Optimal egg size theory predicts females must balance investment per offspring to maximize fitness based on environmental quality. In wetlands, environmental quality can be duration of water and predator presence. Ectotherms using habitats that dry or contain predators are likely under selection to optimize offspring production. We measured reproductive output of wood frogs (Rana sylvatica) in 30 wetlands in Subarctic Canada, where rapid climate changes are accelerating wetland drying. We predicted wetlands with short hydroperiods would have larger ova, smaller clutch sizes, and larger ovum-to-clutch-sizes than wetlands with long hydroperiods or with fish predators. We found partial support for predictions with larger ova in habitats with short hydroperiods and no fish but no evidence of larger clutch sizes in wetlands with fish. Our study implicates changes to wetland hydroperiod as a source of plasticity affecting one aspect of reproductive effort (ovum size) in an ectotherm but not another (clutch size).
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Spaceborne missions, a leap in technology, were sparse, starting with the CHRIS/PROBA and EO1/Hyperion missions in the early 2000s, and providing spectroscopy data with limited spectral coverage and/or low data quality in the SWIR. Since 2019, several countries and agencies have successfully launched a number of spaceborne imaging spectroscopy systems into orbit or deployed them on the International Space Station (ISS) such as DESIS, PRISMA, HISUI, GF-5, EnMAP and EMIT. Among these recent missions, the German Environmental Mapping and Analysis Program (EnMAP) stands for its long-term development, sophisticated design with on-board calibration, high data quality requirements, and extensive accompanying science program. EnMAP was launched in April 2022 and, following a successful commissioning phase, started its operational activities in November 2022. The EnMAP mission encompasses global coverage from 80° N to 80° S through on-demand data acquisitions. Data are free and open access with 30 m spatial resolution, a high spectral resolution with a spectral sampling distance of 6.5 nm and 10 nm in the VNIR and SWIR regions respectively, and a high signal-to-noise ratio. In this paper, we aim to present the mission's current status, coverage, science capabilities and performance two years after launch. We show the potential of EnMAP for space-based imaging spectroscopy to operate in various environments, including high and low light levels, dense forests, Antarctic glaciers, and arid agricultural areas. EnMAP enables various applications in fields such as agriculture and forestry, soil compositional, raw materials, and methane mapping, as well as water quality assessment, and snow and ice properties. The results show that EnMAP's performance exceeds the mission requirements, and highlights the significant potential for contribution to scientific exploitation in various geo- and biochemical sciences. EnMAP is also expected to serve as a key tool for the development and testing of data processing algorithms for upcoming global operational missions.
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Precambrian basement is a critical factor influencing induced earthquake rates in the Central United States, but the impact of reducing injection depths has not been widely demonstrated. Beginning in 2015, state regulatory efforts in Oklahoma and Kansas mandated that wells injecting into the lower Arbuckle Group, a basal sedimentary unit, be backfilled with cement (i.e. “plugged back”) so that they inject into shallower formations. This plug back activity gives us a unique opportunity to investigate the relationship between injection depth and induced seismicity rate. To evaluate the impact that decreased injection rates and plug backs had on the seismicity rates, we create a suite of rate-state earthquake models. Observed seismicity rates are best fit when only lower Arbuckle volumes are considered, suggesting the lower Arbuckle injectors were primarily responsible for the seismicity and that plug backs were effective at isolating the injected volumes to shallower formations. Our models demonstrate that if these wells had not been plugged back, seismicity rates would be multiple times larger than they are today. We find that the combination of well plug backs and injection volume decreases can be effective strategies for reducing induced seismicity rates.","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0320240030","usgsCitation":"Skoumal, R.J., Barbour, A.J., Rubenstein, J.L., and Glasgow, M.E., 2024, Reduced injection rates and shallower depths mitigated induced seismicity in Oklahoma: The Seismic Record, v. 4, no. 4, p. 279-287, https://doi.org/10.1785/0320240030.","productDescription":"9 p.","startPage":"279","endPage":"287","ipdsId":"IP-169748","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":466770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320240030","text":"Publisher Index Page"},{"id":464919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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2023","interactions":[],"lastModifiedDate":"2025-12-22T21:27:01.378005","indexId":"sir20245098","displayToPublicDate":"2024-11-12T13:16:24","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5098","displayTitle":"Water-Quality Comparisons in the Greater Mooses Tooth Unit of the National Petroleum Reserve in Alaska, 2010 and 2023","title":"Water-quality comparisons in the Greater Mooses Tooth unit of the National Petroleum Reserve in Alaska, 2010 and 2023","docAbstract":"The United States has long held oil reserves in the National Petroleum Reserve in Alaska (NPR–A), but oil production did not begin until 2015. The waters of the NPR–A are generally considered “pristine,” but water quality has not been characterized temporally or spatially in a rigorous manner. In 2010 and 2023, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, collected water-quality samples from four small, beaded streams in the NPR–A, three of which currently (2024) have oil and gas infrastructure within their drainage. Samples collected preconstruction and postconstruction were analyzed and compared to determine concentration changes in nutrients, major ions, trace elements, and volatile organic compounds to evaluate the effectiveness of required operating procedures designed to minimize potential effects to water quality from oil and gas activities.
The four small streams in the Greater Mooses Tooth unit of the NPR–A had similar water-quality characteristics in the 2010 and 2023 samples. Most analytes were measured at low concentrations or below the reporting level for both samples. For analytes that were detected, variability between the two samples was generally low and mostly showed lower concentrations in the 2023 samples, possibly partially because of recent rainfall that led to streamflow being much higher at the time of the 2023 sample. Trichloromethane was present in the sample at one site in both years and at a second site in the 2023 sample. All three detections of trichloromethane were within the expected natural background range for the area. The few increases in analyte concentrations in the watersheds with oil and gas facilities were all within the range of predevelopment concentrations or background concentrations for the area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245098","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Hall, B.M., 2024, Water-quality comparisons in the Greater Mooses Tooth unit of the National Petroleum Reserve in Alaska, 2010 and 2023: U.S. Geological Survey Scientific Investigations Report 2024–5098, 11 p., https://doi.org/10.3133/sir20245098.","productDescription":"Report: vi, 11 p.; Dataset","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-162398","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":497913,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117793.htm","linkFileType":{"id":5,"text":"html"}},{"id":463853,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245098/full"},{"id":463848,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5098/coverthb.jpg"},{"id":463849,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5098/sir20245098.pdf","text":"Report","size":"3.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5098"},{"id":463850,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5098/sir20245098.XML"},{"id":463851,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5098/images/"},{"id":463852,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"}],"country":"United States","state":"Alaska","otherGeospatial":"Greater Mooses Tooth Unit of the National Petroleum Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.66,\n 70.5\n ],\n [\n -152,\n 70.5\n ],\n [\n -152,\n 70\n ],\n [\n -150.66,\n 70\n ],\n [\n -150.66,\n 70.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Background
Colorado River Cutthroat Trout (CRCT; Oncorhynchus clarkii pleuriticus) conservation populations may be at risk from wildfire and post-fire debris flows hazards.
