{"pageNumber":"227","pageRowStart":"5650","pageSize":"25","recordCount":184717,"records":[{"id":70262313,"text":"70262313 - 2023 - Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.","interactions":[],"lastModifiedDate":"2025-01-22T17:19:20.260328","indexId":"70262313","displayToPublicDate":"2023-11-21T10:13:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9341,"text":"Ichthyology & Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.","docAbstract":"<p><span>Since the early 1990s, &gt; 3,000 ha of wetlands (and adjacent prairie) have been restored on the row-crop agricultural landscape of Winnebago County, Iowa, U.S.A. From 2014–2016, we surveyed 45 wetlands among 19 easements for occupancy by Eastern Tiger Salamanders (</span><i>Ambystoma tigrinum tigrinum</i><span>) and used radio-telemetry to measure their patterns of movement and habitat use. Rates of occupancy increased with wetland age, from &lt; 25% for wetlands 1–2 years old to ∼75% for wetlands &gt; 11 years old. A two-year survey (2014 and 2015) of ten wetlands restored in 2013 showed that nine were occupied after two years; we did not find a relationship between distance to the nearest salamander population and occupancy of newly restored wetlands by salamanders. We tracked 30 salamanders after they left their breeding wetlands for an average of 69±37 d (range = 14–109 d) and relocated them a total of 393 times. Typically, once a salamander left its breeding wetland, it traveled 50–350 m over several days, found a suitable burrow, then remained for much of the rest of the season. Mean daily distances traveled by salamanders were 7.9±5.6 m (range = 0–135 m); the range of maximum straight-line distances moved was 26–659 m; only one individual salamander traveled in a statistically linear path, relative to a random walk. While ∼90% of the landscape was composed of row-crop fields, salamanders used protective grassy habitats (e.g., restored prairie, road ditches) on ∼88% of our observations. Only three salamanders used row-crop fields, and two of them were killed by heavy equipment. Regardless of the terrestrial habitat types used by salamanders, we found them underground on 336 (84.8%) of our observations.</span></p>","language":"English","publisher":"BioOne","doi":"10.1643/h2020083","usgsCitation":"Bartelt, P., Devries, A., and Klaver, R.W., 2023, Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.: Ichthyology & Herpetology, v. 111, no. 4, p. 571-583, https://doi.org/10.1643/h2020083.","productDescription":"13 p.","startPage":"571","endPage":"583","ipdsId":"IP-116927","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Winnebago County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.9691,43.5044],[-93.6782,43.5047],[-93.6485,43.5045],[-93.4964,43.504],[-93.4971,43.4347],[-93.4971,43.3446],[-93.4977,43.2568],[-93.6184,43.2572],[-93.7354,43.257],[-93.853,43.2568],[-93.9699,43.2573],[-93.9705,43.3447],[-93.9699,43.4334],[-93.9691,43.5044]]]},\"properties\":{\"name\":\"Winnebago\",\"state\":\"IA\"}}]}","volume":"111","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartelt, Paul E.","contributorId":348825,"corporation":false,"usgs":false,"family":"Bartelt","given":"Paul E.","affiliations":[{"id":56262,"text":"Waldorf University","active":true,"usgs":false}],"preferred":false,"id":923810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Alyse T.","contributorId":348826,"corporation":false,"usgs":false,"family":"Devries","given":"Alyse T.","affiliations":[{"id":56262,"text":"Waldorf University","active":true,"usgs":false}],"preferred":false,"id":923811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923809,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250365,"text":"70250365 - 2023 - Stress gradients structure spatial variability in coastal tidal marsh plant composition and diversity in a major Pacific coast estuary","interactions":[],"lastModifiedDate":"2023-12-05T12:53:18.910274","indexId":"70250365","displayToPublicDate":"2023-11-21T06:47:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Stress gradients structure spatial variability in coastal tidal marsh plant composition and diversity in a major Pacific coast estuary","docAbstract":"<div class=\"JournalAbstract\"><p>Understanding the drivers of variability in plant diversity from local to landscape spatial scales is a challenge in ecological systems. Environmental gradients exist at several spatial scales and can be nested hierarchically, influencing patterns of plant diversity in complex ways. As plant community dynamics influence ecosystem function, understanding the drivers of plant community variability across space is paramount for predicting potential shifts in ecosystem function from global change. Determining the scales at which stress gradients influence vegetation composition is crucial to inform management and restoration of tidal marshes for specific functions. Here, we analyzed vegetation community composition in 51 tidal marshes from the San Francisco Bay Estuary, California, USA. We used model-based compositional analysis and rank abundance curves to quantify environmental (elevation/tidal frame position, distance to channel, and channel salinity) and species trait (species form, wetland indicator status, and native status) influences on plant community variability at the marsh site and estuary scales. While environmental impacts on plant diversity varied by species and their relationships to each other, overall impacts increased in strength from marsh to estuary scales. Relative species abundance was important in structuring these tidal marsh communities even with the limited species pools dominated by a few species. Rank abundance curves revealed different community structures by region with higher species evenness at plots higher in the tidal frame and adjacent to freshwater channels. By identifying interactions (species–species, species–environment, and environment–trait) at multiple scales (local, landscape), we begin to understand how variability measurements could be interpreted for conservation and land management decisions.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1215964","usgsCitation":"Rankin, L.L., Jones, S., Janousek, C.N., Buffington, K., Takekawa, J., and Thorne, K., 2023, Stress gradients structure spatial variability in coastal tidal marsh plant composition and diversity in a major Pacific coast estuary: Frontiers in Ecology and Evolution, v. 11, 1215964, 16 p., https://doi.org/10.3389/fevo.2023.1215964.","productDescription":"1215964, 16 p.","ipdsId":"IP-156855","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441577,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1215964","text":"Publisher Index Page"},{"id":435118,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94F802H","text":"USGS data release","linkHelpText":"Marsh Vegetation Surveys Across the San Francisco Bay Estuary, 2008-2018"},{"id":423234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.94698987792064,\n              38.31950691888645\n            ],\n            [\n              -122.94698987792064,\n              37.20784358966503\n            ],\n            [\n              -121.36495862792067,\n              37.20784358966503\n            ],\n            [\n              -121.36495862792067,\n              38.31950691888645\n            ],\n            [\n              -122.94698987792064,\n              38.31950691888645\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Rankin, Lyndsay L. 0000-0003-4968-1946","orcid":"https://orcid.org/0000-0003-4968-1946","contributorId":332147,"corporation":false,"usgs":true,"family":"Rankin","given":"Lyndsay","email":"","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Scott F. 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":204137,"corporation":false,"usgs":false,"family":"Jones","given":"Scott F.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":889565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janousek, Christopher N. 0000-0003-2124-6715","orcid":"https://orcid.org/0000-0003-2124-6715","contributorId":103951,"corporation":false,"usgs":false,"family":"Janousek","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":889566,"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":889567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203688,"corporation":false,"usgs":false,"family":"Takekawa","given":"John","affiliations":[{"id":36688,"text":"Suisun Resource Conservation District","active":true,"usgs":false}],"preferred":false,"id":889568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":889569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250318,"text":"70250318 - 2023 - Observing coastal wetland transitions using national land cover products","interactions":[],"lastModifiedDate":"2024-02-26T16:06:21.729112","indexId":"70250318","displayToPublicDate":"2023-11-20T09:41:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5866,"text":"Progress in Physical Geography: Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Observing coastal wetland transitions using national land cover products","docAbstract":"<p><span>Over the coming century, climate change and sea-level rise are predicted to cause widespread change to coastal wetlands. Estuarine vegetated wetlands can adapt to sea-level rise through both vertical development (i.e., biophysical feedbacks and sedimentation) and upslope/horizontal migration. Quantifying changes to estuarine vegetated wetlands over time can help to inform current and future decisions regarding land management and resource stewardship. In this study, we show how coastal land cover maps readily available in the US can be used to assess and understand estuarine vegetated wetland changes. This assessment involves two steps: (1) identifying the net gain/loss of estuarine vegetated wetlands and (2) determining which land cover types contribute to the net gain/loss. From this information, we developed estuarine vegetated wetland change scenarios that evaluate whether estuarine vegetated wetland gain kept up with loss and whether the contribution was from: (1) estuarine vegetated wetland migration or tidal restoration; (2) land building (i.e., development); or (3) both. We assessed changes from 1996 to 2016 for: (1) the conterminous US; (2) each major US coastline; and (3) focal estuaries with the most change per coast. We found that the change scenario (1, 2, or 3) varied across coastlines. Moving forward, national coastal land cover programs can be informed by utilizing methodologies that leverage contemporary information for delineating the estuarine zone from upslope/adjacent wetlands. We highlight approaches that could be used to address this challenge and provide complementary information related to wetland condition changes.