High resolution topobathymetric field surveys were conducted by the U.S. Geological Survey in collaboration with Northeastern University and in cooperation with the U.S. Fish and Wildlife Service and The Nature Conservancy in a selected shoreline along Gandys Beach, New Jersey, from January to April 2018. These data are a critical model input for hydrodynamic and wave models and can affect the accuracy of model outputs such as wave height, water surface elevation, current velocity, and sediment transport. Gandys Beach is a living shoreline where constructed oyster reefs (CORs) were built to protect the shoreline and enhance habitat for oyster and other species. Because of the complex topography and bathymetry of the study area, higher spatial resolution topobathymetric data are required to resolve the vertical variations near the CORs. During the field survey, the global navigation satellite system positioning method was used to establish the elevation of a benchmark referenced to the North American Vertical Datum of 1988. The topobathymetric data were collected using a total station. Horizontal accuracy of plus or minus 0.05 foot (ft) and vertical accuracy of plus or minus 0.10 ft were calculated using root mean square error between duplicate surveys. Two existing datasets were integrated with the survey data to create an updated topobathymetric dataset for model input and analysis: (1) the U.S. Geological Survey Coastal National Elevation Database 1-meter resolution data developed after Hurricane Sandy and (2) The Nature Conservancy 2017 elevation monitoring data at 10-meter resolution. A root mean square error analysis comparing survey data with the new topobathymetric dataset versus the survey data compared to the original Coastal National Elevation Data dataset showed errors of 0.31 and 2.61 ft, respectively. This improved dataset can be used for wave and hydrodynamic modeling in support of the effectiveness assessment of the CORs and living shoreline restoration along Gandys Beach.
Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"Per- and polyfluoroalkyl substances (PFAS) are contaminants that can lead to adverse health effects in aquatic organisms, including reproductive toxicity and developmental abnormalities. To assess the ecological health risk of PFAS in Pennsylvania stream surface water, we conducted a comprehensive analysis that included both measured and predicted estimates. The potential combined exposure effects of 14 individual PFAS to aquatic biota were estimated using the sum of exposure-activity ratios (ΣEARs) in 280 streams. Additionally, machine learning techniques were utilized to predict potential PFAS exposure effects in unmonitored stream reaches, considering factors such as land use, climate, and geology. Leveraging a tailored convolutional neural network (CNN), a validation accuracy of 78% was achieved, directly outperforming traditional methods that were also used, such as logistic regression and gradient boosting (accuracies of ~65%). Feature importance analysis highlighted key variables that contributed to the CNN’s predictive power. The most influential features highlighted the complex interplay of anthropogenic and environmental factors contributing to PFAS contamination in surface waters. Industrial and urban land cover, rainfall intensity, underlying geology, agricultural factors, and their interactions emerged as key determinants. These findings may help to inform biotic sampling strategies, water quality monitoring efforts, and policy decisions aimed to mitigate the ecological impacts of PFAS in surface waters.
","language":"English","publisher":"MDPI","doi":"10.3390/toxics12120921","usgsCitation":"Breitmeyer, S.E., Williams, A., Conlon, M.D., Wertz, T.A., Heflin, B., Shull, D., and Duris, J.W., 2024, Predicted potential for aquatic exposure effects of per- and polyfluorinated alkyl substances (PFAS) in Pennsylvania’s statewide network of streams: Toxics, v. 12, no. 12, 921, 27 p., https://doi.org/10.3390/toxics12120921.","productDescription":"921, 27 p.","ipdsId":"IP-170831","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":466706,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/toxics12120921","text":"Publisher Index Page"},{"id":465482,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"12","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":921971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Amy 0000-0002-7679-181X","orcid":"https://orcid.org/0000-0002-7679-181X","contributorId":347547,"corporation":false,"usgs":false,"family":"Williams","given":"Amy","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental 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Brian","contributorId":347548,"corporation":false,"usgs":false,"family":"Heflin","given":"Brian","affiliations":[{"id":34928,"text":"Independent Researcher","active":true,"usgs":false}],"preferred":false,"id":921975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shull, Dustin 0000-0002-0188-7964","orcid":"https://orcid.org/0000-0002-0188-7964","contributorId":347549,"corporation":false,"usgs":false,"family":"Shull","given":"Dustin","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":921976,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":1981,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science 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The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 2 (April–June) of 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
This is the fourth quarterly report to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data. Additional information about Landsat 9 prelaunch, commissioning, and early on-orbit imaging performance is available at https://www.mdpi.com/journal/remotesensing/special_issues/15B4V2K92K.
This is the second quarterly report that does not include analysis results for Landsat 7 because Enhanced Thematic Mapper Plus imaging was suspended on January 19, 2024, after the satellite transitioned into full sunlight. The satellite has been drifting since early 2022 when it was lowered from the nominal orbit altitude, and the transition into full sunlight is a result of the satellite operating in its extended science mission. Additional information about the imaging suspension is available at https://www.usgs.gov/landsat-missions/news/landsat-7-imaging-suspended. Additional information about the Landsat 7 extended science mission is available at https://www.usgs.gov/landsat-missions/landsat-7-extended-science-mission.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241077","usgsCitation":"Haque, M.O., Hasan, M.N., Shrestha, A., Rengarajan, R., Lubke, M., Shaw, J.L., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Clauson, J., Thome, K., Kaita, E., Levy, R., Miller, J., and Ding, L., 2024, ECCOE Landsat quarterly Calibration and Validation report—Quarter 2, 2024: U.S. Geological Survey Open-File Report 2024–1077, 56 p., https://doi.org/10.3133/ofr20241077.","productDescription":"Report: viii, 56 p.; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-168175","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":465270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1077/coverthb.jpg"},{"id":465271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1077/ofr20241077.pdf","text":"Report","size":"5.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1077"},{"id":465272,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1077/ofr20241077.XML"},{"id":465273,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1077/images/"},{"id":465274,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1077/images/"},{"id":465275,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"- EarthExplorer"},{"id":465277,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241077/full"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
In 2021, the Tennessee Department of Environment and Conservation (TDEC) and the U.S. Geological Survey worked in cooperation to develop a geographic information system (GIS)-based methodology that systematically assesses the vulnerability of public-supply drinking water to potential contaminants consistent with the standards set forth in the Tennessee Source Water Assessment Program (SWAP). As of June 2022, public-supply water was provided by 643 active public water systems across Tennessee that withdrew water for public use from 1,378 individual water sources. With the newly developed methodology, referred to as “TN-SWAPyT,” TDEC can consistently delineate source water assessment zones and evaluate source susceptibility on the basis of information such as the proximity of contaminant sources, land-use activities, geologic information, and additional environmental spatial data. A major benefit of the TN-SWAPyT methodology is to provide TDEC with consistent reports that can be used as a starting point for assessing public supplies. Communities and public water systems can then build upon these reports by using local knowledge and site-specific information.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"This book is an illustrative guide designed to introduce young minds to the exciting world of geologic hazards science careers. From geomorphologist to volcanologist, this book showcases a variety of science-based professions through fun and engaging activities. Each section of the book features a different science career and includes information about how the job got its name and what a typical day in the life of someone in that profession might look like. Readers will also have a chance to color, test their knowledge with trivia, and play a few games along the way. As a sequel to the biology-related science careers activity book, \"I Am a…Science Careers Book for Kids, Part 2\" is a fun and colorful way for kids to learn about the many exciting career opportunities available in the world of science.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip246","isbn":"978-1-4113-4592-8","programNote":"USGS Natural Hazards Mission Area","usgsCitation":"Sobieszczyk, S., 2024, I am a...Science careers book for kids, part 2: U.S. Geological Survey General Information Product 246, 51 p., https://doi.org/10.3133/gip246.","productDescription":"ii, 51 p.","numberOfPages":"51","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-168336","costCenters":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"links":[{"id":494227,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118087.htm"},{"id":465012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/246/coverthb.jpg"},{"id":465013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/246/gip246.pdf","text":"Report","size":"4.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 246 PDF"}],"contact":"Youth and Education in Science
