{"pageNumber":"147","pageRowStart":"3650","pageSize":"25","recordCount":41062,"records":[{"id":70240475,"text":"70240475 - 2023 - When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates","interactions":[],"lastModifiedDate":"2023-11-08T16:48:35.179325","indexId":"70240475","displayToPublicDate":"2023-02-07T06:48:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates","docAbstract":"<p id=\"spara021\">Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.</p><p id=\"spara022\">Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (<i>i.e.,</i><span>&nbsp;</span>weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network.</p><p id=\"spara023\">We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score &lt; 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (<i>i.e.,</i><span>&nbsp;</span>training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (<i>e.g.,</i><span>&nbsp;</span>XGBoost) perform equally well or better than more complex methods (<i>e.g.,</i><span>&nbsp;</span>artificial neural networks) and remain easier to interpret.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102662","usgsCitation":"Mordensky, S.P., Lipor, J., DeAngelo, J., Burns, E., and Lindsey, C.R., 2023, When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates: Geothermics, v. 110, 102662, 22 p., https://doi.org/10.1016/j.geothermics.2023.102662.","productDescription":"102662, 22 p.","ipdsId":"IP-142531","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":444577,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2023.102662","text":"Publisher Index Page"},{"id":435466,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V1Q9XM","text":"USGS data release","linkHelpText":"Geothermal resource favorability: select features and predictions for the western United States curated for DOI 10.1016/j.geothermics.2023.102662"},{"id":412868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -127.12518216384296,\n              49.86387644792583\n            ],\n            [\n              -127.12518216384296,\n              31.096405781605768\n            ],\n            [\n              -102.87766710543923,\n              31.096405781605768\n            ],\n            [\n              -102.87766710543923,\n              49.86387644792583\n            ],\n            [\n              -127.12518216384296,\n              49.86387644792583\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"110","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":863887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863890,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240262,"text":"sir20225128 - 2023 - Groundwater quality near the Montebello Oil Field, Los Angeles County, California","interactions":[],"lastModifiedDate":"2023-09-18T19:56:22.528962","indexId":"sir20225128","displayToPublicDate":"2023-02-06T13:11:18","publicationYear":"2023","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":"2022-5128","displayTitle":"Groundwater Quality Near the Montebello Oil Field, Los Angeles County, California","title":"Groundwater quality near the Montebello Oil Field, Los Angeles County, California","docAbstract":"<p>Groundwater quality and potential sources and migration pathways of chemical constituents associated with hydrocarbon-bearing formations were assessed by the U.S. Geological Survey for the California State Water Resources Control Board Oil and Gas Regional Monitoring Program (RMP). Groundwater samples were collected as part of the RMP from 21 preexisting wells used for public supply, monitoring, or irrigation in and near the Montebello Oil Field and analyzed for constituents associated with hydrocarbon-bearing formations and constituents used to identify recently recharged groundwater and older groundwater. The newly collected RMP data were supplemented with historical sample data from 849 groundwater wells and analyzed with respect to explanatory factors that have the potential to influence water quality. Potential sources and migration pathways of fluids (water, gas, or oil) from hydrocarbon-bearing formations that could affect groundwater quality in the Montebello Oil Field include large volumes of recycled produced water (water withdrawn from an oil well and brought to the surface that may include oil, water, and gas from the geologic formation and water or gas injected for enhanced recovery) that have been reinjected since the 1960s to enhance oil production, oil and gas wells with well-integrity issues, and oil and gas wells with an uncemented annulus that intersects groundwater resource zones.<br>Trace amounts of dissolved petroleum hydrocarbons, thermogenic gas (propane through pentane range), or both, were detected in seven groundwater samples collected in 2014 and 2018 as part of the RMP. Five of those samples also contained manufactured volatile organic compounds and at least some modern-age groundwater (recharged during or after 1953), indicating that the hydrocarbons could have originated from surficial, or shallow, sources unrelated to oil and gas development. Two samples contained low concentrations of petroleum hydrocarbons (less than 0.1 microgram per liter) and did not contain detections of manufactured volatile organic compounds in pre-modern groundwater. These samples were collected from relatively deep wells (greater than 140 meters below land surface) with perforations completed in marine sediments that may contain water with similar compositions to produced water.<br>The RMP sample results and available historical data in and near the Montebello Oil Field did not provide conclusive evidence that oil and gas development has adversely affected groundwater resources. All samples with detectable petroleum hydrocarbons, thermogenic gases, or both, were collected from sites that also are within 500 meters of anthropogenic hydrocarbon sources not associated with oil and gas development or sources. In addition, naturally occurring sources of hydrocarbons that exist at intervals shallower than, or are in areas outside of, economically productive oil- and gas-producing zones could affect groundwater quality.<br>A definitive analysis of relations of groundwater quality to potential anthropogenic and natural explanatory factors was not possible because of the low density of new and historical sampling data, particularly in parts of the Montebello Oil Field where the largest relative risks to groundwater from hydrocarbon-bearing formations exist. Areas to consider for more detailed monitoring and analysis in the future that may present the largest relative potential risks to groundwater quality include (1) areas downgradient from historical surface ponds and sumps and (2) areas with co-located high net injection (oil reservoir injection exceeds production), old oil and gas wells that may be more likely to develop well-integrity issues than newer wells, and oil and gas wells with uncemented boreholes intersecting groundwater zones. To help fill gaps resulting from sparse groundwater wells, temperature and resistivity borehole log data could be analyzed to locate anomalies that identify potential areas where relatively warm or saline water from deeper hydrocarbon-bearing formations is present in groundwater.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225128","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Stanton, J.S., Land, M., Landon, M.K., Shimabukuro, D.H., McMahon, P.B., Davis, T.A., Hunt, A.G., and Sowers, T.A., 2023, Groundwater quality near the Montebello Oil Field, Los Angeles County, California: U.S. Geological Survey Scientific Investigations Report 2022–5128, 80 p., https://doi.org/10.3133/sir20225128.","productDescription":"Report: ix, 80 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128118","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":412628,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FZ2SBH","text":"USGS data release","description":"USGS data release","linkHelpText":"Water chemistry data for samples collected at groundwater sites in the Montebello Oil Field study area, September 2014–October 2018, Los Angeles County, California"},{"id":412629,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5128/images"},{"id":412627,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225128/full","text":"Reports","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5128"},{"id":412626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5128/sir20225128.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5128"},{"id":412625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5128/coverthb.jpg"},{"id":412630,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5128/sir20225128.XML"}],"country":"United States","state":"California","otherGeospatial":"Montebello Oil Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.12,\n              34.04\n            ],\n            [\n              -118.12,\n              34.00\n            ],\n            [\n              -118.02,\n              34.00\n            ],\n            [\n              -118.02,\n              34.04\n            ],\n            [\n              -118.12,\n              34.04\n            ]\n          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jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":863144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Tracy A. 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":2715,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":863146,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":863147,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sowers, Theron A. 0000-0002-3208-5411","orcid":"https://orcid.org/0000-0002-3208-5411","contributorId":301944,"corporation":false,"usgs":false,"family":"Sowers","given":"Theron A.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":863148,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256526,"text":"70256526 - 2023 - Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models","interactions":[],"lastModifiedDate":"2024-08-22T11:07:08.990132","indexId":"70256526","displayToPublicDate":"2023-02-06T11:29:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18324,"text":"Hydrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models","docAbstract":"<p><span>Stoneflies are a globally threatened aquatic insect order. In Arkansas, a diverse group of winter stonefly (Capniidae:&nbsp;</span><span class=\"html-italic\">Allocapnia</span><span>) have not been surveyed since the 1980s, likely because species-level identification requires the rarely-collected adult form.&nbsp;</span><i><span class=\"html-italic\">Allocapnia mohri</span></i><span>, a regional endemic, was previously commonly found in mountainous, intermittent streams from the Ouachita Mountains ecoregion north to the Ozark Highlands, but no species distributional models including land use or climate variables exist to our knowledge. We collected adults from 71 stream reaches from the historic Arkansas range from November to April 2020 and 2021. We modeled distributions using random forest (RF) models populated with landscape, climate, and both data to determine which were most predictive of species presence. Correlations between landscape or climate variables and presence were examined using multiple logistic regression. The landscape RF models performed better than the climate or landscape + climate RF models.&nbsp;</span><i><span class=\"html-italic\">A. mohri</span></i><span>&nbsp;presence sites tended to have a greater elevation, a lower mean July temperature, and a greater percentage of very slow infiltration soils in the watershed, compared to absence sites.&nbsp;</span><i><span class=\"html-italic\">A. mohri</span></i><span>&nbsp;was absent at the Ouachita Mountains sites and may be experiencing a range contraction or migration northward.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/hydrobiology2010013","usgsCitation":"Annaratone, B., Larson, C., Prater, C., Dowling, A., Magoulick, D.D., and Evans-White, M.A., 2023, Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models: Hydrobiology, v. 2, no. 1, p. 196-211, https://doi.org/10.3390/hydrobiology2010013.","productDescription":"16 p.","startPage":"196","endPage":"211","ipdsId":"IP-148164","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":444581,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrobiology2010013","text":"Publisher Index Page"},{"id":433011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.01694463644638,\n              36.49973760721201\n            ],\n            [\n              -94.64880267254001,\n              36.47406350173745\n            ],\n            [\n              -94.42836217709565,\n              35.38954127077116\n            ],\n            [\n              -94.47263609475836,\n              33.690237372303145\n            ],\n            [\n              -93.92329526083718,\n              33.50875350986783\n            ],\n            [\n              -93.15882305498532,\n              33.95704519399207\n            ],\n            [\n              -92.44070215460535,\n              34.644196725743356\n            ],\n            [\n              -91.1183522293626,\n              35.76377161713451\n            ],\n            [\n              -91.01694463644638,\n              36.49973760721201\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Annaratone, Brianna","contributorId":341024,"corporation":false,"usgs":false,"family":"Annaratone","given":"Brianna","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Camryn","contributorId":341025,"corporation":false,"usgs":false,"family":"Larson","given":"Camryn","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prater, Clay","contributorId":341026,"corporation":false,"usgs":false,"family":"Prater","given":"Clay","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dowling, Ashley","contributorId":341027,"corporation":false,"usgs":false,"family":"Dowling","given":"Ashley","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":907822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans-White, Michelle A.","contributorId":341028,"corporation":false,"usgs":false,"family":"Evans-White","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70241253,"text":"70241253 - 2023 - Ice and ocean constraints on early human migrations into North America along the Pacific Coast","interactions":[],"lastModifiedDate":"2023-03-16T13:29:11.876097","indexId":"70241253","displayToPublicDate":"2023-02-06T08:21:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Ice and ocean constraints on early human migrations into North America along the Pacific Coast","docAbstract":"<p><span>Founding populations of the first Americans likely occupied parts of Beringia during the Last Glacial Maximum (LGM). The timing, pathways, and modes of their southward transit remain unknown, but blockage of the interior route by North American ice sheets between ~26 and 14 cal kyr BP (ka) favors a coastal route during this period. Using models and paleoceanographic data from the North Pacific,&nbsp;we identify climatically favorable intervals when humans could have plausibly traversed the Cordilleran coastal corridor during the terminal Pleistocene. Model simulations suggest that northward coastal currents strengthened during the LGM and at times of enhanced freshwater input, making southward transit by boat more difficult. Repeated Cordilleran glacial-calving events would have further challenged coastal transit on land and at sea. Following these events, ice-free coastal areas opened and seasonal sea ice was present along the Alaskan margin until at least 15 ka. Given evidence for humans south of the ice sheets by 16 ka and possibly earlier, we posit that early people may have taken advantage of winter sea ice that connected islands and coastal refugia. Marine ice-edge habitats offer a rich food supply and traversing coastal sea ice could have mitigated the difficulty of traveling southward in watercraft or on land over glaciers.