopy or intercanopy) to regions (e.g., across a 100s of km2 study site with complex topography, precipitation, and temperature) and ultimately to a continental perspective (e.g., North American drylands).
4. Recent developments in technology and data availability position the scientific community to integrate lab, field, modeling, and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro-to-macroscale. This multi-scale approach promises a path forward to resolving a longstanding disconnect between measured and modeled data in dryland litter decomposition.
5. Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach.
6. We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2435.70029","usgsCitation":"Throop, H.L., Li, J., Moorhead, D., Reed, S., Todd-Brown, K., Besser, A., Bloom, D., Ingalls, T., and Cueva, A., 2025, Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands: Functional Ecology, 11 p., https://doi.org/10.1111/1365-2435.70029.","productDescription":"11 p.","ipdsId":"IP-176124","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488192,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.70029","text":"Publisher Index Page"},{"id":485815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":936890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Jiwei","contributorId":355122,"corporation":false,"usgs":false,"family":"Li","given":"Jiwei","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moorhead, Daryl L.","contributorId":355123,"corporation":false,"usgs":false,"family":"Moorhead","given":"Daryl L.","affiliations":[{"id":84710,"text":"Toledo University, Biology Department, Toledo, OH USA","active":true,"usgs":false}],"preferred":false,"id":936892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":936893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Todd-Brown, Katherine","contributorId":197914,"corporation":false,"usgs":false,"family":"Todd-Brown","given":"Katherine","affiliations":[],"preferred":false,"id":936894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Besser, Alexi","contributorId":355124,"corporation":false,"usgs":false,"family":"Besser","given":"Alexi","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bloom, Dellena","contributorId":355125,"corporation":false,"usgs":false,"family":"Bloom","given":"Dellena","affiliations":[{"id":84713,"text":"University of Florida, Engineering School of Sustainable Infrastructure and Environment, Gainesville, FL USA","active":true,"usgs":false}],"preferred":false,"id":936896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ingalls, Thomas","contributorId":355126,"corporation":false,"usgs":false,"family":"Ingalls","given":"Thomas","affiliations":[{"id":84709,"text":"Arizona State University, Earth and Space Sciences, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":936897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cueva, Alejandro","contributorId":355127,"corporation":false,"usgs":false,"family":"Cueva","given":"Alejandro","affiliations":[{"id":84714,"text":"El Colegio de la Frontera Sur, Departemento de Ecosistema Ecologico, San Cristobal, Mexico","active":true,"usgs":false}],"preferred":false,"id":936898,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70264861,"text":"70264861 - 2025 - Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction","interactions":[],"lastModifiedDate":"2025-05-28T14:53:12.678207","indexId":"70264861","displayToPublicDate":"2025-03-25T10:05:14","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction","docAbstract":"The Sangre de Cristo Range in southern Colorado exposes some of the deepest Cenozoic structural levels in the Rocky Mountain region, including mylonitic shear zones associated with both the Laramide orogeny and Rio Grande rift. We investigated the relation between Laramide contraction and Rio Grande rift extension with detailed geologic mapping, kinematic analysis, and geochronometry in a 50 km2 area centered on the Independence Mine shear zone (IMSZ). The 15−100-m-thick IMSZ is one of several shallowly to moderately (∼45° ± 20°) W-SW−dipping brittle-plastic shear zones along the western flank of the range. These shear zones display microstructural evidence of initiation as top-NE contractional mylonite zones, consistent with regional Laramide kinematics, which have been pervasively overprinted by shear fabrics indicating top-SW extensional reactivation. Both top-NE and top-SW shear fabrics involve cataclasis and quartz dislocation creep, although top-SW shear is more commonly localized along phyllosilicate-lined shear bands. Shear zones are hosted predominately within Proterozoic gneiss, and contain abundant chlorite and white mica derived from alteration of hornblende and feldspar, which indicates that weakening driven by fluid reactions played an important role in localizing strain. Extensional overprinting appears to be most pervasive along more steeply dipping portions of shear zones and where secondary phyllosilicates form an interconnected weak phase, which suggests that reactivation was primarily controlled by geometry and rheological contrasts inherited from contraction. One top-SW shear zone adjacent to the IMSZ cuts a late Oligocene gabbro stock, and monazite grains synkinematic with top-SW shear in the IMSZ yielded late Oligocene to Early Miocene U-Th-Pb dates that correspond with initiation of the Rio Grande rift. Reactivation of weak reverse faults may represent an important structural control during initial extension in the middle crust, prior to slip along the high-angle Sangre de Cristo normal fault system.