Aim
To predict burn severity and potential post-fire debris flow hazard classifications to CRCT conservation populations before wildfires occur.
Methods
We used remote sensing, spatial analyses, and machine learning to model 28 wildfire incidents (2016–2020) and spatially predict burn severity from pre-wildfire environmental factors to evaluate the likelihood (%) and volume (m3) hazard classification of post-fire debris flow.
Key results
Burn severity was best predicted by fuels, followed by topography, physical ecosystem conditions, and weather (mean adjusted R2 = 0.54). Predictions of high or moderate burn severity covered 1.1 (15% of study area) and 1.5 (19% of study area) million ha, respectively, and varied by watershed. Combined high or moderate debris flow hazard classification included 80% of stream reaches with conservation populations and 97% of conservation population point nodes.
Conclusions
Predicted burn severity and potential post-fire debris flow indicated moderate to high hazard for CRCT conservation populations native to the Green and Yampa rivers of the Upper Colorado River Basin.
Implications
Future management actions can incorporate predicted burn severity and potential post-fire debris flow to mitigate impacts to CRCT and other at-risk resource values before a wildfire occurs.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF23199","usgsCitation":"Wells, A.G., Yackulic, C., Kostelnik, J., Bock, A.R., Zuellig, R.E., Carlisle, D.M., Roberts, J., Rogers, K., and Munson, S.M., 2024, Before the fire: Predicting burn severity and potential post-fire debris-flow hazards to Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus) conservation populations: International Journal of Wildland Fire, v. 33, WF23199, 19 p., https://doi.org/10.1071/WF23199.","productDescription":"WF23199, 19 p.","ipdsId":"IP-160628","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":481050,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf23199","text":"Publisher Index Page"},{"id":480839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 44.731125592643274\n ],\n [\n -111.1376953125,\n 42.114523952464246\n ],\n [\n -112.78564453124999,\n 41.902277040963696\n ],\n [\n -112.6318359375,\n 38.03078569382294\n ],\n [\n -111.9287109375,\n 36.756490329505176\n ],\n [\n -110.1708984375,\n 35.8356283888737\n ],\n [\n -106.63330078125,\n 35.55010533588552\n ],\n [\n -106.787109375,\n 35.88905007936091\n ],\n [\n -104.83154296875,\n 38.77121637244273\n ],\n [\n -104.96337890625,\n 40.93011520598305\n ],\n [\n -111.0498046875,\n 44.731125592643274\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2024-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":924578,"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":924579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":924580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zuellig, Robert E. 0000-0002-4784-2905 rzuellig@usgs.gov","orcid":"https://orcid.org/0000-0002-4784-2905","contributorId":1620,"corporation":false,"usgs":true,"family":"Zuellig","given":"Robert","email":"rzuellig@usgs.gov","middleInitial":"E.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924582,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":924583,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, James J. 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":924584,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rogers, Kevin B.","contributorId":220104,"corporation":false,"usgs":false,"family":"Rogers","given":"Kevin B.","affiliations":[],"preferred":false,"id":924585,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":924586,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260892,"text":"70260892 - 2024 - Triggering the 2022 eruption of Mauna Loa","interactions":[],"lastModifiedDate":"2024-11-14T15:40:19.077739","indexId":"70260892","displayToPublicDate":"2024-11-12T09:35:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Triggering the 2022 eruption of Mauna Loa","docAbstract":"Distinguishing periods of intermittent unrest from the run-up to eruption is a major challenge at volcanoes around the globe. Comparing multidisciplinary monitoring data with mineral chemistry that records the physical and spatio-temporal evolution of magmas fundamentally advances our ability to forecast eruptions. The recent eruption of Mauna Loa, Earth’s largest active volcano, provides a unique opportunity to differentiate unrest from run-up and improve forecasting of future eruptions. After decades of intermittent seismic and geodetic activity over 38 years of repose, Mauna Loa began erupting on 27 November 2022. Here we present a multidisciplinary synthesis that tracks the spatio-temporal evolution of precursory activity by integrating mineral and melt chemistry, fluid inclusion barometry, numerical modeling of mineral zoning, syn-eruptive gas plume measurements, the distribution and frequency of earthquake hypocenters, seismic velocity changes, and ground deformation. These diverse data indicate that the eruption occurred following a 2-month period of sustained magma intrusion from depths of 3–5 km up to 1–2 km beneath the summit caldera, providing a new model of the plumbing system at this very high threat volcano. Careful correlation of both the geochemistry and instrumental monitoring data improves our ability to distinguish unrest from the run-up to eruption by providing deeper understanding of the both the monitoring data and the magmatic system—an approach that could be applied at other volcanic systems worldwide.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-024-52881-7","usgsCitation":"Lynn, K.J., Downs, D.T., Trusdell, F., Wieser, P.E., Rangel, B., McDade, B.R., Hotovec-Ellis, A.J., Bennington, N.L., Anderson, K.R., Ruth, D.C., DeVitre, C., Ellis, A.P., Nadeau, P.A., Clor, L., Kelly, P.J., Dotray, P., and Chang, J., 2024, Triggering the 2022 eruption of Mauna Loa: Nature Communications, v. 15, 9451, 12 p., https://doi.org/10.1038/s41467-024-52881-7.","productDescription":"9451, 12 p.","ipdsId":"IP-166194","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466771,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-024-52881-7","text":"Publisher Index Page"},{"id":464028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": 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Vaccines exist for many infectious pathogens, and at a time of rapid technological advances in vaccinology, developing vaccines and vaccination programs for free-living endangered wildlife could help efforts to prevent extinctions from disease threats. Vaccination efforts could focus on protecting members of the target species or could be directed at reservoir populations to prevent pathogen spillover. Vaccination strategies need to be substantiated by research on safety and effectiveness, include risk and feasibility assessments, account for differences in host biology and disease epidemiology, and align with relevant