&nbsp;We identify 24.5 to 22 ka and 16.4 to 14.8 ka as environmentally favorable time periods for coastal migration, when climate conditions provided both winter sea ice and ice-free summer conditions that facilitated year-round marine resource diversity and multiple modes of mobility along the&nbsp;North Pacific coast.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2208738120","usgsCitation":"Praetorius, S.K., Alder, J.R., Condron, A., Mix, A., Walczak, M., Caissie, B.E., and Erlandson, J., 2023, Ice and ocean constraints on early human migrations into North America along the Pacific Coast: Proceedings of the National Academy of Sciences, v. 120, no. 7, e2208738120, 11 p., https://doi.org/10.1073/pnas.2208738120.","productDescription":"e2208738120, 11 p.","ipdsId":"IP-133916","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":444585,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://archimer.ifremer.fr/doc/00820/93170/","text":"Publisher Index Page"},{"id":435467,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95V8DP2","text":"USGS data release","linkHelpText":"Data release for Ice and ocean constraints on early human migrations into North America along the Pacific coast"},{"id":414279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Pacific Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.72062762561171,\n              38.37875574725757\n            ],\n            [\n              -119.99459846253501,\n              39.301388384686106\n            ],\n            [\n              -122.4899431341521,\n              50.08880882681328\n            ],\n            [\n              -133.2466928684764,\n              60.77522068257534\n            ],\n            [\n              -146.986168078397,\n              63.47516560131629\n            ],\n            [\n              -159.91403683656446,\n              70.55186684208343\n            ],\n            [\n              -169.5393000094379,\n              69.74709289484804\n            ],\n            [\n              -170.83530973680112,\n              63.391879804034915\n            ],\n            [\n              -179.9,\n              50.520343621759565\n            ],\n            [\n              -156.35796682332455,\n              54.28410261306894\n            ],\n            [\n              -142.96073969458683,\n              58.298844624993336\n            ],\n            [\n              -129.39963004812796,\n              49.10107755766387\n            ],\n            [\n              -126.51878468736493,\n              43.42260588965587\n            ],\n            [\n              -123.72062762561171,\n              38.37875574725757\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - 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,{"id":70242966,"text":"70242966 - 2023 - Dynamics of the wave-driven circulation in the lee of nearshore reefs","interactions":[],"lastModifiedDate":"2023-04-25T11:45:54.368684","indexId":"70242966","displayToPublicDate":"2023-02-06T06:41:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12811,"text":"JGR-Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of the wave-driven circulation in the lee of nearshore reefs","docAbstract":"<div class=\"article-section__content en main\"><p>Nearshore rocky reefs with scales of order 10–100&nbsp;m are common along the world's coastline and often shape wave-driven hydrodynamics and shoreline morphology in their lee. The interaction of waves with these reefs generally results in either two or four-cell mean circulation systems (2CC and 4CC, respectively), with diverging flows behind the reefs and at the shoreline in the 2CC case and flows that diverge in the lee and converge at the shoreline in the 4CC case. By applying a phase-resolving wave-flow model to conduct a&nbsp;detailed analysis of mean momentum balances for waves interacting with nearshore reefs, we develop an understanding of the drivers of 2CC and 4CC flow dynamics and how they vary for different reef geometries and wave and&nbsp;water&nbsp;level&nbsp;conditions. The 2CC or 4CC patterns were primarily driven by alongshore pressure gradients toward the exposed (nonreef fronted) or reef-fronted beach. These alongshore pressure gradients were dependent on the cross-shore setup dynamics governed by the balance between pressure (i.e., related to the setup) and radiation stress gradients, and mean bottom stresses exerted on the water column. If shoreline wave setup in the lee of the reef was less than the exposed beach, a 4CC pattern developed with convergent flow at the shoreline in the lee of the reef; otherwise, a 2CC emerged with divergent flow at the shoreline. Across the parameter space investigated, reef roughness, distance to the shoreline, and beach slope were the three parameters most likely to change the flow patterns between 2CC and 4CC.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JC019013","usgsCitation":"da Silva, R.F., Hansen, J., Lowe, R., Rijnsdorp, D.P., and Buckley, M.L., 2023, Dynamics of the wave-driven circulation in the lee of nearshore reefs: JGR-Oceans, v. 128, no. 3, e2022JC019013, 25 p., https://doi.org/10.1029/2022JC019013.","productDescription":"e2022JC019013, 25 p.","ipdsId":"IP-139998","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jc019013","text":"Publisher Index Page"},{"id":416227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"da Silva, Renan F.","contributorId":304414,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Jeff","contributorId":304415,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Ryan","contributorId":304417,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rijnsdorp, Dirk P.","contributorId":304416,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":870369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870371,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70262362,"text":"70262362 - 2023 - Birth rates and neonate survival in a parasite rich moose population in Vermont, USA","interactions":[],"lastModifiedDate":"2025-01-23T15:49:46.104582","indexId":"70262362","displayToPublicDate":"2023-02-05T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":693,"text":"Alces","active":true,"publicationSubtype":{"id":10}},"title":"Birth rates and neonate survival in a parasite rich moose population in Vermont, USA","docAbstract":"<p><span>Moose (</span><i>Alces alces</i><span>) populations are declining across much of their southern geographic range in North America. In Vermont and other northeastern states, measurable declines are attributed to low calf survival and reduced productivity associated with persistent winter tick (</span><i>Dermacentor albipictus</i><span>) parasitism. In 2017–2020, we studied 75 radio-collared female moose (38 calves and 37 adults) in Vermont to examine physiological, spatial, and temporal parameters relative to calf survival and adult productivity. Physiological measures included concentration of fecal glucocorticoid metabolites (fGCM) which reflects stress, and urea nitrogen:creatinine ratios in urine (UN:C) which proxy nutritional state. The pregnancy rate at capture across years was 0.67 (95% CI = 0.50 – 0.80), and was negatively related to presence of lungworm (</span><i>Dictyocaulus</i><span>&nbsp;spp.). The birth rate calculated as the average number of offspring delivered per adult female was &lt;1.0 overall (2017–2020, LCI = 0.22, UCI = 0.86), similar across years, but increased with age. Logistic exposure models indicated that daily calf survival to 60 d increased as Julian birth date and days since birth increased (log odds = 0.0819, SE = 0.0215). The per capita independence rate, or rate that adult females add independent calves to the population, was negatively related to UN:C ratios and positively with fGCM. Further, this rate was related to autumnal habitat use of adult females; it was greater in home ranges characterized by large amounts of mature (canopy) evergreen forests and wetland habitats, and small amounts of mixed forests and elevation than in ranges with abundant levels of mixed forest at high elevation. We conclude that winter ticks can negatively affect moose fecundity, and efforts to reduce host (moose) density through harvest or parasite (host) abundance through habitat manipulation may improve productivity and recruitment in local moose populations.</span></p>","language":"English","publisher":"Lakehead University","usgsCitation":"DeBow, J., Blouin, J., Rosenblatt, E., Alexander, C., Fortin, N., Gieder, K., Murdoch, J., and Donovan, T.M., 2023, Birth rates and neonate survival in a parasite rich moose population in Vermont, USA: Alces, v. 58, p. 51-73.","productDescription":"23 p.","startPage":"51","endPage":"73","ipdsId":"IP-139061","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480995,"rank":1,"type":{"id":15,"text":"Index 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James","contributorId":349022,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":923929,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923931,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70260146,"text":"70260146 - 2023 - Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes","interactions":[],"lastModifiedDate":"2024-10-29T14:32:35.765073","indexId":"70260146","displayToPublicDate":"2023-02-04T09:26:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes","docAbstract":"<div id=\"preview-section-abstract\"><div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><div id=\"sp0065\" class=\"u-margin-s-bottom\"><span>We investigate the rates of magmatic processes using&nbsp;clinopyroxene&nbsp;diffusion chronometry on volcanic products erupted in August 2017 at the end of the 9-month eruption of Bogoslof volcano. The eruptive products contain plagioclase,&nbsp;clinopyroxene, and&nbsp;amphibole, all of which exhibit sharp chemical boundaries and are occasionally observed in multi-phase crystal clots with shared zoning boundaries across different mineral phases. At the shared boundaries in crystal clots, clinopyroxene and plagioclase continued to grow but abruptly changed composition from Mg# 81.7&nbsp;±&nbsp;5.8 to 72.9&nbsp;±&nbsp;3.0 and An</span><sub>82.5±1.4</sub><span>&nbsp;</span>to An<sub>61.3±5.7</sub><span>, respectively. Additionally, the sharp boundary marks where&nbsp;amphibole&nbsp;became unstable and began forming a reaction rim. Synthesizing these observations, we were able to determine that the shared boundaries formed as a result of rapid decompression during&nbsp;magma&nbsp;ascent, followed by storage in a shallow cryptodome, where&nbsp;magma&nbsp;accumulated prior to erupting.</span></div><div class=\"u-margin-s-bottom\"><span><br data-mce-bogus=\"1\"></span></div><div id=\"sp0070\" class=\"u-margin-s-bottom\"><span>In order to determine the timescales of magma ascent and subsequent crystal residence times, we applied diffusion chronometry on zoned clinopyroxene&nbsp;phenocrysts&nbsp;using Mg# concentrations at 1056&nbsp;°C determined from Fe</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">Ti oxide pairs. Our diffusion modeling results show that diffusion began at the stepwise boundaries in clinopyroxenes no more than180&nbsp;days before the final explosive event.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0075\" class=\"u-margin-s-bottom\">These results were then used to calculate crystal growth rates for shared plagioclase and amphibole rims, as shared zones in crystal clots indicate that the boundaries in all three phases formed contemporaneously. We calculate growth rates of plagioclase crystals (1.7&nbsp;±&nbsp;0.99&nbsp;×&nbsp;10<sup>−6</sup><span>&nbsp;</span>um/s) and amphibole reaction rims (2.8&nbsp;±&nbsp;0.47&nbsp;×&nbsp;10<sup>−6</sup><span>&nbsp;</span>um/s). The calculated natural growth rate of plagioclase was then used to constrain additional magmatic timescales from growth rate chronometry, results of which support our diffusion timescales.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0080\" class=\"u-margin-s-bottom\"><span>Our results indicate that the distinct boundaries in all three mineral phases formed due to ascent-driven decompression followed by shallow emplacement of mafic magma that occurred continually throughout the course of the eruption. By subtracting diffusion timescales from the date that the samples were erupted, the oldest crystal boundaries correspond to March 2017, seemingly correlating with increases in both&nbsp;seismicity&nbsp;and SO</span><sub>2</sub><span>&nbsp;</span>emissions. These observations may suggest that our petrochronometric results are supported by interdisciplinary observations.</div></div></div></div></div><div id=\"preview-section-introduction\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107741","usgsCitation":"Moshrefzadeh, J., Izbekof, P., Loewen, M.W., Larsen, J., and Regan, S., 2023, Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes: Journal of Volcanology and Geothermal Research, v. 435, 107741, 16 p., https://doi.org/10.1016/j.jvolgeores.2022.107741.","productDescription":"107741, 16 p.","ipdsId":"IP-140665","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2022.107741","text":"Publisher Index Page"},{"id":463335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.04917846434188,\n              53.937993642724905\n            ],\n            [\n              -168.04917846434188,\n              53.92389191228028\n            ],\n            [\n              -168.0270096873428,\n              53.92389191228028\n            ],\n            [\n              -168.0270096873428,\n              53.937993642724905\n            ],\n            [\n              -168.04917846434188,\n              53.937993642724905\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"435","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moshrefzadeh, Jamshid 0000-0001-7333-5651","orcid":"https://orcid.org/0000-0001-7333-5651","contributorId":242807,"corporation":false,"usgs":false,"family":"Moshrefzadeh","given":"Jamshid","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbekof, Pavel 0000-0001-9052-7655","orcid":"https://orcid.org/0000-0001-9052-7655","contributorId":242806,"corporation":false,"usgs":false,"family":"Izbekof","given":"Pavel","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, Sean P.","contributorId":219815,"corporation":false,"usgs":false,"family":"Regan","given":"Sean P.","affiliations":[{"id":13599,"text":"University of Alaska - Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917196,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240729,"text":"70240729 - 2023 - A restructured Bayesian approach to estimate the abundance of a rare and invasive fish","interactions":[],"lastModifiedDate":"2023-05-25T15:45:17.03652","indexId":"70240729","displayToPublicDate":"2023-02-04T07:20:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"A restructured Bayesian approach to estimate the abundance of a rare and invasive fish","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section c-article-content-visibility\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Quantifying invasive species abundance informs management and control strategies. However, estimating abundance can be challenging, particularly when dealing with rare species early in the invasion process. Data generated from control strategies, such as removing invasive species, are usually not suited to conventional statistical modelling approaches. Hence, we developed a Bayesian model using data generated by a grass carp (<i>Ctenopharyngodon idella</i>) control program in the Sandusky River, Ohio (USA) for estimating the abundance of rare, invasive species. The model is a restructured N-mixture model modified to incorporate the data generating process (i.e., setting a trammel net to isolate a sampling area followed by boat-mounted electrofishing). Allowing the estimation of grass carp abundance from the species removal data, which had very few detections relative to the sampling effort. Our results indicated that the average number of grass carp present in the river at any one time did not change substantially from 2018 to 2020. The highest abundance estimates were in the lower and upper-middle segments of the river, suggesting possible recolonization from Lake Erie, and possibly other tributaries. Ultimately, the ability to use species-control data to estimate abundance provides important information for management, particularly for invasive ‘sleeper’ species in freshwater ecosystems.