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192
Email: usgs_yes@usgs.gov
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2024-12-18","noUsgsAuthors":false,"publicationDate":"2024-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Sobieszczyk, Steven 0000-0002-0834-8437","orcid":"https://orcid.org/0000-0002-0834-8437","contributorId":205030,"corporation":false,"usgs":true,"family":"Sobieszczyk","given":"Steven","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920603,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70261664,"text":"fs20243052 - 2024 - Lithium resource in the Smackover Formation brines of Southern Arkansas","interactions":[],"lastModifiedDate":"2025-08-15T16:30:14.115117","indexId":"fs20243052","displayToPublicDate":"2024-12-18T10:51:05","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3052","displayTitle":"Lithium Resource in the Smackover Formation Brines of Southern Arkansas","title":"Lithium resource in the Smackover Formation brines of Southern Arkansas","docAbstract":"Lithium-rich brine deposits occur throughout the United States, including in the Smackover Formation. The concentration of lithium in Smackover Formation brines was predicted across southern Arkansas by using a machine-learning model that incorporated lithium concentration data and geologic information. Between 5.1 and 19.0 million metric tons of lithium are calculated to be present in the brines of the Smackover Formation in southern Arkansas. The range in possible total lithium reflects the uncertainty in machine-learning predictions of lithium concentrations and the range of Smackover Formation porosity. This estimate quantifies the in-place lithium resource and does not consider the technological and economic feasibility of extracting the lithium from the brines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243052","issn":"2327-6916, 2327-6932","collaboration":"Prepared in cooperation with the Arkansas Department of Energy and Environment, Office of the State Geologist","programNote":"Energy Resources Program","usgsCitation":"Knierim, K.J., Masterson, A.L., Freeman, P.A., McDevitt, B., Herzberg, A.H., Li, P., Mills, C., Doolan, C., Jubb, A.M., Ausbrooks, S.M., and Chenault, J., 2024, Lithium resource in the Smackover Formation brines of southern Arkansas: U.S. Geological Survey Fact Sheet 2024–3052, 4 p., https://doi.org/10.3133/fs20243052.","productDescription":"Report: 4 p.; Data Release","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-172337","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":494229,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118086.htm","linkFileType":{"id":5,"text":"html"}},{"id":465210,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3052/fs20243052.pdf","size":"1.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3052"},{"id":465209,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3052/images"},{"id":465208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3052/coverthb.jpg"},{"id":465231,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243052/full","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3052 HTML"},{"id":465230,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3052/fs20243052.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2024-3052 XML"},{"id":465228,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/70259385","text":"Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning"},{"id":465219,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QPRYZN","text":"USGS Data Release","linkHelpText":"- Lithium observations, machine-learning predictions, and mass estimates from the Smackover Formation brines in southern Arkansas"}],"country":"United States","state":"Arkansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.00896297632752,\n 33.862680632060474\n ],\n [\n -94.00896297632752,\n 33.04929982263086\n ],\n [\n -92.24865389098971,\n 33.04929982263086\n ],\n [\n -92.24865389098971,\n 33.862680632060474\n ],\n [\n -94.00896297632752,\n 33.862680632060474\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021.
The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245109","collaboration":"Prepared in cooperation with the Rhode Island Water Resources Board","usgsCitation":"Chamberlin, C.A., Armstrong, I.P., and Stagnitta, T.J., 2024, Estimating domestic self-supplied water use in Rhode Island, 2014–21: U.S. Geological Survey Scientific Investigations Report 2024–5109, 29 p., https://doi.org/10.3133/sir20245109.","productDescription":"Report: vii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152675","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":464969,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WU48KY","text":"USGS data release","linkHelpText":"Monthly and annual population and self-supplied domestic water withdrawal maps of Rhode Island, 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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Understanding the causes of mortality for a declining species is essential for developing effective conservation and management strategies, particularly when anthropogenic activities are the primary threat. Using a competing hazards framework allows for robust estimation of the cause-specific variation in risk that may exist across multiple dimensions, such as time and individual. Here, we estimated cause-specific rates of severe injury and mortality for North Atlantic right whales (Eubalaena glacialis), a critically endangered species that is currently in peril due to human-caused interactions. We developed a multistate capture–recapture model that leveraged 30 years of intensive survey effort yielding sightings of individuals with injury assessments and necropsies of carcass recoveries. We examined variation in the hazard rates of severe injury and mortality due to entanglements in fishing gear and vessel strikes as explained by temporal patterns and the age and reproductive status of the individual. We found strong evidence for increased rates of severe entanglement injuries after 2013 and for females with calves, with consequently higher marginal mortality. The model results also suggested that despite vessel strikes causing a lower average rate of severe injuries, the higher mortality rate conditional on injury results in significant total mortality risk, particularly for females resting from a recent calving event. Large uncertainty in the estimation of carcass recovery rate for vessel strike deaths permeated into the apportionment of mortality causes. The increased rates of North Atlantic right whale mortality in the last decade, particularly for reproducing females, has been responsible for the severe decline in the species. By apportioning the human-caused threats using a quantitative approach with estimation of relevant uncertainty, this work can guide development of conservation and management strategies to facilitate species recovery. Our approach is relevant to other monitored populations where cause-specific injuries from multiple threats can be observed in live and dead individuals.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70086","usgsCitation":"Linden, D., Hostetler, J.A., Pace, R., Garrison, L.P., Knowlton, A., Lesage, V., Williams, R., and Runge, M.C., 2024, Quantifying uncertainty in anthropogenic causes of injury and mortality for an endangered baleen whale: Ecosphere, v. 15, no. 12, e70086, 12 p., https://doi.org/10.1002/ecs2.70086.","productDescription":"e70086, 12 p.","ipdsId":"IP-157942","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488298,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70086","text":"Publisher Index Page"},{"id":483337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Linden, Daniel W.","contributorId":229525,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":930730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":930731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pace, Richard M III","contributorId":352277,"corporation":false,"usgs":false,"family":"Pace","given":"Richard M","suffix":"III","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":930732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrison, Lance P.","contributorId":296893,"corporation":false,"usgs":false,"family":"Garrison","given":"Lance","email":"","middleInitial":"P.","affiliations":[{"id":64230,"text":"NOAA-NMFS Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":930733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knowlton, Amy R.","contributorId":352046,"corporation":false,"usgs":false,"family":"Knowlton","given":"Amy R.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":930734,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lesage, Veronique","contributorId":352311,"corporation":false,"usgs":false,"family":"Lesage","given":"Veronique","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":930735,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Robert A. 0000-0002-2973-8493","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":203802,"corporation":false,"usgs":false,"family":"Williams","given":"Robert A.","affiliations":[{"id":36721,"text":"USGS-Emeritus","active":true,"usgs":false}],"preferred":false,"id":930736,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":930737,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261711,"text":"70261711 - 2024 - A benchmark for computational analysis of animal behavior, using animal-borne tags","interactions":[],"lastModifiedDate":"2024-12-19T15:23:34.579209","indexId":"70261711","displayToPublicDate":"2024-12-18T09:18:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A benchmark for computational analysis of animal behavior, using animal-borne tags","docAbstract":"Animal-borne sensors (‘bio-loggers’) can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community.