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02772.1","usgsCitation":"Sitar, M., Singleton, J.S., Rahl, J., Caine, J., King, J., Kylander-Clark, A.R., and O’Sullivan, P., 2025, Structural analysis of brittle-plastic shear zones in the Sangre de Cristo Range, southern Colorado USA: Superposition of Rio Grande rift extension on Laramide contraction: Geosphere, v. 21, no. 3, p. 446-469, https://doi.org/10.1130/GES02772.1.","productDescription":"24 p.","startPage":"446","endPage":"469","ipdsId":"IP-163394","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488514,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02772.1","text":"Publisher Index Page"},{"id":483877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Sangre de Christo Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 38.125\n ],\n [\n -105.75,\n 37.5\n ],\n [\n -105.25,\n 37.5\n ],\n [\n -105.25,\n 38.125\n ],\n [\n -105.75,\n 38.125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Sitar, Michael C. 0000-0003-0688-1067","orcid":"https://orcid.org/0000-0003-0688-1067","contributorId":352709,"corporation":false,"usgs":false,"family":"Sitar","given":"Michael C.","affiliations":[{"id":48080,"text":"Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":932081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Singleton, John S. 0000-0001-9399-7732","orcid":"https://orcid.org/0000-0001-9399-7732","contributorId":306242,"corporation":false,"usgs":false,"family":"Singleton","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":932082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rahl, Jeffrey M. 0000-0002-9195-8294","orcid":"https://orcid.org/0000-0002-9195-8294","contributorId":352710,"corporation":false,"usgs":false,"family":"Rahl","given":"Jeffrey M.","affiliations":[{"id":37754,"text":"Washington and Lee University, Lexington, VA","active":true,"usgs":false}],"preferred":false,"id":932083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":932084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Jacob","contributorId":352711,"corporation":false,"usgs":false,"family":"King","given":"Jacob","affiliations":[{"id":48080,"text":"Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":932085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kylander-Clark, Andrew R C","contributorId":269776,"corporation":false,"usgs":false,"family":"Kylander-Clark","given":"Andrew","email":"","middleInitial":"R C","affiliations":[{"id":27356,"text":"UC-Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":932086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Sullivan, Paul","contributorId":352712,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","affiliations":[{"id":84291,"text":"GeoSep Services, Moscow, ID","active":true,"usgs":false}],"preferred":false,"id":932087,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268343,"text":"70268343 - 2025 - C4 photosynthesis, trait spectra, and the fast-efficient phenotype","interactions":[],"lastModifiedDate":"2025-06-23T14:52:23.53561","indexId":"70268343","displayToPublicDate":"2025-03-25T09:49:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"C4 photosynthesis, trait spectra, and the fast-efficient phenotype","title":"C4 photosynthesis, trait spectra, and the fast-efficient phenotype","docAbstract":"It has been 60 years since the discovery of C4 photosynthesis, an event that rewrote our understanding of plant adaptation, ecosystem responses to global change, and global food security. Despite six decades of research, one aspect of C4 photosynthesis that remains poorly understood is how the pathway fits into the broader context of adaptive trait spectra, which form our modern view of functional trait ecology. The C4 CO2-concentrating mechanism supports a general C4 plant phenotype capable of fast growth and high resource-use efficiencies. The fast-efficient C4 phenotype has the potential to operate at high productivity rates, while allowing for less biomass allocation to root production and nutrient acquisition, thereby providing opportunities for the evolution of novel trait covariances and the exploitation of new ecological niches. We propose the placement of the C4 fast-efficient phenotype near the acquisitive pole of the world-wide leaf economic spectrum, but with a pathway-specific span of trait space, wherein selection shapes both acquisitive and conservative adaptive strategies. A trait-based perspective of C4 photosynthesis will open new paths to crop improvement, global biogeochemical modeling, the management of invasive species, and the restoration of disturbed ecosystems, particularly in grasslands.