regulatory frameworks. Engagement with stakeholders and the public is important to ensure the success of endangered species vaccination programs. Challenges such as funding, regulation, and societal acceptance are barriers to progress in vaccination programs for some species and geographic regions. We recommend the development of scientifically based international guidelines and a transdisciplinary forum with a specific emphasis on endangered wildlife vaccination. New technologies could be used collaboratively to prevent transmission of diseases for which vaccines are not currently available. Careful approaches and enhanced collaborations could help ensure the successful development of wildlife vaccination programs and promote resilience of endangered wildlife populations to increasing anthropogenic and environmental stressors on biodiversity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110842","usgsCitation":"Gulland, F., Barbieri, M., Cleaveland, S., Gilbert, M., Hall, A., and Rocke, T.E., 2024, Vaccination of endangered wildlife as a conservation tool: Hindsights and new horizons in the pandemic era: Biological Conservation, v. 300, 110842, 10 p., https://doi.org/10.1016/j.biocon.2024.110842.","productDescription":"110842, 10 p.","ipdsId":"IP-169951","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":498707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/67179","text":"External Repository"},{"id":465630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"300","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gulland, Frances","contributorId":244392,"corporation":false,"usgs":false,"family":"Gulland","given":"Frances","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":922270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbieri, Michelle","contributorId":347708,"corporation":false,"usgs":false,"family":"Barbieri","given":"Michelle","affiliations":[{"id":83208,"text":"b Pacific Islands Fisheries Science Center, 1845 Wasp Boulevard, Honolulu HI 96818, USA","active":true,"usgs":false}],"preferred":false,"id":922271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleaveland, Sarah","contributorId":124536,"corporation":false,"usgs":false,"family":"Cleaveland","given":"Sarah","email":"","affiliations":[{"id":5092,"text":"Boyd Orr Centre for Population and Ecosystems Health, Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, UK","active":true,"usgs":false}],"preferred":false,"id":922272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilbert, Martin","contributorId":225478,"corporation":false,"usgs":false,"family":"Gilbert","given":"Martin","affiliations":[{"id":41138,"text":"College of Veterinary Medicine, Cornel University, Ithaca, NY, USA","active":true,"usgs":false}],"preferred":false,"id":922273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Ailsa J.","contributorId":347709,"corporation":false,"usgs":false,"family":"Hall","given":"Ailsa J.","affiliations":[{"id":83209,"text":"School of Biology, University of St. Andrews, St Andrews, KY16 9ST, UK","active":true,"usgs":false}],"preferred":false,"id":922274,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":922275,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260455,"text":"dr1201 - 2024 - Post Carr Fire bioassessment data report, Whiskeytown National Recreation Area, Shasta County, California","interactions":[],"lastModifiedDate":"2024-11-13T15:27:55.660405","indexId":"dr1201","displayToPublicDate":"2024-11-12T08:22:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1201","displayTitle":"Post Carr Fire Bioassessment Data Report, Whiskeytown National Recreation Area, Shasta County, California","title":"Post Carr Fire bioassessment data report, Whiskeytown National Recreation Area, Shasta County, California","docAbstract":"The U.S. Geological Survey, in cooperation with the National Park Service, analyzed water and sediment chemistry, benthic macroinvertebrate assemblages, fish and amphibian assemblages, fish and invertebrate tissues, instream habitat characteristics, and sediment heterogeneity at 10 stream sites within Whiskeytown National Recreation Area, Shasta County, California, during August 2020, 2 years after the Carr Fire. The post-Carr Fire data were compared to available pre-Carr Fire data to help determine if there have been wildfire-induced changes in the aquatic communities within the Whiskeytown National Recreational Area. Benthic sediment results for metals of biological concern were compared with consensus-based probable effect concentrations from previously published sediment-quality guidelines. Results from 2020 sampling indicated exceedances of these guidelines at one site for cadmium, chromium, copper, and zinc; there were exceedances of the guidelines at three sites for nickel. Concentrations of metals of biological concern in fish and invertebrate tissue samples generally varied among sites and years, with no pattern with specific reference to the Carr Fire. Average zinc and lead concentrations in composite invertebrate samples were slightly higher in 2020 than in previous years, and arsenic levels were lower in 2020 for invertebrate and fish tissues. Post-Carr Fire stream-habitat and sediment-size characterization values did not change substantially when compared to pre-Carr Fire values, or had high variation among all sites and years. Fish and amphibian inventories demonstrated that fewer total fish and amphibians were collected post-Carr Fire, but higher numbers of native Sacramento Sucker (Catostomus occidentalis) and Sacramento Pikeminnow (Ptychocheilus grandis) were collected than in previous years. The combined histories of mining and frequent wildfires in the area pose an increased risk for metal contamination throughout the aquatic system. Continued monitoring for multilevel trophic effects of contaminants can provide information about the overall health of the Whiskeytown National Recreation Area and surrounding region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1201","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wulff, M.L., Brown, L.R., and Violette, V.L., 2024, Post Carr Fire bioassessment data report, Whiskeytown National Recreation Area, Shasta County, California: U.S. Geological Survey Data Report 1201, 26 p., https://doi.org/10.3133/dr1201.","productDescription":"Report: viii, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-125210","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":463558,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90WGKWI","text":"USGS Data Release","description":"Wulff, M.L., Brown, L.R., and Violette, V.L., 2023, Post Carr Fire Bioassessment Data, Whiskeytown National Recreation Area, Shasta County, California, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P90WGKWI.","linkHelpText":"Post Carr Fire Bioassessment Data, Whiskeytown National Recreation Area, Shasta County, California, 2020"},{"id":463557,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1201/full"},{"id":463556,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1201/images"},{"id":463555,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1201/dr1201.XML"},{"id":463554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1201/dr1201.