To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers.
We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available.
In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE, to enable community use of BEBE.
","language":"English","publisher":"BMC","doi":"10.1186/s40462-024-00511-8","usgsCitation":"Hoffmann, B., Cusimano, M., Baglione, V., Canestrari, D., Chevallier, D., DeSantis, D.L., Jeantet, L., Ladds, M., Maekawa, T., Vicente, M., Moreno-Gonzalez, V., Pagano, A.M., Trapote, E., Vainio, O., Vehkaoja, A., Yoda, K., Zacarian, K., and Friedlaender, A., 2024, A benchmark for computational analysis of animal behavior, using animal-borne tags: Movement Ecology, v. 12, 78, 25 p., https://doi.org/10.1186/s40462-024-00511-8.","productDescription":"78, 25 p.","ipdsId":"IP-152357","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":466709,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-024-00511-8","text":"Publisher Index 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Infectious disease dynamics often depend on environmental conditions that drive occurrence, transmission, and outbreaks. Remote sensing can contribute to infectious disease research and management by providing standardized environmental data across broad spatial and temporal extents, often at no cost to the user. Here, we 1) conduct a systematic review of primary literature to quantify current uses of remote sensing in disease ecology and 2) synthesize qualitative information to identify opportunities for further integration of remote sensing into disease ecology. We identify that modern advances in airborne remote sensing are promoting early detection of forest pathogens and that satellite data is contributing to the study of geographically widespread human diseases. We discuss opportunities for increased use of data products that characterize vegetation, surface water, and soil; provide data at high spatio-temporal and spectral resolutions; and quantify uncertainty in measurements. Additionally, combining remote sensing with animal movement telemetry can provide novel insights into wildlife disease. Integrating these opportunities will advance research and management of infectious diseases.","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2024.1712","usgsCitation":"Teitelbaum, C., Ferraz, A., De La Cruz, S.E., Gilmour, M., and Brosnan, I., 2024, The potential of remote sensing for improved infectious disease ecology research and practice: Proceedings of the Royal Society B: Biological Sciences, v. 291, 20241712, 12 p., https://doi.org/10.1098/rspb.2024.1712.","productDescription":"20241712, 12 p.","ipdsId":"IP-170705","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466710,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2024.1712","text":"Publisher Index Page"},{"id":465563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"291","noUsgsAuthors":false,"publicationDate":"2024-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Teitelbaum, Claire S.","contributorId":337675,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire S.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":922111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferraz, António","contributorId":347661,"corporation":false,"usgs":false,"family":"Ferraz","given":"António","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":922112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922113,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmour, Morgan E.","contributorId":245099,"corporation":false,"usgs":false,"family":"Gilmour","given":"Morgan E.","affiliations":[],"preferred":false,"id":922114,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brosnan, Ian G.","contributorId":347663,"corporation":false,"usgs":false,"family":"Brosnan","given":"Ian G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":922115,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272012,"text":"70272012 - 2024 - Managing to survive despite the weather: Seeding decisions affecting simulated dryland restoration outcomes","interactions":[],"lastModifiedDate":"2025-09-30T15:53:37.174326","indexId":"70272012","displayToPublicDate":"2024-12-18T08:46:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Managing to survive despite the weather: Seeding decisions affecting simulated dryland restoration outcomes","docAbstract":"Limited favorable weather windows for post-germination early seedling survival are associated with low restoration success in drylands. We examined whether post-fire seeding decisions could alter early seedling emergence and restoration success across western North American sagebrush ecosystems with a simulation approach. Seedling emergence estimates were based on germination of a specified percentile of sown seeds followed by favorable conditions for seedling development. We asked how three categories of seeding decisions affected emergence: post-fire seeding year, seasonal seeding delay (via seed coating technologies or later seeding timing), or native perennial grass seed source (via differing germination behavior). We also tested potential effects of mean annual precipitation on seeding decision outcomes (interactive effect) and included topographic microclimate and site (random effect) in models. Emergence was highest when the best seed source (of 10) was seeded in the best post-fire year (of 5). High emergence also resulted from seeding in the best post-fire year with an average seed source or seeding with the best source in the first post-fire year. Emergence was higher overall with higher mean precipitation. Seeding decision outcomes were sensitive to annual mean precipitation, with greater differences observed due to decisions at lower precipitation levels. While sensitive to assumptions related to seedling development and germination speed, these results suggest that restoration approaches linked to germination behavior and weather variability could improve restoration success rates in variable drylands like sagebrush ecosystems.
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12201 Sunrise Valley Drive
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No abstract available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2024.110926","usgsCitation":"Petracca, L., Gardner, B., Maletzke, B., and Converse, S.J., 2024, Response to Santiago-Ávila et al. (2024): Biological Conservation, v. 302, 110926, 2 p., https://doi.org/10.1016/j.biocon.2024.110926.","productDescription":"110926, 2 p.","ipdsId":"IP-167848","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":503958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"302","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Petracca, L.S.","contributorId":351913,"corporation":false,"usgs":false,"family":"Petracca","given":"L.S.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":960939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, B.","contributorId":341497,"corporation":false,"usgs":false,"family":"Gardner","given":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":960940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maletzke, B.T.","contributorId":351917,"corporation":false,"usgs":false,"family":"Maletzke","given":"B.T.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":960941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":960942,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261453,"text":"tm9A6.1 - 2024 - Temperature","interactions":[{"subject":{"id":80044,"text":"twri09A6.1 - 2006 - Chapter A6. Section 6.1. Temperature","indexId":"twri09A6.1","publicationYear":"2006","noYear":false,"displayTitle":"Chapter A6. Section 6.1. Temperature","title":"Chapter A6. Section 6.1. Temperature"},"predicate":"SUPERSEDED_BY","object":{"id":70261453,"text":"tm9A6.1 - 2024 - Temperature","indexId":"tm9A6.1","publicationYear":"2024","noYear":false,"title":"Temperature"},"id":1}],"lastModifiedDate":"2024-12-18T15:19:29.063796","indexId":"tm9A6.1","displayToPublicDate":"2024-12-17T13:20:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"9-A6.1","displayTitle":"Temperature","title":"Temperature","docAbstract":"The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.1, provides guidance and protocols for the measurement of temperature of air, of a surface-water body or in groundwater, which include the scientific basis of the measurement, selection and maintenance of equipment, calibration verification, troubleshooting, and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.1, version 2.0, by Franceska D. Wilde.