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03006-6","usgsCitation":"Gouveia, A., Qian, S.S., Mayer, C.A., Smith, J.A., Bossenbroek, J., Hintz, W.D., Mapes, R., Weimer, E., Navarro, J., Dettmers, J.M., Young, R., Buszkiewicz, J., and Kocovsky, P.M., 2023, A restructured Bayesian approach to estimate the abundance of a rare and invasive fish: Biological Invasions, v. 25, p. 1711-1721, https://doi.org/10.1007/s10530-023-03006-6.","productDescription":"11 p.","startPage":"1711","endPage":"1721","ipdsId":"IP-131639","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":413170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.17770473625303,\n              41.308643520054744\n            ],\n            [\n              -82.89527024570958,\n              41.308643520054744\n            ],\n            [\n              -82.89527024570958,\n              41.49866213865516\n            ],\n            [\n              -83.17770473625303,\n              41.49866213865516\n            ],\n            [\n              -83.17770473625303,\n              41.308643520054744\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2023-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gouveia, Ana R.","contributorId":302502,"corporation":false,"usgs":false,"family":"Gouveia","given":"Ana R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qian, S. S.","contributorId":243524,"corporation":false,"usgs":false,"family":"Qian","given":"S.","email":"","middleInitial":"S.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayer, C. A.","contributorId":156230,"corporation":false,"usgs":false,"family":"Mayer","given":"C.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":864558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, J. A.","contributorId":219770,"corporation":false,"usgs":false,"family":"Smith","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":864559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bossenbroek, J.","contributorId":302503,"corporation":false,"usgs":false,"family":"Bossenbroek","given":"J.","email":"","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hintz, W. D.","contributorId":302504,"corporation":false,"usgs":false,"family":"Hintz","given":"W.","email":"","middleInitial":"D.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mapes, R.","contributorId":302505,"corporation":false,"usgs":false,"family":"Mapes","given":"R.","email":"","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weimer, E.","contributorId":302506,"corporation":false,"usgs":false,"family":"Weimer","given":"E.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Navarro, J.","contributorId":302507,"corporation":false,"usgs":false,"family":"Navarro","given":"J.","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864564,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dettmers, J. M.","contributorId":302508,"corporation":false,"usgs":false,"family":"Dettmers","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":864565,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Young, R.","contributorId":241798,"corporation":false,"usgs":false,"family":"Young","given":"R.","affiliations":[{"id":48424,"text":"UAE University","active":true,"usgs":false}],"preferred":false,"id":864566,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Buszkiewicz, J. T.","contributorId":302509,"corporation":false,"usgs":false,"family":"Buszkiewicz","given":"J. T.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864567,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":864568,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70240278,"text":"70240278 - 2023 - Ecotoxicological studies indicate that sublethal and lethal processes limit insect-mediated contaminant flux","interactions":[],"lastModifiedDate":"2023-09-06T16:04:51.26529","indexId":"70240278","displayToPublicDate":"2023-02-03T09:59:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Ecotoxicological studies indicate that sublethal and lethal processes limit insect-mediated contaminant flux","docAbstract":"Merolimnic insects can accumulate and transport considerable amounts of aquatic contaminants to terrestrial systems. The rate of contaminant biotransport, termed insect-mediated contaminant flux (IMCF), depends on emergent insect biomass and contaminant accumulation, both functions of environmental concentration. Here we develop a mathematical model of IMCF and apply it to three ecotoxicological studies obtained through the U.S. Environmental Protection Agency's ECOTOX database to determine at which concentration maximum IMCF occurs. Model results demonstrate that the maximum IMCF depends on competing rates of biomass loss and contaminant accumulation and does not necessarily occur at the highest insect or environmental contaminant concentration. Additionally, modeling results suggest that sublethal contaminant effects (e.g., decreased growth) on insect biomass can be an important and potentially underappreciated control on IMCF.","language":"English","publisher":"Wiley","doi":"10.1002/etc.5574","usgsCitation":"Olson, C., Beaubien, G., Otter, R., Walters, D., and Mills. M.A, 2023, Ecotoxicological studies indicate that sublethal and lethal processes limit insect-mediated contaminant flux: Environmental Toxicology and Chemistry, v. 42, no. 9, p. 1982-1992, https://doi.org/10.1002/etc.5574.","productDescription":"11 p.","startPage":"1982","endPage":"1992","ipdsId":"IP-144950","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":444603,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5574","text":"Publisher Index Page"},{"id":412682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, C.I","contributorId":301967,"corporation":false,"usgs":false,"family":"Olson","given":"C.I","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":863220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaubien, G.B","contributorId":301968,"corporation":false,"usgs":false,"family":"Beaubien","given":"G.B","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":863221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Otter, R.R","contributorId":301970,"corporation":false,"usgs":false,"family":"Otter","given":"R.R","email":"","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":863222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205915,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":863223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills. M.A","contributorId":301972,"corporation":false,"usgs":false,"family":"Mills. M.A","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":863224,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240274,"text":"70240274 - 2023 - Enhancing the predictability of ecology in a changing world: A call for an organism-based approach","interactions":[],"lastModifiedDate":"2023-02-03T15:57:47.282162","indexId":"70240274","displayToPublicDate":"2023-02-03T09:51:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5523,"text":"Frontiers in Applied Mathematics and Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Enhancing the predictability of ecology in a changing world: A call for an organism-based approach","docAbstract":"Ecology is usually very good in making descriptive explanations of what is observed, but is often unable to make predictions of the response of ecosystems to change. This has implications in a human-dominated world where a suite of anthropogenic stresses are threatening the resilience and functioning of ecosystems that sustain mankind through a range of critical regulating and supporting services. In ecosystems, cause-and-effect relationships are difficult to elucidate because of complex networks of negative and positive feedbacks. Therefore, being able to effectively predict when and where ecosystems could pass into different (and potentially unstable) new states is vitally important under rapid global change. Here, we argue that such better predictions may be reached if we focus on organisms instead of species, because organisms are the principal biotic agents in ecosystems that react directly on changes in their environment. Several studies show that changes in ecosystems may be accurately described as the result of changes in organisms and their interactions. Organism-based theories are available that are simple and derived from first principles, but allow many predictions. Of these we discuss Trait-based Ecology, Agent Based Models, and Maximum Entropy Theory of Ecology and show that together they form a logical sequence of approaches that allow organism-based studies of ecological communities. Combining and extending them makes it possible to predict the spatiotemporal distribution of groups of organisms in terms of how metabolic energy is distributed over areas, time, and resources. We expect that this “Organism-based Ecology” (OE) ultimately will improve our ability to predict ecosystem dynamics.","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fams.2023.1046185","usgsCitation":"Musters, C., DeAngelis, D., Harvey, J.A., Mooij, W.M., van Bodegom, P.M., and de Snoo, G.R., 2023, Enhancing the predictability of ecology in a changing world: A call for an organism-based approach: Frontiers in Applied Mathematics and Statistics, v. 9, 1046185, 10 p., https://doi.org/10.3389/fams.2023.1046185.","productDescription":"1046185, 10 p.","ipdsId":"IP-141728","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444606,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fams.2023.1046185","text":"Publisher Index Page"},{"id":412681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2023-01-24","publicationStatus":"PW","contributors":{"editors":[{"text":"Siekmann, Ivo","contributorId":302056,"corporation":false,"usgs":false,"family":"Siekmann","given":"Ivo","email":"","affiliations":[],"preferred":false,"id":863367,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Musters, C.J.M.","contributorId":301956,"corporation":false,"usgs":false,"family":"Musters","given":"C.J.M.","email":"","affiliations":[{"id":65374,"text":"Institute of Environmental Sciences, Leiden University","active":true,"usgs":false}],"preferred":false,"id":863207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Don 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":221357,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Don","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":863208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Jeffrey A.","contributorId":301957,"corporation":false,"usgs":false,"family":"Harvey","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":35358,"text":"Netherlands Institute of Ecology","active":true,"usgs":false}],"preferred":false,"id":863209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mooij, Wolf M.","contributorId":215556,"corporation":false,"usgs":false,"family":"Mooij","given":"Wolf","email":"","middleInitial":"M.","affiliations":[{"id":39277,"text":"Dept. of Aquatic Ecology, Netherlands Institute of Ecology, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":863210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Bodegom, Peter M.","contributorId":301958,"corporation":false,"usgs":false,"family":"van Bodegom","given":"Peter","email":"","middleInitial":"M.","affiliations":[{"id":65374,"text":"Institute of Environmental Sciences, Leiden University","active":true,"usgs":false}],"preferred":false,"id":863211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"de Snoo, Geert R.","contributorId":301959,"corporation":false,"usgs":false,"family":"de Snoo","given":"Geert","email":"","middleInitial":"R.","affiliations":[{"id":65376,"text":"Institute of Environmental Sciences, Leiden University and Netherlands Institute of Ecology","active":true,"usgs":false}],"preferred":false,"id":863212,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70243018,"text":"70243018 - 2023 - Mineralogical, magnetic and geochemical data constrain the pathways and extent of weathering of mineralized sedimentary rocks","interactions":[],"lastModifiedDate":"2023-04-26T12:05:16.59314","indexId":"70243018","displayToPublicDate":"2023-02-03T06:56:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Mineralogical, magnetic and geochemical data constrain the pathways and extent of weathering of mineralized sedimentary rocks","docAbstract":"<p id=\"sp0005\">The oxidative weathering of sulfidic rock can profoundly impact watersheds through the resulting export of acidity and metals. Weathering leaves a record of mineral transformation, particularly involving minor redox-sensitive phases, that can inform the development of conceptual and quantitative models. In sulfidic sedimentary rocks, however, variations in depositional history,<span>&nbsp;</span>diagenesis<span>&nbsp;and&nbsp;mineralization&nbsp;can change or overprint the distributions of these trace minerals, complicating the interpretation of weathering signatures. Here we show that a combination of bulk mineralogical and geochemical techniques, micrometer-resolution X-ray fluorescence microprobe analysis and rock magnetic measurements, applied to drill core samples and single weathered fractures, can provide data that enable the development of a geochemically consistent weathering model.