Background: Desert tortoise (Gopherus agassizii) populations have continued to decline due to infectious and other diseases, predation, and habitat alteration. The potential contribution of minerals and heavy metals to tortoise health and susceptibility to disease remains uncertain.
Objective: The objective of this study was to evaluate the results of elemental analysis of trace minerals and macrominerals in scute keratin, kidney, and liver tissue from ill and dying desert tortoises salvaged for necropsy between 1993 and 2000.
Methods: Salvaged tortoises were categorized by age (adult, juvenile), geographic location, and primary disease based on necropsy findings. A subset of tortoises that were injured or killed by vehicular trauma or predation but with no notable pathologic abnormalities were used as controls. A panel of 21 trace minerals and 6 macrominerals was analyzed in scute keratin, kidney, and liver tissue samples by inductively-coupled plasma spectrometry and atomic absorption spectrophotometry.
Results: Necropsies were done on 46 tortoises, including 9 juveniles salvaged from 5 regions in the Colorado and Mojave deserts of California. Primary diseases were cutaneous dyskeratosis (n=9), infection/ inflammation (n=8), malnutrition (n=7), mycoplasmosis (n=5), and urolithiasis (n=3); 14 tortoises were classified as controls. Concentrations of elements differed significantly by tissue, age, desert region, and disease (P < 0.05). Tortoises with cutaneous dyskeratosis had significantly higher Se concentrations, primarily in keratin and liver, than tortoises with other diseases (P < 0.001). Juveniles were more likely than adults to have high Pb, Sn, and Zn levels (P < 0.05). All tortoises had detectable levels of more than one potentially toxic heavy metal, including As, Cd, Cr, Hg, Ni, Pb, Sn and V.
Conclusions: Potentially toxic elements are frequently found in tissue from tortoises in desert regions of California, with significantly higher concentrations in diseased tortoises. Metal exposure from soils, mining, historic and ongoing military activities, and other human activities could increase susceptibility to disease in desert tortoises.
","language":"English","publisher":"Frontiers","doi":"10.3389/fvets.2024.1481367","usgsCitation":"Berry, K.H., Christopher, M., and Jacobson, E., 2024, Potentially toxic elements in wild Agassiz’s desert tortoises: Tissue concentrations and association with disease: Frontiers in Veterinary Sciences, v. 11, 1481367, 15 p., https://doi.org/10.3389/fvets.2024.1481367.","productDescription":"1481367, 15 p.","ipdsId":"IP-166170","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466752,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fvets.2024.1481367","text":"Publisher Index Page"},{"id":465561,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Colorado Desert, Mojave Desert, Sonoran Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.05397514870228,\n 35.97731275545118\n ],\n [\n -118.05397514870228,\n 32.60377435565428\n ],\n [\n -113.73422113613373,\n 32.60377435565428\n ],\n [\n -113.73422113613373,\n 35.97731275545118\n ],\n [\n -118.05397514870228,\n 35.97731275545118\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Berry, Kristin H. 0000-0003-1591-8394 kristin_berry@usgs.gov","orcid":"https://orcid.org/0000-0003-1591-8394","contributorId":437,"corporation":false,"usgs":true,"family":"Berry","given":"Kristin","email":"kristin_berry@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopher, Mary M. 0000-0002-5841-8501","orcid":"https://orcid.org/0000-0002-5841-8501","contributorId":346499,"corporation":false,"usgs":false,"family":"Christopher","given":"Mary M.","affiliations":[],"preferred":false,"id":922131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobson, Elliiott","contributorId":347667,"corporation":false,"usgs":false,"family":"Jacobson","given":"Elliiott","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":922132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261040,"text":"ofr20241042 - 2024 - Assessing community needs for terrestrial analog studies","interactions":[],"lastModifiedDate":"2024-11-21T14:52:20.838537","indexId":"ofr20241042","displayToPublicDate":"2024-11-20T12:16:52","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1042","displayTitle":"Assessing Community Needs for Terrestrial Analog Studies","title":"Assessing community needs for terrestrial analog studies","docAbstract":"The U.S. Geological Survey (USGS) developed and released a survey to assess the terrestrial analog needs of the planetary science community. The goal was to assess the current state of terrestrial analog studies and determine community needs related to the use of field sites for training and research, data dissemination and archiving, and sample collections.
The survey was designed to gather feedback from community members who have a self-described interest in the use of terrestrial analogs. The web-based questionnaire contained a total of 33 questions and was designed to take <10 minutes to complete. The questionnaire was divided into four sections: (1) “Respondent Details,” (2) “Field Analog Use,” (3) “Data Portal Use,” and (4) “Geologic Materials Collection Use.” Comment boxes were provided for 12 of the 33 questions, which allowed respondents to provide more detailed comments to individual questions. The questionnaire received a total of 248 responses. We identified 21 notable findings which are matched with one or more recommendations to be addressed by the planetary science community.
In general, the findings highlight the importance of terrestrial analog studies to the planetary science community. The findings address how and why the community uses terrestrial analogs, areas in which further support can lead to a greater return on investment, and how the community can better manage data and samples from these studies.
The results from this survey identify a need for additional training opportunities and analog-focused workshops. There is a gap in formal education related to field techniques for a significant part of researchers who conduct fieldwork. There is also a subset of the community who are interested in conducting field-based studies but are, however, unaware of relevant sites and methods. Workshops would provide an opportunity for scientists at all career stages to share their results and discuss common challenges such as logistics, field safety, funding, and data and sample archiving. Trainings, workshops, and better communication may also lead to increased field-analog work at locations in closer proximity to home institutions, reducing costs associated with large field expeditions and ultimately leading to more available funding for more localized field studies.
The survey also shows that the ability to archive a diverse array of field data is a major challenge for terrestrial studies and finds that existing practices are not compliant with National Aeronautics and Space Administration (NASA) data management policies. The survey points to a strong need for a central data repository, allowing for easier access to existing analog data and the archiving of new field data.
The community would benefit from additional physical sample archiving, consolidated into several key institutions to promote easier access, such as NASA and USGS centers. Though scientists would still need to acquire their own samples in the field for certain studies, many studies would benefit from an archive of existing samples and associated data for widely used analog sites, reducing redundant sampling practices.
This report finds that a coordinated effort to improve and standardize training, data archiving, sample curation, and communication regarding terrestrial analog studies will best serve the planetary science community in our exploration goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241042","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"Edgar, L.A., Rumpf, M.E., Skinner, J.A., Jr., Gullikson, A.L., Keszthelyi, L., Hunter, M.A., Gaither, T., 2024, Assessing community needs for terrestrial analog studies: U.S. Geological Survey Open-File Report 2024–1042, 63 p., https://doi.org/10.3133/ofr20241042.","productDescription":"iii, 63 p.","onlineOnly":"Y","ipdsId":"IP-124254","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":464364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1042/covrthb.jpg"},{"id":464365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1042/ofr20241042.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
Anadromous fishes play important roles in nutrient dynamics for freshwater ecosystems; however, the trophic pathways have been less documented for iteroparous species like river herring (Alosa pseudoharengus and A. aestivalis) compared to semelparous species like Pacific salmon (Oncorhynchus spp.). Given recent increases in restoration activities to improve connectivity, an understanding of how anadromous river herring influence the morphology, physiology, and life history of predatory fishes can help predict restoration responses. We aimed to quantify the trophic influence of juvenile anadromous river herring on predatory white perch (Morone americana) and yellow perch (Perca flavescens) using a combination of stable isotopes, growth rates, and condition indices. We sampled six lakes in coastal Massachusetts—three lakes with anadromous river herring and three similar lakes without river herring. Bayesian mixing models of δ13C and δ15N indicated white perch consumed juvenile river herring in higher proportions (69–75%) compared to co-occurring prey fishes (11–16%). Lakes with juvenile river herring contained perch with significantly higher condition values, higher immature growth rates (age 1 and 2), lower mature growth rates (> age 3), significantly smaller mature lengths, and lower mortality rates compared to perch in lakes without river herring. These divergent life history traits of perch in response to consumption of juvenile river herring are consistent with observations in other predatory fishes. Direct links between river herring and predator condition, growth, and life history trajectories suggest broad influences on ecosystem structure across trophic levels through physiological, morphometric, and life history modifications.