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1201/coverthb.jpg"}],"country":"United States","state":"California","county":"Shasta County","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.7971714207388,\n 41.04817475780641\n ],\n [\n -122.7971714207388,\n 40.53716575964799\n ],\n [\n -122.2801689286946,\n 40.53716575964799\n ],\n [\n -122.2801689286946,\n 41.04817475780641\n ],\n [\n -122.7971714207388,\n 41.04817475780641\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Depleted hydrocarbon reservoirs are subsurface geological structures capable of sequestering vast quantities of carbon dioxide (CO2) as well as storing other energy gases for later usage, such as natural gas, and potentially hydrogen (H2). Here we outline a methodology to quantify multi-gas storage resources in depleted conventional gas reservoirs for usage in assessments by the United States Geological Survey (USGS) at the scale of sedimentary basins. The methodology consists first of quantifying accessible pore volume in a depleted reservoir for natural gas storage using up to three equations. Input data are derived from commonly reported or estimated reservoir parameters and natural gas production volumes, and equations may be combined in linear models to improve pore volume estimates. Storage estimates from these equations are tested and validated for 31 reservoirs in the Michigan Basin Province, USA that were previously converted to underground gas storage facilities and have known (federally reported) natural gas storage capacities. Secondly, natural gas storage capacities can be transformed via fluid substitution calculations to estimate the storage resources for non-native fluids, applied here for, CO2, H2, and methane-H2 blends, accounting for molecule-specific deviations from ideal gas behavior at reservoir pressures and temperatures as well as differing storage efficiencies. Importantly, the storage of non-native fluids may not be appropriate in all depleted gas reservoir settings due to potential risks like leakage, in particular in the case of H2 storage, requiring additional knowledge of caprock sealing capacity. Given this caveat, we demonstrate the fluid substitution method for natural gas reservoirs of the Northern Niagaran Reef and Southern Niagaran Reef USGS plays in the Michigan Basin Province, as these trends of Silurian pinnacle reefs are capped with tight-sealing evaporite facies. The deterministic equations outlined from this methodology can be incorporated into future probabilistic USGS gas storage assessments for CO2, H2, and natural gas resources in the United States.
","conferenceTitle":"17th International Conference on Greenhouse Gas Control Technologies, GHGT-17","conferenceDate":"October 20-24, 2024","conferenceLocation":"Calgary, Alberta, Canada","language":"English","publisher":"SSRN","doi":"10.2139/ssrn.5014690","usgsCitation":"Jones, M.M., Wiens, A.M., Buursink, M., Brennan, S., Freeman, P., Varela, B.A., Gallotti, J.S., and Warwick, P., 2024, A methodology to estimate CO2 and energy gas storage resources in depleted conventional gas reservoirs, 17th International Conference on Greenhouse Gas Control Technologies, GHGT-17, Calgary, Alberta, Canada, October 20-24, 2024, 11 p., https://doi.org/10.2139/ssrn.5014690.","productDescription":"11 p.","ipdsId":"IP-170771","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494404,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0001-5996-1728","orcid":"https://orcid.org/0000-0001-5996-1728","contributorId":344228,"corporation":false,"usgs":true,"family":"Jones","given":"Matthew","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":918316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiens, Ashton M. 0000-0002-7030-0602","orcid":"https://orcid.org/0000-0002-7030-0602","contributorId":271176,"corporation":false,"usgs":true,"family":"Wiens","given":"Ashton","email":"","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buursink, Marc L. 0000-0001-6491-386X","orcid":"https://orcid.org/0000-0001-6491-386X","contributorId":203357,"corporation":false,"usgs":true,"family":"Buursink","given":"Marc L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brennan, Sean T. 0000-0002-7102-9359","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":204982,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":224150,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gallotti, Joao S. 0000-0002-7901-029X","orcid":"https://orcid.org/0000-0002-7901-029X","contributorId":302892,"corporation":false,"usgs":true,"family":"Gallotti","given":"Joao","email":"","middleInitial":"S.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":918322,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":207248,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918323,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263800,"text":"70263800 - 2024 - Detection probabilities of Flathead Catfish in small Kansas impoundments","interactions":[],"lastModifiedDate":"2025-03-26T15:57:43.955275","indexId":"70263800","displayToPublicDate":"2024-11-11T09:47:29","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Detection probabilities of Flathead Catfish in small Kansas impoundments","docAbstract":"A primary challenge of Flathead Catfish Pylodictis olivaris management is uncertainty associated with sampling strategies and resulting ambiguity in population-level information. Assessment of impoundment and environmental conditions that affect detection probability may aid in reducing sample variance and benefit inferences regarding changes to Flathead Catfish populations. We sampled eight small impoundments in Kansas (37–114 surface ha) using low-frequency electrofishing in summer, 2021. We revisited sites nine times over three months using an occupancy modeling framework to estimate the influence of impoundment and environmental conditions on detection probability of Flathead Catfish. We employed an information theoretic approach and ranked models built with impoundment as a random effect and three environmental variables predicted to influence detection of Flathead Catfish in small impoundments. Detection probability across all populations was 0.526 (SE = 0.020) and was influenced by water temperature, mean depth of the impoundment, and proportion of impoundment sampled. Generally, detection probability increased with all measured variables. The inclusion of detection probability in assessments of Flathead Catfish in small impoundments can inform interpretation of catch-related metrics. Further, variable detection suggests collection of multiple samples during a defined sampling period might be more suitable for characterizing populations than a single sample.