</span></p>","language":"English","publisher":"SAGE Publications","doi":"10.1177/03091333231216588","usgsCitation":"Enwright, N., Osland, M., Thorne, K., Guntenspergen, G.R., Grace, J., Steyer, G., Herold, N., Chivoiu, B., and Han, M., 2023, Observing coastal wetland transitions using national land cover products: Progress in Physical Geography: Earth and Environment, v. 48, no. 1, p. 113-135, https://doi.org/10.1177/03091333231216588.","productDescription":"23 p.","startPage":"113","endPage":"135","ipdsId":"IP-151539","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":435119,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U43QEO","text":"USGS data release","linkHelpText":"Estuarine vegetated wetland change scenarios for estuaries in the conterminous United States, 1996&amp;ndash;2019"},{"id":423177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":209771,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":219805,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":889435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":206247,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steyer, Gregory 0000-0001-7231-0110","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":218813,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":889438,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Herold, Nate","contributorId":127749,"corporation":false,"usgs":false,"family":"Herold","given":"Nate","email":"","affiliations":[{"id":7054,"text":"NOAA/NMFS, Silver Spring, MD","active":true,"usgs":false}],"preferred":false,"id":889439,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chivoiu, Bogdan 0000-0002-4568-3496","orcid":"https://orcid.org/0000-0002-4568-3496","contributorId":141229,"corporation":false,"usgs":false,"family":"Chivoiu","given":"Bogdan","affiliations":[{"id":13722,"text":"University of Louisiana-Lafayette","active":true,"usgs":false}],"preferred":false,"id":889440,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Han, Minoo 0000-0002-6009-602X","orcid":"https://orcid.org/0000-0002-6009-602X","contributorId":332099,"corporation":false,"usgs":false,"family":"Han","given":"Minoo","email":"","affiliations":[{"id":79381,"text":"Han Consulting contracted to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":889441,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250205,"text":"70250205 - 2023 - Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty","interactions":[],"lastModifiedDate":"2023-11-28T13:21:31.650315","indexId":"70250205","displayToPublicDate":"2023-11-20T07:08:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5213,"text":"Epidemics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-42680-x","usgsCitation":"Howerton, E., Contamin, L., Mullany, L.C., Qin, M., Reich, N.G., Bents, S., Borchering, R.K., Jung, S., Loo, S.L., Smith, C.P., Levander, J., Kerr, J., Espino, J., van Panhuis, W., Hochheiser, H., Galanti, M., Yamana, T.K., Pei, S., Shaman, J.L., Rainwater-Lovett, K., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Lemaitre, J.C., Kaminsky, J., Dent Hulse, J., Lee, E.C., McKee, C., Hill, A., Karlen, D., Chinazzi, M., Davis, J.T., Mu, K., Xiong, X., Pastore Piontti, A., Vespignani, A., Rosenstrom, E.T., Ivy, J.S., Mayorga, M.E., Swann, J.L., Espana, G., Cavany, S., Moore, S., Perkins, A., Hladish, T.J., Pillai, A.N., Ben Toh, K., Longini, I., Chen, S., Paul, R., Janies, D., Thill, J., Bouchnita, A., Bi, K., Lachmann, M., Fox, S., Ancel Meyers, L., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Hurt, B., Chen, J., Mortveit, H., Wilson, A., Marathe, M., Hoops, S., Bhattacharya, P., Machi, D., Gunnels, B.L., Healy, J.M., Slayton, R.B., Johansson, M.A., Biggerstaff, M., Truelove, S., Runge, M.C., Shea, K., Viboud, C., and Lessler, J., 2023, Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty: Epidemics, v. 14, 7260, 15 p., https://doi.org/10.1038/s41467-023-42680-x.","productDescription":"7260, 15 p.","ipdsId":"IP-154417","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-42680-x","text":"Publisher Index Page"},{"id":423011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Howerton, Emily 0000-0002-0639-3728","orcid":"https://orcid.org/0000-0002-0639-3728","contributorId":258035,"corporation":false,"usgs":false,"family":"Howerton","given":"Emily","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":888822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Contamin, Lucie","contributorId":258068,"corporation":false,"usgs":false,"family":"Contamin","given":"Lucie","email":"","affiliations":[],"preferred":false,"id":888823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullany, Luke C","contributorId":301869,"corporation":false,"usgs":false,"family":"Mullany","given":"Luke","email":"","middleInitial":"C","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":888824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qin, Michelle","contributorId":296526,"corporation":false,"usgs":false,"family":"Qin","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":888825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reich, Nicholas G.","contributorId":258146,"corporation":false,"usgs":false,"family":"Reich","given":"Nicholas","email":"","middleInitial":"G.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":888826,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bents, Samantha","contributorId":331818,"corporation":false,"usgs":false,"family":"Bents","given":"Samantha","email":"","affiliations":[{"id":52216,"text":"National Institutes of Health Fogarty International Center","active":true,"usgs":false}],"preferred":false,"id":888827,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borchering, Rebecca K. 0000-0003-4309-2913","orcid":"https://orcid.org/0000-0003-4309-2913","contributorId":258031,"corporation":false,"usgs":false,"family":"Borchering","given":"Rebecca","email":"","middleInitial":"K.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":888828,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jung, Sung-mok","contributorId":331819,"corporation":false,"usgs":false,"family":"Jung","given":"Sung-mok","email":"","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel 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On rare occasions it erupts more differentiated&nbsp;magmas&nbsp;(&lt;1% of erupted volume), such as basaltic&nbsp;andesites&nbsp;and andesites, from its&nbsp;rift zones. These differentiated magmas offer an opportunity to understand better the&nbsp;petrology, magma storage, magma mixing, and eruptive triggers that occur in Kīlauea's rift zone reservoirs. This study focuses on an eruption from the Southwest Rift Zone of Kīlauea, which is dominantly basaltic andesite with subordinate&nbsp;basalt. This eruption originated at the Kamakaiʻa Hills during the early 19th century and has two eruptive phases: 1) an early ‘a‘ā phase that is primarily exposed in the eastern part of the flow field, with minor western lobes, and 2) a late pāhoehoe phase that makes up most of the western part of the flow field. The early ‘a‘ā phase covers at least 5.8&nbsp;km</span><sup>2</sup><span>&nbsp;</span>with an erupted volume of ∼150&nbsp;×&nbsp;10<sup>6</sup>&nbsp;m<sup>3</sup><span>&nbsp;</span>and consists of uniform composition basaltic andesites with 3.72–4.15&nbsp;wt% MgO over its ∼7&nbsp;km flow length. The late pāhoehoe phase reached &gt;10&nbsp;km from its vent, covers an area of ∼7.1&nbsp;km<sup>2</sup>, has a volume of ∼100&nbsp;×&nbsp;10<sup>6</sup>&nbsp;m<sup>3</sup><span>, and initially erupted basaltic andesite near its vent (4.50–5.64&nbsp;wt% MgO extending to 3.8&nbsp;km from vent) with channel and tube-fed basalt (6.21–12.38&nbsp;wt% MgO sampled at &gt;3.8&nbsp;km from vent) emplaced during its waning stages. Most Kamakaiʻa Hills lavas are crystal-poor, containing ≤1.5% glomerocrysts and individual&nbsp;phenocrysts&nbsp;of plagioclase +&nbsp;clinopyroxene&nbsp;+ Fe</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Ti oxides ±&nbsp;orthopyroxene, as well as olivine in lavas with &gt;6&nbsp;wt% MgO.</span></p><p id=\"sp0075\">Major-oxide and trace-element concentrations throughout the Kamakaiʻa Hills lavas demonstrate the involvement of three distinct magmatic processes. First, the basaltic andesites of the early ‘a‘ā phase are the products of fractionation of plagioclase + clinopyroxene + Fe<img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">Ti oxides ± orthopyroxene, indicative of magmas that have been stored in rift zone reservoirs for decades or longer. Second, the near-vent (within ∼400&nbsp;m of vent) basaltic andesites of the late pāhoehoe phase yield chemical concentrations that indicate magma mixing with a more differentiated magma (of a similar evolved composition to basaltic andesites at ∼55–56&nbsp;wt% SiO<sub>2</sub><span>&nbsp;</span>and&nbsp;∼3.4–4.1&nbsp;wt% MgO that erupted in the lower East Rift Zone in 2018). Third, the progressively more mafic magma (containing olivine + plagioclase + clinopyroxene) that continued to erupt throughout the waning stages of activity suggests an eruptive triggering process whereby an intruding summit or uprift reservoir basalt overpressurized and forced out the stored, differentiated magma of the Kamakaiʻa Hills rift zone reservoir.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107967","usgsCitation":"Downs, D.T., Sas, M., and Hazlett, R.W., 2023, Chemistry and petrography of early 19th century basaltic andesites and basalts from the Kamakaiʻa Hills in the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi: Journal of Volcanology and Geothermal Research, v. 444, 107967, 19 p., https://doi.org/10.1016/j.jvolgeores.2023.107967.","productDescription":"107967, 19 p.","ipdsId":"IP-148287","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":435120,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TLM9YD","text":"USGS data release","linkHelpText":"Major- and trace-element chemical analyses of whole-rock and glass from the Kamakaiʻa Hills of the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi"},{"id":422713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaiʻi","otherGeospatial":"Kamakaiʻa Hills, Kīlauea Volcano, Southwest Rift Zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.53595307076637,\n              19.09998767098206\n            ],\n            [\n              -155.5226475641525,\n              19.108725037100598\n            ],\n            [\n              -155.50845458316687,\n              19.117944797569507\n            ],\n            [\n       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Center","active":true,"usgs":true}],"preferred":true,"id":888365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sas, May","contributorId":194298,"corporation":false,"usgs":false,"family":"Sas","given":"May","email":"","affiliations":[],"preferred":false,"id":888366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazlett, Richard W. 0000-0002-8841-0906","orcid":"https://orcid.org/0000-0002-8841-0906","contributorId":214066,"corporation":false,"usgs":false,"family":"Hazlett","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":38976,"text":"Pomona College, Claremont, CA; UH Hilo, Hilo HI; Department of Interior","active":true,"usgs":false}],"preferred":false,"id":888367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70251057,"text":"70251057 - 2023 - Modeling groundwater-level responses to multiple stresses using transfer-function models and wavelet analysis in a coastal aquifer system","interactions":[],"lastModifiedDate":"2024-01-19T13:26:30.651329","indexId":"70251057","displayToPublicDate":"2023-11-19T07:24:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling groundwater-level responses to multiple stresses using transfer-function models and wavelet analysis in a coastal aquifer system","docAbstract":"<p>In coastal aquifers, dynamic stresses such as climate forcings, groundwater withdrawals, and ocean tidal fluctuations cause nonlinear responses to groundwater levels. Such responses to the stresses impact groundwater resources and related flooding and infrastructure risks at multiple scales. We used time-series models such as transfer-function models and wavelet analysis to quantify the relative contribution of these stresses to groundwater-level fluctuation in wells from the unconfined and confined aquifers in an Atlantic coastal aquifer. Climate forcings, such as precipitation and temperature, explained most of the groundwater-level variation for wells in the unconfined aquifer, whereas groundwater withdrawals were the dominant driver of groundwater levels for wells in the confined aquifer. The impact of groundwater withdrawals also was detected in several wells in the unconfined aquifer. Although the influence of ocean tides on groundwater levels commonly is observed in coastal aquifers, we found that daily groundwater withdrawals can obscure the semi-diurnal coherence signal of the two series. The magnitude of groundwater-level fluctuation that could be explained solely by tides was minor compared to that explained by climate or withdrawal stresses. Transfer-function modeling showed seasonal withdrawals from wells in confined aquifers had a significant, yet heterogeneous influence on groundwater levels in coastal aquifers, which highlights climate and withdrawals as key compounding stresses in coastal hydrology. This study demonstrates the value of time-series approaches to advance characterization of groundwater systems in areas with limited hydrogeologic parameter information.