Temperature of air and water is routinely measured when water samples are collected, is often measured continually at USGS streamgages, and is a parameter regularly measured during laboratory and field experiments. The field method for measuring temperature described in this chapter is applicable to air and most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
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Email: nfm@usgs.gov
","tableOfContents":"Walleye Sander vitreus is an important species that has been widely introduced outside of its native distribution. The goal of this study was to assess the effects of an established Walleye population in the Lake Pend Oreille (LPO) system, Idaho.
Food habits of Walleyes were described using stomach contents and stable isotopes (δ15N, δ13C). Trophic structure of the LPO system's food web was identified using stable isotopes. Annual consumption by Walleyes of important prey items was estimated using a bioenergetics model.
Walleyes consumed a diversity of prey items, including macroinvertebrates and fishes. Kokanee Oncorhynchus nerka, the most frequently consumed prey item, occurred in 23% of all Walleye diets. Combined, native cyprinids and catostomids occurred in 31% of all Walleye stomachs. Select taxa (e.g., native cyprinids, kokanee) were consistently consumed by Walleyes across seasons, regions, and cohorts, whereas other taxa (e.g., Westslope Cutthroat Trout O. lewisi, Smallmouth Bass Micropterus dolomieu) were consumed inconsistently. Stable isotope analysis suggested that Walleyes occupied similar trophic positions as other top‐level piscivores in the system. As Walleye age increased, δ15N increased and δ13C decreased, indicating increased consumption of pelagic prey resources and prey at higher trophic positions. The estimated biomass of kokanee consumed annually by Walleyes was 27,121 kg (95% confidence interval = 9178–61,603). Comparatively, native cyprinids represented about 46% of the total biomass of kokanee consumed by Walleyes, whereas native catostomids represented about 11% and native salmonids represented about 15% of the total biomass of kokanee consumed by Walleyes.
This study revealed that Walleyes consumed various fishes across the LPO system. Although kokanee were the most frequently consumed prey item, native cyprinids and catostomids (combined) occurred at similar proportions. This study contributes to our growing knowledge of the effects of nonnative Walleyes on important salmonids and native fishes in western systems.
The Colorado River is an important water source in the southwestern United States and northern Mexico. High concentrations of dissolved solids in the river, sourced mainly from the Upper Colorado River Basin (UCOL), cause hundreds of millions of dollars in damages annually to crops and infrastructure. Determinations of total dissolved solids (TDS) in river and tributary samples often rely on summed concentrations of constituents in solution reported as the sum of constituents (SOC), which includes the bicarbonate concentration converted to the equivalent carbonate mass that would be present as a residue after drying. Alternatively, salinity, similar to SOC but including the entire concentration of bicarbonate in solution, may be used as a measure of dissolved solids. Use of SOC results may under-represent actual dissolved-solids concentrations and loads in streams where bicarbonate is a substantial component of the dissolved solids in solution. The objective of this manuscript is to evaluate the differences between the SOC and salinity determinations of dissolved solids in UCOL streams and rivers. Water-quality data from the U.S. Geological Survey were used to compute salinity concentrations at UCOL stream sites for comparison with SOC determinations. Results from 8,001 samples at 418 UCOL sites indicate a median increase in dissolved solids of 20% (13% and 30%, 25th and 75th percentiles, respectively) using the salinity method compared with SOC results. Differences in dissolved solids attributable to the computational approach for handling bicarbonate at UCOL sites were significantly greater than laboratory variability based on results from 890 replicate analyses. Salinity may be a more useful indicator of water quality than SOC in systems with substantial proportions of bicarbonate in the composition of dissolved solids, including the Colorado River and UCOL sites.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pwat.0000310","usgsCitation":"Tillman, F.D., Miller, M., Wise, D., McCleskey, R., and Day, N.K., 2024, Salinity or sum of constituents— Methods comparison for computing dissolved solids concentrations in streams of the Upper Colorado River Basin: PLOS Water, v. 3, no. 12, e0000310, 13 p., https://doi.org/10.1371/journal.pwat.0000310.","productDescription":"e0000310, 13 p.","ipdsId":"IP-151803","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":466711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pwat.0000310","text":"Publisher Index Page"},{"id":465280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.07478126793694,\n 37.362761189486605\n ],\n [\n -110.7918874182937,\n 35.77503910288557\n ],\n [\n -106.92482149871722,\n 35.26377010349002\n ],\n [\n -105.78177189040801,\n 37.551686330409765\n ],\n [\n -106.7657709766068,\n 38.233772867977024\n ],\n [\n -105.31950823092234,\n 38.84018310941224\n ],\n [\n -104.67840732485422,\n 40.36065226066836\n ],\n [\n -106.71988351439666,\n 42.913593391958784\n ],\n [\n -109.98783943768271,\n 43.360892248620246\n ],\n [\n -110.9078832909733,\n 40.740953521572834\n ],\n [\n -112.07478126793694,\n 37.362761189486605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Daniel R. 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":921475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":921476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261593,"text":"sir20245113 - 2024 - Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","interactions":[],"lastModifiedDate":"2025-08-15T16:34:23.184884","indexId":"sir20245113","displayToPublicDate":"2024-12-17T09:08:14","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5113","displayTitle":"Perchlorate, Metals, Organic Compounds, and Lead Isotopes in Groundwater, Surface Water, Shallow Groundwater, and Soil Within and Near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","title":"Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022","docAbstract":"The Middleton Municipal Airport–Morey Field (C29) is in the City of Middleton and adjacent to the towns of Middleton and Springfield, Wisconsin. Nearby homes in the towns rely on private drinking water wells, and residents are concerned about the potential contamination of groundwater and surface water by airport activities, including flights by small aircraft that use leaded aviation fuel and a fireworks display in July 2021.
The U.S. Geological Survey, in cooperation with the Town of Middleton, completed a study in 2022 to characterize the occurrence and sources of perchlorate, metals (including lead), and organic compounds in samples of groundwater, surface water, shallow groundwater, and soils within and near the airport. Lead isotopes were also measured to determine sources of lead by comparing samples to environmental references.
Magnitudes of concentrations from samples of water and soil collected in 2022, and their spatial patterns across site locations, indicate the fireworks display in July 2021 was a likely source of perchlorate and metals in the airport study area. The highest perchlorate concentration was measured in surface water at the southeastern corner of the airport near the fireworks launch site; the highest concentrations of fireworks-associated metals were measured in shallow groundwater near the same location. Fireworks were not the only possible source of perchlorate and metals in the airport study area because both were also detected upgradient and away from the fireworks launch site.