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10641-024-01595-2","usgsCitation":"Mattocks, S., Bittner, S., Luzanau, V., Mohammadi, H., Roy, A.H., Staudinger, M., and Jordaan, A., 2024, River herring influence perch morphology, physiology, and life history: Environmental Biology of Fishes, v. 107, p. 1179-1201, https://doi.org/10.1007/s10641-024-01595-2.","productDescription":"23 p.","startPage":"1179","endPage":"1201","ipdsId":"IP-103045","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.03687326915752,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.047149016365864\n ],\n [\n -70.5974201441574,\n 42.873848597989394\n ],\n [\n -71.03687326915752,\n 42.873848597989394\n ]\n ]\n ],\n \"type\": \"Polygon\"\n },\n \"id\": 0\n }\n ]\n}","volume":"107","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mattocks, Steven","contributorId":349651,"corporation":false,"usgs":false,"family":"Mattocks","given":"Steven","affiliations":[{"id":83496,"text":"Massachusetts Division of Fisheries and Widlife","active":true,"usgs":false}],"preferred":false,"id":924535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bittner, Steven","contributorId":349652,"corporation":false,"usgs":false,"family":"Bittner","given":"Steven","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luzanau, Vasili","contributorId":349653,"corporation":false,"usgs":false,"family":"Luzanau","given":"Vasili","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohammadi, Habibollah","contributorId":349654,"corporation":false,"usgs":false,"family":"Mohammadi","given":"Habibollah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924534,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staudinger, Michelle D.","contributorId":349655,"corporation":false,"usgs":false,"family":"Staudinger","given":"Michelle D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":349656,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":924540,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261138,"text":"70261138 - 2024 - Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels","interactions":[],"lastModifiedDate":"2024-11-26T16:34:22.629421","indexId":"70261138","displayToPublicDate":"2024-11-20T10:27:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels","docAbstract":"Zebra mussels (Dreissena polymorpha) are invasive species that alter ecosystems and food webs with the potential to affect aquatic mercury cycling and bioaccumulation in fishes, although the effect of zebra mussels on fish tissue mercury has not been tested in inland lakes. We assessed differences in fish tissue mercury concentrations and food webs in Minnesota lakes with and without zebra mussels while controlling for other lake and watershed characteristics. Mercury concentrations in adult walleye (Sander vitreus) and yellow perch (Perca flavescens) were 72 % and 157 % higher, respectively, in lakes containing zebra mussels compared to uninvaded lakes. Mercury in young of year (age-0) fish was also elevated, with mercury concentrations 97 % and 82 % higher in age-0 walleye and yellow perch, respectively, in zebra mussel lakes. Walleye mercury concentrations exceeded 0.22 ppm — a threshold triggering more restrictive human consumption advisories for sensitive populations — at a 23 % smaller size, and average-sized walleye (420 mm) exceeded this threshold at a rate of 77 % in invaded lakes, compared to 35 % in uninvaded lakes. Walleye and yellow perch relied more on littoral resources in lakes with zebra mussels but did not feed at meaningfully higher trophic levels. Increased fish tissue mercury in lakes invaded by zebra mussels have consequential implications for fisheries and human health.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.177515","usgsCitation":"Blinick, N.S., Link, D., Ahrenstoroff, T.D., Bethke, B.J., Fleishman, A.B., Janssen, S., Krabbenhoft, D.P., Nelson, J.K., Rantala, H.M., Rude, C.L., and Hansen, G.J., 2024, Increased mercury concentrations in walleye and yellow perch in lakes invaded by zebra mussels: Science of the Total Environment, v. 957, 177515, 12 p., https://doi.org/10.1016/j.scitotenv.2024.177515.","productDescription":"177515, 12 p.","ipdsId":"IP-159866","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.177515","text":"Publisher Index Page"},{"id":464530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.44450475587576,\n 44.76946704997556\n ],\n [\n -92.83025695554119,\n 44.71178849475393\n ],\n [\n -93.02272126378875,\n 45.52262408934601\n ],\n [\n -92.78467467108655,\n 46.52137470873771\n ],\n [\n -91.87563497943265,\n 47.44395650508943\n ],\n [\n -96.82965701302123,\n 47.79003353490211\n ],\n [\n -96.44450475587576,\n 44.76946704997556\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"957","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blinick, Naomi S.","contributorId":346507,"corporation":false,"usgs":false,"family":"Blinick","given":"Naomi","email":"","middleInitial":"S.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, Denver","contributorId":346509,"corporation":false,"usgs":false,"family":"Link","given":"Denver","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahrenstoroff, Tyler D.","contributorId":346508,"corporation":false,"usgs":false,"family":"Ahrenstoroff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":919403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bethke, Bethany J.","contributorId":275047,"corporation":false,"usgs":false,"family":"Bethke","given":"Bethany","email":"","middleInitial":"J.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":919404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fleishman, Abram B. 0000-0002-7209-0899","orcid":"https://orcid.org/0000-0002-7209-0899","contributorId":225023,"corporation":false,"usgs":false,"family":"Fleishman","given":"Abram","email":"","middleInitial":"B.","affiliations":[{"id":41020,"text":"Conservation Metrics","active":true,"usgs":false}],"preferred":false,"id":919405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919407,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelson, Jenna K.R.","contributorId":346510,"corporation":false,"usgs":false,"family":"Nelson","given":"Jenna","email":"","middleInitial":"K.R.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":919409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rantala, Heidi M.","contributorId":330595,"corporation":false,"usgs":false,"family":"Rantala","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":65315,"text":"MN DNR","active":true,"usgs":false}],"preferred":false,"id":919410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rude, Claire L.","contributorId":346514,"corporation":false,"usgs":false,"family":"Rude","given":"Claire","email":"","middleInitial":"L.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":919411,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hansen, Gretchen J.A. 0000-0003-0241-7048","orcid":"https://orcid.org/0000-0003-0241-7048","contributorId":300822,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J.A.","affiliations":[{"id":65266,"text":"Department of Fish, Wildlife, and Conservation Biology, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":919412,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70264788,"text":"70264788 - 2024 - Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","interactions":[],"lastModifiedDate":"2025-03-24T15:31:14.707392","indexId":"70264788","displayToPublicDate":"2024-11-20T10:25:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17109,"text":"Citizen Science: Theory and Practice","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","title":"Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution","docAbstract":"Citizen science commonly uses social networking platforms because they provide the easiest way to contact people. Social networking platforms can also be especially effective in that they gather people by interest and region. By sharing questionnaires and collecting photographs in angling-themed Facebook groups, we assessed the applicability of social networking groups in citizen science surveys to evaluate the distribution patterns of invasive bigheaded carp in Hungary. Altogether, we received 1,234 responses from 29 Facebook groups to four survey solicitations, with responses coming from 417 locations from across Hungary. The majority of responses were received in the first (mean ± SD; 74.3% ± 5.3) and second days (12.5% ± 5.5) after a survey questionnaire was posted. Group size was positively correlated with reach but inversely with reach ratio (reached members divided by the total number of group members). We collected 311 photos of 622 bigheaded carp, of which 470 were H. molitrix and 67 were H. nobilis. Although spatial bias occurred both in responses to survey questionnaires and available photographs, presence of bigheaded carp was confirmed in all medium and large rivers and many lentic habitats in Hungary. We demonstrated that social media groups can be used to survey interested members of the public and facilitate rapid data collection, providing an effective platform for citizen science. Repeated, spaced sharing of survey solicitations in as many groups as possible (regardless of group size) is the cornerstone for effective data collection. Our survey provided more effective and inexpensively obtained information about the distribution of bigheaded carp than standard catch-based methods.
","language":"English","publisher":"Ubiquity Press","doi":"10.5334/cstp.780","usgsCitation":"Vitál, Z., Chapman, D., Halasi-Kovács, B., and Mozsár, A., 2024, Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution: Citizen Science: Theory and Practice, v. 9, no. 1, 29, 14 p., https://doi.org/10.5334/cstp.780.","productDescription":"29, 14 p.","ipdsId":"IP-158985","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":488378,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5334/cstp.780","text":"Publisher Index Page"},{"id":483722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hungary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 19.905749040559556,\n 48.16445870730942\n ],\n [\n 19.646587056605625,\n 48.262319010335716\n ],\n [\n 19.47381240063592,\n 48.118342076328645\n ],\n [\n 18.825907440751536,\n 48.072184012061996\n ],\n [\n 18.774075043960778,\n 47.84077194152326\n ],\n [\n 18.653132784781832,\n 47.77114616748298\n ],\n [\n 17.651039780159408,\n 47.77114616748298\n ],\n [\n 17.314129201019796,\n 48.02598450726734\n ],\n [\n 17.11543834665531,\n 47.98552594077279\n ],\n [\n 17.003134820275022,\n 47.86395979415386\n ],\n [\n 17.029051018669804,\n 47.71886558279843\n ],\n [\n 16.5625594475527,\n 47.75953279753682\n ],\n [\n 16.407062257180257,\n 47.67234986658315\n ],\n [\n 16.71805663792503,\n 47.520887155888005\n ],\n [\n 16.44161718837492,\n 47.409925547425814\n ],\n [\n 16.44161718837492,\n 46.999097587853385\n ],\n [\n 16.268842532405188,\n 47.016769767732626\n ],\n [\n 16.1047066092342,\n 46.8752285993159\n ],\n [\n 16.28611999800259,\n 46.84569374552734\n ],\n [\n 16.57119818035133,\n 46.46621228452659\n ],\n [\n 17.460987658593552,\n 45.91002968951361\n ],\n [\n 18.065698954485782,\n 45.747503011802735\n ],\n [\n 18.4803581288121,\n 45.747503011802735\n ],\n [\n 18.713603914371276,\n 45.91604008269749\n ],\n [\n 18.869101104743663,\n 45.84988995631136\n ],\n [\n 19.68978072059778,\n 46.16788887622772\n ],\n [\n 20.510460336451843,\n 46.16788887622772\n ],\n [\n 20.648680061226855,\n 46.14993774774203\n ],\n [\n 20.795538518801777,\n 46.26352932418982\n ],\n [\n 21.10653289954655,\n 46.269501321699835\n ],\n [\n 22.24684562894288,\n 47.6897981229599\n ],\n [\n 22.480091414502084,\n 47.82337424756798\n ],\n [\n 22.69605973446386,\n 47.800168248983425\n ],\n [\n 22.89475058882843,\n 47.97396052110528\n ],\n [\n 22.81700199364164,\n 48.118342076328645\n ],\n [\n 22.626949872075784,\n 48.112574584327916\n ],\n [\n 22.46281394890471,\n 48.262319010335716\n ],\n [\n 22.229568163346727,\n 48.44028881239183\n ],\n [\n 21.754437859430936,\n 48.36573198861302\n ],\n [\n 21.41752728029016,\n 48.594788498150564\n ],\n [\n 21.10653289954655,\n 48.52618014157136\n ],\n [\n 20.78689978600312,\n 48.606214177684194\n ],\n [\n 20.510460336451843,\n 48.554778265864115\n ],\n [\n 20.329046947684617,\n 48.3312842835895\n ],\n [\n 19.905749040559556,\n 48.16445870730942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vitál, Zoltán","contributorId":352562,"corporation":false,"usgs":false,"family":"Vitál","given":"Zoltán","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":931686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":931687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Halasi-Kovács, Béla","contributorId":352563,"corporation":false,"usgs":false,"family":"Halasi-Kovács","given":"Béla","affiliations":[{"id":84260,"text":"Hungarian University of Agriculture and Life Sciences","active":true,"usgs":false}],"preferred":false,"id":931688,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mozsár, Attila","contributorId":352564,"corporation":false,"usgs":false,"family":"Mozsár","given":"Attila","affiliations":[{"id":84261,"text":"Balaton