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.130426","usgsCitation":"Yang, G., and McCoy, K., 2023, Modeling groundwater-level responses to multiple stresses using transfer-function models and wavelet analysis in a coastal aquifer system: Journal of Hydrology, v. 627, no. Part B, 130426, 12 p., https://doi.org/10.1016/j.jhydrol.2023.130426.","productDescription":"130426, 12 p.","ipdsId":"IP-150305","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":441582,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2023.130426","text":"Publisher Index Page"},{"id":424621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","city":"Virginia Beach","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.26319664375336,\n              37.04695559476376\n            ],\n            [\n              -76.26319664375336,\n              36.59981472352801\n            ],\n            [\n              -75.83944187250752,\n              36.59981472352801\n            ],\n            [\n              -75.83944187250752,\n              37.04695559476376\n            ],\n            [\n              -76.26319664375336,\n              37.04695559476376\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"627","issue":"Part B","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yang, Guoxiang 0000-0001-5587-3683","orcid":"https://orcid.org/0000-0001-5587-3683","contributorId":267279,"corporation":false,"usgs":false,"family":"Yang","given":"Guoxiang","affiliations":[{"id":55459,"text":"NSA Contractor to USGS VA and WV WSC","active":true,"usgs":false}],"preferred":false,"id":892914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Kurt J. 0000-0002-9756-8238","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":216196,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt J.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70241016,"text":"ofr20231015 - 2023 - Evaluating management alternatives for Wyoming elk feedgrounds in consideration of chronic wasting disease","interactions":[],"lastModifiedDate":"2026-02-11T20:44:17.631411","indexId":"ofr20231015","displayToPublicDate":"2023-11-17T17:35:00","publicationYear":"2023","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":"2023-1015","displayTitle":"Evaluating Management Alternatives for Wyoming Elk Feedgrounds in Consideration of Chronic Wasting Disease","title":"Evaluating management alternatives for Wyoming elk feedgrounds in consideration of chronic wasting disease","docAbstract":"<h1>Executive Summary</h1><p>The authors used decision and modeling analyses to evaluate management alternatives for a decision on whether to permit <i>Cervus canadensis</i> (elk) feeding on two sites on Bridger-Teton National Forest, Dell Creek and Forest Park. Supplemental feeding of elk could increase the transmission of chronic wasting disease (CWD) locally and disease spread regionally, potentially impacting elk populations over time with wider implications for <i>Odocoileus hemionus</i> (mule deer) and <i>Odocoileus virginianus</i> (white-tailed deer) populations and hunting, tourism, and regional revenue. Supplemental feeding is thought to improve overwinter elk survival and reduce the commingling of elk with cattle during months when brucellosis transmission risk is highest. We worked with the U.S. Department of Agriculture Forest Service to identify their fundamental objectives and associated performance metrics related to this feedground decision. We then developed disease and habitat selection models to quantify the effect of four management alternatives on select performance metrics. The four alternatives were to continue to permit feeding, phaseout permits to feed in three years, permit feeding on an emergency basis, or stop permitting feeding. In this report, we present methods and summarized results on disease and habitat selection models and summaries of other performance metrics analyzed by BIO-WEST, Inc. and Cirrus Ecological Solutions as part of an Environmental Impact Statement.</p><p>Data from Wyoming Game and Fish Department (WGFD) supported the assumption that supplemental elk feeding allows for larger elk populations in a region. We documented that herd units (HU) without feedgrounds had 23 percent lower densities of elk per area of winter range when compared against HUs with feedgrounds, after accounting for differences in sightability of elk during counts on and off feedgrounds. Thus, throughout our analyses, we assumed feedground closures would reduce elk carrying capacity resulting in an average decline of previously fed elk population segments by 23 percent (5th and 95th percentiles = [11 percent, 35 percent]) by year 20. Most of that decline occurred within the first few years after a feedground ceases to operate. We used a panel of CWD experts to help estimate CWD trans-mission in fed and unfed elk population segments. In aggregate, the expert panel estimated that median values of direct and indirect transmission of CWD are expected to be 1.9 and 4 times higher, respectively, in fed elk populations compared to unfed elk. We used these disease transmission estimates in combination with local elk demographic rates and carrying capacity estimates to project disease and population dynamics.</p><p>In year 20, we predicted CWD prevalence would increase to 42 percent (5th and 95th percentiles = [29 percent, 55 percent]), and 13 percent (5th and 95th percentiles = [4 percent, 26 percent]) on average for fed and unfed elk population segments, respectively, given a starting prevalence of 1.6 percent. The prevalence estimates for the unfed elk population segments are in the range of previous observations of CWD in elk in the western United States. The average CWD prevalence from 2016 to 2018 in the unfed elk population of Wind Cave National Park in South Dakota was 18 percent overall but up to 30 percent in some regions (Sargeant and others, 2021). Meanwhile, CWD prevalence in the Iron Mountain and Laramie Peak elk herds in Wyoming from 2016 to 2018 was 14 percent and 7 percent, respectively, despite being present since at least 2002 (Wyoming Game and Fish Department, 2020b).</p><p>From 2016 to 2020, elk that were fed at Dell Creek and Forest Park constituted on average 12–20 percent of the total elk on their respective HUs. As a result, the differences between management alternatives are modest when considering the closure of only one feedground on a HU. The no feeding alternative for Forest Park resulted in a CWD prevalence of 17 percent (SD = 7 percent) in the Afton HU compared to 20 percent (SD = 7 percent) with continued feeding by year 20. In the Upper Green River HU, no feeding on Dell Creek resulted in a CWD prevalence of 27 percent (SD = 6 percent) compared to 30 percent (SD = 5 percent) with continued feeding. In terms of disease-associated mortality, we predicted the closure of Forest Park and Dell Creek feedgrounds would reduce the total number of CWD mortalities by 9 percent in the Upper Green River HU and 26 percent in the Afton HU during the 20-year timespan.</p><p>Our spatial analyses predicted that management alternative effects vary by HU as a function of private property and other wildlife winter ranges proximity relative to feedground location. The predicted number of elk abortions on private land, as a proxy for brucellosis risk to cattle, may increase by 8–21 percent in the absence of feeding at Dell Creek and Forest Park.</p><p>Eight feedgrounds are located on Bridger-Teton National Forest, all of which have permits that have expired or will expire prior to 2028. In addition, WGFD could change their management of feedgrounds given new information; therefore, we also assessed the cumulative effects of continued feeding, phaseout, and no feeding management alternatives across five HUs south of Jackson, Wyoming (Afton HU, Fall Creek HU, Piney HU, Pinedale HU, and Upper Green River HU). These five HUs ranged from about 41 to 85 percent of the elk herd using feedgrounds, which corresponded to a CWD prevalence at year 20 of 23–34 percent if all feedgrounds in those five HUs remained open relative to 12 to 14 percent if all feedgrounds were closed. We predicted feedground closures may result in immediate reductions in population size relative to alternatives that continue feeding (for example, continued feeding and emergency feeding alternatives); however, over longer periods of time, CWD-associated mortality leads to larger population reductions. The no feeding alternative resulted in higher elk population sizes compared to the continued feeding alternative after about 10 years of implementation. Delayed action under a phaseout alternative resulted in increasing the CWD prevalence to 20 percent relative to 12 to 14 percent, on average, without feeding on HUs with a large population of fed elk such as the Upper Green River HU.</p><p>Summarizing our cumulative results across all five of the analyzed HUs, we predicted continued feeding will lead to fewer elk by year 20 (mean = 8,300, standard deviation [SD] = 740) compared to no feeding at U.S. Department of Agri-culture Forest Service sites (10,700, SD = 890). The closure of all feedgrounds was projected to result in the largest elk populations at year 20 (12,500, SD = 980). No feeding at all sites also resulted in the largest cumulative harvest of 57,700 (SD = 2,600) compared to 51,100 (SD = 3,800) for continued feeding at all current feedground sites on the five HUs. Continued feeding also resulted in the lowest brucellosis costs to producers ($194,600, SD = $11,500) compared to no feeding on all feedgrounds ($243,000, SD = $13,700). Assuming moderate reductions in hunter interest because of increasing CWD prevalence in elk, we predicted that no feeding resulted in regional revenues generated by hunting activities of $190 million (SD = $10 million) compared to $173 million (SD = $10 million) for continued feeding over the 20-year timeframe.</p><p>Recent CWD detections in mule deer and elk in Grand Teton National Park has elevated the importance of the cur-rent decision on whether, and how, to permit elk feeding on Dell Creek and Forest Park and the management of the other feedgrounds. Aggressive male harvest has slowed, but not stopped, the increasing prevalence of CWD in mule deer (Conner and others, 2021). It is unclear whether harvest management can be an effective tool to slow the spread of CWD in elk. There are also no effective treatments or vaccines for CWD, and it is unlikely that any will be developed that can be easily deployed in the near future. Thus, reducing artificial aggregations is one of the few management approaches suggested by the Western Association of Fish and Wildlife Agencies (Almberg and others, 2017).