</span></p><p id=\"sp0010\"><span>This work focused on one watershed in the Upper Colorado River Basin sitting within the Mesaverde Formation, a sedimentary sandstone bedrock with disseminated sulfide minerals, including pyrite and&nbsp;sphalerite, that were introduced during diagenesis and subsequent magmatic-hydrothermal mineralization. Combined analytical methods revealed the pathways of iron (Fe), carbonate and&nbsp;silicate mineral&nbsp;weathering and showed how pH controls element retention or release from the actively weathering fractured sandstone. Drill core logging, whole rock X-ray diffraction, and geochemical measurements document the progression from unweathered rock at depth to weathered rock at the surface. X-ray microprobe analyses of a 1-cm size weathering profile along a fracture surface are consistent with the mobilization of Fe(II) and Fe(III) into acidic&nbsp;pore water&nbsp;from the dissolution of primary pyrite, Fe-sphalerite, chlorite, and minor&nbsp;siderite&nbsp;and&nbsp;pyrrhotite. These reactions are followed by the precipitation of secondary minerals such as of&nbsp;goethite&nbsp;and&nbsp;jarosite, a Fe-(oxyhydr)oxide and hydrous Fe(III) sulfate, respectively.&nbsp;</span>Microscale<span>&nbsp;analyses also helped explain the weathering reactions responsible for the mineralogical transformations observed in the top and most weathered section of the drill core. For example, dissolution of feldspar and chlorite neutralizes the acidity generated by Fe and sulfide mineral oxidation, oversaturating the solution in both Fe-oxides. The combination of X-ray spectromicroscopy and magnetic measurements show that the Fe(III) product is goethite, mainly present either as a coatings on fracture surfaces in the actively weathering region of the core or more homogeneously contained within the unconsolidated&nbsp;regolith&nbsp;at the top of the core. Low-temperature magnetic data reveal the presence of ferromagnetic Fe-sulfide pyrrhotite that, although it occurs at trace concentrations, could provide a qualitative proxy for unweathered sulfide minerals because the loss of pyrrhotite is associated with the onset of oxidative weathering. Pyrrhotite loss and goethite formation are detectable through room-temperature magnetic&nbsp;coercivity&nbsp;changes, suggesting that rock magnetic measurements can determine weathering intensity in rock samples at many scales. This work contributes evidence that the weathering of sulfidic sedimentary rocks follows a geochemical pattern in which the abundance of sulfide minerals controls the generation of acidity and dissolved elements, and the pH-dependent mobility of these elements controls their export to the ground- and surface-water.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2022.11.005","usgsCitation":"Carrero, S., Slotznick, S.P., Fakra, S.C., Sitar, M.C., Bone, S.E., Mauk, J.L., Manning, A.H., Swanson-Hysell, N., Williams, K.H., Banfield, J.F., and Gilbert, B., 2023, Mineralogical, magnetic and geochemical data constrain the pathways and extent of weathering of mineralized sedimentary rocks: Geochimica et Cosmochimica Acta, v. 343, p. 180-195, https://doi.org/10.1016/j.gca.2022.11.005.","productDescription":"16 p.","startPage":"180","endPage":"195","ipdsId":"IP-144517","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":444613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/9rx7w6vm","text":"Publisher Index Page"},{"id":416368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.02298126226637,\n              54.47123140197621\n            ],\n            [\n              -107.02298126226637,\n              53.04438952769195\n            ],\n            [\n              -106.457428641961,\n              53.04438952769195\n            ],\n            [\n              -106.457428641961,\n              54.47123140197621\n            ],\n            [\n              -107.02298126226637,\n              54.47123140197621\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.17636327510458,\n              38.98415958443957\n            ],\n            [\n              -107.17636327510458,\n              38.76066749873635\n            ],\n            [\n              -106.78664053376538,\n              38.76066749873635\n            ],\n            [\n              -106.78664053376538,\n              38.98415958443957\n            ],\n            [\n              -107.17636327510458,\n              38.98415958443957\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"343","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carrero, Sergio","contributorId":304474,"corporation":false,"usgs":false,"family":"Carrero","given":"Sergio","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":870596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slotznick, Sarah P.","contributorId":298122,"corporation":false,"usgs":false,"family":"Slotznick","given":"Sarah","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":870597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fakra, Sirine C.","contributorId":304475,"corporation":false,"usgs":false,"family":"Fakra","given":"Sirine","email":"","middleInitial":"C.","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":870598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sitar, M. Cole","contributorId":304476,"corporation":false,"usgs":false,"family":"Sitar","given":"M.","email":"","middleInitial":"Cole","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":870599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bone, Sharon E.","contributorId":304477,"corporation":false,"usgs":false,"family":"Bone","given":"Sharon","email":"","middleInitial":"E.","affiliations":[{"id":36408,"text":"SLAC National Accelerator Laboratory","active":true,"usgs":false}],"preferred":false,"id":870600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":870601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":870602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Swanson-Hysell, Nicholas L.","contributorId":304479,"corporation":false,"usgs":false,"family":"Swanson-Hysell","given":"Nicholas L.","affiliations":[],"preferred":false,"id":870606,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, Kenneth H.","contributorId":268895,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","email":"","middleInitial":"H.","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":870607,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Banfield, Jillian F.","contributorId":152634,"corporation":false,"usgs":false,"family":"Banfield","given":"Jillian","email":"","middleInitial":"F.","affiliations":[{"id":18952,"text":"Department of Earth and Planetary Science, University of California Berkeley, CA 94720, USA","active":true,"usgs":false}],"preferred":false,"id":870608,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gilbert, Benjamin","contributorId":304478,"corporation":false,"usgs":false,"family":"Gilbert","given":"Benjamin","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":870603,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70240928,"text":"70240928 - 2023 - A Bayesian multi-stage modelling framework to evaluate impacts of energy development on wildlife populations: An application to Greater Sage-Grouse (Centrocercus urophasianus)","interactions":[],"lastModifiedDate":"2023-03-01T12:44:09.159474","indexId":"70240928","displayToPublicDate":"2023-02-03T06:41:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7479,"text":"MethodsX","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian multi-stage modelling framework to evaluate impacts of energy development on wildlife populations: An application to Greater Sage-Grouse (Centrocercus urophasianus)","docAbstract":"<p><span>Increased demand for domestic production of renewable energy has led to expansion of energy infrastructure across western North America. Much of the western U.S. comprises remote landscapes that are home to a variety of vegetation communities and wildlife species, including the imperiled sagebrush ecosystem and indicator species such as greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>). Geothermal sources in particular have potential for continued development across the western U.S. but impacts to greater sage-grouse and other species are unknown. To address this information gap, we describe a novel two-pronged methodology that analyzes impacts of geothermal energy production on pattern and process of greater sage-grouse populations using (a) before-after control-impact (BACI) measures of population growth and lek absence rates and (b) concurrent-to-operation evaluations of demographic rates. Growth and absence rate analyses utilized 14 years of lek survey data collected prior (2005–2011) and concurrent (2012–2018) to geothermal operations at two sites in Nevada, USA. Demographic analyses utilized relocation data, restricted inference to concurrent years, and incorporated 17 additional control sites. Demographic results were applied to &gt;100 potential geothermal sites distributed across the study region to generate spatially explicit predictions of unrealized population-level impacts.</span></p><dl class=\"list\"></dl>","language":"English","publisher":"Elsevier","doi":"10.1016/j.mex.2023.102023","usgsCitation":"Prochazka, B.G., O’Neil, S.T., and Coates, P.S., 2023, A Bayesian multi-stage modelling framework to evaluate impacts of energy development on wildlife populations: An application to Greater Sage-Grouse (Centrocercus urophasianus): MethodsX, v. 10, 102023, 13 p., https://doi.org/10.1016/j.mex.2023.102023.","productDescription":"102023, 13 p.","ipdsId":"IP-133919","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444616,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mex.2023.102023","text":"Publisher Index Page"},{"id":435470,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OLC725","text":"USGS data release","linkHelpText":"Median Estimates of Impact Potential from Geothermal Energy Production Activities on Greater Sage-Grouse Populations in Nevada and California (2022)"},{"id":413524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865336,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241013,"text":"70241013 - 2023 - Shrinking body size and climate warming: Many freshwater salmonids do not follow the rule","interactions":[],"lastModifiedDate":"2023-04-12T14:28:25.004001","indexId":"70241013","displayToPublicDate":"2023-02-03T06:31:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Shrinking body size and climate warming: Many freshwater salmonids do not follow the rule","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Declining body size is believed to be a universal response to climate warming and has been documented in numerous studies of marine and anadromous fishes. The Salmonidae are a family of coldwater fishes considered to be among the most sensitive species to climate warming; however, whether the shrinking body size response holds true for freshwater salmonids has yet to be examined at a broad spatial scale. We compiled observations of individual fish lengths from long-term surveys across the Northern Hemisphere for 12 species of freshwater salmonids and used linear mixed models to test for spatial and temporal trends in body size (fish length) spanning recent decades. Contrary to expectations, we found a significant increase in length overall but with high variability in trends among populations and species. More than two-thirds of the populations we examined increased in length over time. Secondary regressions revealed larger-bodied populations are experiencing greater increases in length than smaller-bodied populations. Mean water temperature was weakly predictive of changes in body length but overall minimal influences of environmental variables suggest that it is difficult to predict an organism's response to changing temperatures by solely looking at climatic factors. Our results suggest that declining body size is not universal, and the response of fishes to climate change may be largely influenced by local factors. It is important to know that we cannot assume the effects of climate change are predictable and negative at a large spatial scale.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16626","usgsCitation":"Solakas, M., Feiner, Z.S., Al-Chokhachy, R., Budy, P., DeWeber, T., Sarvala, J., Sass, G., Tolentino, S.A., Walsworth, T., and Jensen, O.P., 2023, Shrinking body size and climate warming: Many freshwater salmonids do not follow the rule: Global Change Biology, v. 29, no. 9, p. 2478-2492, https://doi.org/10.1111/gcb.16626.","productDescription":"15 p.","startPage":"2478","endPage":"2492","ipdsId":"IP-146706","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":444617,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16626","text":"Publisher Index Page"},{"id":413696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Solakas, Mary","contributorId":302883,"corporation":false,"usgs":false,"family":"Solakas","given":"Mary","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":865714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feiner, Zachary S.","contributorId":150494,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary","email":"","middleInitial":"S.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":865715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216703,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":865716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":865717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWeber, Tyrell","contributorId":302884,"corporation":false,"usgs":false,"family":"DeWeber","given":"Tyrell","email":"","affiliations":[{"id":65570,"text":"Fisheries Research Station of Baden, Germany","active":true,"usgs":false}],"preferred":false,"id":865718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sarvala, Jouko","contributorId":302885,"corporation":false,"usgs":false,"family":"Sarvala","given":"Jouko","email":"","affiliations":[{"id":25452,"text":"University of Turku","active":true,"usgs":false}],"preferred":false,"id":865719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sass, Greg G.","contributorId":244466,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":865720,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tolentino, Scott A.","contributorId":302886,"corporation":false,"usgs":false,"family":"Tolentino","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":65571,"text":"Utah Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":865721,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walsworth, Timothy E.","contributorId":275032,"corporation":false,"usgs":false,"family":"Walsworth","given":"Timothy E.