Limnological Research Institute","active":true,"usgs":false}],"preferred":false,"id":931689,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261033,"text":"70261033 - 2024 - Surveying waterfowl broods in wetlands using aerial drones","interactions":[],"lastModifiedDate":"2024-11-20T16:52:17.116684","indexId":"70261033","displayToPublicDate":"2024-11-20T09:46:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Surveying waterfowl broods in wetlands using aerial drones","docAbstract":"Effective waterfowl management relies on the collection of relevant demographic data to inform land management decisions; however, some types of data are difficult to obtain. For waterfowl, brood surveys are difficult to conduct because wetland habitats often obscure ducklings from being visually assessed. Here, we used Unoccupied Aerial Systems (UAS) to assess what wetland habitat characteristics influenced brood abundance in Suisun Marsh, California, USA. Using a thermal imaging camera, we surveyed 17 wetland units encompassing 332 ha of flooded area on seven waterfowl hunting clubs during the waterfowl breeding season. Additionally, using a combination of multispectral imagery collected from the UAS flights and LiDAR data from the previous year, we mapped habitat composition within each unit to relate to brood observation counts. From June 3-7, 2019, we identified 113 individual broods comprised of 827 ducklings. We found a positive relationship between the number of broods observed and the proportion of the unit that was flooded. We also found a positive relationship between the number of broods observed and the area of effective habitat, a metric of flooded habitat within a specific distance of flooded vegetation. Brood surveys using UAS could complement the traditional Breeding Population Survey and provide local managers with fine-scale and timely information regarding shifts in brood abundance in the region.","language":"English","publisher":"eScholarship","doi":"10.15447/sfews.2024v22iss3art2","usgsCitation":"Mackell, D.A., Casazza, M.L., Overton, C.T., Buffington, K., Freeman, C., Ackerman, J.T., and Thorne, K., 2024, Surveying waterfowl broods in wetlands using aerial drones: San Francisco Estuary and Watershed Science, v. 22, no. 3, 3, 16 p., https://doi.org/10.15447/sfews.2024v22iss3art2.","productDescription":"3, 16 p.","ipdsId":"IP-159150","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2024v22iss3art2","text":"Publisher Index Page"},{"id":464360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Suisun Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.08563453767741,\n 38.23592936614091\n ],\n [\n -122.08563453767741,\n 38.115419770174015\n ],\n [\n -122.00107572096182,\n 38.115419770174015\n ],\n [\n -122.00107572096182,\n 38.23592936614091\n ],\n [\n -122.08563453767741,\n 38.23592936614091\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Mackell, Desmond Alexander 0000-0002-1682-2581","orcid":"https://orcid.org/0000-0002-1682-2581","contributorId":266036,"corporation":false,"usgs":true,"family":"Mackell","given":"Desmond","email":"","middleInitial":"Alexander","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Chase M. 0000-0003-2284-1380","orcid":"https://orcid.org/0000-0003-2284-1380","contributorId":335090,"corporation":false,"usgs":false,"family":"Freeman","given":"Chase M.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":918980,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918981,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918982,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261527,"text":"70261527 - 2024 - Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","interactions":[],"lastModifiedDate":"2025-05-13T15:59:07.445123","indexId":"70261527","displayToPublicDate":"2024-11-20T09:00:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D","docAbstract":"Numerical simulation of sediment transport and subsequent morphological evolution rely on accurate parameterizations of sediment characteristics. However, these data are often not available or are spatially and/or temporally limited. This study approaches the problem of limited sediment grain-size data with a series of simulations assessing model sensitivity to sediment parameters and initial bed composition configurations in Delft3D, leading to improved modeling practices. A previously validated Delft3D sediment transport and morphology model for Dauphin Island, Alabama, USA, is used as the benchmark case. A method for the generation of representative sediment grain sizes and their spatially varying distributions is presented via end-member analysis of in situ surficial sediment samples. Derived sediment classes and their spatial distributions are applied to two sensitivity case simulations with increasing bed composition complexity. First, multiple sediment classes are applied in a single fully mixed layer, regardless of sediment type. Second, multiple sediment classes are applied in a thin, fully mixed transport layer with underlayers containing only the non-cohesive sediment classes below. Simulations were carried out in a probabilistic, Delft3D MorMerge configuration to capture long-term morphology change for 10 years. We found there is sensitivity to the inclusion of additional sediment classes and sediment distribution made evident in bed level and morphology change. Inclusion of highly mobile fine sediments altered model results in each sensitivity case. The model was also found to be sensitive to initial bed composition in terms of bed level and morphology change, with notable differences between sensitivity cases on decadal timescales, indicating an armoring effect in the second sensitivity case, which used the transport and underlayer bed configuration. The results of this study offer guidance for numerical modelers concerned with sediment behavior in coastal and estuarine environments.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse12112108","usgsCitation":"Jenkins, R., Smith, C., Passeri, D., and Ellis, A.M., 2024, Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D: Journal of Marine Science and Engineering, v. 12, no. 11, 2108, 29 p., https://doi.org/10.3390/jmse12112108.","productDescription":"2108, 29 p.","ipdsId":"IP-170386","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466755,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse12112108","text":"Publisher Index Page"},{"id":465109,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.39043742176105,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.17648303472457\n ],\n [\n -87.49364396321667,\n 30.854668400719234\n ],\n [\n -88.39043742176105,\n 30.854668400719234\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Robert L. III 0000-0003-2078-4618","orcid":"https://orcid.org/0000-0003-2078-4618","contributorId":202181,"corporation":false,"usgs":true,"family":"Jenkins","given":"Robert L.","suffix":"III","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":920898,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261053,"text":"70261053 - 2024 - Methodology for inclusion of produced and stored carbon dioxide in the U.S. Geological Survey Federal lands greenhouse gas inventory","interactions":[],"lastModifiedDate":"2024-11-21T15:07:34.730743","indexId":"70261053","displayToPublicDate":"2024-11-20T08:58:39","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Methodology for inclusion of produced and stored carbon dioxide in the U.S. Geological Survey Federal lands greenhouse gas inventory","docAbstract":"The U.S. Geological Survey (USGS) has developed two new carbon dioxide (CO2) emissions and sequestration accounting methods for use in future reports. The first method is a Federal lease-produced CO2 emissions calculation for an update of the report, “Federal Lands Greenhouse Gas Emissions and Sequestration in the United States.” The methodology to incorporate Federal lease CO2 production emissions into the updated report relies on CO2 sales royalty data from the Office of Natural Resources Revenue (ONRR). The end usage points for the gas include enhanced oil recovery with CO2 (CO2-EOR), food and beverage, and chemical production. CO2-EOR is the main end point for natural CO2 production in the United States; it accounted for 94% of usage in 2022 [1]. Federal lands emissions from this sector are estimated at 460 metric tons of CO2 in 2022, a very small amount relative to most other Federal lands emissions sector estimates.
The second new method, planned for a separate report, is a calculation of the geologic storage of CO2 on Federal lands. The second method estimates the CO2 stored under Federal surface lands and documents Federal climate change mitigation efforts. Currently, there is no storage of CO2 at an industrial level on Federal lands, however multiple proposals and projects are planned. This method was developed on non-Federal lands datasets in an effort to prepare for when these activities on Federal lands will require accounting. National estimates for CO2 geologic storage using this method, but without a Federal lands filtering step, totaled 8.0 million metric tons (Mt) in 2022.
The two methods described here are new benchmark methods in a collection of accounting procedures to document the current state of greenhouse gas emissions and their storage on Federal lands. These benchmarks can then be used to measure any subsequent changes in emissions from or carbon storage beneath Federal lands. While the magnitude of the values is currently non-existent to small, emissions mitigation goals established by decision makers indicate that these values will grow, and their documentation will take on greater value and use.
Flooding rice (Oryza sativa) agricultural fields during winter to facilitate rice straw decomposition has mitigated the loss of some of the natural wetlands in California’s Central Valley. We conducted bird surveys in 253 rice checks (2,158 ha) within 177 rice fields in the Sacramento Valley during the fall and winter of 2021-2022 and 2022-2023 to evaluate factors influencing bird use of winter-flooded, post-harvest rice fields enrolled in the California Winter Rice Habitat Incentive Program. We counted 143,932 birds from 57 species, including dabbling ducks (86.4%), geese (8.0%), shorebirds (0.9%), wading birds (0.7%), and other birds (4.0%). Extrapolating from the lowest densities observed in rice fields during the 70-day mandatory flooding period, we estimated that properties enrolled in this public-private partnership provided habitat for at least 271,312 birds day-1 (16,248 ha; 2021-2022) and 147,315 birds day-1 (8,448 ha; 2022-2023), totaling >10 million bird-use-days each winter. Water depth had the greatest influence on bird abundance and diversity. Relatively shallow water depths (≤13 cm) had greater abundance of shorebirds, wading birds, and geese, and higher diversity, whereas intermediate depths (~23 cm) resulted in the greatest dabbling duck abundance. Duck, goose, and wading bird abundances were greatest and species richness and family diversity were highest 8 days after the onset of flooding in rice fields (typically late October), followed by a decline in bird use until 65-87 days post flooding, after which bird use increased slightly. Bird abundance and species diversity were lowest in rice fields with the greatest hunting intensity (≥3 days week-1). We identified several habitat variables that could be managed and prioritized by landowner incentive programs to increase bird use of winter-flooded rice, including water depth, variation in emergent vegetation height, mudflat habitat availability, rice check shape, hunting intensity, and post-harvest treatment of residual rice straw.