","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.70057","usgsCitation":"Monson, R., Li, S., Ainsworth, E.A., Fan, Y., Hodge, J., Knapp, A.K., Leakey, A., Lombardozzi, D., Reed, S., Sage, R.F., Smith, M.D., Smith, N.G., Still, C.J., and Way, D.A., 2025, C4 photosynthesis, trait spectra, and the fast-efficient phenotype: New Phytologist, v. 246, no. 3, p. 879-893, https://doi.org/10.1111/nph.70057.","productDescription":"15 p.","startPage":"879","endPage":"893","ipdsId":"IP-175808","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":496378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.70057","text":"Publisher Index Page"},{"id":491104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"246","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Monson, Russell K.","contributorId":357242,"corporation":false,"usgs":false,"family":"Monson","given":"Russell K.","affiliations":[{"id":85357,"text":"Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado 80309, USA","active":true,"usgs":false}],"preferred":false,"id":940873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Shuai","contributorId":357243,"corporation":false,"usgs":false,"family":"Li","given":"Shuai","affiliations":[{"id":85358,"text":"Guangdong Provincial Key Lab. of Applied Botany, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, Guangdong, China; Carl R. Woese Institute for Genomic Biology, Uni of Illinois at Urbana-Champaign, Urbana, Illinois, USA","active":true,"usgs":false}],"preferred":false,"id":940874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ainsworth, Elizabeth A.","contributorId":266079,"corporation":false,"usgs":false,"family":"Ainsworth","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":54883,"text":"USDA ARS GCPRU, 1201 W. Gregory Drive, Urbana, IL 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fan, Yuzhen","contributorId":357244,"corporation":false,"usgs":false,"family":"Fan","given":"Yuzhen","affiliations":[{"id":85359,"text":"Division of Plant Sciences, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia","active":true,"usgs":false}],"preferred":false,"id":940876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodge, John G.","contributorId":357245,"corporation":false,"usgs":false,"family":"Hodge","given":"John G.","affiliations":[{"id":85360,"text":"Center for Advanced Bioenergy and Bioproducts Innovation, Urbana, Illinois, 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knapp, Alan K.","contributorId":223624,"corporation":false,"usgs":false,"family":"Knapp","given":"Alan","email":"","middleInitial":"K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leakey, Andrew D.B.","contributorId":266112,"corporation":false,"usgs":false,"family":"Leakey","given":"Andrew D.B.","affiliations":[{"id":54910,"text":"Departments of Plant Biology and Crop Sciences, University of Illinois at Urbana-Champaign, 1206 W Gregory Dr, Urbana, IL 61801, USA","active":true,"usgs":false}],"preferred":false,"id":940879,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lombardozzi, Danica","contributorId":357246,"corporation":false,"usgs":false,"family":"Lombardozzi","given":"Danica","affiliations":[{"id":85361,"text":"Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80521 USA","active":true,"usgs":false}],"preferred":false,"id":940880,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":940881,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sage, Rowan F.","contributorId":296142,"corporation":false,"usgs":false,"family":"Sage","given":"Rowan","email":"","middleInitial":"F.","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":940882,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smith, Melinda D.","contributorId":223621,"corporation":false,"usgs":false,"family":"Smith","given":"Melinda","email":"","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940883,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Nicholas G.","contributorId":266125,"corporation":false,"usgs":false,"family":"Smith","given":"Nicholas","email":"","middleInitial":"G.","affiliations":[{"id":54920,"text":"Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA","active":true,"usgs":false}],"preferred":false,"id":940884,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Still, Christopher J.","contributorId":167581,"corporation":false,"usgs":false,"family":"Still","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":24761,"text":"University of California, Santa Barbara; Oregon State University","active":true,"usgs":false}],"preferred":false,"id":940885,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Way, Danielle A.","contributorId":199465,"corporation":false,"usgs":false,"family":"Way","given":"Danielle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":940886,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70265266,"text":"70265266 - 2025 - No magmatic driving force for Europan sea-floor volcanism","interactions":[],"lastModifiedDate":"2025-05-28T14:55:26.641908","indexId":"70265266","displayToPublicDate":"2025-03-24T15:17:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6448,"text":"Nature Astronomy","active":true,"publicationSubtype":{"id":10}},"title":"No magmatic driving force for Europan sea-floor volcanism","docAbstract":"The internal ocean of Jupiter’s moon Europa is thought to be a prime candidate for hosting extraterrestrial life. Europa’s silicate interior may contribute to habitability via the generation of reactants through hydrothermal activity, serpentinization, or other geological processes occurring on or just below Europa’s seafloor. However, silicate melting is thought to occur at >100 km depth in Europa’s mantle and it is unknown if this magma is able to penetrate and travel through the moon’s likely thick, brittle lithosphere to erupt at the seafloor. Here we combine previous modeling approaches to Europan interior melt generation and lithospheric dyke transport to show that Europan seafloor volcanism is strongly inhibited by its lithosphere. The low stress state of the Europan interior hinders the ability of dykes to penetrate through the lithosphere. Should dykes form, they penetrate <5% of the 200–250 km-thick lithosphere. Low mantle melt fractions (3–5%) drive sluggish pore-space magma flow, leading to dyke influxes 10,000 times lower than that necessary for seafloor eruption. These results strongly suggest that models of Europan habitability reliant on present-day volcanism at its seafloor are implausible.