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":865722,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jensen, Olaf P.","contributorId":92159,"corporation":false,"usgs":false,"family":"Jensen","given":"Olaf","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":865723,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70240321,"text":"70240321 - 2023 - Monitoring and modeling dispersal of a submerged nearshore berm at the mouth of the Columbia River, USA","interactions":[],"lastModifiedDate":"2023-02-06T12:34:33.761565","indexId":"70240321","displayToPublicDate":"2023-02-03T06:31:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modeling dispersal of a submerged nearshore berm at the mouth of the Columbia River, USA","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">A submerged, low-relief nearshore berm was constructed in the Pacific Ocean near the mouth of the Columbia River, USA, using 216,000&nbsp;m<sup>3</sup><span>&nbsp;</span>of sediment dredged from the adjacent navigation channel. The material dredged from the navigation channel was placed on the northern flank of the ebb-tidal delta in water depths between 12 and 15&nbsp;m and created a distinct feature that could be tracked over time. Field measurements and numerical modeling were used to evaluate the transport pathways, time scales, and physical processes responsible for dispersal of the berm and evaluate the suitability of the location for operational placement of dredged material to enhance the sediment supply to eroding beaches onshore of the placement site. Repeated multibeam bathymetric surveys characterized the initial berm morphology and dispersion of the berm between September 22, 2020, and March 10, 2021. During this time, the volume of sediment within the berm decreased by about 40%to 127,000&nbsp;m<sup>3</sup>, the maximum height decreased by almost 60%, and the center of the deposit shifted onshore over 200&nbsp;m. Observations of berm morphology were compared with predictions from a three-dimensional hydrodynamic and sediment transport model application to refine poorly constrained model input parameters including sediment transport coefficients, bed schematization, and grain size. The calibrated sediment transport model was used to predict the amount, timing, and direction of transport outside of the observed survey area. Model simulations predicted that tidal currents were weak in the vicinity of the berm and wave processes including enhanced bottom stresses and asymmetric bottom orbital velocities resulted in dominant onshore movement of sediment from the berm toward the coastline. Roughly 50% of the berm volume was predicted to disperse away from the initial placement site during the 169 day hindcast. Between 9 and 17% of the initial volume of the berm was predicted to accumulate along the shoreface of a shoreline reach experiencing chronic erosion directly onshore of the placement site. Scenarios exploring alternate placement locations suggested that the berm was relatively effective in enhancing the sediment supply along the eroding coastline north of the inlet. The transferable monitoring and modeling framework developed in this study can be used to inform implementation of strategic nearshore placements and regional sediment management in complex, high-energy coastal environments elsewhere.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2023.104285","usgsCitation":"Stevens, A.W., Moritz, H.R., Elias, E.P., Gelfenbaum, G.R., Ruggiero, P.R., Pearson, S.G., McMillan, J.M., and Kaminsky, G.M., 2023, Monitoring and modeling dispersal of a submerged nearshore berm at the mouth of the Columbia River, USA: Coastal Engineering, v. 181, 104285, 16 p., https://doi.org/10.1016/j.coastaleng.2023.104285.","productDescription":"104285, 16 p.","ipdsId":"IP-138861","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444620,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2023.104285","text":"Publisher Index Page"},{"id":435471,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RVK9S9","text":"USGS data release","linkHelpText":"Bathymetry data and sediment transport modeling of a submerged nearshore berm at the mouth of the Columbia River, Oregon and Washington, 2020-2021"},{"id":412725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.27081924424007,\n              46.46595252705819\n            ],\n            [\n              -124.27081924424007,\n              45.99496323160062\n            ],\n            [\n              -123.23854278794916,\n              45.99496323160062\n            ],\n            [\n              -123.23854278794916,\n              46.46595252705819\n            ],\n            [\n              -124.27081924424007,\n              46.46595252705819\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"181","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":863394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moritz, Hans R.","contributorId":210776,"corporation":false,"usgs":false,"family":"Moritz","given":"Hans","email":"","middleInitial":"R.","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":863395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Edwin PL","contributorId":302064,"corporation":false,"usgs":false,"family":"Elias","given":"Edwin","email":"","middleInitial":"PL","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":863397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ruggiero, Peter R","contributorId":221035,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","email":"","middleInitial":"R","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":863398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearson, Stuart G","contributorId":302066,"corporation":false,"usgs":false,"family":"Pearson","given":"Stuart","email":"","middleInitial":"G","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":863399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McMillan, James M","contributorId":301196,"corporation":false,"usgs":false,"family":"McMillan","given":"James","email":"","middleInitial":"M","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":863400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kaminsky, George M","contributorId":221036,"corporation":false,"usgs":false,"family":"Kaminsky","given":"George","email":"","middleInitial":"M","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":863401,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70242940,"text":"70242940 - 2023 - Seafloor observations eliminate a landslide as the source of the 1918 Puerto Rico Tsunami","interactions":[],"lastModifiedDate":"2023-04-24T11:32:06.068145","indexId":"70242940","displayToPublicDate":"2023-02-03T06:29:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seafloor observations eliminate a landslide as the source of the 1918 Puerto Rico Tsunami","docAbstract":"<p><span>The 11 October 1918 devastating tsunami in northwest Puerto Rico had been used as an example for earthquake‐induced landslide tsunami hazard. Three pieces of evidence pointed to a landslide as the origin of the tsunami: the discovery of a large submarine landslide scar from bathymetry data collected by shipboard high‐resolution multibeam sonar, reported breaks of submarine cable within the scar, and the fit of tsunami models to flooding observations. Newly processed seafloor imagery collected by remotely operated vehicle (ROV) show, however, pervasive Fe–Mn crust (patina) on the landslide walls and floor, indicating that the landslide scar is at least several hundred years old. </span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mmultiscripts xmlns=&quot;&quot;><mi mathvariant=&quot;normal&quot;>C</mi><mprescripts /><none /><mn>14</mn></mmultiscripts></math>\"><sup><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mmultiscripts\"><span id=\"MathJax-Span-5\" class=\"mn\">14</span></span></span></span></span></sup><span class=\"MJX_Assistive_MathML\">C</span></span></span><span>&nbsp;dates of sediment covering the landslide floor verify this interpretation. Although we have not searched the region systematically for an alternative tsunami source, we propose a possible source—a two‐segment normal‐fault rupture along the eastern wall of Mona rift. The proposed fault location matches the published normal faults with steep bathymetry and is close to the International Seismological Center–Global Earthquake Model catalog locations of the 1918 mainshock and aftershocks. The ROV observations further show fresh vertical slickensides and rock exposure along the proposed fault trace. Hydrodynamic models from an&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-6\" class=\"math\"><span><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"msub\"><span id=\"MathJax-Span-9\" class=\"mi\">M<sub>w</sub></span></span></span></span></span></span></span><span>&nbsp;7.2 earthquake rupture along the eastern wall of the rift faithfully reproduce the reported tsunami amplitudes, polarities, and arrival times. Our analysis emphasizes the value of close‐up observations and physical samples to augment remote sensing data in natural hazard studies.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220146","usgsCitation":"ten Brink, U.S., Chaytor, J., Flores, C., Wei, Y., Detmer, S., Lucas, L., Andrews, B.D., and Georgiopoulou, A., 2023, Seafloor observations eliminate a landslide as the source of the 1918 Puerto Rico Tsunami: Bulletin of the Seismological Society of America, v. 113, no. 1, p. 268-280, https://doi.org/10.1785/0120220146.","productDescription":"13 p.","startPage":"268","endPage":"280","ipdsId":"IP-143248","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467122,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/66579","text":"External Repository"},{"id":416167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -67.46355938873742,\n              18.733553875631756\n            ],\n            [\n              -67.46355938873742,\n              17.79501404751062\n            ],\n            [\n              -65.55276024440502,\n              17.79501404751062\n            ],\n            [\n              -65.55276024440502,\n              18.733553875631756\n            ],\n            [\n              -67.46355938873742,\n              18.733553875631756\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":870291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flores, Claudia 0000-0003-0676-7061 cflores@usgs.gov","orcid":"https://orcid.org/0000-0003-0676-7061","contributorId":304396,"corporation":false,"usgs":true,"family":"Flores","given":"Claudia","email":"cflores@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Yong","contributorId":242870,"corporation":false,"usgs":false,"family":"Wei","given":"Yong","affiliations":[{"id":48562,"text":"JISAO, University of Washington, WA 98105 USA","active":true,"usgs":false}],"preferred":false,"id":870293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Detmer, Simon","contributorId":304397,"corporation":false,"usgs":false,"family":"Detmer","given":"Simon","email":"","affiliations":[{"id":66054,"text":"Dept. of Geology, Geography, and Environment, Calvin University, Grand Rapids, MI","active":true,"usgs":false}],"preferred":false,"id":870294,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lucas, Lilian","contributorId":304398,"corporation":false,"usgs":false,"family":"Lucas","given":"Lilian","email":"","affiliations":[{"id":66055,"text":"Dept. of Geology, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":870295,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrews, Brian D. 0000-0003-1024-9400 bandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-1024-9400","contributorId":201662,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian","email":"bandrews@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870296,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Georgiopoulou, Aggeliki","contributorId":265270,"corporation":false,"usgs":false,"family":"Georgiopoulou","given":"Aggeliki","affiliations":[],"preferred":false,"id":870297,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70243012,"text":"70243012 - 2023 - Field evaluation of semi-automated moisture estimation from geophysics using machine learning","interactions":[],"lastModifiedDate":"2023-04-26T11:53:56.65994","indexId":"70243012","displayToPublicDate":"2023-02-02T06:49:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Field evaluation of semi-automated moisture estimation from geophysics using machine learning","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025–0.046 cm<sup>3</sup>/cm<sup>3</sup>). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/vzj2.20246","usgsCitation":"Terry, N., Day-Lewis, F., Lane, J.W., Johnson, C., and Werkema, D., 2023, Field evaluation of semi-automated moisture estimation from geophysics using machine learning: Vadose Zone Journal, v. 22, no. 2, e20246, 21, https://doi.org/10.1002/vzj2.20246.","productDescription":"e20246, 21","ipdsId":"IP-140463","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444627,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/vzj2.20246","text":"Publisher Index Page"},{"id":435473,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N9IY4C","text":"USGS data release","linkHelpText":"Geophysical and Other Data From an Irrigation Monitoring Experiment at Haddam Meadows, CT, July 2019"},{"id":416365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Haddam Meadows State Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -72.5210095743184,\n              41.489521582364574\n            ],\n            [\n              -72.5210095743184,\n              41.47135891770725\n            ],\n            [\n              -72.49582058082348,\n              41.47135891770725\n            ],\n            [\n              -72.49582058082348,\n              41.489521582364574\n            ],\n            [\n              -72.5210095743184,\n              41.489521582364574\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"22","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil C. 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":870558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, F.D. 