Ratios of lead isotopes indicate that lead measured in water and soil within the airport study area was primarily sourced from background atmospheric lead deposition or Wisconsin galena lead ore. However, two groundwater samples (one upgradient and one downgradient from the airport; both with concentrations less than 1 microgram per liter) had isotopic signatures matching leaded aviation fuel sold at the airport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245113","collaboration":"Prepared in cooperation with the Town of Middleton, Wisconsin","usgsCitation":"Schachter, L.A., and Stuntebeck, T.D., 2024, Perchlorate, metals, organic compounds, and lead isotopes in groundwater, surface water, shallow groundwater, and soil within and near the Middleton Municipal Airport–Morey Field (C29), Middleton, Wisconsin, 2022: U.S. Geological Survey Scientific Investigations Report 2024–5113, 55 p., https://doi.org/10.3133/sir20245113.","productDescription":"Report: viii, 55 p.; Data Release; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166313","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":494232,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118085.htm","linkFileType":{"id":5,"text":"html"}},{"id":465140,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245113/full"},{"id":465139,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":465137,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5113/images/"},{"id":465135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5113/sir20245113.pdf","text":"Report","size":"9.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5113"},{"id":465134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5113/coverthb.jpg"},{"id":465138,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IEJULZ","text":"USGS data release","linkHelpText":"Lead concentrations and isotope ratios for selected water and soil samples near Middleton Municipal Airport–Morey Field (C29), Middleton, WI, 2022"},{"id":465136,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5113/sir20245113.XML"}],"country":"United States","state":"Wisconsin","city":"Middleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.55428476671052,\n 43.12980057216322\n ],\n [\n -89.55428476671052,\n 43.11162168312745\n ],\n [\n -89.51852520964913,\n 43.11162168312745\n ],\n [\n -89.51852520964913,\n 43.12980057216322\n ],\n [\n -89.55428476671052,\n 43.12980057216322\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
Long-term drought caused Lake Powell, a reservoir on the Colorado River (USA), to decline to its lowest elevation in >50 years during 2022–2023, allowing warm water to pass through intakes of Glen Canyon Dam and facilitating invasion by non-native Smallmouth Bass (Micropterus dolomieu). Establishment of bass downstream of the dam could threaten persistence of several native fishes, including two federally listed species. Subsequent detection of larval Smallmouth Bass in a spring-fed slough (river mile -12 slough) connected to the river in Glen Canyon National Recreation Area (NRA) increased urgency to stem further invasion. The National Park Service is evaluating proposed actions to limit effects from non-native predators on native species in the Colorado River, including potentially channelizing the slough. This locally rare, spring-fed waterbody provides habitat for other species, including Western Tiger Salamanders (Ambystoma mavortium subsp.) of uncertain origin. We found salamanders from the slough had two distinct mitochondrial DNA haplotypes identical to sequences from nearby Arizona Tiger Salamander (A. m. nebulosum) populations, confirming they are the native genotype. We detected Red-spotted Toads (Anaxyrus punctatus) and Woodhouse’s Toads (A. woodhousii) from three other sites in Glen Canyon NRA and 34 sites in adjacent, downstream Grand Canyon National Park (spanning ∼464 km of river) with environmental DNA and traditional surveys. However, we did not detect salamanders elsewhere, matching prior information that salamanders are rare in the Colorado River corridor below Glen Canyon Dam. Based on this information, we discuss management options for the local population of Arizona Tiger Salamanders.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2024.12.15.628570","usgsCitation":"Hossack, B., Stemp, K.M., Goldberg, C.S., Duke, A.C., Preston, T., Arnold, J.A., and Ray, A.R., 2024, Rare habitats, rare species, and invasive predators highlight management complexities in the Colorado River system: BioRxiv, https://doi.org/10.1101/2024.12.15.628570.","productDescription":"21 p.","ipdsId":"IP-173018","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496928,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.12.15.628570","text":"External Repository"},{"id":496819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":207343,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stemp, Kenzi Marie 0000-0001-7566-8513","orcid":"https://orcid.org/0000-0001-7566-8513","contributorId":362931,"corporation":false,"usgs":true,"family":"Stemp","given":"Kenzi","middleInitial":"Marie","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":950845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Caren S","contributorId":362932,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","middleInitial":"S","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":950846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duke, Alexandra C.","contributorId":362933,"corporation":false,"usgs":false,"family":"Duke","given":"Alexandra","middleInitial":"C.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":950847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Preston, Taryn","contributorId":292557,"corporation":false,"usgs":false,"family":"Preston","given":"Taryn","email":"","affiliations":[{"id":62075,"text":"National Park Service, Grand Canyon National Park","active":true,"usgs":false}],"preferred":false,"id":950848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arnold, J. Andrew","contributorId":213088,"corporation":false,"usgs":false,"family":"Arnold","given":"J.","email":"","middleInitial":"Andrew","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":950849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ray, Adam R","contributorId":148959,"corporation":false,"usgs":false,"family":"Ray","given":"Adam","email":"","middleInitial":"R","affiliations":[{"id":17603,"text":"Department of Fisheries and Wildlife, Oregon State University, 104 Nash Hall, 2820 Southwest Campus Way, Corvallis, OR 97331","active":true,"usgs":false}],"preferred":false,"id":950850,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261851,"text":"70261851 - 2024 - Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA","interactions":[],"lastModifiedDate":"2024-12-31T15:24:53.181359","indexId":"70261851","displayToPublicDate":"2024-12-17T08:49:54","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA","docAbstract":"National parks in the U.S. play a large role in providing habitat for native pollinators. In parks that are established to preserve cultural landscapes, park managers recognize an opportunity to improve pollinator habitat while maintaining historically accurate conditions. In this study we document floral resources and native bees within managed park grasslands, with the goal of providing managers information to help them maximize pollinator habitat while meeting other management objectives. The study was performed on 37 grassland properties in the mid-Atlantic region of the eastern U.S., distributed across four national parks; each property was managed with one of three management types: cool-season hayed, cool-season pasture, or warm-season meadows managed with multiple approaches. We surveyed bees and open flowers on 50-m transects twice each year in 2021 and 2022. Repeated measures ANOVA models revealed mean bee abundance, richness, evenness, and diversity did not vary among sites or management types. This finding was further supported by a principal coordinates analysis that showed bee community composition was similar across management types. Nonetheless, we found evidence to indicate the three management types did not produce equivalent habitat for bees. Species accumulation curves showed that the effective number of flower species was consistently lower in cool-season pastures, relative to the other two management types. Furthermore, we detected positive correlations between bee and flower diversity metrics in one of the two years, suggesting that floral metrics can influence bee communities, at least under certain conditions. Collectively, our study suggests that cool-season fields that are hayed and warm-season meadows have higher floral