","language":"English","publisher":"eScholarship","doi":"10.15447/sfews.2024v22iss3art3","usgsCitation":"Peterson, S.H., Ackerman, J.T., Schacter, C., Hartman, C.A., and Herzog, M.P., 2024, Bird habitat value and management priorities of the California Winter Rice Habitat Incentive Program: San Francisco Estuary and Watershed Science, v. 22, no. 3, 3, 33 p., https://doi.org/10.15447/sfews.2024v22iss3art3.","productDescription":"3, 33 p.","ipdsId":"IP-160639","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466756,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2024v22iss3art3","text":"Publisher Index Page"},{"id":464348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.19759344829976,\n 39.48444038138939\n ],\n [\n -122.19759344829976,\n 38.468110879064824\n ],\n [\n -121.01107001079963,\n 38.468110879064824\n ],\n [\n -121.01107001079963,\n 39.48444038138939\n ],\n [\n -122.19759344829976,\n 39.48444038138939\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"22","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schacter, Carley R. 0000-0001-5493-2768","orcid":"https://orcid.org/0000-0001-5493-2768","contributorId":333758,"corporation":false,"usgs":false,"family":"Schacter","given":"Carley R.","affiliations":[{"id":79969,"text":"USFWS; Former USGS employee","active":true,"usgs":false}],"preferred":false,"id":918985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918987,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70275335,"text":"70275335 - 2024 - Economic losses to inland recreational fisheries from harmful algal blooms","interactions":[],"lastModifiedDate":"2026-04-29T14:46:48.519661","indexId":"70275335","displayToPublicDate":"2024-11-19T09:31:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Economic losses to inland recreational fisheries from harmful algal blooms","docAbstract":"This paper presents research on the recreational impacts of harmful algal blooms (HABs) and other water quality changes in the U.S. heartland. We examine the link between recreational fishing and water quality using a random utility model of reservoir choices, and data on effort and health-based advisories for reservoirs in Nebraska. We find that advisories linked specifically to algal blooms affect the demand for and value of fishing, and that these effects are heterogeneous. The estimated welfare loss at HAB-afflicted reservoirs is approximately $12 per trip, with larger losses experienced by gamefish-oriented and college-educated fishers.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2024.123238","usgsCitation":"Jayasekera, D.H., Melstrom, R., and Pope, K.L., 2024, Economic losses to inland recreational fisheries from harmful algal blooms: Journal of Environmental Management, v. 372, 123238, 8 p., https://doi.org/10.1016/j.jenvman.2024.123238.","productDescription":"123238, 8 p.","ipdsId":"IP-170673","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":503780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2024.123238","text":"Publisher Index Page"},{"id":503622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","noUsgsAuthors":false,"publicationDate":"2024-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Jayasekera, D. Harshanee","contributorId":370631,"corporation":false,"usgs":false,"family":"Jayasekera","given":"D.","middleInitial":"Harshanee","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":960595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melstrom, Richard","contributorId":370632,"corporation":false,"usgs":false,"family":"Melstrom","given":"Richard","affiliations":[{"id":88053,"text":"Loyola University-Chicago","active":true,"usgs":false}],"preferred":false,"id":960596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":960597,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70261011,"text":"70261011 - 2024 - Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021","interactions":[],"lastModifiedDate":"2024-11-20T16:09:06.755316","indexId":"70261011","displayToPublicDate":"2024-11-19T09:29:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021","docAbstract":"Quaternary ammonium compounds (QAC) are high production chemicals used in many commercial and household disinfection products. During the SARS-CoV-2 (COVID-19) pandemic, QACs were included on lists of COVID-19 disinfectants. Increased QAC use could lead to higher levels of QACs in wastewater treatment plant (WWTP) effluents, which could subsequently be released into the environment. To evaluate QACs in WWTP effluent, three WWTPs in the northeastern United States were monitored from May 2020 through August 2021. Target QACs included six benzylalkyldimethyl ammonium compounds (BAC), three dialkyldimethyl ammonium compounds (DADMAC), two ethylbenzylalkyldimethyl ammonium compounds (EBAC), and benzethonium. At least one QAC was detected in every sample with individual concentrations up to 1600 ng L−1. BAC-C14 was detected most frequently, found in 93% of effluent samples; BAC-C12, BAC-C16, EBAC-C12 and EBAC-C14 were all detected in greater than 80% of samples. Few temporal patterns were observed in QAC concentrations with respect to weekly COVID-19 cases: at WWTP 2, DADMAC-C8:C10 and DADMAC-C10 were positively correlated, and DADMAC-C8 negatively correlated. There were several seasonal trends at WWTP 1, including significant differences of ƩDADMAC, which were higher in fall than summer; ƩBAC was higher during the fall than both spring and summer; and ƩQAC where higher during the fall than spring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2024.143753","usgsCitation":"Hladik, M.L., Gross, M.S., Black, G.P., Kolpin, D., Masoner, J.R., Phillips, P.J., Bradley, P., and Smalling, K., 2024, Temporal concentrations of Quaternary ammonium compounds in wastewater treatment effluents during the COVID-19 pandemic, 2020–2021: Chemosphere, v. 368, 143753,8 p., https://doi.org/10.1016/j.chemosphere.2024.143753.","productDescription":"143753,8 p.","ipdsId":"IP-164654","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":489869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2024.143753","text":"Publisher Index Page"},{"id":464347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"368","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221087,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Michael S.","contributorId":340328,"corporation":false,"usgs":false,"family":"Gross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":81579,"text":"California Department of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":918908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Gabrielle Pecora 0000-0002-1578-742X","orcid":"https://orcid.org/0000-0002-1578-742X","contributorId":303108,"corporation":false,"usgs":true,"family":"Black","given":"Gabrielle","email":"","middleInitial":"Pecora","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":918911,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918912,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":205668,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918913,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","middleInitial":"L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918914,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273866,"text":"70273866 - 2024 - Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape","interactions":[],"lastModifiedDate":"2026-02-10T15:13:38.843978","indexId":"70273866","displayToPublicDate":"2024-11-19T08:03:14","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17157,"text":"Frontiers in Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape","docAbstract":"Soil moisture maps provide quantitative information that, along with climate and energy balance, is critical to integrate with hydrologic processes for characterizing landscape conditions. However, soil moisture maps are difficult to produce for natural landscapes because of vegetation cover and complex topography. Satellite-based L-band microwave sensors are commonly used to develop spatial soil moisture data products, but most existing L-band satellites provide only coarse scale (one to tens of kilometers grid size), information that is unsuitable for measuring soil moisture variation at hillslope or watershed-scales. L-band sensors are typically deployed on satellite platforms and aircraft but have been too large to deploy on small uncrewed aircraft systems (UAS). There is a need for greater spatial resolution and development of effective measures of soil moisture across a variety of natural vegetation types. To address these challenges, a novel UAS-based L-band radiometer system was evaluated that has recently been tested in agricultural settings. In this study, L-band UAS was used to map soil moisture at 3–50-m (m) resolution in a 13 square kilometer (km2) mixed grassland-forested landscape in Sonoma County, California. The results represent the first application of this technology in a natural landscape with complex topography and vegetation. The L-band inversion of the radiative transfer model produced soil moisture maps with an average unbiased root mean squared error (ubRMSE) of 0.07 m3/m3 and a bias of 0.02 m3/m3. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help inform wildfire risk, improve hydrologic models, streamflow forecasting, and early detection of landslides.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2024.1337953","usgsCitation":"Stern, M.A., Ferrell, R., Flint, L.E., Kozanitas, M., Ackerly, D., Elston, J., Stachura, M., Dai, E., and Thorne, J.H., 2024, Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape: Frontiers in Remote Sensing, v. 5, 1337953, 12 p., https://doi.org/10.3389/frsen.2024.1337953.","productDescription":"1337953, 12 p.","ipdsId":"IP-159618","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2024.1337953","text":"Publisher Index Page"},{"id":499713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","otherGeospatial":"Mayacamas Mountains, Pepperwood Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.71354880264356,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.57616137564548\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrell, Ryan","contributorId":366124,"corporation":false,"usgs":false,"family":"Ferrell","given":"Ryan","affiliations":[{"id":37798,"text":"Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":955320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Lorraine E. 0000-0002-7868-441X","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":306090,"corporation":false,"usgs":false,"family":"Flint","given":"Lorraine","email":"","middleInitial":"E.","affiliations":[{"id":66369,"text":"Earth Knowledge, Inc.","active":true,"usgs":false}],"preferred":false,"id":955321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kozanitas, Melina","contributorId":366125,"corporation":false,"usgs":false,"family":"Kozanitas","given":"Melina","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":955322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerly, David","contributorId":139541,"corporation":false,"usgs":false,"family":"Ackerly","given":"David","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":955323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elston, Jack","contributorId":334719,"corporation":false,"usgs":false,"family":"Elston","given":"Jack","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955324,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stachura, Maciej","contributorId":334720,"corporation":false,"usgs":false,"family":"Stachura","given":"Maciej","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955325,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, Eryan","contributorId":366129,"corporation":false,"usgs":false,"family":"Dai","given":"Eryan","affiliations":[{"id":87362,"text":"Weather Stream Inc.","active":true,"usgs":false}],"preferred":false,"id":955326,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thorne, James H.","contributorId":173762,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":955327,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260938,"text":"ofr20241068 - 2024 - Determination of antimycin–a in a liquid formulation by high performance liquid chromatography–mass spectrometry","interactions":[],"lastModifiedDate":"2024-11-18T21:32:05.056061","indexId":"ofr20241068","displayToPublicDate":"2024-11-18T15:29:45","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1068","displayTitle":"Determination of Antimycin–A in a Liquid Formulation by High Performance Liquid Chromatography–Mass Spectrometry","title":"Determination of antimycin–a in a liquid formulation by high performance liquid chromatography–mass spectrometry","docAbstract":"Pesticide formulations containing the active ingredient antimycin–a (ANT–A) have been used by fisheries and aquaculture managers for several decades to remove nuisance fish species. Analytical methods for measuring ANT–A during pesticide treatments have been done using high performance liquid chromatography (HPLC) paired with multiple detection methods (for example, electrochemical, ultraviolet, fluorescence, mass spectrometry). However, instruments and analytical chemistry methods can advance over time because of the need to develop timely, reliable, cost effective, and reproducible methods. Subsequently, ANT–A analytical chemistry methods and sample processing techniques also have improved over the past several decades. In the present study, we describe a liquid chromatography–mass spectrometry method and its verification across three analysts. Each analyst group created a single calibration curve and verified ANT–A in a liquid formulation using the averaged total response of all major ANT–A homologs (A1, A3, A3, A4). The advantage of this technique is that it creates a more resilient ANT–A quantification method amendable to batch-batch differences in major homologs. The method demonstrated how ANT–A can be effectively measured with high accuracy (98–99 percent), precision (2.7–16.2 percent), and specificity within a pesticide liquid formulation using a method applicable for Federal registration requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241068","usgsCitation":"Saari, G.N., Steiner, J.N., Lada, B., and Carmosini, N., 2024, Determination of antimycin–a in a liquid formulation by high performance liquid chromatography–mass spectrometry: U.S. Geological Survey Open-File Report 2024–1068, 7 p., https://doi.org/10.3133/ofr20241068.","productDescription":"Report: vii, 7 p; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-166047","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":464197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1068/ofr20241068.pdf","text":"Report","size":"671 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR-2024-1068"},{"id":464198,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1068/images"},{"id":464200,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1068/ofr20241068.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR-2024-1068"},{"id":464204,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20241068/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":464206,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1GT55QY","text":"USGS data release","linkHelpText":"Data release for determination of antimycin–a in liquid formulation by high performance liquid chromatography–mass spectrometry"},{"id":464196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1068/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
The Decompartmentalization Physical Model (DPM) was an experimental facility in the central Everglades operated between 2010 and 2022 to release high flows through a levee-enclosed area of degraded ridge and slough wetland that had been isolated from flow for sixty years. The purpose of DPM experimental program was to make measurements before, during, and after seasonal high-flow releases that could help guide the Congressionally authorized Everglades restoration project known as the Decompartmentalization and Sheet Flow Enhancement Project.