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Kowalewski","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kramer, Nicholas W.","contributorId":351292,"corporation":false,"usgs":false,"family":"Kramer","given":"Nicholas W.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lundgren, Seth A.","contributorId":351293,"corporation":false,"usgs":false,"family":"Lundgren","given":"Seth A.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":928340,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260851,"text":"70260851 - 2024 - Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels","interactions":[],"lastModifiedDate":"2024-11-12T15:20:21.159268","indexId":"70260851","displayToPublicDate":"2024-11-11T09:17:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19829,"text":"Nature Communications, Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels","docAbstract":"Ecological disturbance can affect carbon storage and stability and is a key consideration for managing lands to preserve or increase ecosystem carbon to ameliorate the global greenhouse gas problem. Dryland soils are massive carbon reservoirs that are increasingly impacted by species invasions and altered fire regimes, including the exotic-grass-fire cycle in the extensive sagebrush steppe of North America. Direct measurement of total carbon in 1174 samples from landscapes of this region that differed in invasion and wildfire history revealed that their impacts depleted soil carbon by 42–49%, primarily in deep horizons, which could amount to 17.1–20.0 Tg carbon lost across the ~400,000 ha affected annually. Disturbance effects on soil carbon stocks were not synergistic, suggesting that soil carbon was lowered to a floor—i.e. a resistant base-level—beneath which further loss was unlikely. Restoration and maintenance of resilient dryland shrublands/rangelands could stabilize soil carbon at magnitudes relevant to the global carbon cycle.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-024-01795-9","usgsCitation":"Maxwell, T.M., Quicke, H.E., Price, S.J., and Germino, M., 2024, Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels: Nature Communications, Earth & Environment, v. 5, 669, 11 p., https://doi.org/10.1038/s43247-024-01795-9.","productDescription":"669, 11 p.","ipdsId":"IP-162810","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":466772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01795-9","text":"Publisher Index Page"},{"id":463870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Maxwell, Toby Matthew 0000-0001-5171-0705","orcid":"https://orcid.org/0000-0001-5171-0705","contributorId":334690,"corporation":false,"usgs":true,"family":"Maxwell","given":"Toby","email":"","middleInitial":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quicke, Harold E.","contributorId":346166,"corporation":false,"usgs":false,"family":"Quicke","given":"Harold","email":"","middleInitial":"E.","affiliations":[{"id":82790,"text":"Environmental Science U.S. LLC","active":true,"usgs":false}],"preferred":false,"id":918296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Price, Samuel J. 0000-0003-4172-4139","orcid":"https://orcid.org/0000-0003-4172-4139","contributorId":297001,"corporation":false,"usgs":true,"family":"Price","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918298,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260886,"text":"70260886 - 2024 - Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance","interactions":[],"lastModifiedDate":"2025-03-11T14:49:17.072232","indexId":"70260886","displayToPublicDate":"2024-11-11T08:52:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance","docAbstract":"The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.
","language":"English","publisher":"Sage","doi":"10.1177/87552930241280401","usgsCitation":"Porter, K., Milner, K.R., and Field, E.H., 2024, Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance: Earthquake Spectra, v. 41, no. 1, p. 636-653, https://doi.org/10.1177/87552930241280401.","productDescription":"19 p.","startPage":"636","endPage":"653","ipdsId":"IP-161498","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":464026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Porter, Keith","contributorId":191074,"corporation":false,"usgs":false,"family":"Porter","given":"Keith","affiliations":[],"preferred":false,"id":918429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":918430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":918431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263970,"text":"70263970 - 2024 - Length in assessing status of freshwater fish populations: A review","interactions":[],"lastModifiedDate":"2025-03-04T15:50:34.260958","indexId":"70263970","displayToPublicDate":"2024-11-10T09:39:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Length in assessing status of freshwater fish populations: A review","docAbstract":"Effective policy formulation regarding the conservation of freshwater fish necessitates an understanding of water‐specific prevailing conditions and trends. Assessing fish populations in inland waters is difficult and expensive because there are many independent systems that need to be evaluated. Therefore, numerous freshwater systems are beset by insufficient data and the lack of systematic assessments of their status. To alleviate this deficiency, the objective of this study was to review length‐based metrics that may have utility in evaluating the well‐being of freshwater fish populations.
Length measurements can serve as proxies for a range of ecological and population dynamics attributes that are essential for the effective management of fish and associated fisheries. A review of the historical development of length measurements in fish conservation is provided, along with an examination of the potential biases that may arise from the use of lengths in practical contexts. In addition, we examine techniques that enable the spatial and temporal visualization of length data sets, as well as a range of indices and metrics that can be computed using length measurements.
Building populations assessments around length may be a cost‐effective strategy that allows a first cut at managing a large number of waters. Length‐based assessments can signal if management intervention is necessary, if management policies are yielding the intended outcome, or if surveys beyond mere length are necessary.
Our review indicates that length offers a straightforward and efficient approach to evaluate the status of fish populations in inland systems. We encourage pursuing additional study and to this end propose specific areas for investigation.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Hydrologic connectivity, the network of water pathways linking aquatic habitats, is vital for the exchange of organisms and abiotic materials between rivers and adjacent waterbodies. This study quantified hydrologic connectivity for 1,283 lakes in the Lower Mississippi River floodplain using satellite imagery, streamgauge data, and geospatial information. We aimed to assess connection frequency patterns between lakes and streams. Eight metrics describing temporal aspects of hydrologic connectivity were estimated, identifying trends by lake features and by stream size. Each lake exhibited a distinct pattern of connection, with specific months of connectivity followed by disconnection, likely influenced by lake characteristics and seasonal precipitation. Larger lakes showed increased connectivity, likely due to their surface area and volume, while smaller lakes were more prone to isolation, especially during dry periods. Lakes connected to large streams exhibited more prolonged and recurring connections, with less seasonal variation. In contrast, lakes near agricultural areas experienced reduced connectivity. However, local factors such as levees and artificial channels often disrupted these general trends. This hydrologic connectivity analysis can provide insight to support floodplain management, facilitate development of frameworks that restore connectivity, promote preservation of ecological integrity, and support management of invasive species spread in agricultural floodplains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2024.112808","usgsCitation":"Ahmad, H., Miranda, L.E., Dunn, C.G., Boudreau, M., and Colvin, M.E., 2024, Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River: Ecological Indicators, v. 169, 112808, 12 p., https://doi.org/10.1016/j.ecolind.2024.112808.","productDescription":"112808, 12 p.","ipdsId":"IP-168197","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490657,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2024.112808","text":"Publisher Index Page"},{"id":490406,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QIH9NJ","text":"USGS data release","linkHelpText":"Code for Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River"},{"id":489294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Mississippi River floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.30878420635052,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 38.86158462464857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"169","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahmad, Hafez","contributorId":353774,"corporation":false,"usgs":false,"family":"Ahmad","given":"Hafez","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":938776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":938777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boudreau, Melanie R.","contributorId":353778,"corporation":false,"usgs":false,"family":"Boudreau","given":"Melanie R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938779,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064I","publicationYear":"2024","noYear":false,"chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2025-12-22T21:31:08.991933","indexId":"sir20235064I","displayToPublicDate":"2024-11-08T10:53:13","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5064","chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","docAbstract":"Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging.