diversity than cool-season pastures within national parks of the mid-Atlantic region, and this higher diversity of forbs has the potential to benefit native bee diversity.","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70719","usgsCitation":"Larson, D., Landsman, A.P., Simanonok, M., Larson, J., Davies, C., and Otto, C., 2024, Bee habitat, but not bee community structure, varies across grassland management in four national parks in the Mid-Atlantic, USA: Ecology and Evolution, v. 14, no. 12, e70719, 12 p., https://doi.org/10.1002/ece3.70719.","productDescription":"e70719, 12 p.","ipdsId":"IP-165538","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":466712,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70719","text":"Publisher Index Page"},{"id":465562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Antietam National Battlefield, Chesapeake and Ohio Canal National Historical Park, Manassas National Battlefield Park, Monocacy National Battlefield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.87075132703544,\n 38.76343738595514\n ],\n [\n -77.19342578059188,\n 38.76343738595514\n ],\n [\n -77.19342578059188,\n 39.7128528705739\n ],\n [\n -78.87075132703544,\n 39.7128528705739\n ],\n [\n -78.87075132703544,\n 38.76343738595514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":260165,"corporation":false,"usgs":true,"family":"Larson","given":"Diane L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landsman, Andrew P 0000-0002-4750-819X","orcid":"https://orcid.org/0000-0002-4750-819X","contributorId":291247,"corporation":false,"usgs":false,"family":"Landsman","given":"Andrew","email":"","middleInitial":"P","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":922030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simanonok, Michael 0000-0002-4710-4515","orcid":"https://orcid.org/0000-0002-4710-4515","contributorId":228829,"corporation":false,"usgs":false,"family":"Simanonok","given":"Michael","email":"","affiliations":[],"preferred":false,"id":922031,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":317994,"corporation":false,"usgs":false,"family":"Larson","given":"Jennifer L.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":922032,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Cora","contributorId":347591,"corporation":false,"usgs":false,"family":"Davies","given":"Cora","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":922033,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922034,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261814,"text":"70261814 - 2024 - Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","interactions":[],"lastModifiedDate":"2024-12-26T15:14:45.383291","indexId":"70261814","displayToPublicDate":"2024-12-17T08:05:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations","docAbstract":"Climate-induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector-borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecast of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits which may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life-history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait-based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi-scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.70074","usgsCitation":"Mcdevitt-Galles, T., DeGaetano, A., Elmendorf, S., Foster, J., Ginsberg, H., Hooten, M.B., LaDeau, S., McClure, K.M., Paull, S.H., Posthumus, E.E., Rochlin, I., and Grear, D.A., 2024, Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations: Ecosphere, v. 15, no. 12, e70074, 17 p., https://doi.org/10.1002/ecs2.70074.","productDescription":"e70074, 17 p.","ipdsId":"IP-155775","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":466713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70074","text":"Publisher Index Page"},{"id":465460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.66548403699112,\n 47.19667094970478\n ],\n [\n -88.50420169961106,\n 44.205989638511255\n ],\n [\n -87.90485319328981,\n 41.39073197003515\n ],\n [\n -82.86371026854579,\n 41.70904546715229\n ],\n [\n -82.40184439476982,\n 43.538614110411345\n ],\n [\n -83.49315804844203,\n 46.63943412739803\n ],\n [\n -86.86116175538491,\n 47.49199734956696\n ],\n [\n -88.28863179000962,\n 47.61050307535439\n ],\n [\n -89.66548403699112,\n 47.19667094970478\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcdevitt-Galles, Travis 0000-0002-4929-5431","orcid":"https://orcid.org/0000-0002-4929-5431","contributorId":315374,"corporation":false,"usgs":true,"family":"Mcdevitt-Galles","given":"Travis","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeGaetano, Arthur 0000-0002-0183-1346","orcid":"https://orcid.org/0000-0002-0183-1346","contributorId":347511,"corporation":false,"usgs":false,"family":"DeGaetano","given":"Arthur","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":921904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elmendorf, Sarah 0000-0003-1085-8521","orcid":"https://orcid.org/0000-0003-1085-8521","contributorId":347512,"corporation":false,"usgs":false,"family":"Elmendorf","given":"Sarah","affiliations":[{"id":83184,"text":"University of Colorado: Boulder","active":true,"usgs":false}],"preferred":false,"id":921905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, John R. 0000-0002-7526-3177","orcid":"https://orcid.org/0000-0002-7526-3177","contributorId":347513,"corporation":false,"usgs":false,"family":"Foster","given":"John R.","affiliations":[],"preferred":false,"id":921906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":347514,"corporation":false,"usgs":false,"family":"Ginsberg","given":"Howard S.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":921907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":292295,"corporation":false,"usgs":false,"family":"Hooten","given":"Mevin","email":"","middleInitial":"B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":921908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaDeau, Shannon 0000-0003-4825-5435","orcid":"https://orcid.org/0000-0003-4825-5435","contributorId":347515,"corporation":false,"usgs":false,"family":"LaDeau","given":"Shannon","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":921909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McClure, Katherine Maria 0000-0001-8595-7677","orcid":"https://orcid.org/0000-0001-8595-7677","contributorId":332279,"corporation":false,"usgs":true,"family":"McClure","given":"Katherine","email":"","middleInitial":"Maria","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":921910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paull, S. H. 0000-0001-5589-9568","orcid":"https://orcid.org/0000-0001-5589-9568","contributorId":292340,"corporation":false,"usgs":false,"family":"Paull","given":"S.","email":"","middleInitial":"H.","affiliations":[{"id":62877,"text":"Battelle, National Ecological Observatory Network, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":921911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Posthumus, Erin E. 0000-0003-3855-2380","orcid":"https://orcid.org/0000-0003-3855-2380","contributorId":204418,"corporation":false,"usgs":false,"family":"Posthumus","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":40537,"text":"USA National Phenology Network, National Coordinating Office; University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":921912,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rochlin, Ilia 0000-0001-7680-6965","orcid":"https://orcid.org/0000-0001-7680-6965","contributorId":347516,"corporation":false,"usgs":false,"family":"Rochlin","given":"Ilia","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":921913,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":921914,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70261417,"text":"sim3530 - 2024 - Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","interactions":[],"lastModifiedDate":"2026-04-02T18:59:12.90477","indexId":"sim3530","displayToPublicDate":"2024-12-16T15:35:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3530","displayTitle":"Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 2 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts","title":"Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts","docAbstract":"The U.S. Geological Survey, in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area being mapped using geophysical and geological data includes the SBNMS and the surrounding region, which totals approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. The seabed is a glaciated terrain that is topographically and texturally diverse. Quadrangle 2, the subject of this scientific investigations map, has a mapped area of 209 km2 and has water depths that range from