The DPM facility was operated by the South Florida Water Management District, with the U.S. Geological Survey (USGS) and several universities participating in experimental design and leading aspects of the research. The USGS research at DPM focused on measuring high-flow hydraulics and its sedimentary and ecological responses in downstream wetlands. USGS investigated interactions between flow and vegetation and microtopography that influenced flow velocity and water depth, bed shear stress, sediment entrainment, and the resulting downstream transport of suspended sediment and fate of particle-associated phosphorus. USGS also investigated high-flow changes in water-column mixing and gas exchange and resulting effects on metabolism of the aquatic ecosystem (primary productivity and respiration). USGS also investigated effects of built structures such as levee gaps that were constructed to reconnect levee-enclosed basins. This report describes the methods and results of the USGS-led data collection at DPM.
The USGS studies at DPM have identified factors that influence effectiveness of restoration, specifically how high-flow releases maximize sheet flow and affect sediment and nutrient dynamics while minimizing undesirable outcomes caused by past management that bypassed wetlands by conveying polluted water through canals to ecologically sensitive downstream areas. The DPM high-flow experiments reconnected the Water Conservation Area 3A and Water Conservation Area 3B basins, and it therefore has become a central feature of the restoration’s Decompartmentalization and Sheet Flow Enhancement Project. DPM’s scientific findings have already influenced the adaptive management of Everglades restoration in guiding elements of the final design and implementation of the Central Everglades Planning Project-South. In addition to serving Everglades restoration, the DPM has the potential to influence similar adaptive management programs throughout the nation’s network of federal and state-managed river corridors, floodplains, and riparian ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241063","usgsCitation":"Harvey, J., Choi, J., Larsen, L., Skalak, K., Maglio, M., Quion, K., Swartz, A., Lin, J.T.Y., Gomez-Velez, J., and Schmadel, N., 2024, High-flow experimental outcomes to inform Everglades restoration, 2010–22: U.S. Geological Survey Open-File Report 2024–1063, 72 p., https://doi.org/10.3133/ofr20241063.","productDescription":"Report: xi, 72 p.; 3 Data Releases","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-148372","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":464267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1063/coverthb.jpg"},{"id":464268,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":464271,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241063/full"},{"id":464270,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1063/images"},{"id":464269,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1063/ofr20241063.XML"},{"id":464274,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9SQ85","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Quion, K., Lin, J.T., Swartz, A., Larsen, L.G., Haase, K., and Schmadel, N., 2024, High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism: U.S. Geological Survey, data release, https://doi.org/10.5066/P9A9SQ85.","linkHelpText":"- High-flow Experimental Outcomes for Everglades Hydraulics and Aquatic Metabolism"},{"id":464272,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQYB1O","text":"USGS Data Release","description":"Harvey, J.W., and Choi, J., 2022, Biophysical Data for Simulating Overland Flow in the Everglades: U.S. Geological Survey data release, https://doi.org/10.5066/P9DQYB1O.","linkHelpText":"- Biophysical Data for Simulating Overland Flow in the Everglades"},{"id":464273,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SP0HM1","text":"USGS Data Release","description":"Harvey, J.W., Choi, J., Larsen, L., Skalak, K., Maglio, M.M., Quion, K.M., Lin, T., Psaltakis, J.W., Buskirk, B.A., Swartz, A.G., Lewis, J.M., Gomez-Velez, J.D., and Schmadel, N.M., 2022, High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9SP0HM1.","linkHelpText":"- High-Flow Field Experiments to Inform Everglades Restoration: Experimental Data 2010 to 2022 (ver. 2.0, October 2023)"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.1076224101966,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 24.751056659514802\n ],\n [\n -79.55347920896048,\n 26.691819233104567\n ],\n [\n -82.1076224101966,\n 26.691819233104567\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
No abstract available.
","language":"English","publisher":"Interagency Grizzly Bear Committee","usgsCitation":"2024, Yellowstone grizzly bear investigations 2023 - Annual report of the Interagency Grizzly Bear Study Team, vi, 124 p.","productDescription":"vi, 124 p.","ipdsId":"IP-171091","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":464111,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://igbconline.org/grizzly-bear-study-team/"},{"id":503354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone ecosysstem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.6518544446856,\n 48.90968626226547\n ],\n [\n -105.7001792785952,\n 48.90968626226547\n ],\n [\n -105.7001792785952,\n 41.948705504153025\n ],\n [\n -116.6518544446856,\n 41.948705504153025\n ],\n [\n -116.6518544446856,\n 48.90968626226547\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":918537,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":918538,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Karabensh, Bryn 0000-0002-2052-5256","orcid":"https://orcid.org/0000-0002-2052-5256","contributorId":219113,"corporation":false,"usgs":true,"family":"Karabensh","given":"Bryn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":918539,"contributorType":{"id":2,"text":"Editors"},"rank":3}]}} ,{"id":70261306,"text":"70261306 - 2024 - Increasing phosphorus loss despite widespread concentration decline in US rivers","interactions":[],"lastModifiedDate":"2024-12-05T15:49:58.942861","indexId":"70261306","displayToPublicDate":"2024-11-18T09:44:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Increasing phosphorus loss despite widespread concentration decline in US rivers","docAbstract":"The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980–2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2402028121","usgsCitation":"Zhi, W., Baniecki, H., Liu, J., Boyer, E.W., Shen, C., Shenk, G.W., Liu, X., and Li, L., 2024, Increasing phosphorus loss despite widespread concentration decline in US rivers: PNAS, v. 121, no. 48, e2402028121, 9 p., https://doi.org/10.1073/pnas.2402028121.","productDescription":"e2402028121, 9 p.","ipdsId":"IP-167332","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":489078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2402028121","text":"Publisher Index Page"},{"id":464807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"121","issue":"48","noUsgsAuthors":false,"publicationDate":"2024-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhi, Wei 0000-0001-5485-1095","orcid":"https://orcid.org/0000-0001-5485-1095","contributorId":336775,"corporation":false,"usgs":false,"family":"Zhi","given":"Wei","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":920317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baniecki, Hubert 0000-0001-6661-5364","orcid":"https://orcid.org/0000-0001-6661-5364","contributorId":346942,"corporation":false,"usgs":false,"family":"Baniecki","given":"Hubert","email":"","affiliations":[{"id":83024,"text":"University of Warsaw, Warsaw, Poland","active":true,"usgs":false}],"preferred":false,"id":920318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Jiangtao","contributorId":346943,"corporation":false,"usgs":false,"family":"Liu","given":"Jiangtao","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":920319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":920320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shen, Chaopeng","contributorId":152465,"corporation":false,"usgs":false,"family":"Shen","given":"Chaopeng","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":920321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shenk, Gary W. 0000-0001-6451-2513","orcid":"https://orcid.org/0000-0001-6451-2513","contributorId":225440,"corporation":false,"usgs":true,"family":"Shenk","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Xiaofeng 0000-0002-8296-7076","orcid":"https://orcid.org/0000-0002-8296-7076","contributorId":317075,"corporation":false,"usgs":false,"family":"Liu","given":"Xiaofeng","email":"","affiliations":[{"id":68932,"text":"Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA, USA","active":true,"usgs":false}],"preferred":false,"id":920323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Li, Li","contributorId":223548,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":920324,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70260965,"text":"70260965 - 2024 - Brittle regime slip partitioned damage and deformation mechanisms along the eastern Denali fault zone in southwestern, Yukon","interactions":[],"lastModifiedDate":"2024-11-18T15:26:34.743256","indexId":"70260965","displayToPublicDate":"2024-11-18T08:26:23","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Brittle regime slip partitioned damage and deformation mechanisms along the eastern Denali fault zone in southwestern, Yukon","docAbstract":"Rare bedrock exposures of the eastern Denali fault zone in southwestern Yukon allow for the measurement, sampling, and analyses of brittle regime fault slip data and deformation mechanisms to explore relations to far field, oblique plate motions. Host rock lithologies and associated slip surfaces show episodic damage zone‐related deformation and calcite ± hematite ± chlorite related hydrothermal fluid flow. This regional scale network of asymmetric fault damage is spatially and kinematically linked to a discrete and narrow fault core. Fault network observations, orientations, slip data, and strain inversions document a slip partitioned strike‐slip fault system with locally and mutually overprinting strike‐, oblique‐, and dip‐slip components. Microstructural analyses reveal crystal plastic and co‐seismic brittle deformation mechanisms active in a narrow range of upper crustal temperature, pressure, fluid, and chemical conditions. The net damage related slip is not exclusively formed by a single kinematic system, but rather a fully partitioned, time integrated system likely operative for much of the fault's brittle regime evolution temporally constrained by previously published thermochronometric data. Although the fault slip data was collected from outcrop‐scale exposures at sites tens of kilometers apart, results show remarkable correlation between fault kinematics and plate motions along the ∼580 km long eastern Denali fault segment. End member, subhorizontal, northeast directed reverse and north directed dextral strike slip fault strain axes closely reflect relative plate motion interactions over at least the last 30 m.y. and act as a proxy for far‐field stresses compatible with the kinematics of the damage zone network.