</p><p>Future surveillance and monitoring can be designed to resolve uncertainties that can improve future decision-making. If feedgrounds close, research could quantify elk population reductions in the absence of feeding, the redistribution of fed elk to other places, or the consequences of elk movement on private property. If feedgrounds remain open, research could assess how rapidly CWD spreads in artificial aggregations of elk; however, surveillance programs would need to be designed with sufficient power to detect initial changes of CWD prevalence. Delaying action on feedground management was projected to be costly. Results of the phaseout alternative relative to the no feeding alternative suggested a 3-year delay was enough for substantial long-term changes in CWD prevalence. The long-term persistence of infectious CWD prions in the environment suggests that feedground management decisions may have long-lasting consequences.</p><p>Our results indicated tradeoffs in the ability of a management agency to achieve all their objectives, and all management alternatives resulted in significant reductions in elk population size. This report contains the foundational elements for formal decision analysis methods, which can be implemented to help decision makers transparently evaluate the consequences of decision alternatives and identify the set of actions that best achieve agency and stakeholder priorities.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231015","collaboration":"Prepared in cooperation with U.S. Department of Agriculture, National Park Service, U.S. Fish and Wildlife Service, and Wyoming Game and Fish Department","usgsCitation":"Cook, J.D., Cross, P.C., Tomaszewski, E.M., Cole, E.K., Campbell Grant, E.H., Wilder, J.M., and Runge, M.C., 2023, Evaluating management alternatives for Wyoming Elk feedgrounds in consideration of chronic wasting disease (ver. 2.0, November 2023): U.S. Geological Survey Open-File Report 2023–1015, 50 p., https://doi.org/10.3133/ofr20231015.","productDescription":"Report: ix, 50 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-145385","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499766,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114473.htm","linkFileType":{"id":5,"text":"html"}},{"id":422707,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1015/versionHist.txt","size":"4.0kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1015 history file"},{"id":422706,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1015/ofr20231015.pdf","text":"Report","size":"7.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1015"},{"id":419233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1015/coverthb2.jpg"},{"id":422704,"rank":2,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9R7XWO1","text":"USGS software release—","linkHelpText":"Simulating chronic wasting disease on Wyoming elk feedgrounds (version 2.0)."}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.03672229293583,\n              43.73180346838649\n            ],\n            [\n              -111.03672229293583,\n              42.40523773968059\n            ],\n            [\n              -109.27478197144448,\n              42.40523773968059\n            ],\n            [\n              -109.27478197144448,\n              43.73180346838649\n            ],\n            [\n              -111.03672229293583,\n              43.73180346838649\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Version 1.0: March 2023: Version 2.0: November 2023","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/norock/\" data-mce-href=\"https://www.usgs.gov/centers/norock/\">Northern Rocky Mountain Science Center</a><br>U.S. Geological Survey<br>2327 University Way, Suite 2 <br>Bozeman, MT 59715</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Decision Framing</li><li>Chronic Wasting Disease, Population Size, and Harvest Projections</li><li>Spatio-Temporal Analysis of Elk Distributions</li><li>Consequences</li><li>Conclusions and Future Directions</li><li>References Cited</li><li>Appendix 1. Additional Chronic Wasting Disease Analysis Details</li></ul>","publishedDate":"2023-03-09","revisedDate":"2023-11-17","noUsgsAuthors":false,"publicationDate":"2023-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Jonathan D. 0000-0001-7000-8727","orcid":"https://orcid.org/0000-0001-7000-8727","contributorId":291411,"corporation":false,"usgs":true,"family":"Cook","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":865728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":865729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomaszewski, Emily M. 0000-0002-3766-8990","orcid":"https://orcid.org/0000-0002-3766-8990","contributorId":302889,"corporation":false,"usgs":true,"family":"Tomaszewski","given":"Emily","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":865730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Eric K.","contributorId":302890,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":65572,"text":"U.S. Fish and Wildlife Service, National Elk Refuge","active":true,"usgs":false}],"preferred":false,"id":865731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilder, James M.","contributorId":302891,"corporation":false,"usgs":false,"family":"Wilder","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":865733,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865734,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250099,"text":"sir20235066 - 2023 - Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","interactions":[],"lastModifiedDate":"2026-03-09T16:53:50.063749","indexId":"sir20235066","displayToPublicDate":"2023-11-17T13:55:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5066","displayTitle":"Updates to the Regional Groundwater-Flow Model of the New Jersey Coastal Plain, 1980–2013","title":"Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","docAbstract":"<p>A 21-layer three-dimensional transient groundwater-flow model of the New Jersey Coastal Plain was developed and calibrated by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection to simulate groundwater-flow conditions during 1980–2013, incorporating average annual groundwater withdrawals and average annual groundwater recharge. This model is the third version of the New Jersey Coastal Plain regional groundwater-flow model that was initially developed as part of the USGS Regional Aquifer System Analysis (RASA) program. The model simulates groundwater flow in 11 aquifers and 10 intervening confining units of the New Jersey Coastal Plain to provide a regional overview of groundwater conditions. Averaged groundwater withdrawal data for 1980 to 2013 were used in the model. The 11 aquifers in New Jersey are, from shallowest to deepest, the Holly Beach water-bearing zone and the confined Cohansey aquifer in Cape May County; the Rio Grande water-bearing zone; the Atlantic City 800-foot sand; the Piney Point, Vincentown, and Wenonah-Mount Laurel aquifers; the Englishtown aquifer system; and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.</p><p>The model was developed with the MODFLOW–2005 numerical code and the UCODE parameter estimation technique and calibrated using water-level and base-flow observations. A total of 3,453 water-level observations from 392 wells in New Jersey and 48 wells in Delaware from 1983 to 2013 were used in model calibration, which includes historical water-level trends for 29 wells in New Jersey during 1980–2013 presented in time-series hydrographs. In addition, derived observations also were included by calculating the vertical gradient at 33 pairs of nested observation wells in New Jersey, for a total of 210 observations. Changes in water levels over time were calculated for 134 wells in New Jersey and four wells in Delaware where water levels had varied substantially (approximately 10 ft) over the 30-year span of synoptic water-level measurements, for a total of 767 observations. A total of 1,485 base-flow observations in 47 surface-water basins in New Jersey from 1980 to 2013 were used in model calibration.</p><p>Updates to the groundwater-flow model include the conversion to a fully three-dimensional model from the previous quasi-three-dimensional model. The new model will allow for potential future uses such as particle tracking or simulation of variable-density groundwater flow that could not be accomplished with earlier versions of the model. Spatially and temporally variable recharge estimated by using a soil-water balance model resulted in a spatially and temporally finer discretization. The Rio Grande water-bearing zone was added to the model as an aquifer layer to refine estimates of simulated flow in Atlantic and Cape May Counties, New Jersey. Hydrogeologic parameters were updated to include the confining units in New Jersey and corresponding hydrogeologic units in Delaware and eastern Maryland.</p><p>The simulated water levels for the New Jersey Coastal Plain aquifers were compared to water-level measurements made during 1980–2013. The average residual for 4,243 water-level observations for New Jersey (simulated water levels minus measured water levels) is 1.5 feet. The simulated water-level contours for the confined aquifers for 2013 were compared to potentiometric surfaces produced from water levels measured during 2013. Simulated water levels generally matched the 2013 potentiometric surfaces of the confined aquifers in the areas of large withdrawals. Hydrographs of wells in the confined Coastal Plain aquifers of New Jersey show that simulated water levels generally match the magnitude and seasonal variation of the observed water levels. Hydrographs of base flow for the 47 streamgaging stations in New Jersey indicate that most of the simulated and estimated data match reasonably well.</p><p>Groundwater withdrawals are an important resource for water supply, agricultural, industrial, and commercial needs in the New Jersey Coastal Plain. Groundwater withdrawals from the New Jersey Coastal Plain aquifers have resulted in persistent, regionally extensive cones of depression in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and upper, middle, and lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Because hydrologic stresses and water-management needs change with time, periodic updates to the groundwater-flow model are required to provide current information about hydrologic conditions in the New Jersey Coastal Plain and to maintain its usefulness as a tool to manage water resources and develop water-resource strategies. The current updates will support the continued application of this model as a tool for evaluating the regional effects of changes in groundwater withdrawals and of current and potential future water-management strategies on groundwater levels in the New Jersey Coastal Plain.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235066","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., and Carleton, G.B., 2023, Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2023–5066, 116 p., https://doi.org/10.3133/sir20235066","productDescription":"Report: xii, 116 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500947,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115639.htm","linkFileType":{"id":5,"text":"html"}},{"id":422695,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5066/images/"},{"id":422693,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5066"},{"id":422696,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W6RXFC","text":"USGS data release","linkHelpText":"MODFLOW-2005 model used to simulate the regional groundwater flow system in the updated New Jersey Coastal Plain model, 1980-2013"},{"id":422694,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.XML"},{"id":422692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5066"},{"id":422691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5066/coverthb.jpg"}],"country":"United States","otherGeospatial":"New Jersey Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.49018324613056,\n              41.03712838002892\n            ],\n            [\n              -75.25922621488034,\n              41.417217443631785\n            ],\n            [\n              -77.41254652738019,\n              39.17183412365296\n            ],\n            [\n              -75.22626723050551,\n              37.8132834585617\n            ],\n            [\n              -72.98505629300531,\n              40.4043207917766\n            ],\n            [\n              -74.49018324613056,\n              41.03712838002892\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\">New Jersey Water Science Center</a><br>3450 Princeton Pike, Suite 110<br>Lawrenceville, New Jersey 08648</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Simulation of Groundwater Flow</li><li>Summary</li><li>References Cited</li><li>Appendix 1: Soil-Water Balance Methodology</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-11-17","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gordon, Alison D. 0000-0002-9502-8633","orcid":"https://orcid.org/0000-0002-9502-8633","contributorId":221457,"corporation":false,"usgs":true,"family":"Gordon","given":"Alison","email":"","middleInitial":"D.