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41550-025-02508-8","usgsCitation":"Green, A., Elder, C., Bland, M., Tackley, P., and Byrne, P., 2025, No magmatic driving force for Europan sea-floor volcanism: Nature Astronomy, v. 9, p. 640-649, https://doi.org/10.1038/s41550-025-02508-8.","productDescription":"10 p.","startPage":"640","endPage":"649","ipdsId":"IP-163125","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":484178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europa","volume":"9","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Green, A.P.","contributorId":352969,"corporation":false,"usgs":false,"family":"Green","given":"A.P.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":331017,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":932627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bland, Michael Thomas 0000-0001-5543-1519","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":352963,"corporation":false,"usgs":true,"family":"Bland","given":"Michael Thomas","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":932628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tackley, Paul","contributorId":352966,"corporation":false,"usgs":false,"family":"Tackley","given":"Paul","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":932629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Byrne, Paul K.","contributorId":237950,"corporation":false,"usgs":false,"family":"Byrne","given":"Paul K.","affiliations":[{"id":47656,"text":"Planetary Research Group, Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":932630,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265967,"text":"70265967 - 2025 - Assessing earthquake risks to lifeline infrastructure systems in the United States","interactions":[],"lastModifiedDate":"2025-04-22T16:01:31.164657","indexId":"70265967","displayToPublicDate":"2025-03-24T10:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21204,"text":"International Journal of Critical Infrastructure Protection","active":true,"publicationSubtype":{"id":10}},"title":"Assessing earthquake risks to lifeline infrastructure systems in the United States","docAbstract":"The security and economic stability of the United States rely heavily on robust lifeline infrastructure systems and yet the risks to such systems are seldom quantified at the national scale. For example, while earthquake risks to buildings in the United States have been investigated at the national scale regularly, such risks to gas pipelines have rarely been investigated nationally. In this paper, we use examples from two critical infrastructure sectors to demonstrate (1) the nature of earthquake risks to lifeline infrastructure systems, (2) complexities involved in regional seismic risk assessments, and (3) how such risks change with time. We found that bridge risks can be underestimated by at least 64 % when viewed from repair costs instead of traffic demands and that regional risks can be underestimated by 19 % when spatial correlations of ground motion are ignored. Further, exceedance of traffic demand can be 50 times more likely to occur when viewed at the regional scale than when viewed at an individual bridge. Similarly, exceedance of repairs can be 180 times more likely to occur when viewed at the pipeline network level than at a segment-specific level. Finally, sensitivity analyses with the 2018 and 2023 USGS National Seismic Hazard Models indicate an increase in bridge risk of at least 24 % and an increase in exposed gas pipeline mileage of 43 %. The evolution of risks, complexities involved in assessments, and limited resources jointly underscore the need for more routine updates to nationwide seismic risk assessments of lifeline systems in the United States.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijcip.2025.100758","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2025, Assessing earthquake risks to lifeline infrastructure systems in the United States: International Journal of Critical Infrastructure Protection, v. 49, 100758, https://doi.org/10.1016/j.ijcip.2025.100758.","productDescription":"100758","ipdsId":"IP-170667","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":484841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934186,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70266111,"text":"70266111 - 2025 - The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","interactions":[],"lastModifiedDate":"2025-04-25T15:31:50.116638","indexId":"70266111","displayToPublicDate":"2025-03-24T10:29:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21214,"text":"Peer Community Journal","active":true,"publicationSubtype":{"id":10}},"title":"The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","docAbstract":"Survival is a key life history parameter that can inform management decisions and basic life history research. Because true survival is often confounded with emigration from the study area, many studies are forced to estimate apparent survival (i.e., probability of surviving and remaining inside the study area), which can be much lower than true survival for highly mobile species. One method for estimating true survival is the Barker joint live-recapture/live-resight (JLRLR) model, which combines capture data from a study area (hereafter the ‘capture site’) with resighting data from a broader geographic area. This model assumes that live resights occur throughout the entire area where animals can disperse to and this assumption is often not met in practice. Here we use simulation to evaluate survival bias from a JLRLR model under study design scenarios that differ in the site selection for resights: global, random, fixed including the capture site, and fixed excluding the capture site. Simulation results indicate that fixed designs that included the capture site showed negative survival bias, whereas fixed designs that excluded the capture site exhibited positive survival bias. The magnitude of the bias was dependent on movement and survival, where scenarios with high survival and frequent movement had minimal bias. In an effort to help minimize bias, we developed a multistate version of the JLRLR and demonstrated reductions in survival bias compared to the single-state version for most designs. Our results suggest minimizing bias can be accomplished by: 1) using a random resight design when feasible if global sampling is not possible, 2) using the multistate JLRLR model when appropriate, 3) including the capture site in the resight sampling frame when possible, and 4) reporting survival as apparent survival if fixed sites are used for resight with the single state JLRLR model.