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":222721,"corporation":false,"usgs":false,"family":"Day-Lewis","given":"F.D.","affiliations":[],"preferred":false,"id":870559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":870560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":870561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Werkema, Dale","contributorId":294506,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":870562,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239888,"text":"70239888 - 2023 - Characterizing historic streamflow to support drought planning in the upper Missouri River basin","interactions":[],"lastModifiedDate":"2026-03-18T16:13:50.675788","indexId":"70239888","displayToPublicDate":"2023-02-01T11:07:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Characterizing historic streamflow to support drought planning in the upper Missouri River basin","docAbstract":"This project combined tree-ring based paleo and modern climate and hydrologic research aimed at understanding the primary influences on drought risk and water reliability in basins critical for western U.S. water resources. New paleohydrologic datasets and analyses were developed and applied to contextualize future streamflow projections and address specific water management questions. These questions centered around optimizing future water management protocols for numerous objectives ranging from improving agricultural water allocation during drought while maintaining instream flows for aquatic ecosystem health, to the testing of operations across large river systems with complex infrastructure critical for downstream flood control, navigation, and hydropower generation. USGS scientists worked closely with the Bureau of Reclamation to estimate both past and future drought risk at key management locations throughout the Missouri basin, the Milk and St. Mary River system, and across the major managed river systems in the western United States. These efforts provided a roadmap for future water management strategies under changing climate and water supply conditions, which are detailed in Reclamation’s newly completed Missouri Headwaters Basin Study, the 2021 SECURE Water Act Report, and the forthcoming update of the St. Mary and Milk Rivers Basin Study. Among the major scientific findings to emerge was a new understanding of the long-term (1200-year) history of drought variability for the Missouri River, which highlighted the unusual severity of the early 2000s drought across the Rocky Mountain headwaters and adjacent high plains. By combining the extended drought record with extensive modern and paleoclimate records, we document how warming exacerbates severities of naturally occurring droughts, with recent decades defined by “hot” droughts and the 2000s (2001-2010) drought ranking as the most severe event in 1200 years. Increasingly severe drought events such as this strain already over-allocated water resources that multiple sectors of society depend heavily upon.","language":"English","publisher":"North Central Climate Adaptation Science Center","usgsCitation":"Pederson, G.T., 2023, Characterizing historic streamflow to support drought planning in the upper Missouri River basin: Final Report, 33 p.","productDescription":"33 p.","ipdsId":"IP-148061","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501260,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/63d1958bd34e06fef1500594","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","otherGeospatial":"upper Missouri River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.05224962042496,\n              50.08090362730903\n            ],\n            [\n              -117.05224962042496,\n              37.030824614225864\n            ],\n            [\n              -89.46041753932424,\n              37.030824614225864\n            ],\n            [\n              -89.46041753932424,\n              50.08090362730903\n            ],\n            [\n              -117.05224962042496,\n              50.08090362730903\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862279,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70268720,"text":"70268720 - 2023 - Central Beaufort Sea Wave and Hydrodynamic Modeling Study--Report 1: Field measurements and model development","interactions":[],"lastModifiedDate":"2025-07-07T15:43:17.143348","indexId":"70268720","displayToPublicDate":"2023-02-01T10:27:02","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"BOEM 2022-078","title":"Central Beaufort Sea Wave and Hydrodynamic Modeling Study--Report 1: Field measurements and model development","docAbstract":"<p>Renewed interest in nearshore oil exploration and production in the shallow waters of the Central Beaufort Sea Shelf has created a need to advance our understanding of the past, current, and future atmospheric and oceanographic conditions that affect existing and planned infrastructure and nearshore ecosystems. At the time of writing this report, Hilcorp Alaska, LLC, has received BOEM approval for an oil and gas Development and Production Plan (DPP) that includes the construction of the Liberty Drilling Island (LDI) in Foggy Island Bay, situated within Stefansson Sound circa 30 km east of Prudhoe Bay (Figure 1.1). The aim of this study is to investigate how longer periods of open water (defined as &lt; 15% ice cover), decreased sea ice cover, and changes in ocean and atmospheric conditions might affect wave and storm surge conditions, sediment transport patterns, and coastal erosion rates within Foggy Island Bay as well as the modeled influence of the offshore artificial island on sediment transport patterns.</p>","language":"English","publisher":"Bureau of Ocean and Energy Management (BOEM)","usgsCitation":"Kasper, J., Erikson, L.H., Ravens, T.M., Bieniek, P., Engelstad, A.C., Nederhoff, C.M., Duvoy, P.X., Fisher, S., Petrone Brown, E., Man, Y., and Reguero, B., 2023, Central Beaufort Sea Wave and Hydrodynamic Modeling Study--Report 1: Field measurements and model development: OCS Study BOEM 2022-078, 237 p.","productDescription":"237 p.","ipdsId":"IP-147574","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":491592,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://espis.boem.gov/final%20reports/BOEM_2022-078.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"Alaska","otherGeospatial":"Foggy Island Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -148.1264407994926,\n              70.38809275423353\n            ],\n            [\n              -148.1264407994926,\n              70.1602757990535\n            ],\n            [\n              -147.44324429215112,\n              70.1602757990535\n            ],\n            [\n              -147.44324429215112,\n              70.38809275423353\n            ],\n            [\n   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Center","active":true,"usgs":true}],"preferred":true,"id":941731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ravens, Thomas M.","contributorId":24668,"corporation":false,"usgs":true,"family":"Ravens","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":942268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bieniek, Peter A.","contributorId":209850,"corporation":false,"usgs":false,"family":"Bieniek","given":"Peter A.","affiliations":[{"id":38014,"text":"Alaska Climate Science Center, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":941733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engelstad, Anita C 0000-0002-0211-4189","orcid":"https://orcid.org/0000-0002-0211-4189","contributorId":268303,"corporation":false,"usgs":true,"family":"Engelstad","given":"Anita","email":"","middleInitial":"C","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":941734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nederhoff, Cornelis M. 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":265889,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Cornelis","email":"","middleInitial":"M.","affiliations":[{"id":33886,"text":"Deltares USA","active":true,"usgs":false}],"preferred":true,"id":941735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duvoy, Paul X.","contributorId":292138,"corporation":false,"usgs":false,"family":"Duvoy","given":"Paul","email":"","middleInitial":"X.","affiliations":[{"id":62836,"text":"Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA","active":true,"usgs":false}],"preferred":false,"id":942269,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fisher, Stephanie","contributorId":357710,"corporation":false,"usgs":false,"family":"Fisher","given":"Stephanie","affiliations":[],"preferred":false,"id":942270,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Petrone Brown, Eloise","contributorId":357552,"corporation":false,"usgs":false,"family":"Petrone Brown","given":"Eloise","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942271,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Man, Yaman","contributorId":357553,"corporation":false,"usgs":false,"family":"Man","given":"Yaman","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":942272,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":942273,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70240636,"text":"70240636 - 2023 - Ecology and ecosystem impacts of submerged and floating aquatic vegetation in the Sacramento-San Joaquin Delta","interactions":[],"lastModifiedDate":"2023-02-10T13:13:30.325947","indexId":"70240636","displayToPublicDate":"2023-02-01T07:11:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Ecology and ecosystem impacts of submerged and floating aquatic vegetation in the Sacramento-San Joaquin Delta","docAbstract":"<p><span>Substantial increases in non-native aquatic vegetation have occurred in the upper San Francisco Estuary over the last 2 decades, largely from the explosive growth of a few submerged and floating aquatic plant species. Some of these species act as ecosystem engineers by creating conditions that favor their further growth and expansion as well as by modifying habitat for other organisms. Over the last decade, numerous studies have investigated patterns of expansion and turn-over of aquatic vegetation species; effects of vegetation on ecosystem health, water quality, and habitat; and effects of particular species or communities on physical processes such as carbon and sediment dynamics. Taking a synthetic approach to evaluate what has been learned over the last few years has shed light on just how significant aquatic plant species and communities are to ecosystems in the Sacramento-San Joaquin Delta. Aquatic vegetation affects every aspect of the physical and biotic environment, acting as ecosystem engineers on the landscape. Furthermore, their effects are constantly changing across space and time, leaving many unanswered questions about the full effects of aquatic vegetation on Delta ecosystems and what future effects may result, as species shift in distribution and new species are introduced. Remaining knowledge gaps underlie our understanding of aquatic macrophyte effects on Delta ecosystems, including their roles and relationships with respect to nutrients and nutrient cycling, evapotranspiration and water budgets, carbon and sediment, and emerging effects on fish species and their habitats. This paper explores our current understanding of submerged and floating aquatic vegetation (SAV and FAV) ecology with respect to major aquatic plant communities, observed patterns of change, interactions between aquatic vegetation and the physical environment, and how these factors affect ecosystem services and disservices within the upper San Francisco Estuary.</span></p>","language":"English","publisher":"University of California","doi":"10.15447/sfews.2023v20iss4art3","usgsCitation":"Christman, M.A., Khanna, S., Drexler, J.Z., and Young, M.J., 2023, Ecology and ecosystem impacts of submerged and floating aquatic vegetation in the Sacramento-San Joaquin Delta: San Francisco Estuary and Watershed Science, v. 20, no. 4, 3, 32 p., https://doi.org/10.15447/sfews.2023v20iss4art3.","productDescription":"3, 32 p.","ipdsId":"IP-144768","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":444640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2023v20iss4art3","text":"Publisher Index Page"},{"id":412940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.65414668802397,\n              38.53804340076624\n            ],\n            [\n              -122.65414668802397,\n              37.37783082362128\n            ],\n            [\n              -121.1606403257308,\n              37.37783082362128\n            ],\n            [\n              -121.1606403257308,\n              38.53804340076624\n            ],\n            [\n              -122.65414668802397,\n              38.53804340076624\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Christman, Mairgareth A.","contributorId":206436,"corporation":false,"usgs":false,"family":"Christman","given":"Mairgareth","email":"","middleInitial":"A.","affiliations":[{"id":37330,"text":"Delta Stewardship Council, Sacramento, CA","active":true,"usgs":false}],"preferred":false,"id":864044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khanna, Shruti","contributorId":205167,"corporation":false,"usgs":false,"family":"Khanna","given":"Shruti","email":"","affiliations":[{"id":37041,"text":"Department of Land, Air, and Water Resources, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":864045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":864046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864047,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243560,"text":"70243560 - 2023 - Change in climatically suitable breeding distributions reduces hybridization potential between Vermivora warblers","interactions":[],"lastModifiedDate":"2023-05-12T12:20:15.008523","indexId":"70243560","displayToPublicDate":"2023-02-01T07:09:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Change in climatically suitable breeding distributions reduces hybridization potential between <i>Vermivora</i> warblers","title":"Change in climatically suitable breeding distributions reduces hybridization potential between Vermivora warblers","docAbstract":"<p id=\"ddi13659-sec-0001-title\" class=\"article-section__sub-title section\"><strong>Aim</strong></p><p>Climate change is affecting the distribution of species and subsequent biotic interactions, including hybridization potential. The imperiled Golden-winged Warbler (GWWA) competes and hybridizes with the Blue-winged Warbler (BWWA), which may threaten the persistence of GWWA due to introgression. We examined how climate change is likely to alter the breeding distributions and potential for hybridization between GWWA and BWWA.</p><p id=\"ddi13659-sec-0002-title\" class=\"article-section__sub-title section\"><strong>Location</strong></p><p>North America.</p><p id=\"ddi13659-sec-0003-title\" class=\"article-section__sub-title section\"><strong>Methods</strong></p><p>We used GWWA and BWWA occurrence data to model climatically suitable conditions under historical and future climate scenarios. Models were parameterized with 13 bioclimatic variables and 3 topographic variables. Using ensemble modeling, we estimated historical and modern distributions, as well as a projected distribution under six future climate scenarios. We quantified breeding distribution area, the position of and amount of overlap between GWWA and BWWA distributions under each climate scenario. We summarized the top explanatory variables in our model to predict environmental parameters of the distributions under future climate scenarios relative to historical climate.</p><p id=\"ddi13659-sec-0004-title\" class=\"article-section__sub-title section\"><strong>Results</strong></p><p>GWWA and BWWA distributions are projected to substantially change under future climate scenarios. GWWA are projected to undergo the greatest change; the area of climatically suitable breeding season conditions is expected to shift north to northwest; and range contraction is predicted in five out of six future climate scenarios. Climatically suitable conditions for BWWA decreased in four of the six future climate scenarios, while the distribution is projected to shift east. A reduction in overlapping distributions for GWWA and BWWA is projected under all six future climate scenarios.</p><p id=\"ddi13659-sec-0005-title\" class=\"article-section__sub-title section\"><strong>Main Conclusions</strong></p><p>Climate change is expected to substantially alter the area of climatically suitable conditions for GWWA and BWWA, with the southern portion of the current breeding ranges likely to become climatically unsuitable. However, interactions between BWWA and GWWA are expected to decline with the decrease in overlapping habitat, which may reduce the risk of genetic introgression.