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carleton, Glen B. 0000-0002-7666-4407","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":306147,"corporation":false,"usgs":false,"family":"Carleton","given":"Glen","email":"","middleInitial":"B.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":888331,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250011,"text":"fs20233042 - 2023 - The 3D Elevation Program—Supporting Missouri’s economy","interactions":[],"lastModifiedDate":"2024-01-25T17:25:00.353292","indexId":"fs20233042","displayToPublicDate":"2023-11-17T13:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3042","displayTitle":"The 3D Elevation Program—Supporting Missouri’s Economy","title":"The 3D Elevation Program—Supporting Missouri’s economy","docAbstract":"<h1>Introduction</h1><p>Because of its geography, Missouri is frequently subject to natural disasters. Ice storms, severe thunderstorms, tornadoes, and flooding are all common occurrences. Since 1990, Missouri has received 40 Federal major disaster declarations. Floods and droughts severely affect the State’s agriculture, which is a leading industry. Another potential major hazard is the New Madrid seismic zone (NMSZ), located in southeastern Missouri. Because Missouri is a major producer of lead, manufacturing and mining are very important to the State’s economy, as are restoring and reclaiming lands damaged by historical mining activities. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233042","usgsCitation":"Nail, D.S., 2023, The 3D Elevation Program—Supporting Missouri’s economy: U.S. Geological Survey Fact Sheet 2023–3042, 2 p., https://doi.org/10.3133/fs20233042","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127176","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":422536,"rank":5,"type":{"id":31,"text":"Publication 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Status of 3DEP in Missouri</li><li>Agriculture and Precision Farming</li><li>Flood Risk Management</li><li>Geologic Resource Assessment and Hazard Mitigation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-17","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Nail, David 0000-0003-0793-2305 dnail@usgs.gov","orcid":"https://orcid.org/0000-0003-0793-2305","contributorId":331534,"corporation":false,"usgs":true,"family":"Nail","given":"David","email":"dnail@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":887991,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250060,"text":"sim3510 - 2023 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","interactions":[{"subject":{"id":70176667,"text":"sim3366 - 2016 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","indexId":"sim3366","publicationYear":"2016","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas"},"predicate":"SUPERSEDED_BY","object":{"id":70250060,"text":"sim3510 - 2023 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","indexId":"sim3510","publicationYear":"2023","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas"},"id":1}],"lastModifiedDate":"2026-01-26T19:06:16.125955","indexId":"sim3510","displayToPublicDate":"2023-11-17T11:58:28","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3510","displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Bexar and Comal Counties, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><strong></strong></span>During 2020–22, the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, revised a previous publication that described the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas. This report presents the refined maps and descriptions of geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties that resulted from additional field data. Two informal geologic units and their corresponding informal hydrostratigraphic unit (HSU) names are introduced in this report; these informal units were identified during geologic mapping work done in counties adjoining the study area. Hydrostratigraphically, the rocks exposed in the study area represent a section of the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, the middle zone of the Trinity aquifer, and the lower confining unit to the middle zone of the Trinity aquifer. The Washita, Eagle Ford, Austin, and Taylor Groups are generally considered to be the upper confining unit to the Edwards aquifer. The Edwards aquifer was subdivided into nine informally named HSUs (from top to bottom) as follows: I, II, III, IV, V, VI, VII, Seco Pass, and VIII. The upper zone of the Trinity aquifer was subdivided into five informal HSUs and two subunits (from top to bottom) as follows: cavernous, Camp Bullis, upper evaporite, fossiliferous (subunits: upper and lower), and lower evaporite. The middle zone of the Trinity aquifer was subdivided into nine named HSUs (from top to bottom) as follows: Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Herff Falls (where present), Rust, Honey Creek, Hensell, and Cow Creek. The middle zone of the Trinity aquifer is underlain by the confining Hammett HSU. Groundwater recharge and flow paths in the study area are influenced not only by the hydrostratigraphic characteristics of the individual HSUs but also by faults and fractures.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3510","issn":"2329-132X","collaboration":"Prepared in cooperation with the Edwards Aquifer Authority","usgsCitation":"Clark, A.K., Golab, J.A., Morris, R.R., and Pedraza, D.E., 2023, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas (ver. 1.1, July 2025): U.S. Geological Survey Scientific Investigations Map 3510, 1 sheet, scale 1:24,000, 24-p. pamphlet, https://doi.org/10.3133/sim3510. [Supersedes USGS Scientific Investigations Map 3366.]","productDescription":"Report: viii, 24 p., 1 Sheet: 68.19 × 50.65 inches; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-137862","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":493048,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3510/SIM3510_ver1.1_VersionHistory.txt","linkFileType":{"id":2,"text":"txt"}},{"id":422633,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GXJ2RS","text":"USGS Data Release","linkHelpText":"Geospatial dataset for the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Bexar and Comal Counties, Texas, at 1:24,000 scale"},{"id":422630,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3510/Images"},{"id":422631,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3510/SIM3510_pamphlet.pdf","text":"Pamphlet","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3510 pdf"},{"id":422661,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3510/coverthb2.jpg"},{"id":422632,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3510/SIM3510.pdf","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3510 Plate 1","linkHelpText":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Bexar and Comal Counties, Texas"},{"id":499035,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115631.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","county":"Bexar County, Comal County","otherGeospatial":"Edwards Aquifer, Trinity Aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.30017089843749,\n              30.0405664305846\n            ],\n            [\n              -98.65447998046875,\n              29.75364773335698\n            ],\n            [\n              -98.78494262695312,\n              29.72025928058346\n            ],\n            [\n              -98.80691528320311,\n              29.699982298744377\n            ],\n            [\n              -98.80691528320311,\n              29.489815619374962\n            ],\n            [\n              -98.60916137695312,\n              29.48383858387499\n            ],\n            [\n              -98.316650390625,\n              29.597341920567366\n            ],\n            [\n              -98.09280395507812,\n              29.685666670118724\n            ],\n            [\n              -97.99942016601562,\n              29.757224408272663\n            ],\n            [\n              -98.0364990234375,\n              29.852555290064018\n            ],\n            [\n              -98.30017089843749,\n              30.0405664305846\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: November 17, 2023; Version 1.1: July 29, 2025","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/ot-water\" href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a><br>U.S. Geological Survey<br>1505 Ferguson Lane<br>Austin, TX 78754–4501</p><p><a data-mce-href=\"../\" href=\"../\"><span class=\"ContentPasted3\">Contact Pubs Warehouse</span></a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Geologic Framework</li><li>Hydrostratigraphy</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-11-17","revisedDate":"2025-07-29","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golab, James A. 0000-0002-3222-6114 jgolab@usgs.gov","orcid":"https://orcid.org/0000-0002-3222-6114","contributorId":173290,"corporation":false,"usgs":false,"family":"Golab","given":"James","email":"jgolab@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":888332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Robert R. 0000-0001-7504-3732","orcid":"https://orcid.org/0000-0001-7504-3732","contributorId":331599,"corporation":false,"usgs":true,"family":"Morris","given":"Robert R.