In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions.
Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p-value cutoff point.
A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected.
A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State.
Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.
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U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH4 ± CO2 saturated aqueous fluids and CH4 ± CO2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH4 ± CO2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re-equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2024.104646","usgsCitation":"Evans, M.A., and Jubb, A., 2024, Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania: International Journal of Coal Geology, v. 295, 104646, 27 p., https://doi.org/10.1016/j.coal.2024.104646.","productDescription":"104646, 27 p.","ipdsId":"IP-164265","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":463907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75,\n 41.75\n ],\n [\n -80,\n 41.75\n ],\n [\n -80,\n 39.5\n ],\n [\n -75,\n 39.5\n ],\n [\n -75,\n 41.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"295","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Mark A.","contributorId":197411,"corporation":false,"usgs":false,"family":"Evans","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":918370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918369,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270845,"text":"70270845 - 2024 - Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation","interactions":[],"lastModifiedDate":"2025-08-28T15:11:50.278531","indexId":"70270845","displayToPublicDate":"2024-11-08T09:59:02","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-159-2024","title":"Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation","docAbstract":"The biological feasibility of introducing Rocky Mountain bighorn sheep (Ovis canadensis canadensis) to the Dulce area of the Jicarilla Apache Nation (JAN) depends on availability and condition of potential habitat and the potential for disease risk, as pneumonia is the largest current threat to wild sheep populations. We modeled quality and quantity of potential bighorn sheep habitat incorporating the three most recent fire scars around Dulce, determined potential winter range within preferred habitat, assessed on the ground vegetation characteristics, and examined potential for disease transmission via risk of contact with domestic sheep and goats. Most of the area of interest for this study has a suitability value ≥ 50%, with approximately 23-29% of the study area considered preferred, or high-quality habitat for bighorn sheep. High-quality habitat for Rocky Mountain bighorn sheep is defined as being within 300 m of escape terrain, within 1.6 km of water, and containing ≤ 30% shrub and tree cover. Of this, approximately 43-56% of potential preferred habitat qualifies as winter range, which is mostly concentrated in the narrow valley bottoms where roads are commonly located and the south-facing slopes surrounding valleys. Analysis of field-collected vegetation data indicate most of the existing forage within the surveyed area to be of moderate or high forage value to bighorn sheep, but horizontal visibility, predominantly in the form of shrubs, is more obscured than what bighorn sheep prefer for most of the area of interest. Maximum shrub and tree cover is also the most limiting factor in the suitability model, primarily due to the prevalence of dense shrub regeneration, particularly Gambel oak, which occurs after high severity burns. The largest quantities of high-quality potential bighorn sheep habitat within the study area occur in unburned areas or those burnt by the predominantly low-moderate severity Amargo fire in 2021. Relative to risk of contact with domestic sheep and goats that can transmit lethal pneumonia-causing pathogens, potentially causing an introduction effort to fail, there is high risk because of the proximity to two hobby-subsistence herds (< 3 km away).
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/10.3996/css73616801","usgsCitation":"Thompson, C.J., and Cain, J.W., 2024, Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation: Cooperator Science Series CSS-159-2024, 80 p., https://doi.org/10.3996/10.3996/css73616801.","productDescription":"80 p.","ipdsId":"IP-167003","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":494875,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/biological-feasibility-introducing-bighorn-sheep-jicarilla-apache-nation","linkFileType":{"id":5,"text":"html"}},{"id":495006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jicarilla Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.01771249033892,\n 36.99249959403626\n ],\n [\n -107.5487950989812,\n 36.99249959403626\n ],\n [\n -107.5487950989812,\n 36.05621273485714\n ],\n [\n -106.01771249033892,\n 36.05621273485714\n ],\n [\n -106.01771249033892,\n 36.99249959403626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Cara J.","contributorId":360559,"corporation":false,"usgs":false,"family":"Thompson","given":"Cara","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":947210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":947211,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260845,"text":"70260845 - 2024 - Riparian methylmercury production increases riverine mercury flux and food web concentrations","interactions":[],"lastModifiedDate":"2025-02-07T16:28:17.344914","indexId":"70260845","displayToPublicDate":"2024-11-08T09:57:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Riparian methylmercury production increases riverine mercury flux and food web concentrations","docAbstract":"The production and uptake of toxic methylmercury (MeHg) impacts aquatic ecosystems globally. Rivers can be dynamic and difficult systems to study for MeHg production and bioaccumulation, hence identifying sources of MeHg to these systems is both challenging and important for resource management within rivers and main-stem reservoirs. Riparian zones, which are known biogeochemical hotspots for MeHg production, are understudied as potential sources of MeHg to rivers. Here, we present a comprehensive quantification of the hydrologic and biogeochemical processes governing MeHg concentrations, loads, and bioaccumulation at 16 locations along 164 km of the agriculturally intensive Snake River (Idaho, Oregon USA) during summer baseflow conditions, with emphasis on riparian production of MeHg. Approximately one-third of the MeHg load of the Snake River could not be attributed to inflowing waters (upgradient, tributaries, or irrigation drains). Across the study reach, increases in MeHg loads in surface waters were significantly correlated with MeHg concentrations in riparian porewaters, suggesting riparian zones were likely an important source of MeHg to the Snake River. Across all locations, MeHg concentrations in surface waters positively correlated with MeHg concentrations in benthic snails and clams, supporting that riparian produced MeHg was assimilated into local aquatic food webs. This study contributes new insights into riparian MeHg production within rivers which can inform mitigation efforts to reduce MeHg bioaccumulation in fish.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.4c08585","usgsCitation":"Krause, V., Baldwin, A.K., Peterson, B.D., Krabbenhoft, D.P., Janssen, S., Willacker, J., Eagles-Smith, C., and Poulin, B., 2024, Riparian methylmercury production increases riverine mercury flux and food web concentrations: Environmental Science & Technology, v. 58, no. 46, p. 20490-20501, https://doi.org/10.1021/acs.est.4c08585.","productDescription":"12 p.","startPage":"20490","endPage":"20501","ipdsId":"IP-168495","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463875,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466774,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c08585","text":"Publisher Index Page"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.76519965515584,\n 44.99304074681157\n ],\n [\n -117.75863076747619,\n 42.94336107731144\n ],\n [\n -116.17776769472738,\n 42.9364463608284\n ],\n [\n -116.25927931073849,\n 44.985691191051046\n ],\n [\n -117.76519965515584,\n 