</p>","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13659","usgsCitation":"Hightower, J.N., Crawford, D.L., Thogmartin, W.E., Aldinger, K.R., Barker Swarthout, S., Buehler, D.A., Confer, J., Friis, C., Larkin, J., Lowe, J.D., Piorkowski, M., Rohrbaugh, R., Rosenberg, K.V., Smalling, C.G., Wood, P.B., Vallender, R., and Roth, A.M., 2023, Change in climatically suitable breeding distributions reduces hybridization potential between Vermivora warblers: Diversity and Distributions, v. 29, no. 2, p. 254-271, https://doi.org/10.1111/ddi.13659.","productDescription":"18 p.","startPage":"254","endPage":"271","ipdsId":"IP-138007","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":444642,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13659","text":"Publisher Index Page"},{"id":435475,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AS9YAC","text":"USGS data release","linkHelpText":"Blue-winged and Golden-winged Warbler Breeding Season Occurrences in North America, 1932-2021"},{"id":416983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hightower, Jessica N.","contributorId":204645,"corporation":false,"usgs":false,"family":"Hightower","given":"Jessica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":872370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Dolly L.","contributorId":299588,"corporation":false,"usgs":false,"family":"Crawford","given":"Dolly","email":"","middleInitial":"L.","affiliations":[{"id":64892,"text":"Pennsylvania Western University","active":true,"usgs":false}],"preferred":false,"id":872371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":872372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":872373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barker Swarthout, Sara","contributorId":176239,"corporation":false,"usgs":false,"family":"Barker Swarthout","given":"Sara","email":"","affiliations":[{"id":34544,"text":"Cornell Lab of Ornithology, Cornell University","active":true,"usgs":false}],"preferred":false,"id":872374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buehler, David A.","contributorId":169746,"corporation":false,"usgs":false,"family":"Buehler","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":872375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Confer, John","contributorId":305334,"corporation":false,"usgs":false,"family":"Confer","given":"John","email":"","affiliations":[{"id":18877,"text":"Ithaca College","active":true,"usgs":false}],"preferred":false,"id":872376,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Friis, Christian","contributorId":194605,"corporation":false,"usgs":false,"family":"Friis","given":"Christian","email":"","affiliations":[],"preferred":false,"id":872377,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Larkin, Jeff","contributorId":199993,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":872378,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lowe, James D.","contributorId":305336,"corporation":false,"usgs":false,"family":"Lowe","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":36682,"text":"Cornell Lab of Ornithology","active":true,"usgs":false}],"preferred":false,"id":872379,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Piorkowski, Martin","contributorId":305338,"corporation":false,"usgs":false,"family":"Piorkowski","given":"Martin","email":"","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":872380,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rohrbaugh, Ronald W.","contributorId":305340,"corporation":false,"usgs":false,"family":"Rohrbaugh","given":"Ronald W.","affiliations":[{"id":36682,"text":"Cornell Lab of Ornithology","active":true,"usgs":false}],"preferred":false,"id":872381,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rosenberg, Kenneth V.","contributorId":171463,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Kenneth","email":"","middleInitial":"V.","affiliations":[{"id":27615,"text":"Cornell Lab of Ornithology, Conservation Science Program","active":true,"usgs":false}],"preferred":false,"id":872382,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Smalling, Curtis G.","contributorId":191724,"corporation":false,"usgs":false,"family":"Smalling","given":"Curtis","email":"","middleInitial":"G.","affiliations":[{"id":33352,"text":"Audubon North Carolina","active":true,"usgs":false}],"preferred":false,"id":872383,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wood, Petra B.","contributorId":305342,"corporation":false,"usgs":false,"family":"Wood","given":"Petra","email":"","middleInitial":"B.","affiliations":[{"id":66214,"text":"West Virginia Cooperative Fish and Wildlife Research Unit,","active":true,"usgs":false}],"preferred":false,"id":872384,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Vallender, Rachel","contributorId":194966,"corporation":false,"usgs":false,"family":"Vallender","given":"Rachel","email":"","affiliations":[{"id":34540,"text":"Canadian Museum of Nature","active":true,"usgs":false},{"id":27312,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, 6 Bruce Street, Mount","active":true,"usgs":false}],"preferred":false,"id":872385,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Roth, Amber M.","contributorId":191723,"corporation":false,"usgs":false,"family":"Roth","given":"Amber","email":"","middleInitial":"M.","affiliations":[{"id":27866,"text":"University of Maine, Department of Wildlife, Fisheries, and Conservation Biology, Orono, ME","active":true,"usgs":false},{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false},{"id":25614,"text":"School of Forest Resources, University of Maine","active":true,"usgs":false}],"preferred":false,"id":872386,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70239954,"text":"70239954 - 2023 - Toward consistent change detection across irregular remote sensing time series observations","interactions":[],"lastModifiedDate":"2024-05-20T13:49:30.008054","indexId":"70239954","displayToPublicDate":"2023-02-01T07:04:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Toward consistent change detection across irregular remote sensing time series observations","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"d1e1111\" class=\"abstract author\"><div id=\"d1e1114\"><p id=\"d1e1115\">The use of remote sensing in time series analysis enables wall-to-wall monitoring of the land surface and is critical for assessing and understanding land cover and land use change and for understanding the Earth system as a whole. However, variability in remote sensing observation frequency through time and across space presents challenges for producing consistent change detection results throughout the available satellite record using approaches such as the Continuous Change Detection and Classification (CCDC) change detection methodology. Here we investigate new modifications to this methodology with the goal of improving accuracy and consistency in results and increasing flexibility for operational usage and future development. The modified method (Band-First Probability, or CCD-BFP) change detection procedure works by calculating a test for each band through time before summarizing between bands. We evaluate the CCD-BFP method compared to an existing implementation of CCDC using a variety of approaches, including a validation dataset of human-interpreted locations, comparison with data from fire events, use of simulated remote sensing data, and qualitative inspection of areas of interest. We find CCD-BFP improves consistency across time and space compared to the existing implementation of CCDC, with more similarity in rates of change across Landsat swath boundaries and before and after the launch of Landsat 7. Also, we find that CCD-BFP detects more of the change events in the validation dataset while reducing the overall number of change detections, indicating that it is able to more accurately capture the most notable land surface change events.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2022.113372","usgsCitation":"Tollerud, H.J., Zhu, Z., Smith, K., Wellington, D., Hussain, R., and Viola, D., 2023, Toward consistent change detection across irregular remote sensing time series observations: Remote Sensing of Environment, v. 285, 113372, 14 p., https://doi.org/10.1016/j.rse.2022.113372.","productDescription":"113372, 14 p.","ipdsId":"IP-143813","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":444644,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2022.113372","text":"Publisher Index Page"},{"id":412355,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tollerud, Heather J. 0000-0001-9507-4456","orcid":"https://orcid.org/0000-0001-9507-4456","contributorId":210820,"corporation":false,"usgs":true,"family":"Tollerud","given":"Heather","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":862497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Zhe 0000-0001-8283-6407","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":190828,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[],"preferred":false,"id":862498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Kelcy 0000-0001-6811-1485","orcid":"https://orcid.org/0000-0001-6811-1485","contributorId":272037,"corporation":false,"usgs":false,"family":"Smith","given":"Kelcy","affiliations":[{"id":56338,"text":"KBR, Inc., Contractor under USGS","active":true,"usgs":false}],"preferred":false,"id":862499,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wellington, Danika F. 0000-0002-2130-0075","orcid":"https://orcid.org/0000-0002-2130-0075","contributorId":237074,"corporation":false,"usgs":false,"family":"Wellington","given":"Danika F.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":862500,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hussain, Reza 0000-0002-5445-3027","orcid":"https://orcid.org/0000-0002-5445-3027","contributorId":301245,"corporation":false,"usgs":false,"family":"Hussain","given":"Reza","affiliations":[{"id":65343,"text":"KBR, Contractor to U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":862501,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viola, Donna","contributorId":127526,"corporation":false,"usgs":false,"family":"Viola","given":"Donna","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":862502,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239890,"text":"70239890 - 2023 - Where forest may not return in the western United States","interactions":[],"lastModifiedDate":"2024-05-20T13:51:18.131988","indexId":"70239890","displayToPublicDate":"2023-02-01T06:52:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Where forest may not return in the western United States","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response to these changing disturbance regimes. Meta-analyses of these studies provide broad guidelines on the biotic and abiotic factors that hinder forest recovery, but study-to-study differences in methods and objectives do not support estimation of the total extent of potentially impaired forest succession. In this research, we provide an estimate of the area of potentially impaired forest succession. The estimate was derived from modeling of an 18-year land cover and Normalized Difference Vegetation Index (NDVI) time series supported by an extensive ancillary dataset. We estimate an upper bound of approximately 3470&nbsp;km<sup>2</sup><span>&nbsp;</span>of disturbed forest that may not return or reattain prior composition and structure. Based on the data used, fire appears to be the main disturbance agent of impaired forest succession, although climatic factors cannot be discounted. The numerous field studies routinely cite distal seed sources as a factor that hinders forest recovery, and we estimate that 20&nbsp;% of the upper bound estimate has no forest cover within a 4.4-ha neighborhood. Our upper bound estimate is about 0.5&nbsp;% of the 2001 mapped extent of western United States forests. The estimate is cognizant of measurement and modeling uncertainties (i.e., upper bound) and uncertainties related to successional rates and trajectories (i.e., potential).</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109756","usgsCitation":"Wickham, J., Neale, A., Riitters, K.H., Nash, M., Dewitz, J., Jin, S., van Fossen, M., and Rosenbaum, D., 2023, Where forest may not return in the western United States: Ecological Indicators, v. 146, 109756, 10 p., https://doi.org/10.1016/j.ecolind.2022.109756.","productDescription":"109756, 10 p.","ipdsId":"IP-131756","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":444649,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109756","text":"Publisher Index Page"},{"id":412278,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.23373688293262,\n              49.80826764186497\n            ],\n            [\n              -125.23373688293262,\n              31.24455371587699\n            ],\n            [\n              -102.39159974853492,\n              31.24455371587699\n            ],\n            [\n              -102.39159974853492,\n              49.80826764186497\n            ],\n            [\n              -125.23373688293262,\n              49.80826764186497\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"146","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wickham, James","contributorId":140259,"corporation":false,"usgs":false,"family":"Wickham","given":"James","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":862281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neale, Anne","contributorId":301168,"corporation":false,"usgs":false,"family":"Neale","given":"Anne","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":862282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riitters, Kurt H. 0000-0003-3901-4453","orcid":"https://orcid.org/0000-0003-3901-4453","contributorId":139788,"corporation":false,"usgs":false,"family":"Riitters","given":"Kurt","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":862283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nash, Maliha","contributorId":301169,"corporation":false,"usgs":false,"family":"Nash","given":"Maliha","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":862284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dewitz, Jon 0000-0002-0458-212X","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":215192,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":862285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":862286,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Fossen, Megan","contributorId":301170,"corporation":false,"usgs":false,"family":"van Fossen","given":"Megan","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":862287,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rosenbaum, D","contributorId":301171,"corporation":false,"usgs":false,"family":"Rosenbaum","given":"D","email":"","affiliations":[{"id":30773,"text":"Oak Ridge Institute for Science and Education","active":true,"usgs":false}],"preferred":false,"id":862288,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70240491,"text":"70240491 - 2023 - Does hatchery rearing of lake trout affect their reproductive behavior in the wild?","interactions":[],"lastModifiedDate":"2023-02-09T12:56:37.830649","indexId":"70240491","displayToPublicDate":"2023-02-01T06:50:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Does hatchery rearing of lake trout affect their reproductive behavior in the wild?","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Stocking of hatchery-reared fishes has been used with variable success as a management action to promote the recovery of populations and species. The practice has been controversial for several reasons, including uncertainty about whether the hatchery rearing experience may affect reproduction after release. Fine-scale acoustic telemetry was used during three spawning seasons to test whether hatchery rearing affects the reproductive behavior of lake trout using a spawning shoal complex in northern Lake Huron. Within sex, wild- and hatchery-reared fish behaved similarly, but significant behavioral differences occurred between sexes. Lake trout of both sexes moved synchronously onto the spawning shoals at the completion of autumn thermal turnover and occupied the same spawning sites (confirmed visually by presence of fertilized eggs) on the shoals. Male lake trout tended to congregate directly on spawning sites, with duration of occupancy varying greatly among years. Female lake trout spent less time on spawning shoals than males and congregated less at spawning sites on shoals. Most fish visited multiple spawning sites among shoals per season, with many making multiple transits among individual spawning sites. We found no evidence to support the hypothesis that hatchery rearing impairs spawning behavior of lake trout and, therefore, conclude that behavior deficiencies on the spawning ground are likely not an impediment to rehabilitation of lake trout in northern Lake Huron. Our study narrows the field of possible impediments to lake trout rehabilitation in the Great Lakes and provides insights that expand the conceptual model of lake trout spawning behavior.