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB029506","usgsCitation":"Caine, J., Orlandini, O.F., Vollmer, F.W., and Lowers, H.A., 2024, Brittle regime slip partitioned damage and deformation mechanisms along the eastern Denali fault zone in southwestern, Yukon: Journal of Geophysical Research: Solid Earth, v. 129, no. 11, e2024JB029506, 35 p., https://doi.org/10.1029/2024JB029506.","productDescription":"e2024JB029506, 35 p.","ipdsId":"IP-149623","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":466757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jb029506","text":"Publisher Index Page"},{"id":464228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"British Columbia, southwest Yukon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -161.0212169953091,\n 60.265114667913366\n ],\n [\n -161.0212169953091,\n 52.584549776442685\n ],\n [\n -131.33133076901765,\n 52.584549776442685\n ],\n [\n -131.33133076901765,\n 60.265114667913366\n ],\n [\n -161.0212169953091,\n 60.265114667913366\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Caine, Jonathan Saul 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":199295,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan Saul","email":"jscaine@usgs.gov","affiliations":[],"preferred":true,"id":918724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orlandini, Omero F. 0000-0002-9578-1203","orcid":"https://orcid.org/0000-0002-9578-1203","contributorId":346333,"corporation":false,"usgs":false,"family":"Orlandini","given":"Omero","email":"","middleInitial":"F.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":918725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vollmer, Frederick W. 0000-0002-0385-8489","orcid":"https://orcid.org/0000-0002-0385-8489","contributorId":271263,"corporation":false,"usgs":false,"family":"Vollmer","given":"Frederick","email":"","middleInitial":"W.","affiliations":[{"id":56326,"text":"State University of New York at New Paltz","active":true,"usgs":false}],"preferred":false,"id":918726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261182,"text":"70261182 - 2024 - Ticks without borders: Microbiome of immature neotropical tick species parasitizing migratory songbirds along northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-11-27T15:42:50.611708","indexId":"70261182","displayToPublicDate":"2024-11-17T09:17:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19837,"text":"Frontiers in Cellular and Infection Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Ticks without borders: Microbiome of immature neotropical tick species parasitizing migratory songbirds along northern Gulf of Mexico","docAbstract":"Introduction: The long-distance, seasonal migrations of birds make them an effective ecological bridge for the movement of ticks. The introduction of exotic tick species to new geographical regions can cause the emergence of novel tick-borne pathogens. This study examined the prevalence of exotic tick species parasitizing migratory songbirds at stopover sites along the northern Gulf of Mexico using the mitochondrial 12S rRNA gene.
Methods: Overall, 421 individual ticks in the genera Amblyomma, Haemaphysalis, and Ixodes were recorded from 28 songbird species, of which Amblyomma and Amblyomma longirostre were the most abundant tick genera and species, respectively. A high throughput 16S ribosomal RNA sequencing approach characterized the microbial communities and identified pathogenic microbes in all tick samples.
Results and discussion: Microbial profiles showed that Proteobacteria was the most abundant phylum. The most abundant pathogens were Rickettsia and endosymbiont Francisella, Candidatus Midichloria, and Spiroplasma. Permutation multivariate analysis of variance revealed that the relative abundance of Francisella and Rickettsia drives microbial patterns across the tick genera. We also noted a higher percentage of positive correlations in microbe-microbe interactions among members of the microbial communities. Network analysis suggested a negative correlation between a) Francisella and Rickettsia and, b) Francisella and Cutibacterium. Lastly, mapping the distributions of bird species parasitized during spring migrations highlighted geographic hotspots where migratory songbirds could disperse ticks and their pathogens at stopover sites or upon arrival to their breeding grounds, the latter showing mean dispersal distances from 421–5003 kilometers. These findings spotlight the potential role of migratory birds in the epidemiology of tick-borne pathogens.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcimb.2024.1472598","usgsCitation":"Karim, S., Zenzal, T.J., Beati, L., Sen, R., Adegoke, A., Kumar, D., Downs, L.P., Keko, M., Nussbaum, A., Becker, D.J., and Moore, F.R., 2024, Ticks without borders: Microbiome of immature neotropical tick species parasitizing migratory songbirds along northern Gulf of Mexico: Frontiers in Cellular and Infection Microbiology, v. 14, 1472598, 15 p., https://doi.org/10.3389/fcimb.2024.1472598.","productDescription":"1472598, 15 p.","ipdsId":"IP-155766","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466758,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcimb.2024.1472598","text":"Publisher Index Page"},{"id":464571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.40131577203148,\n 31.254592735096182\n ],\n [\n -88.36729061913346,\n 30.10135972035171\n ],\n [\n -87.46455520517436,\n 30.10135972035171\n ],\n [\n -87.55501002782326,\n 31.31260199216662\n ],\n [\n -88.40131577203148,\n 31.254592735096182\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1339319721782,\n 30.466724457964204\n ],\n [\n -93.1658440056944,\n 29.43813226845178\n ],\n [\n -90.77810437140585,\n 29.325063575125725\n ],\n [\n -90.7750284309227,\n 30.626660373854534\n ],\n [\n -93.1339319721782,\n 30.466724457964204\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Karim, Shahid","contributorId":346547,"corporation":false,"usgs":false,"family":"Karim","given":"Shahid","email":"","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zenzal, Theodore J. Jr. 0000-0001-7342-1373","orcid":"https://orcid.org/0000-0001-7342-1373","contributorId":224399,"corporation":false,"usgs":true,"family":"Zenzal","given":"Theodore","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":919540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beati, Lorenza","contributorId":148019,"corporation":false,"usgs":false,"family":"Beati","given":"Lorenza","email":"","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":919541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sen, Raima","contributorId":346549,"corporation":false,"usgs":false,"family":"Sen","given":"Raima","email":"","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adegoke, Abdulsalam","contributorId":346552,"corporation":false,"usgs":false,"family":"Adegoke","given":"Abdulsalam","email":"","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Deepak","contributorId":346555,"corporation":false,"usgs":false,"family":"Kumar","given":"Deepak","email":"","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Downs, Latoyia P.","contributorId":346558,"corporation":false,"usgs":false,"family":"Downs","given":"Latoyia","email":"","middleInitial":"P.","affiliations":[{"id":38697,"text":"University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keko, Mario","contributorId":346561,"corporation":false,"usgs":false,"family":"Keko","given":"Mario","email":"","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":919546,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nussbaum, Ashly","contributorId":346564,"corporation":false,"usgs":false,"family":"Nussbaum","given":"Ashly","email":"","affiliations":[{"id":16976,"text":"Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":919547,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Becker, Daniel J.","contributorId":334313,"corporation":false,"usgs":false,"family":"Becker","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":919548,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Moore, Frank R.","contributorId":54582,"corporation":false,"usgs":false,"family":"Moore","given":"Frank","email":"","middleInitial":"R.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":919549,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70261913,"text":"70261913 - 2024 - Genome sequences of toxigenic cyanobacteria from a bloom in Lake Mattamuskeet, North Carolina (United States)","interactions":[],"lastModifiedDate":"2026-02-10T17:49:18.930628","indexId":"70261913","displayToPublicDate":"2024-11-17T08:50:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2422,"text":"Journal of Phycology","active":true,"publicationSubtype":{"id":10}},"title":"Genome sequences of toxigenic cyanobacteria from a bloom in Lake Mattamuskeet, North Carolina (United States)","docAbstract":"Lake Mattamuskeet, the largest lake in North Carolina, USA, has undergone decades-long eutrophication causing reduced water quality and promoting cyanobacterial blooms that may produce toxins. It is therefore necessary to evaluate the cyanobacterial diversity of the lake and their toxigenic potential. We present draft genomes of Microcystis, Pelatocladus, Raphidiopsis, and Umezakia strains isolated from Lake Mattamuskeet. The whole-genome shotgun projects for Umezakia ovalisporum BLCC-F208, Microcystis sp. BLCC-F209, Microcystis sp. BLCC-F210, Pelatocladus sp. BLCC-F211, U. ovalisporum BLCC-F215, and Raphidiopsis BLCC-F218 have been deposited in GenBank under accession numbers JBHFLK000000000, JBHFLL000000000, CP169647, JBHFLM000000000, JBHFLN000000000, and JBHFLO000000000, respectively. Based on the genomic analysis, several biosynthetic gene clusters (BCGs) with varying degrees of similarity to known toxic and bioactive compound gene clusters were identified across the different cyanobacterial strains.