","language":"English","publisher":"PeerJ","doi":"10.24072/pcjournal.533","usgsCitation":"Dzul, M.C., Yackulic, C., and Kendall, W.L., 2025, The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models: Peer Community Journal, v. 5, e34, 24 p., https://doi.org/10.24072/pcjournal.533.","productDescription":"e34, 24 p.","ipdsId":"IP-158705","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":487775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24072/pcjournal.533","text":"Publisher Index Page"},{"id":485061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265015,"text":"70265015 - 2025 - Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","interactions":[],"lastModifiedDate":"2025-04-28T15:14:09.946352","indexId":"70265015","displayToPublicDate":"2025-03-24T09:11:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","title":"Bayesian calibration of the 40K decay scheme with implications for 40K-based geochronology","docAbstract":"The K/Ar and 40Ar/39Ar geochronometers are based on the naturally occurring radionuclide 40K. Their precision and accuracy are limited by uncertainties on the 40K decay constants and, in the case of the 40Ar/39Ar geochronometer, the isotopic composition of neutron fluence monitors. To address these limitations, we introduce a Bayesian calibration of the 40K decay scheme. We formulate robust priors for all model parameters including partial 40K decay constants, 238U and 235U decay constants, and age offset parameters to account for phenomena that can perturb apparent U-Pb and 40Ar/39Ar ages. We then harness a set of complementary 40Ar/39Ar, 238U/206Pb, and 235U/207Pb data from well- characterized geological samples with ages from 1.919 ka to 2000 Ma to derive Bayesian estimates of the 40K decay constants. Posterior values for the partial 40K decay constants are
Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R2) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R2 of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.
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for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","title":"Optimizing per vessel hour capture efficiency for rare, heterogeneously distributed fishes: Invasive grass carp Ctenopharyngodon idella in the Sandusky River","docAbstract":"Natural resources management is often concerned with conserving rare-native or controlling rare-invasive fishes. Informing and assessing conservation and control efforts frequently requires information from captures. When little is understood about spatial and temporal fish distributions, captures can be infrequent and costly. If successful management depends on effective management response, optimizing for efficiency may be the difference between success and failure. We compared per vessel hour capture efficiencies for invasive grass carp (Ctenopharyngodon idella) between two methods: electrofishing-only (electrofishing) and in combination with a trammel net (combination). Capture and effort information including 174 captures from 1853 capture attempts from 1706 total hours of effort in the Sandusky River, OH, USA from 2020–2023 was used to fit a generalized linear model. Captures were allowed to vary by river kilometer, month, and year to account for unequal capture rates and effort. Captures were offset by total vessel hours or the count of independent efforts to compare methods that prioritize detection at a single location (e.g., combination) to methods that prioritize exploiting more locations (e.g., electrofishing). Including trammel nets was intended to increase single site detection, but we found that electrofishing-only was at least 2.4x more efficient (catch per vessel hour) than when combined with a trammel net with no significant difference in catch per removal effort. Complex methods intended to increase single site detection may reduce the number of efforts completed. Therefore, overall capture efficiency and total capture numbers for rare fish may be increased through methods that prioritize per-hour efficiency.
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unresolved. For four regions of North America that include parts of the United States and Canada (Sacramento-San Joaquin River Basins, Lower Colorado River Basin, Great Lakes Region, Mid-Atlantic Region), we construct and compare classification tree models to reveal robust predictors for the establishment and ecological impact stages of freshwater fish invasion. We subsequently apply the models to identify invasive fish species in trade and conduct pathway analyses to determine which trades (aquarium, biological supply, live bait, live food, water garden) and source continents pose the greatest risk to each region. Model results differed by invasion stage and region. Across regions, establishment models shared climate-related predictors including climate match and temperature tolerance. Three of the four impact models contained prior establishment success. The greatest number of species (548) were predicted to establish in the Sacramento-San Joaquin while the fewest (5) were predicted to establish in the Mid-Atlantic. Forty species were predicted to establish in multiple regions, five of which were also predicted to have high impact. The aquarium trade and Asia supplied the most species predicted to establish. Taken together, the results highlight region-specific models, indicating no universal model predicts invasion. Climate-related and prior establishment variables were most useful to risk assessments. The regional models, and identified high-risk pathways and potential invaders, could be applied to prevent future fish invasions in North America.
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