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pedraza, Diana E. 0000-0003-4483-8094","orcid":"https://orcid.org/0000-0003-4483-8094","contributorId":217877,"corporation":false,"usgs":true,"family":"Pedraza","given":"Diana E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888170,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250061,"text":"sir20235099 - 2023 - Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables","interactions":[],"lastModifiedDate":"2026-03-13T15:15:40.637546","indexId":"sir20235099","displayToPublicDate":"2023-11-17T09:01:14","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5099","displayTitle":"Machine-Learning Predictions of Groundwater Specific Conductance in the Mississippi Alluvial Plain, South-Central United States, With Evaluation of Regional Geophysical Aerial Electromagnetic Data as Explanatory Variables","title":"Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables","docAbstract":"<p>The Mississippi Alluvial Plain, located in the south-central United States, is undergoing long-term groundwater-level declines within the surficial Mississippi River Valley alluvial aquifer (hereinafter referred to as “alluvial aquifer”), which has raised concerns about future groundwater availability. In some parts of the alluvial aquifer, groundwater availability for common uses such as irrigation, public supply, and domestic use is limited by quality (for example, high salinity) rather than quantity of water stored in the aquifer. The Mississippi Alluvial Plain region has an abundance of water-quality measurements in the alluvial aquifer and deeper aquifers; however, large areas lack direct measurements of salinity to evaluate regional groundwater availability. Statistical models can interpolate between wells to fill in spatial data gaps. In 2021, the U.S. Geological Survey trained two boosted regression tree (BRT) machine-learning models on specific conductance data available between 1942 and 2020 to predict spatially continuous surfaces of groundwater salinity at multiple depths for the alluvial aquifer and deeper aquifers. Well construction information, water levels, and surficial variables such as geomorphology and soils were included as explanatory variables in this baseline model. Additionally, subsurface electrical resistivity data from the first aquifer-wide aerial electromagnetic (AEM) survey for the region were incorporated to create a geophysical model. This work expands on prior BRT salinity predictions of the alluvial aquifer and extends predictions south to the Gulf of Mexico, where groundwater salinity is high. AEM survey data were not available for the southern extent of the alluvial aquifer at the time of modeling. A BRT model was trained without (baseline) and with (geophysical) AEM variables to test the ability of the models to predict salinity where explanatory data are missing and response data are sparse. Additionally, model sensitivity to AEM survey data was evaluated to better understand how AEM variables influence specific conductance predictions. Model performance was improved with the addition of geophysical data, which added three-dimensional information, thereby improving salinity predictions at depth. Groundwater specific conductance predictions can help inform other geophysical investigations in the southern extent of the study area, where high groundwater specific conductance can obfuscate changes in aquifer sediment resistivity and could limit groundwater resources for agricultural, public supply, and domestic uses.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235099","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Killian, C.D., and Knierim, K.J., 2023, Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables: U.S. Geological Survey Scientific Investigations Report 2023–5099, 36 p., 1 pl., https://doi.org/10.3133/sir20235099.","productDescription":"Report: viii, 36 p., 1 Plate: 33.04 × 37.14 inches; Dataset; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-117784","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":501148,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115638.htm","linkFileType":{"id":5,"text":"html"}},{"id":423108,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235099/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5099 HTML"},{"id":422628,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sir/2023/5099/sir20235099_plate01.pdf","text":"Plate 1","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5099 Plate 1","linkHelpText":"—Raster Predictions of Specific Conductance at Groundwater Wells by Depth in the Mississippi Alluvial Plain Region"},{"id":422626,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WSE8JS","text":"USGS Data Release","linkHelpText":"Machine-learning model predictions and rasters of groundwater salinity in the Mississippi Alluvial Plain"},{"id":422623,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5099/Images"},{"id":422622,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5099/sir20235099.pdf","size":"31.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5099"},{"id":422621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5099/coverthb.jpg"},{"id":422624,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5099/sir20235099.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5099 XML"},{"id":422627,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS Dataset","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -92.8114869520446,\n              37.89139322749202\n            ],\n            [\n              -92.8114869520446,\n              28.689695810736353\n            ],\n            [\n              -87.62594007704502,\n              28.689695810736353\n            ],\n            [\n              -87.62594007704502,\n              37.89139322749202\n            ],\n            [\n              -92.8114869520446,\n              37.89139322749202\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a> <br>U.S. Geological Survey&nbsp;<br><span class=\"HQEo7\" role=\"link\" data-markjs=\"true\" data-mce-tabindex=\"0\">640 Grassmere Park, suite 100 <br>Nashville, TN 37211</span>&nbsp;</p><p><a data-mce-href=\"../\" href=\"../\"><span class=\"ContentPasted3\">Contact Pubs Warehouse</span></a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-11-17","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Killian, Courtney D. 0000-0002-2137-2722","orcid":"https://orcid.org/0000-0002-2137-2722","contributorId":213990,"corporation":false,"usgs":true,"family":"Killian","given":"Courtney","email":"","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888172,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250515,"text":"70250515 - 2023 - Less is more: Less herbicide does more when biological control is present in Pontederia crassipes","interactions":[],"lastModifiedDate":"2023-12-14T12:43:11.880092","indexId":"70250515","displayToPublicDate":"2023-11-17T06:42:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Less is more: Less herbicide does more when biological control is present in Pontederia crassipes","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara012\">An experiment along with simulation modeling was applied to study the combinations of herbicide treatment and biological control that best limit invasive water hyacinth (<i>Pontederia crassipes</i>, formerly<span>&nbsp;</span><i>Eichhornia crassipes</i>) in freshwater aquatic systems. The experiment consisted of 14 different treatments of<span>&nbsp;</span><i>P. crassipes</i><span>&nbsp;</span>in 1.67&nbsp;m<sup>2</sup><span>&nbsp;</span>outdoor tank mesocosms. Seven treatments were with and seven were without insect biological control agents,<span>&nbsp;</span><i>Neochetina eichhorniae</i>. In both of the sets of seven treatments, there was one no-herbicide treatment, a one-time full-strength herbicide treatment with 40&nbsp;%, 80&nbsp;% and 100&nbsp;% coverage of the<span>&nbsp;</span><i>P. crassipes</i>, and a one-time half-strength herbicide treatment with 40&nbsp;%, 80&nbsp;%, and 100&nbsp;% surface area coverage. An overarching hypothesis was that leaving part of a tank unsprayed, providing habitat for the maintenance of biological control agents, would optimize control. Data from the experiment, measured on five days over the 167-day period, were used to calibrate a difference equation model of<span>&nbsp;</span><i>P. crassipes</i><span>&nbsp;</span>with and without the biological control agent. The model was then used to project longer term dynamics of the system. The model predicted that an initial one-time herbicide treatment, combined with application of the biocontrol agent at 80&nbsp;% areal coverage, could maintain<span>&nbsp;</span><i>P. crassipes</i><span>&nbsp;</span>at levels lower than the carrying capacity of the plant's biomass over the long term, though not enough that<span>&nbsp;</span><i>N. eichhorniae</i><span>&nbsp;</span>would be considered, by itself, a highly effective control. However, the results suggest that a combination of biocontrol with 80&nbsp;% spraying coverage every 600 days or so would be an effective integrated biocontrol strategy for maintaining decreased<span>&nbsp;</span><i>P. crassipes</i><span>&nbsp;</span>biomass at low levels over the long term.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110566","usgsCitation":"Xu, L., Goode, A.B., Tipping, P.W., Smith, M.C., Gettys, L., Knowles, B.K., Pokorny, E., Salinas, L., and DeAngelis, D., 2023, Less is more: Less herbicide does more when biological control is present in Pontederia crassipes: Ecological Modelling, v. 487, 110566, 11 p., https://doi.org/10.1016/j.ecolmodel.2023.110566.","productDescription":"110566, 11 p.","ipdsId":"IP-149426","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2023.110566","text":"Publisher Index Page"},{"id":423572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"487","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Linhao","contributorId":221358,"corporation":false,"usgs":false,"family":"Xu","given":"Linhao","email":"","affiliations":[{"id":40353,"text":"Co-Innovation Center for Sustainable Forestry in Southern China, Jiangsu Province Key","active":true,"usgs":false}],"preferred":false,"id":890219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goode, Ashley B.C.","contributorId":332463,"corporation":false,"usgs":false,"family":"Goode","given":"Ashley","middleInitial":"B.C.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tipping, Philip W.","contributorId":332464,"corporation":false,"usgs":false,"family":"Tipping","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Melissa C.","contributorId":221360,"corporation":false,"usgs":false,"family":"Smith","given":"Melissa","email":"","middleInitial":"C.","affiliations":[{"id":40354,"text":"USDA-ARS Invasive Plant Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gettys, Lyn A.","contributorId":332465,"corporation":false,"usgs":false,"family":"Gettys","given":"Lyn A.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":890223,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowles, Brittany K.","contributorId":332466,"corporation":false,"usgs":false,"family":"Knowles","given":"Brittany","email":"","middleInitial":"K.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890224,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pokorny, Eileen","contributorId":332467,"corporation":false,"usgs":false,"family":"Pokorny","given":"Eileen","email":"","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890225,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salinas, Luz","contributorId":332468,"corporation":false,"usgs":false,"family":"Salinas","given":"Luz","email":"","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":890226,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeAngelis, Don 0000-0002-1570-4057","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":221357,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Don","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":890227,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250086,"text":"ofr20211030P - 2023 - System characterization report on the Pléiades Neo Imager","interactions":[{"subject":{"id":70250086,"text":"ofr20211030P - 2023 - System characterization report on the Pléiades Neo Imager","indexId":"ofr20211030P","publicationYear":"2023","noYear":false,"chapter":"P","displayTitle":"System Characterization Report on the Pléiades Neo Imager","title":"System characterization report on the Pléiades Neo Imager"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2024-06-17T19:42:45.516982","indexId":"ofr20211030P","displayToPublicDate":"2023-11-16T15:55:10","publicationYear":"2023","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":"2021-1030","chapter":"P","displayTitle":"System Characterization Report on the Pléiades Neo Imager","title":"System characterization report on the Pléiades Neo Imager","docAbstract":"<h1>Executive Summary</h1><p>This report addresses system characterization of the Pléiades Neo satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.