","language":"English","publisher":"Wiley","doi":"10.1111/jpy.13523","usgsCitation":"Moretto, J., Berthold, D., Lefler, F., Mazzei, V., Loftin, K.A., and Laughinghouse, D., 2024, Genome sequences of toxigenic cyanobacteria from a bloom in Lake Mattamuskeet, North Carolina (United States): Journal of Phycology, v. 60, no. 6, p. 1349-1355, https://doi.org/10.1111/jpy.13523.","productDescription":"7 p.","startPage":"1349","endPage":"1355","ipdsId":"IP-170755","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":498256,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jpy.13523","text":"Publisher Index Page"},{"id":465629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","county":"Hyde County","otherGeospatial":"Albemarle-Pamlico Peninsula, Lake Mattamuskeet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.35112692142471,\n 35.56784290852124\n ],\n [\n -76.35112692142471,\n 35.437352291803705\n ],\n [\n -76.03141728533264,\n 35.437352291803705\n ],\n [\n -76.03141728533264,\n 35.56784290852124\n ],\n [\n -76.35112692142471,\n 35.56784290852124\n ]\n ]\n ],\n \"type\": \"Polygon\"\n },\n \"id\": 0\n }\n ]\n}","volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Moretto, Jéssica A.","contributorId":347704,"corporation":false,"usgs":false,"family":"Moretto","given":"Jéssica A.","affiliations":[{"id":83207,"text":"University of Florida, Institute of Food and Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":922257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berthold, David E.","contributorId":347705,"corporation":false,"usgs":false,"family":"Berthold","given":"David E.","affiliations":[{"id":83207,"text":"University of Florida, Institute of Food and Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":922258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lefler, Forrest W.","contributorId":347706,"corporation":false,"usgs":false,"family":"Lefler","given":"Forrest W.","affiliations":[{"id":83207,"text":"University of Florida, Institute of Food and Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":922259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzei, Viviana 0000-0001-8614-0693 vmazzei@usgs.gov","orcid":"https://orcid.org/0000-0001-8614-0693","contributorId":296094,"corporation":false,"usgs":true,"family":"Mazzei","given":"Viviana","email":"vmazzei@usgs.gov","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":922260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":922261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laughinghouse, Dail H. IV","contributorId":347707,"corporation":false,"usgs":false,"family":"Laughinghouse","given":"Dail H.","suffix":"IV","affiliations":[{"id":83207,"text":"University of Florida, Institute of Food and Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":922262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260975,"text":"70260975 - 2024 - Layered intrusions in the Precambrian: Observations and perspectives","interactions":[],"lastModifiedDate":"2025-02-07T16:06:06.999202","indexId":"70260975","displayToPublicDate":"2024-11-16T11:21:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Layered intrusions in the Precambrian: Observations and perspectives","docAbstract":"Layered intrusions are plutonic bodies of cumulates that form by the crystallization of mantle-derived melts. These intrusions are characterized by igneous layering distinguishable by shifts in mineralogy, texture, or composition. Layered intrusions have been fundamental to our understanding of igneous petrology; however, it is their status as important repositories of critical metals – such as platinum-group elements, chromium, and vanadium – that has predominantly driven associated research in recent decades. Many layered intrusions were emplaced during the Precambrian, predominantly at the margins of ancient cratons during intervals of supercontinent accretion and destruction. It appears that large, layered intrusions require rigid crust to ensure their preservation, and their geometry and layering is primarily controlled by the nature of melt emplacement.
Layered intrusions are best investigated by integrating observations from various length-scales. At the macroscale, intrusion geometries can be discerned, and their presence understood in the context of the regional geology. At the mesoscale, the layering of an intrusion may be characterized, intrusion-host rock contact relationships studied, and the nature of stratiform mineral occurrences described. At the microscale, the mineralogy and texture of cumulate rocks and any mineralization are elucidated, particularly when novel microtextural and mineral chemical datasets are integrated. For example, here we demonstrate how mesoscale observations and microscale datasets can be combined to understand the petrogenesis of the perplexing snowball oiks outcrop located in the Upper Banded Series of the Stillwater Complex. Our data suggest that the orthopyroxene oikocrysts did not form in their present location, but rather formed in a dynamic magma chamber where crystals were transported either by convective currents or within crystal-rich slurries.
Critical metals may be transported to the level of a nascent intrusion as dissolved components in the melt. Alternatively, ore minerals are entrained from elsewhere in a plumbing system, potentially facilitated by volatile-rich phases. There are many ore-forming processes propounded by researchers to occur at the level of emplacement; however, each must address the arrival of the ore mineral, its concentration of metals, and its accumulation into orebodies. In this contribution, several of these processes are described as well as our perspectives on the future of layered intrusion research.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2024.107615","usgsCitation":"Smith, W.D., Jenkins, M., Augustin, C.T., Virtanen, V.J., Vukmanovic, Z., and O’Driscoll, B., 2024, Layered intrusions in the Precambrian: Observations and perspectives: Precambrian Research, v. 415, 107615, 31 p., https://doi.org/10.1016/j.precamres.2024.107615.","productDescription":"107615, 31 p.","ipdsId":"IP-169762","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":466760,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.precamres.2024.107615","text":"Publisher Index Page"},{"id":464288,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"415","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, William D.","contributorId":335361,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":918775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":918776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Augustin, Claudia T.","contributorId":346348,"corporation":false,"usgs":false,"family":"Augustin","given":"Claudia","email":"","middleInitial":"T.","affiliations":[{"id":82834,"text":"Mineral Deposits Group, Department of Earth Sciences, Carleton University","active":true,"usgs":false}],"preferred":false,"id":918777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Virtanen, Ville J.","contributorId":346349,"corporation":false,"usgs":false,"family":"Virtanen","given":"Ville","email":"","middleInitial":"J.","affiliations":[{"id":82835,"text":"Institut des Sciences de la Terre d’Orléans; Department of Geosciences and Geography, University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":918778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vukmanovic, Zoja","contributorId":346350,"corporation":false,"usgs":false,"family":"Vukmanovic","given":"Zoja","email":"","affiliations":[{"id":82836,"text":"School of Environmental Sciences, University of East Anglia","active":true,"usgs":false}],"preferred":false,"id":918779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Driscoll, Brian","contributorId":346351,"corporation":false,"usgs":false,"family":"O’Driscoll","given":"Brian","email":"","affiliations":[{"id":35511,"text":"Department of Earth and Environmental Sciences, University of Ottawa","active":true,"usgs":false}],"preferred":false,"id":918780,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261717,"text":"70261717 - 2024 - Hydroacoustic observations reveal drivers of mixing and salinization of a karst subterranean estuary during intense precipitation","interactions":[],"lastModifiedDate":"2024-12-19T15:38:35.633185","indexId":"70261717","displayToPublicDate":"2024-11-16T09:35:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Hydroacoustic observations reveal drivers of mixing and salinization of a karst subterranean estuary during intense precipitation","docAbstract":"Karst subterranean estuaries within globally ubiquitous carbonate aquifers are coastal groundwater ecosystems that provide an essential water resource for human populations. To understand the drivers of salinization within a coastal aquifer in the Yucatan Peninsula (Mexico), we employed hydroacoustics in flooded caves to observe how oceanic and atmospheric events facilitate mixing between the meteoric lens (fresh-brackish groundwater) and the saline groundwater on tidal and episodic timescales. Precipitation during Tropical Storm Carlotta increased the flow and salinity of the meteoric lens without evidence for vertical mixing across the halocline. We postulate that vertical migration of haloclines in the conduit relative to those within the rock matrix during precipitation creates lateral density gradients that drive mixing, and ultimately creates a brackish layer within the meteoric lens. These results provide a mechanistic explanation for vertical and lateral exchange in a coastal carbonate aquifer, which has implications for groundwater response to future climatic change.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL109993","usgsCitation":"Ganju, N., Pohlman, J., Suttles, S.E., and Brankovits, D., 2024, Hydroacoustic observations reveal drivers of mixing and salinization of a karst subterranean estuary during intense precipitation: Geophysical Research Letters, v. 51, no. 22, e2024GL109993, 10 p., https://doi.org/10.1029/2024GL109993.","productDescription":"e2024GL109993, 10 p.","ipdsId":"IP-164811","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466761,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl109993","text":"Publisher Index Page"},{"id":465334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":"Ox Bel Ha cave system, Yucatan peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.30558586746815,\n 20.291951181554595\n ],\n [\n -88.15009160916765,\n 20.291951181554595\n ],\n [\n -88.15009160916765,\n 19.703686313193117\n ],\n [\n -87.30558586746815,\n 19.703686313193117\n ],\n [\n -87.30558586746815,\n 20.291951181554595\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"22","noUsgsAuthors":false,"publicationDate":"2024-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pohlman, John 0000-0002-3563-4586","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":220804,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":921578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suttles, Steven E. 0000-0002-4119-8370 ssuttles@usgs.gov","orcid":"https://orcid.org/0000-0002-4119-8370","contributorId":192272,"corporation":false,"usgs":true,"family":"Suttles","given":"Steven","email":"ssuttles@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brankovits, David","contributorId":296665,"corporation":false,"usgs":false,"family":"Brankovits","given":"David","affiliations":[{"id":64117,"text":"Molecular Ecology Group, Water Research Institute, National Research Council of Italy (IRSA CNR), Pallanza","active":true,"usgs":false}],"preferred":false,"id":921580,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261271,"text":"70261271 - 2024 - Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source","interactions":[],"lastModifiedDate":"2024-12-04T15:22:55.307538","indexId":"70261271","displayToPublicDate":"2024-11-16T08:12:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source","docAbstract":"Maunaloa—the largest active volcano on Earth—erupted in 2022 after its longest known repose period (~38 years) and two decades of volcanic unrest. This eruptive hiatus at Maunaloa encompasses most of the ~35-year-long Puʻuʻōʻō eruption of neighboring Kīlauea, which ended in 2018 with a collapse of the summit caldera and an unusually voluminous (~1 km3) rift eruption. A long-term pattern of such anticorrelated eruptive behavior suggests that a magmatic connection exists between these volcanoes within the asthenospheric mantle source and melting region, the lithospheric mantle, and/or the volcanic edifice. The exact nature of this connection is enigmatic. In the past, the distinct compositions of lavas from Kīlauea and Maunaloa were thought to require completely separate magma pathways from the mantle source of each volcano to the surface. Here, we use a nearly 200-yr record of lava chemistry from both volcanoes to demonstrate that melt from a shared mantle source within the Hawaiian plume may be transported alternately to Kīlauea or Maunaloa on a timescale of decades. This process led to a correlated temporal variation in 206Pb/204Pb and 87Sr/86Sr at these volcanoes since the early 19th century with each becoming more active when it received melt from the shared source. Ratios of highly over moderately incompatible trace elements (e.g., Nb/Y) at Kīlauea reached a minimum from ~2000 to 2010, which coincides with an increase in seismicity and inflation at the summit of Maunaloa. Thereafter, a reversal in Nb/Y at Kīlauea signals a decline in the degree of mantle partial melting at this volcano and suggests that melt from the shared source is now being diverted from Kīlauea to Maunaloa for the first time since the early to mid-20th century. These observations link a mantle-related shift in melt generation and transport at Kīlauea to the awakening of Maunaloa in 2002 and its eruption in 2022. Monitoring of lava chemistry is a potential tool that may be used to forecast the behavior (e.g., eruption rate and frequency) of these adjacent volcanoes on a timescale of decades. A future increase in eruptive activity at Maunaloa is likely if the temporal increase in Nb/Y continues at Kīlauea.