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.11.002","usgsCitation":"Binder, T., Holbrook, C., Bronte, C.R., He, J., and Kreuger, C., 2023, Does hatchery rearing of lake trout affect their reproductive behavior in the wild?: Journal of Great Lakes Research, v. 49, no. 1, p. 288-302, https://doi.org/10.1016/j.jglr.2022.11.002.","productDescription":"15 p.","startPage":"288","endPage":"302","ipdsId":"IP-143625","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":444651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.11.002","text":"Publisher Index Page"},{"id":412906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Drummond Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.9887827687768,\n              46.146551298056295\n            ],\n            [\n              -83.9887827687768,\n              45.85667753419378\n            ],\n            [\n              -83.36831872855939,\n              45.85667753419378\n            ],\n            [\n              -83.36831872855939,\n              46.146551298056295\n            ],\n            [\n              -83.9887827687768,\n              46.146551298056295\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Binder, Thomas 0000-0001-9266-9120 tbinder@usgs.gov","orcid":"https://orcid.org/0000-0001-9266-9120","contributorId":4958,"corporation":false,"usgs":true,"family":"Binder","given":"Thomas","email":"tbinder@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bronte, Charles R.","contributorId":190727,"corporation":false,"usgs":false,"family":"Bronte","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":863985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"He, Ji","contributorId":172649,"corporation":false,"usgs":false,"family":"He","given":"Ji","affiliations":[],"preferred":false,"id":863986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kreuger, Charles","contributorId":302311,"corporation":false,"usgs":false,"family":"Kreuger","given":"Charles","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":863987,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70251801,"text":"70251801 - 2023 - Timing of rhyolite intrusion and Carlin-type gold mineralization at the Cortez Hills Carlin-type deposit, Nevada, USA","interactions":[],"lastModifiedDate":"2024-02-29T12:41:18.941661","indexId":"70251801","displayToPublicDate":"2023-02-01T06:37:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Timing of rhyolite intrusion and Carlin-type gold mineralization at the Cortez Hills Carlin-type deposit, Nevada, USA","docAbstract":"<div id=\"135305323\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Carlin-type gold deposits (CTDs) of Nevada are the largest producers of gold in the United States, a leader in world gold production. Although much has been resolved about the characteristics and origin of CTDs in Nevada, major questions remain, especially about (1) the role of magmatism, whether only a source of heat or also metals, (2) whether CTDs only formed in the Eocene, and (3) whether pre-Eocene metal concentrations contributed to Eocene deposits. These issues are exemplified by the CTDs of the Cortez region, the second largest concentration of these deposits after the Carlin trend.</p><p>Carlin-type deposits are notoriously difficult to date because they rarely generate dateable minerals. An age can be inferred from crosscutting relationships with dated dikes and other intrusions, which we have done for the giant Cortez Hills CTD. What we term “Cortez rhyolites” consist of two petrographic-geochemical groups of siliceous dikes: (1) quartz-sanidine-plagioclase-biotite-phyric, high-SiO<sub>2</sub><span>&nbsp;</span>rhyolites emplaced at 35.7 Ma based on numerous<span>&nbsp;</span><sup>40</sup>Ar/<sup>39</sup>Ar dates and (2) plagioclase-biotite-quartz ± hornblende-phyric, low-SiO<sub>2</sub><span>&nbsp;</span>rhyolites, which probably were emplaced at the same time but possibly as early as ~36.2 Ma. The dikes form a NNW-trending belt that is ~6 to 10 km wide<span>&nbsp;</span><strong>×</strong><span>&nbsp;</span>40 km long and centered on the Cortez Hills deposit, and they require an underlying felsic pluton that fed the dikes. Whether these dikes pre- or postdated mineralization has been long debated. We show that dike emplacement spanned the time of mineralization. Many of both high- and low-SiO<sub>2</sub><span>&nbsp;</span>dikes are altered and mineralized, although none constitute ore. In altered-mineralized dikes, plagioclase has been replaced by kaolinite and calcite, and biotite by smectite, calcite, and marcasite. Sanidine is unaltered except in a few samples that are completely altered to quartz and kaolinite. Sulfides present in mineralized dikes are marcasite, pyrite, arsenopyrite, and As-Sb–bearing pyrite. Mineralized dikes are moderately enriched in characteristic Carlin-type elements (Au, Hg, Sb, Tl, As, and S), as well as elements found in some CTDs (Ag, Bi, Cu, Mo), and variably depleted in MgO, CaO, Na<sub>2</sub>O, K<sub>2</sub>O, MnO, Rb, Sr, and Ba. In contrast, some high-SiO<sub>2</sub><span>&nbsp;</span>rhyolites are unaltered and cut high-grade ore, which shows that they are post-ore. Both mineralized and post-ore dikes have indistinguishable sanidine<span>&nbsp;</span><sup>40</sup>Ar/<sup>39</sup>Ar dates. These characteristics, along with published interpretations that other giant CTDs formed in a few tens of thousands of years, indicate the Cortez Hills CTD formed at 35.7 Ma. All Cortez-area CTDs are in or adjacent to the Cortez rhyolite dike swarm, which suggests that the felsic pluton that fed the dikes was the hydrothermal heat source. Minor differences in alteration and geochemistry between dikes and typical Paleozoic sedimentary rock-hosted ore probably reflect low permeability and low reactivity of the predominantly quartzofeldspathic dikes.</p><p>Despite widespread pre-35.7 Ma mineralization in the Cortez region, including deposits near several CTDs, we find no evidence that older deposits or Paleozoic basinal rocks contributed metals to Cortez-area CTDs. Combining our new information about the age of Cortez Hills with published and our dates on other CTDs demonstrates that CTD formation coincided with the southwestern migration of magmatism across Nevada, supporting a genetic relationship to Eocene magmatism. CTDs are best developed where deep-seated (~6–8 km), probably granitic plutons, expressed in deposits only as dikes, established large, convective hydrothermal systems.</p></div>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4976","usgsCitation":"Henry, C., John, D.A., Leonardson, R.W., McIntosh, W.T., Heizler, M.T., Colgan, J.P., and Watts, K., 2023, Timing of rhyolite intrusion and Carlin-type gold mineralization at the Cortez Hills Carlin-type deposit, Nevada, USA: Economic Geology, v. 118, no. 1, p. 57-91, https://doi.org/10.5382/econgeo.4976.","productDescription":"35 p.","startPage":"57","endPage":"91","ipdsId":"IP-124218","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.4976","text":"Publisher Index Page"},{"id":426115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.68213037399164,\n              41.86699645110528\n            ],\n            [\n              -117.68213037399164,\n              39.53528398745098\n            ],\n            [\n              -114.43017724899187,\n              39.53528398745098\n            ],\n            [\n              -114.43017724899187,\n              41.86699645110528\n            ],\n            [\n              -117.68213037399164,\n              41.86699645110528\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"118","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henry, Christopher D.","contributorId":175501,"corporation":false,"usgs":false,"family":"Henry","given":"Christopher D.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":895621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leonardson, Robert W.","contributorId":242799,"corporation":false,"usgs":false,"family":"Leonardson","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":895623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McIntosh, William T","contributorId":334431,"corporation":false,"usgs":false,"family":"McIntosh","given":"William","email":"","middleInitial":"T","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":895624,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heizler, Matt T. 0000-0002-3911-4932","orcid":"https://orcid.org/0000-0002-3911-4932","contributorId":229568,"corporation":false,"usgs":false,"family":"Heizler","given":"Matt","email":"","middleInitial":"T.","affiliations":[{"id":41669,"text":"New Mexico Bureau of Geology and Mineral Resources, New Mexico Tech","active":true,"usgs":false}],"preferred":false,"id":895625,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":895626,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895627,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70240935,"text":"70240935 - 2023 - Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie","interactions":[],"lastModifiedDate":"2024-05-20T16:23:27.294825","indexId":"70240935","displayToPublicDate":"2023-02-01T06:36:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Harmful algal blooms (HABs) are a recurring problem in many temperate large lake and coastal marine ecosystems, caused mainly by anthropogenic eutrophication. Implementation of agricultural conservation practices (ACPs) offers a means to reduce non-point source nutrient runoff and mitigate HABs. However, the effectiveness of ACPs in a changing climate remains uncertain. We used an integrated biophysical modeling approach to predict how Lake Erie cyanobacterial HAB severity (bloom biomass) may change under several climate and ACP implementation scenarios, using western Lake Erie and its largely agricultural watershed as our study system. An ensemble of general circulation model projections was used to drive spatially explicit land use and hydrology models of the Maumee River watershed, the output of which informed a predictive model of Lake Erie HAB severity. Results show that, in the absence of changes in ACPs, the frequency of severe HABs is projected to increase during coming decades, owing to increased inputs of nutrients from the watershed. These anticipated increases are due to increased total precipitation and more frequent higher-magnitude rainfall events. While further implementation of ACPs appears capable of reducing severe HAB events, widespread implementation would be necessary to reduce HAB severity below current management targets. This study highlights how continued climate change will only exacerbate the need for land management practices that can reduce nutrient runoff in agriculturally dominated ecosystems, such as Lake Erie. It also shows how interdisciplinary, biophysical modeling approaches can help identify strategies to mitigate HABs in the face of anthropogenic stressors.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.11.009","usgsCitation":"Fraker, M.E., Aloysius, N.R., Martin, J.F., Keitzer, S.C., Dippold, D.A., Yen, H., Arnold, J.G., Daggupati, P., Johnson, M.V., Robertson, D., Sowa, S.P., White, M.J., and Ludsin, S.A., 2023, Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie: Journal of Great Lakes Research, v. 49, no. 1, p. 209-219, https://doi.org/10.1016/j.jglr.2022.11.009.","productDescription":"11 p.","startPage":"209","endPage":"219","ipdsId":"IP-136384","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444660,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.11.009","text":"Publisher Index Page"},{"id":413606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.54931314843981,\n              41.61838726545028\n            ],\n            [\n              -82.86844995386474,\n              41.289162489225475\n            ],\n            [\n              -81.53966855800157,\n              41.47044290278254\n            ],\n            [\n              -80.15597883999482,\n              41.945939927238726\n            ],\n            [\n              -78.87112410184554,\n              42.6121865802632\n            ],\n            [\n              -78.76130745755944,\n              42.998913499774915\n            ],\n            [\n              -79.35431733670504,\n              43.0791772338647\n            ],\n            [\n              -80.36463046413846,\n              42.86222422480026\n            ],\n            [\n              -81.01254866542764,\n              42.83807110066172\n            ],\n            [\n              -81.84715516200271,\n              42.692954038490456\n            ],\n            [\n              -82.64881666529249,\n              42.2311751476457\n            ],\n            [\n              -83.02219325586584,\n              42.27181831635397\n            ],\n            [\n              -83.47244149743949,\n              42.28806825056833\n            ],\n            [\n              -83.54931314843981,\n              41.61838726545028\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fraker, Michael E. 0000-0002-1813-706X","orcid":"https://orcid.org/0000-0002-1813-706X","contributorId":150962,"corporation":false,"usgs":false,"family":"Fraker","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aloysius, Noel R","contributorId":302749,"corporation":false,"usgs":false,"family":"Aloysius","given":"Noel","email":"","middleInitial":"R","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Jay F. 0000-0002-1599-5931","orcid":"https://orcid.org/0000-0002-1599-5931","contributorId":254345,"corporation":false,"usgs":false,"family":"Martin","given":"Jay","email":"","middleInitial":"F.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":865350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keitzer, S. 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