</p><p>Pléiades Neo is a constellation of four identical very-high-resolution optical satellites operated by Airbus Defence and Space. The first two satellites, Pléiades Neo-3 and -4, were launched in April and August 2021, respectively. The next two satellites, launched in December 2022, did not reach orbit because of Vega-C launch vehicle failure. Pléiades Neo provides several technical improvements to previous Pléiades-HR satellites, including the addition of coastal aerosol (deep blue) and red edge spectral bands, with improved ground sample distance and swath. The Pléiades Neo satellites were designed and built by Airbus Defence and Space with the high-resolution, multispectral imager for Earth imaging and use the S950 optical satellite bus. The high-resolution sensor on Pléiades Neo collects Earth data in the visible and near-infrared region with six bands and a panchromatic band. The satellites can operate off nadir to achieve a revisit of less than 1 day. More information on Pléiades Neo satellites and sensors is available in the “Land Remote Sensing Satellites Online Compendium” (<a data-mce-href=\"https://calval.cr.usgs.gov/apps/compendium\" href=\"https://calval.cr.usgs.gov/apps/compendium\">https://calval.cr.usgs.gov/apps/compendium#</a>) and from the manufacturer (<a data-mce-href=\"https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/\" href=\"https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/\">https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/</a>).</p><p>The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Pléiades Neo has an interior geometric performance in the range of 0.01 meter (m; 0.008 pixel) to −0.017 m (−0.014 pixel) in band-to-band registration; an exterior geometric performance in the range of −7.015 m (−0.702 pixel) to 3.846 m (0.385 pixel) offset in comparison to Sentinel-2 using ground control points of 2.2 to 7.2 m (95-percent circular error); a radiometric performance in the range of −0.070 (minimum) to −0.053 (maximum) in offset and 1.107 (minimum) to 1.202 (maximum) in slope; and a spatial performance in the range of 1.002 to 1.226 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.22 to 0.34 (bands 2–7).</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System Characterization of Earth Observation Sensors","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030P","usgsCitation":"Cantrell, S.J., Sampath, A., Vrabel, J.C., Bresnahan, P., Anderson, C., Kim, M., and Park, S., 2023, System characterization report on the Pléiades Neo Imager (ver. 1.1, April 2024), chap. P <em>of</em> Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 52 p., https://doi.org/10.3133/ofr20211030P.","productDescription":"Report: vi, 52 p.; Version History","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-154436","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":422656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/p/coverthb2.jpg"},{"id":422657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/p/ofr20211030p.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–P"},{"id":422658,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/p/ofr20211030p.XML"},{"id":428107,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/p/versionHist.txt","text":"Version History","size":"1.99 kB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: November 16, 2023; Version 1.1: April 29, 2024","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>System Description</li><li>Procedures</li><li>Measurements</li><li>Analysis</li><li>Summary and Conclusions</li><li>Selected References</li><li>Appendix 1. Explanation of Ground Control Points Method and Metadata</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-11-16","revisedDate":"2024-04-29","noUsgsAuthors":false,"publicationDate":"2023-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Cantrell, Simon J. 0000-0001-6909-1973","orcid":"https://orcid.org/0000-0001-6909-1973","contributorId":259304,"corporation":false,"usgs":false,"family":"Cantrell","given":"Simon J.","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":888269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sampath, Aparajithan 0000-0002-6922-4913","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":222486,"corporation":false,"usgs":false,"family":"Sampath","given":"Aparajithan","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":888270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vrabel, James C. 0000-0002-0120-4721","orcid":"https://orcid.org/0000-0002-0120-4721","contributorId":264751,"corporation":false,"usgs":false,"family":"Vrabel","given":"James C.","affiliations":[{"id":27608,"text":"Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":888271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bresnahan, Paul 0000-0002-3491-0956","orcid":"https://orcid.org/0000-0002-3491-0956","contributorId":306120,"corporation":false,"usgs":false,"family":"Bresnahan","given":"Paul","affiliations":[{"id":27608,"text":"Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":888272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":888275,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kim, Minsu 0000-0003-4472-0926","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":297371,"corporation":false,"usgs":false,"family":"Kim","given":"Minsu","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":888273,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Park, Seonkyung 0000-0003-3203-1998 seonkyungpark@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":222488,"corporation":false,"usgs":false,"family":"Park","given":"Seonkyung","email":"seonkyungpark@contractor.usgs.gov","affiliations":[{"id":40547,"text":"United Support Services, Contractor to the USGS Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":888274,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250271,"text":"70250271 - 2023 - Investigating permafrost carbon dynamics in Alaska with artificial intelligence","interactions":[],"lastModifiedDate":"2023-11-30T13:12:50.071693","indexId":"70250271","displayToPublicDate":"2023-11-16T07:09:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Investigating permafrost carbon dynamics in Alaska with artificial intelligence","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integrates<span>&nbsp;</span><i>in-situ</i><span>&nbsp;</span>measurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO<sub>2</sub>), and methane flux (CH<sub>4</sub>)—with high precision and minimal loss (i.e. ALT<sup>RMSE</sup>: 1.327 cm [1969–2022]; CO<sub>2</sub><sup>RMSE</sup>: 0.697<span>&nbsp;</span><i>µ</i>molCO<sub>2</sub>m<sup>−2</sup>s<sup>−1</sup><span>&nbsp;</span>[2003–2021]; CH<sub>4</sub><sup>RMSE</sup>: 0.715 nmolCH<sub>4</sub>m<sup>−2</sup>s<sup>−1</sup><span>&nbsp;</span>[2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.</p></div>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ad0607","usgsCitation":"Gay, B., Pastick, N., Zufle, A., Armstrong, A., Miner, K., and Qu, J., 2023, Investigating permafrost carbon dynamics in Alaska with artificial intelligence: Environmental Research Letters, v. 18, no. 12, 125001, 20 p., https://doi.org/10.1088/1748-9326/ad0607.","productDescription":"125001, 20 p.","ipdsId":"IP-158731","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":441585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad0607","text":"Publisher Index Page"},{"id":423088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -157.71401031875757,\n              58.963334167122895\n            ],\n            [\n              -152.79213531875774,\n              62.03364889814105\n            ],\n            [\n              -147.07924469375772,\n              63.08656488912206\n            ],\n            [\n              -142.24526031875774,\n              62.44303153277835\n            ],\n            [\n              -141.01479156875783,\n              62.198069009088584\n            ],\n            [\n              -141.01479156875783,\n              66.69800816270453\n            ],\n            [\n              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0000-0002-4321-6739","orcid":"https://orcid.org/0000-0002-4321-6739","contributorId":222683,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":889235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zufle, Andreas 0000-0001-7001-4123","orcid":"https://orcid.org/0000-0001-7001-4123","contributorId":332011,"corporation":false,"usgs":false,"family":"Zufle","given":"Andreas","email":"","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":889236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Armstrong, Amanda 0000-0002-9123-8924","orcid":"https://orcid.org/0000-0002-9123-8924","contributorId":332012,"corporation":false,"usgs":false,"family":"Armstrong","given":"Amanda","email":"","affiliations":[{"id":40052,"text":"NASA Goddard","active":true,"usgs":false}],"preferred":false,"id":889237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miner, Kimberly 0000-0002-1006-1283","orcid":"https://orcid.org/0000-0002-1006-1283","contributorId":329027,"corporation":false,"usgs":false,"family":"Miner","given":"Kimberly","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":889238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qu, J.J.","contributorId":182468,"corporation":false,"usgs":false,"family":"Qu","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":889239,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250062,"text":"70250062 - 2023 - Editorial: Rapid, reproducible, and robust environmental modeling for decision support: worked examples and open-source software tools","interactions":[],"lastModifiedDate":"2023-11-16T12:36:06.571747","indexId":"70250062","displayToPublicDate":"2023-11-16T06:32:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Rapid, reproducible, and robust environmental modeling for decision support: worked examples and open-source software tools","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2023.1260581","usgsCitation":"White, J., Fienen, M., Moore, C.R., and Guthke, A., 2023, Editorial: Rapid, reproducible, and robust environmental modeling for decision support: worked examples and open-source software tools: Frontiers in Earth Science, v. 11, 1260581, 3 p., https://doi.org/10.3389/feart.2023.1260581.","productDescription":"1260581, 3 p.","ipdsId":"IP-155062","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":441587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1260581","text":"Publisher Index Page"},{"id":422650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Jeremy","contributorId":260166,"corporation":false,"usgs":false,"family":"White","given":"Jeremy","affiliations":[{"id":52529,"text":"Interra","active":true,"usgs":false}],"preferred":false,"id":888173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Catherine R.","contributorId":251908,"corporation":false,"usgs":false,"family":"Moore","given":"Catherine","email":"","middleInitial":"R.