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egae121","usgsCitation":"Pietruszka, A., Heaton, D.E., Marske, J.P., Norman, M.D., Robbins, M.G., Mershon, R.B., Lynn, K.J., Downs, D.T., Steiner, A.R., Rhodes, J.M., and Garcia, M.O., 2024, Awakening of Maunaloa linked to melt shared from Kilauea’s mantle source: Journal of Petrology, v. 65, no. 12, egae121, 9 p., https://doi.org/10.1093/petrology/egae121.","productDescription":"egae121, 9 p.","ipdsId":"IP-169683","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egae121","text":"Publisher Index Page"},{"id":464749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano, Maunaloa volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.62647011347312,\n 19.636068332660543\n ],\n [\n -155.62647011347312,\n 19.326511618337022\n ],\n [\n -155.16252314077784,\n 19.326511618337022\n ],\n [\n -155.16252314077784,\n 19.636068332660543\n ],\n [\n -155.62647011347312,\n 19.636068332660543\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pietruszka, Aaron J.","contributorId":346909,"corporation":false,"usgs":false,"family":"Pietruszka","given":"Aaron J.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heaton, Daniel E.","contributorId":172800,"corporation":false,"usgs":false,"family":"Heaton","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":920180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marske, Jared P.","contributorId":172801,"corporation":false,"usgs":false,"family":"Marske","given":"Jared","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":920181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norman, Marc D.","contributorId":344700,"corporation":false,"usgs":false,"family":"Norman","given":"Marc","email":"","middleInitial":"D.","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":920182,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robbins, Mahinaokalani G.","contributorId":346912,"corporation":false,"usgs":false,"family":"Robbins","given":"Mahinaokalani","email":"","middleInitial":"G.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mershon, Reed B.","contributorId":346915,"corporation":false,"usgs":false,"family":"Mershon","given":"Reed","email":"","middleInitial":"B.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":920184,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920185,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":920186,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steiner, Arron R.","contributorId":346918,"corporation":false,"usgs":false,"family":"Steiner","given":"Arron","email":"","middleInitial":"R.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":920187,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rhodes, J. Michael","contributorId":215130,"corporation":false,"usgs":false,"family":"Rhodes","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":920188,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Garcia, Michael O.","contributorId":225524,"corporation":false,"usgs":false,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":920189,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70263369,"text":"70263369 - 2024 - Seismicity zoning at Coso geothermal field and stress changes from fluid production and migration","interactions":[],"lastModifiedDate":"2025-02-07T18:50:48.949723","indexId":"70263369","displayToPublicDate":"2024-11-15T11:43:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Seismicity zoning at Coso geothermal field and stress changes from fluid production and migration","docAbstract":"As part of U.S. Geological Survey's (USGS) efforts to identify and assess geothermal energy resources of the US, a three-dimensional (3D) geologic and thermal model has been constructed for the Williston Basin, USA. The geologic model consists of all sedimentary units above the Proterozoic and Archean crystalline rock (called basement herein), with a total sedimentary thickness of up to 5 km near the basin center. Twenty-nine geologic units were mapped from interpreted formation tops from 16,465 wells. A 3D temperature model was constructed to a depth of 7 km by constructing a 3D heat flow model for the sedimentary units, followed by estimating underlying temperature using a one-dimensional (1D) analytic solution for heat flow within the underlying crystalline basement. Using the sedimentary basin model, heat flow was simulated in 3D and was calibrated using three temperature datasets: 1) 24 high-confidence static temperature logs (equilibrium thermal profiles), 2) more than15,000 drill stem test (DST) measurements from >7,000 wells, and 3) more than 45,000 bottomhole temperature (BHT) measurements from >14,000 wells. The DST and BHT datasets provide broad spatial coverage, but are lower confidence, primarily because measurements were made prior to attaining thermal equilibrium. DST and BHT measurements were binned regionally to develop representative thermal profiles that generally agree with these lower quality data (hereafter called pseudowell temperature profiles). Layer properties (primarily thermal conductivity and compaction curves) were set to best estimate values, then the heat flow model was calibrated to fit pseudowell and static temperature logs primarily by adjusting basal heat flow to approximate the overall temperature profile. Minor adjustments to thermal conductivity allowed adjusting changes in slope at lithologic contacts. Resulting maps include 3D temperature and basal (bottom of sedimentary units) heat flow estimates, which are used as input for the temperature model of the basement. The crystalline basement temperature model uses an analytic 1D solution to the heat flow equation that requires estimates of heat flow and temperature at the upper boundary (i.e., the sediment/basement contact), radiogenic heat production within the crystalline basement, and reference thermal conductivity (i.e., uncorrected for temperature). Two regions of high heat flow are identified: 1) in western North Dakota along the North American Central Plains Conductivity Anomaly and 2) in eastern Montana near the Poplar dome. Within the sedimentary column in the center of the basin of the basin, an area of approximately 100,000 km2 is predicted to have moderate- to high-temperature geothermal resources (>90 °C) under the thickest sequences of sediments. Where thick insulation and high heat flow coincide, electric-grade resources can be less than 4 km deep. Assuming a maximum feasible drilling depth of 7 km, temperatures are predicted to be as high as 175 °C. The geologic model may be used to identify strata at sufficient temperatures that may have natural permeability or that may have conditions that favor development of enhanced/engineered geothermal systems resources.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2024.103196","usgsCitation":"Gelman, S.E., and Burns, E.R., 2024, Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources: Geothermics, v. 125, 103196, 9 p., https://doi.org/10.1016/j.geothermics.2024.103196.","productDescription":"103196, 9 p.","ipdsId":"IP-165645","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":466763,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2024.103196","text":"Publisher Index Page"},{"id":464292,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.05487036081263,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 45.9204646960259\n ],\n [\n -100.81731222757732,\n 49.09401622161886\n ],\n [\n -107.05487036081263,\n 49.09401622161886\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"125","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gelman, Sarah E. 0000-0003-2549-9509","orcid":"https://orcid.org/0000-0003-2549-9509","contributorId":270004,"corporation":false,"usgs":true,"family":"Gelman","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918758,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270062,"text":"70270062 - 2024 - Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands","interactions":[],"lastModifiedDate":"2025-08-08T15:24:31.376369","indexId":"70270062","displayToPublicDate":"2024-11-15T10:19:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands","docAbstract":"Expansions in the extent and infestation levels of exotic annual grass (EAG) within the rangelands of the western United States are well documented. Land managers are tasked with developing plans to limit EAG spread and prevent irreversible ecosystem deterioration. The most common EAG species and the subject of extensive study is Bromus tectorum (cheatgrass). Cheatgrass has spread rapidly in western rangelands since its initial invasion more than 100 years ago. Another concerning aggressive EAG, Taeniatherum caput-medusae (medusahead), is also commonly found in some of these areas. To control the spread of EAGs, researchers have investigated applying several control methods during different developmental stages of cheatgrass and medusahead. These control strategies require accurate maps of the timing and spatial patterns of the developmental stages to apply mitigation strategies in the correct areas at the right time. In this study, we developed annual phenological datasets for cheatgrass and medusahead with two objectives. The first objective was to determine if cheatgrass and medusahead can be differentiated at 30 m resolution using their phenological differences. The second objective was to establish an annual phenology metric regression tree model used to map the growing seasons of cheatgrass and medusahead. Harmonized Landsat and Sentinel-2 (HLS)-derived predicted weekly cloud-free 30 m normalized difference vegetation index (NDVI) images were used to develop these metric maps. The result of this effort was maps that identify the start and end of sustained growing season time for cheatgrass and medusahead at 30 m for the Snake River Plain and Northern Basin and Range ecoregions. These phenological datasets also identify the start and end-of-season NDVI values, along with maximum NDVI throughout the study period. These metrics may be utilized to characterize annual growth patterns for cheatgrass and medusahead. This approach can be utilized to plan time-sensitive control measures such as herbicide applications or cattle grazing.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16224258","usgsCitation":"Benedict, T.D., Boyte, S., and Dahal, D., 2024, Differentiating cheatgrass and medusahead phenological characteristics in western United States rangelands: Remote Sensing, v. 16, no. 22, 4258, 21 p., https://doi.org/10.3390/rs16224258.","productDescription":"4258, 21 p.","ipdsId":"IP-171996","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":494184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16224258","text":"Publisher Index Page"},{"id":493848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -100.28187929406397,\n 48.82060636906533\n ],\n [\n -124.99361768794509,\n 48.88697493321598\n ],\n [\n -124.99361768794509,\n 30.85327470627726\n ],\n [\n -99.69664006714606,\n 30.849197853937767\n ],\n [\n -100.28187929406397,\n 48.82060636906533\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"22","noUsgsAuthors":false,"publicationDate":"2024-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Benedict, Trenton David 0000-0001-8672-2204","orcid":"https://orcid.org/0000-0001-8672-2204","contributorId":346111,"corporation":false,"usgs":true,"family":"Benedict","given":"Trenton","middleInitial":"David","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":945268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":945269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahal, Devendra 0000-0001-9594-1249","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":192023,"corporation":false,"usgs":false,"family":"Dahal","given":"Devendra","affiliations":[],"preferred":false,"id":945270,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}