44.99304074681157\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"46","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Krause, Virginia","contributorId":346163,"corporation":false,"usgs":false,"family":"Krause","given":"Virginia","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":918280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":918282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":918283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":221744,"corporation":false,"usgs":true,"family":"Willacker","given":"James","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918285,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918286,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poulin, Brett A.","contributorId":328488,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":918287,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261200,"text":"70261200 - 2024 - Near-term ecological forecasting for climate change action","interactions":[],"lastModifiedDate":"2024-12-10T15:40:21.945944","indexId":"70261200","displayToPublicDate":"2024-11-08T08:55:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Near-term ecological forecasting for climate change action","docAbstract":"A substantial increase in predictive capacity is needed to anticipate and mitigate the widespread change in ecosystems and their services in the face of climate and biodiversity crises. In this era of accelerating change, we cannot rely on historical patterns or focus primarily on long-term projections that extend decades into the future. In this Perspective, we discuss the potential of near-term (daily to decadal) iterative ecological forecasting to improve decision-making on actionable time frames. We summarize the current status of ecological forecasting and focus on how to scale up, build on lessons from weather forecasting, and take advantage of recent technological advances. We also highlight the need to focus on equity, workforce development, and broad cross-disciplinary and non-academic partnerships.
","language":"English","publisher":"Nature","doi":"10.1038/s41558-024-02182-0","usgsCitation":"Dietze, M., White, E.P., Abeyta, A., Boettiger, C., Bueno Watts, N., Carey, C.C., Chaplin-Kramer, R., Emanuel, R.E., Ernest, S.M., Figueiredo, R., Gerst, M., Johnson, L.R., Kenney, M.A., McLachlan, J.S., Paschalidis, I., Peters, J., Rollinson, C.R., Simonis, J., Sullivan-Wiley, K., Thomas, R.Q., Wardle, G.M., Willson, A., and Zwart, J.A., 2024, Near-term ecological forecasting for climate change action: Nature Climate Change, v. 14, p. 1236-1244, https://doi.org/10.1038/s41558-024-02182-0.","productDescription":"9 p.","startPage":"1236","endPage":"1244","ipdsId":"IP-151657","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":489045,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10919/122612","text":"External Repository"},{"id":464589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dietze, Michael","contributorId":248349,"corporation":false,"usgs":false,"family":"Dietze","given":"Michael","affiliations":[],"preferred":false,"id":919605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Ethan P.","contributorId":190112,"corporation":false,"usgs":false,"family":"White","given":"Ethan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":919606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abeyta, Antoinette","contributorId":346577,"corporation":false,"usgs":false,"family":"Abeyta","given":"Antoinette","email":"","affiliations":[{"id":82890,"text":"University of New Mexico Gallup","active":true,"usgs":false}],"preferred":false,"id":919607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boettiger, Carl 0000-0002-1642-628X","orcid":"https://orcid.org/0000-0002-1642-628X","contributorId":332018,"corporation":false,"usgs":false,"family":"Boettiger","given":"Carl","email":"","affiliations":[{"id":79359,"text":"Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":919608,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bueno Watts, Nievita","contributorId":346578,"corporation":false,"usgs":false,"family":"Bueno Watts","given":"Nievita","email":"","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":919609,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":919610,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chaplin-Kramer, Rebecca 0000-0002-1539-5231","orcid":"https://orcid.org/0000-0002-1539-5231","contributorId":213447,"corporation":false,"usgs":false,"family":"Chaplin-Kramer","given":"Rebecca","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":919611,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emanuel, Ryan E.","contributorId":346579,"corporation":false,"usgs":false,"family":"Emanuel","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":919612,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ernest, S.K. 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Initial reproductive success post-translocation is important for establishing short-lived species such as quail, but factors influencing reproductive success are poorly understood. We evaluated the effect of source population and variation in delayed release strategy (1−9 weeks) on nest initiation and nest survival of wild-caught, translocated scaled quail. We trapped and translocated scaled quail in 2016–2017 from source populations in the Edwards Plateau and Rolling Plains ecoregions of Texas, USA, to a large contiguous (>40,000 ha) release site in Knox County, Texas. We used a multi-state mark-recapture model with state uncertainty to test for effects of release treatment, source population, age, release location, and year on nest initiation and survival. Increased length of holding time decreased re-nesting effort. Yearlings were more likely to initiate nests than adults and the probability of re-nesting was lower during the year with drought conditions. There was no effect of source population on any of the parameters we evaluated. Future scaled quail reintroduction efforts may benefit from prioritizing translocation of yearlings and conducting translocations when drought conditions are not forecasted.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22660","usgsCitation":"Ruzicka, R., Rollins, D., Kendall, W.L., and Doherty, P.F., 2024, Effects of release strategy, source population, and age on reintroduced scaled quail reproduction: Journal of Wildlife Management, v. 88, no. 8, e22660, 15 p., https://doi.org/10.1002/jwmg.22660.","productDescription":"e22660, 15 p.","ipdsId":"IP-163958","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22660","text":"Publisher Index Page"},{"id":485451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Knox County","otherGeospatial":"Edwards Plateau, Rolling Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.06618223574085,\n 33.8841524446256\n ],\n [\n -100.06618223574085,\n 33.291492418907126\n ],\n [\n -99.37113169882426,\n 33.291492418907126\n ],\n [\n -99.37113169882426,\n 33.8841524446256\n ],\n [\n -100.06618223574085,\n 33.8841524446256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"88","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruzicka, Rebekah E.","contributorId":354109,"corporation":false,"usgs":false,"family":"Ruzicka","given":"Rebekah E.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rollins, Dale","contributorId":140708,"corporation":false,"usgs":false,"family":"Rollins","given":"Dale","email":"","affiliations":[],"preferred":false,"id":935801,"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":935802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doherty, Paul F. 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From 2018 through 2020 the U.S. Geological Survey and U.S. Army Corps of Engineers led a series of calls and meetings, and a workshop to develop a draft UMRS hydrogeomorphic change conceptual model and hierarchical classification scheme. This project was funded through an Upper Mississippi River Restoration 2018 science in support of restoration proposal entitled, “Conceptual Model and Hierarchical Classification of Hydrogeomorphic Settings in the Upper Mississippi River System.” This report documents the background leading up to and the major findings from the workshop. The resulting conceptual model focuses on the drivers and boundary conditions that affect the major hydrogeomorphic processes along the valley corridor using a continuum of spatial and temporal scales and resolutions. The draft hierarchical classification was based on three existing and three new nested geospatial datasets that ultimately can be used to characterize hydrogeomorphic settings that span the UMRS valley corridor. The conceptual model and hierarchical classification will help characterize recent (mid-1990s through mid-2010s) decadal-scale processes and sources for potential hydrogeomorphic change that span a range of spatial scales from watershed hydrology and sediment sources to channel hydraulics and sediment transport.