about 19 meters (m) on the Stellwagen Bank crest to about 68 m in the Stellwagen Basin. Seven map types, each at a scale of 1:25,000, depict seabed topography, ruggedness, backscatter intensity, distribution of geologic substrates, sediment mobility, distribution of fine- and coarse-grained sand, and substrate mud content. These maps show the distribution of geologic substrates across the southwestern part of Stellwagen Bank, in Stellwagen Basin to the west and southwest of the bank, and in Little Stellwagen Basin and the western part of Race Point Channel to the south of the bank. Interpretations of multibeam sonar bathymetric and seabed backscatter imagery, photographs, video imagery, and grain-size analyses were used to create the geology-based maps. Data from 733 stations were analyzed, including 656 sediment samples. The geologic substrate maps of quadrangle 2 show the distribution of 19 geologic substrates that represent a wide range of textures, such as rippled and immobile sand, immobile muddy sand and sandy mud, sand that partially veneers gravel, and a boulder ridge. Mapped substrates are characterized by sediment grain-size composition, surface morphology, substrate layering, the mobility or immobility of substrate surfaces, and water depth range. This scientific investigations map portrays the major geological elements (substrates, topographic features, and processes) of environments in quadrangle 2. It is intended to provide a foundation for research into present and past sediment transport processes in a complex terrain, provide insights into the ecological requirements of invertebrate and vertebrate species that utilize the various substrates, and support seabed management in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3530","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","programNote":"Coastal/Marine Hazards and Resources Program","usgsCitation":"Valentine, P.C., and Cross, V.A., 2024, Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts: U.S. Geological Survey Scientific Investigations Map 3530, 8 sheets, scale 1:25,000, 27-p. pamphlet, https://doi.org/10.3133/sim3530.","productDescription":"Pamphlet: v, 27 p.; 8 Sheets: 26.98 x 35.69 inches or smaller; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-153982","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":499036,"rank":17,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118083.htm","linkFileType":{"id":5,"text":"html"}},{"id":465083,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3341","text":"Scientific Investigations Map 3341","linkHelpText":"- Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts"},{"id":465082,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3515","text":"Scientific Investigations Map 3515","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 5 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465080,"rank":13,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapF.pdf","text":"Map F","size":"876 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map F","linkHelpText":"- Distribution of Fine- and Coarse-Grained Sand and Boulder Ridges"},{"id":465079,"rank":12,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapE.pdf","text":"Map E","size":"882 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map E","linkHelpText":"- Sediment Mobility"},{"id":465078,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapD2.pdf","text":"Map D, Sheet 2","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map D2","linkHelpText":"- Distribution of Geologic Substrates: Seabed geology and sun-illuminated topography"},{"id":502036,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3544","text":"Scientific Investigations Map 3544","linkHelpText":"- Seabed Maps Showing Topography, Ruggedness, Backscatter Intensity, Sediment Mobility, and the Distribution of Geologic Substrates in Quadrangle 3 of the Stellwagen Bank National Marine Sanctuary Region Offshore of Boston, Massachusetts"},{"id":465081,"rank":14,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapG.pdf","text":"Map G","size":"895 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map G","linkHelpText":"- Distribution of Substrate Mud Content and Boulder Ridges"},{"id":464927,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UL3LWN","text":"USGS data release","linkHelpText":"Geospatial datasets of seabed topography, sediment mobility, and the distribution of geologic substrates in quadrangle 2 of the Stellwagen Bank National Marine Sanctuary region offshore of Boston, Massachusetts"},{"id":465074,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapA.pdf","text":"Map A","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map A","linkHelpText":"- Sun-Illuminated Topography and Boulder Ridges"},{"id":465077,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapD1.pdf","text":"Map D, Sheet 1","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map D1","linkHelpText":"- Distribution of Geologic Substrates: Seabed geology and station data types"},{"id":465076,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapC.pdf","text":"Map C","size":"22.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map C","linkHelpText":"- Backscatter Intensity and Sun-Illuminated Topography"},{"id":465075,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_mapB.pdf","text":"Map B","size":"1.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 Map B","linkHelpText":"- Seabed Ruggedness"},{"id":464926,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3530/images/"},{"id":464925,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3530/sim3530.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3530 XML"},{"id":464924,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3530/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3530 HTML"},{"id":464923,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3530/sim3530_pamphlet.pdf","text":"Pamphlet","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3530 PDF"},{"id":464922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3530/coverthb2.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Stellwagen Bank National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.19346273969718,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.21157101051443\n ],\n [\n -70.35655387736588,\n 42.097308493871026\n ],\n [\n -70.19346273969718,\n 42.097308493871026\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
Objective: Understanding angler responses to fisheries management actions such as regulation changes have important implications for the effectiveness and efficacy of such management strategies. We examined the ability of remote vehicle counters to provide a relative index of angler effort and present a case study demonstrating use of vehicle counters to assess potential changes in angler effort associated with implementation of more restrictive panfish regulations in a subset of Wisconsin lakes.
Methods: We compared vehicle counts with compulsory creel and game-camera based estimates of angler hours and number of angling parties. During 2016, a series of more restrictive panfish regulations were implemented across 132 Wisconsin lakes. We deployed vehicle counters at a subset of lakes within each regulation type during pre- (2015 and 2016) and post-regulation time periods (2021 and 2022) to assess whether the distribution of angler effort (as indexed using vehicle counters) among regulation types may have shifted in response to regulation implementation.
Result: At lakes with paired vehicle counters and compulsory creel data, vehicle counts explained 57-72% of variation in daily angler effort (h) and 65-85% of variation in daily number of angling parties. Across lakes with paired vehicle counters and game cameras, vehicle counters explained 77% of variation in the number of apparent angling parties; however, effectiveness of vehicle counters for explaining variation in number of apparent angling parties varied among lakes. Vehicle counters explained 63-74% of variation in number of apparent angling parties when considering paired vehicle counter-game camera observations pooled within regulation types. We did not observe any systematic shifts in effort indicative of redistribution of angler effort in response to panfish regulations.
Conclusion: Results suggest that, given appropriate validation measures, vehicle counters could be used as a cost-effective tool to index angler effort, particularly when interest lies in understanding effort dynamics over large spatial scales. Our findings suggest a localized scale for implementation of specialized regulations may be appropriate given angler behaviors and preferences for Wisconsin panfish.