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","language":"English","publisher":"Nature","doi":"10.1038/s43247-024-01837-2","usgsCitation":"Royer, C., Bedford, C., Johnson, J., Horgan, B., Broz, A., Forni, O., Connell, S., Wiens, R., Mandon, L., Kathir, B., Hausrath, E., Udry, A., Madariaga, J., Dehouck, E., Anderson, R.B., Beck, P., Beyssac, O., Clavé, É., Clegg, S., Cloutis, E., Fouchet, T., Gabriel, T.S., Garczynski, B., Klidaras, A., Manelski, H., Mayhew, L., Nunez, J., Ollila, A., Schröder, S., Simon, J., Wolf, U., Stack, K., Cousin, A., and Maurice, S., 2024, Intense alteration on early Mars revealed by high-aluminum rocks at Jezero Crater: Communications Earth & Environment, v. 5, 671, 13 p., https://doi.org/10.1038/s43247-024-01837-2.","productDescription":"671, 13 p.","ipdsId":"IP-159028","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":466775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01837-2","text":"Publisher Index Page"},{"id":463905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Jezero Crater, Mars","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Royer, C.","contributorId":290121,"corporation":false,"usgs":false,"family":"Royer","given":"C.","email":"","affiliations":[],"preferred":false,"id":918336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedford, C.C.","contributorId":346181,"corporation":false,"usgs":false,"family":"Bedford","given":"C.C.","email":"","affiliations":[{"id":82793,"text":"Purdue University Earth, Atmospheric and Planetary Sciences department, West Lafayette, IN, USA","active":true,"usgs":false}],"preferred":false,"id":918337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, J.R.","contributorId":296826,"corporation":false,"usgs":false,"family":"Johnson","given":"J.R.","email":"","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":918338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horgan, B.H.N.","contributorId":296798,"corporation":false,"usgs":false,"family":"Horgan","given":"B.H.N.","email":"","affiliations":[{"id":64183,"text":"Department of Earth, Atmospheric, and Planetary Sciences, Purdue University","active":true,"usgs":false}],"preferred":false,"id":918339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Broz, A.","contributorId":346182,"corporation":false,"usgs":false,"family":"Broz","given":"A.","email":"","affiliations":[{"id":82793,"text":"Purdue University Earth, Atmospheric and Planetary Sciences department, West Lafayette, IN, USA","active":true,"usgs":false}],"preferred":false,"id":918340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forni, O.","contributorId":290037,"corporation":false,"usgs":false,"family":"Forni","given":"O.","affiliations":[{"id":62314,"text":"Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":918341,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Connell, S.","contributorId":290071,"corporation":false,"usgs":false,"family":"Connell","given":"S.","email":"","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":918342,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wiens, R. 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The depth of magma storage has recently been identified as high-priority information for volcanic observatories, yet this information is not currently obtainable via petrological monitoring methods on timescales relevant to eruption response. Fluid inclusion barometry (using micro-thermometry or Raman spectroscopy) is a well-established petrological method to estimate magma storage depths and has been proposed to have potential as a rapid-response monitoring tool, although this has not been formally demonstrated. To address this deficiency, we performed a near-real-time rapid-response simulation for the September 2023 eruption of Kīlauea, Hawaiʻi. We show that Raman-based fluid inclusion barometry can robustly determine reservoir depths within a day of receiving samples — a transformative timescale that has not previously been achieved by petrological methods. Fluid inclusion barometry using micro-thermometric techniques has typically been limited to systems with relatively deep magma storage (>0.4 g/cm3 or >7 km) where measurements of CO2 density are easy and accurate because the CO2 fluid homogenizes into the liquid phase. Improvements of the accuracy of Raman spectroscopy measurements of fluids with low CO2 density over the past couple of decades has enabled measurements of fluid inclusions from shallower magmatic systems. However, one caveat of examining shallower systems is that the fraction of H2O in the fluid may be too high to reliably convert CO2 density to pressure. To test the global applicability of rapid response fluid inclusion barometry, we compiled a global melt inclusion dataset (>4000 samples) and calculate the fluid composition at the point of vapor saturation (XH2O). We show that fluid inclusions in crystal-hosts from mafic compositions (<57 wt. % SiO2) — likely representative of magmas recharging many volcanic systems worldwide — trap fluids with XH2O low enough to make fluid inclusion barometry useful at many of the world’s most active and hazardous mafic volcanic systems (e.g., Iceland, Hawaiʻi, Galápagos Islands, East African Rift, Réunion, Canary Islands, Azores, Cabo Verde).
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