","language":"English","publisher":"American Fisheries society","doi":"10.1002/nafm.11054","usgsCitation":"Dembkowski, D., Latzka, A., Feiner, Z., and Isermann, D.A., 2024, Use of vehicle counters to index and evaluate potential shifts in angler effort following implementation of more restrictive panfish regulations in Wisconsin lakes: North American Journal of Fisheries Management, v. 44, no. 6, p. 1342-1357, https://doi.org/10.1002/nafm.11054.","productDescription":"16 p.","startPage":"1342","endPage":"1357","ipdsId":"IP-163236","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Vilas County","otherGeospatial":"Escanaba Lake, Nebish Lake, Northern Highland Fishery Research Area","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.9879,46.0971],[-88.9329,46.0746],[-88.9332,45.9822],[-89.0478,45.9822],[-89.0477,45.8953],[-89.1091,45.8973],[-89.1752,45.8993],[-89.1754,45.859],[-89.3008,45.8606],[-89.3007,45.9014],[-89.3628,45.8987],[-89.4256,45.8987],[-89.5498,45.8988],[-89.6741,45.8987],[-89.7571,45.8985],[-89.797,45.898],[-89.8199,45.8984],[-89.9212,45.8981],[-89.9846,45.8974],[-90.0428,45.8972],[-90.0442,45.9823],[-90.0134,45.9824],[-89.9853,45.9821],[-89.9289,45.9818],[-89.9282,46.0693],[-89.9288,46.1558],[-89.9287,46.2428],[-89.929,46.3],[-89.7599,46.268],[-89.7368,46.2636],[-89.5829,46.2347],[-89.5331,46.2252],[-89.5133,46.2215],[-89.4272,46.2048],[-89.3759,46.1949],[-89.2666,46.1737],[-89.2302,46.1662],[-89.0854,46.1365],[-88.9879,46.0971]]]},\"properties\":{\"name\":\"Vilas\",\"state\":\"WI\"}}]}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":275009,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Latzka, Alexander W.","contributorId":348855,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feiner, Zachary S.","contributorId":348857,"corporation":false,"usgs":false,"family":"Feiner","given":"Zachary S.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":923834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923835,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261327,"text":"sir20245092 - 2024 - Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","interactions":[],"lastModifiedDate":"2025-08-15T16:35:47.148112","indexId":"sir20245092","displayToPublicDate":"2024-12-16T12:46:53","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5092","displayTitle":"Desert Tortoise Translocation Plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","title":"Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area","docAbstract":"The U.S. Department of the Army proposes to commence military activity at the Fort Irwin National Training Center within the Western Training Area (WTA) and to translocate Mojave Desert tortoises (Gopherus agassizii; hereafter tortoise) that will be affected to the Western Training Area Translocation Site (WTATS). This desert tortoise translocation plan provides a timeline of activities, actions for which permits may be required, and guidelines for assessing the short-term and long-term success of this desert tortoise translocation. Importantly, the monitoring projects described are designed to document the ultimate effects of the Army's translocation action (not just inform future translocations elsewhere). Results from the translocation, corresponding monitoring, and research projects will inform future translocations throughout the Mojave Desert for expanding human development. The plan has three main objectives: (1) provide guidelines to achieve a safe, humane, and successful translocation of tortoises from the WTA, with minimal effect to resident desert tortoises at sites where translocated animals are released (recipient sites); (2) study translocated, resident, and reference animals (tortoises living near translocation areas but whose home ranges do not overlap those of translocated or resident tortoises) to learn as much as possible about the ecology, conservation, and management of the desert tortoise; and (3) define best management practices for successful translocation and provide metrics to evaluate success over multiple time scales, which we identify for the short- and long-term.
The procedures to plan, implement, monitor, and study translocation of tortoises were written using terms and conditions outlined in the U.S. Fish and Wildlife Service Biological Opinion 2021 that described effects of the expansion of the military base boundary, as well as recommendations provided in the Desert Tortoise Recovery Plan (and 5-year review). We provide guidance on appropriate translocation timing and procedures, as well as on how tortoise ecology and habitat can best be studied to further knowledge on tortoise translocation. The plan provides analysis for landscape tortoise density and abundance estimates, suitable sites for translocation of tortoises, and short- and long-term metrics that are addressed and measured by specific monitoring and research projects that can be used to assess the success of translocation activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245092","collaboration":"Prepared in cooperation with the U.S. Department of Defense, U.S. Army Garrison Fort Irwin, California","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Esque, T., Xiong, A., Doyle, S., Murphy, S., Wilhite, C., and Nussear, K., 2024, Desert Tortoise translocation plan for the U.S. Department of the Army National Training Center and Fort Irwin Western Training Area: U.S. Geological Survey Scientific Investigations Report 2024–5092, 94 p., https://doi.org/10.3133/sir20245092.","productDescription":"Report: x, 94 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-159450","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":494233,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118082.htm","linkFileType":{"id":5,"text":"html"}},{"id":465229,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245092/full"},{"id":464818,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5092/images"},{"id":464817,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5092/sir20245092.xml"},{"id":464815,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5092/covrthb.jpg"},{"id":464813,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93ZU0R9","text":"USGS Data Release","description":"Carr, N.B., and Leinwand, I.I.F., 2020, Terrestrial Development Index for the western United States—1-kilometer moving window: U.S. Geological Survey data release, https://doi.org/10.5066/P93ZU0R9.","linkHelpText":"Terrestrial Development Index for the western United States—1-kilometer moving window"},{"id":464816,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5092/sir20245092.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Fort Irwin Western Training Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.5,\n 35.5\n ],\n [\n -117.5,\n 34.75\n ],\n [\n -116.25,\n 34.75\n ],\n [\n -116.25,\n 35.5\n ],\n [\n -117.5,\n 35.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Climate change coupled with large-scale surface disturbances necessitate active restoration strategies to promote resilient and genetically diverse native plant communities. However, scarcity of native plant materials hinders restoration efforts, leading practitioners to choose from potentially viable but nonlocal seed sources. Genome scans for genetic variation linked with selective environmental gradients have become a useful tool in such efforts, allowing rapid delineation of seed transfer zones along with predictions of genomic vulnerability to climate change. When properly applied, genome scans can reduce the risk of maladaptation due to mismatches between seed source and planting site. However, results are rarely replicated among complimentary data sources. Here, we compared RAD-seq datasets with 819 and 2699 SNPs (in 625 and 356 individuals, respectively) from the Mojave Desert winter annual Chylismia brevipes. Overall, we found that the datasets consistently characterized both neutral population structure and genetic–environmental associations. Ancestry analyses indicated consistent spatial genetic structuring into four regional populations. We also detected a marked signal of isolation by resistance (IBR), wherein spatial genetic structure was better explained by habitat resistance than by geographic distance. Potentially adaptive loci identified from genome scans were associated with the same environmental gradients—fall precipitation, winter minimum temperature, and precipitation timing—regardless of dataset. Paired with our finding that habitat resistance best explained genetic divergence, our results suggest that isolation of populations within environmentally similar habitats—and subsequent local adaption along gradients parallel to these habitats—drive genome-wide divergence in this species. Moreover, strong genetic associations with winter precipitation timing, along with forecasted shifts in precipitation regime due to midcentury climate change, could impact future population dynamics, habitat distribution, and genetic connectivity for C. brevipes populations within the Mojave Desert.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.70046","usgsCitation":"Shryock, D., Lê, N., DeFalco, L., and Esque, T., 2024, Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation: Conservation Genetics, v. 17, no. 12, e70046, 18 p., https://doi.org/10.1111/eva.70046.","productDescription":"e70046, 18 p.","ipdsId":"IP-159454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.70046","text":"Publisher Index Page"},{"id":465575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.2859722224079,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 33.84962249242069\n ],\n [\n -113.08194078286547,\n 38.02841230408214\n ],\n [\n -120.2859722224079,\n 38.02841230408214\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lê, Nila","contributorId":347238,"corporation":false,"usgs":false,"family":"Lê","given":"Nila","affiliations":[{"id":83101,"text":"California Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":922100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}