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":888175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guthke, Anneli","contributorId":331600,"corporation":false,"usgs":false,"family":"Guthke","given":"Anneli","email":"","affiliations":[{"id":79251,"text":"Stuttgart Center for Simulation Science, Cluster of Excellence","active":true,"usgs":false}],"preferred":false,"id":888176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250150,"text":"70250150 - 2023 - Environmental surveillance and detection of infectious highly pathogenic avian influenza virus in Iowa wetlands","interactions":[],"lastModifiedDate":"2023-12-21T14:51:14.281714","indexId":"70250150","displayToPublicDate":"2023-11-15T10:52:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"Environmental surveillance and detection of infectious highly pathogenic avian influenza virus in Iowa wetlands","docAbstract":"<p><span>Avian influenza viruses (AIVs) infect both wild birds and domestic poultry, resulting in economically costly outbreaks that have the potential to impact public health. Currently, a knowledge gap exists regarding the detection of infectious AIVs in the aquatic environment. In response to the 2021–2022 Eurasian strain highly pathogenic avian influenza (HPAI) A/goose/Guangdong/1/1996 clade 2.3.4.4 lineage H5 outbreak, an AIV environmental outbreak response study was conducted using a One Health approach. An optimized method was used to temporally sample (April and May 2022) and analyze (culture and molecular methods) surface water from five water bodies (four wetlands and one lake used as a comparison location) in areas near confirmed HPAI detections in wild bird or poultry operations. Avian influenza viruses were isolated from water samples collected in April from all four wetlands (not from the comparison lake sample); HPAI H5N1 was isolated from one wetland. No virus was isolated from the May samples. Several factors, including increased water temperatures, precipitation, biotic and abiotic factors, and absence of AIV-contaminated fecal material due to fewer waterfowl present, may have contributed to the lack of virus isolation from May samples. Results demonstrate surface water as a plausible medium for transmission of AIVs, including the HPAI virus.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.estlett.3c00668","usgsCitation":"Hubbard, L.E., Givens, C.E., Stelzer, E., Killian, M.L., Kolpin, D., Szablewski, C.M., and Poulson, R., 2023, Environmental surveillance and detection of infectious highly pathogenic avian influenza virus in Iowa wetlands: Environmental Science & Technology Letters, v. 10, no. 12, p. 1181-1187, https://doi.org/10.1021/acs.estlett.3c00668.","productDescription":"7 p.","startPage":"1181","endPage":"1187","ipdsId":"IP-152787","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":441589,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.estlett.3c00668","text":"Publisher Index Page"},{"id":435121,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y9EZI9","text":"USGS data release","linkHelpText":"Sampling information and water-quality data collected during viable avian influenza virus sampling in Iowa wetlands, 2022"},{"id":422842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70251362,"text":"70251362 - 2023 - Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.","interactions":[],"lastModifiedDate":"2024-02-07T13:11:58.68272","indexId":"70251362","displayToPublicDate":"2023-11-15T07:10:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17151,"text":"Journal of Geophysical Research: Biogeosciences.","active":true,"publicationSubtype":{"id":10}},"title":"Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.","docAbstract":"<p><span>Mountain headwater streams actively cycle carbon, receiving it from terrestrial landscapes and exporting it through downstream transport and gas exchange with the atmosphere. Although their importance is now widely recognized, aquatic carbon fluxes in headwater streams remain poorly characterized. In this study, aquatic carbon fluxes were measured in 15 mountain headwater streams and were used in a geostatistical analysis to determine how landscape characteristics influence aquatic carbon fluxes. In-stream sensors were used to measure fluorescent dissolved organic matter (fDOM) (a surrogate for dissolved organic carbon (DOC)) at a subset of sites to characterize dynamic responses to hydroclimatic events. Wetlands have a positive influence on aquatic carbon fluxes, whereas perennial snow/ice has the opposite effect, reflecting differences in soil organic matter content in these landscapes. Mean annual temperature (MAT) has a complex influence on DOC, with peak DOC exports in basins with MAT of 0–2°C. Precipitation has a strong positive influence on aquatic carbon fluxes, and declining snowpacks in the western United States may reduce future aquatic carbon exports. fDOM (and by implication DOC) and&nbsp;</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007538","usgsCitation":"Clow, D.W., Akie, G.A., Striegl, R.G., Penn, C., Sexstone, G., and Keith, G.L., 2023, Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.: Journal of Geophysical Research: Biogeosciences., v. 128, no. 11, e2023JG007538, 21 p., https://doi.org/10.1029/2023JG007538.","productDescription":"e2023JG007538, 21 p.","ipdsId":"IP-152741","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":441592,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jg007538","text":"Publisher Index Page"},{"id":425467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126.33671793374008,\n              50.04663794752611\n            ],\n            [\n              -126.33671793374008,\n              36.6265614981065\n            ],\n            [\n              -101.92206066401474,\n              36.6265614981065\n            ],\n            [\n              -101.92206066401474,\n              50.04663794752611\n            ],\n            [\n              -126.33671793374008,\n              50.04663794752611\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akie, Garrett Alexander 0000-0002-6356-7106","orcid":"https://orcid.org/0000-0002-6356-7106","contributorId":290236,"corporation":false,"usgs":true,"family":"Akie","given":"Garrett","email":"","middleInitial":"Alexander","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":894266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Penn, Colin 0000-0002-5195-2744","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":218031,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keith, Gabrielle L. 0000-0002-2304-8504 gkeith@usgs.gov","orcid":"https://orcid.org/0000-0002-2304-8504","contributorId":256699,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894269,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250424,"text":"70250424 - 2023 - Two new species of small-eared shrews of the Genus Cryptotis Pomel, 1848, from the Colombian Andes (Mammalia: Eulipotyphla: Soricidae)","interactions":[],"lastModifiedDate":"2023-12-08T13:01:01.009246","indexId":"70250424","displayToPublicDate":"2023-11-15T06:57:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17104,"text":"Annals of the Carnegie Museum","active":true,"publicationSubtype":{"id":10}},"title":"Two new species of small-eared shrews of the Genus Cryptotis Pomel, 1848, from the Colombian Andes (Mammalia: Eulipotyphla: Soricidae)","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">Shrews (Mammalia: Eulipotyphla: Soricidae) reach the southern limit of their New World distribution in the Andes and eastern coastal highlands of northern South America. South of Honduras, the family is represented only by species of the genus<span>&nbsp;</span><i>Cryptotis</i><span>&nbsp;</span>Pomel, 1848. In South America, soricids are restricted to moist, high-elevation environments above 1000 m, and their distribution appears to be discontinuous. Study of specimens from a previous gap in the known geographical range of shrews in the Central Cordillera of southwestern Colombia reveals the presence of two unique populations that are distinguishable from each other and their congeners by a combination of morphological and morphometrical characters. They are described herein as,<span>&nbsp;</span><strong><i>Cryptotis huttereri,</i><span>&nbsp;</span>n. sp.</strong><span>&nbsp;</span>and<span>&nbsp;</span><strong><i>Cryptotis andinus,</i><span>&nbsp;</span>n. sp.</strong><span>&nbsp;</span>Both species are members of the<span>&nbsp;</span><i>Cryptotis thomasi</i><span>&nbsp;</span>group, one of five species groups of small-eared shrews defined partly on the basis of postcranial morphology and potential locomotor behavior. Although species in the<span>&nbsp;</span><i>C. thomasi</i><span>&nbsp;</span>group share similar postcranial architecture, as exemplified by the morphology of the forelimb, the group appears to be polyphyletic, implying convergence in locomotor behavior, possibly one uniquely adapted for Andean-type montane habitats. Recognition of<span>&nbsp;</span><i>C. huttereri</i><span>&nbsp;</span>and<span>&nbsp;</span><i>C. andinus</i><span>&nbsp;</span>brings the total number of known South American soricids to 19 species, with 11 species occurring in Colombia. Of those, seven species are endemic to that country.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.2992/007.088.0303","usgsCitation":"Woodman, N., 2023, Two new species of small-eared shrews of the Genus Cryptotis Pomel, 1848, from the Colombian Andes (Mammalia: Eulipotyphla: Soricidae): Annals of the Carnegie Museum, v. 88, no. 3, p. 203-234, https://doi.org/10.2992/007.088.0303.","productDescription":"32 p.","startPage":"203","endPage":"234","ipdsId":"IP-156848","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":423324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Columbia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.77051137686733,\n              -0.34366101536659244\n            ],\n            [\n              -68.8173863768678,\n              -0.34366101536659244\n            ],\n            [\n              -68.8173863768678,\n              8.11055906521743\n            ],\n            [\n              -80.77051137686733,\n              8.11055906521743\n            ],\n            [\n              -80.77051137686733,\n              -0.34366101536659244\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"88","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889875,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70262408,"text":"70262408 - 2023 - Marshbird response to herbicide control of cattail in northwestern Minnesota","interactions":[],"lastModifiedDate":"2025-01-21T15:55:36.155755","indexId":"70262408","displayToPublicDate":"2023-11-15T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16872,"text":"The Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Marshbird response to herbicide control of cattail in northwestern Minnesota","docAbstract":"<p><span>Wetlands provide essential habitat for a wide variety of wildlife species. In the once wetland-rich Prairie Pothole Region and adjacent areas of central North America, many wetlands have been converted to agricultural production. Many remaining wetlands experience ecological change via the invasion and spread of non-native plant species, such as non-native narrowleaf (</span><i>Typha angustifolia</i><span>) and hybrid cattail (</span><i>Typha</i><span>&nbsp;x&nbsp;</span><i>glauca</i><span>), which spread aggressively and displace native vegetation, especially in large, impounded wetlands. Management of wetlands in these landscapes often includes broad-scale herbicide application intended to break up mats of cattail and restore areas to more wildlife-friendly conditions. Although restoration of wildlife habitat is a common goal of such management, marshbird response to invasive cattail control is poorly understood. To evaluate the effects of cattail management on wetland wildlife, we conducted standardized call-broadcast surveys for 5 species of marshbirds at 9 study sites that included survey locations associated with areas treated with herbicide and paired areas not treated with herbicide in wetland impoundments in northwestern Minnesota, USA, using a before-after, control-impact study design. We surveyed American bitterns (</span><i>Botaurus lentiginosus</i><span>), least bitterns (</span><i>Ixobrychus exilis</i><span>), pied-billed grebes (</span><i>Podilymbus podiceps</i><span>), soras (</span><i>Porzana carolina</i><span>), and Virginia rails (</span><i>Rallus limicola</i><span>) during the breeding season prior to herbicide application (late summer and early autumn of 2015) and during the 3 breeding seasons after herbicide application (2016–2018). We modeled species counts using a generalized linear mixed model with year-by-treatment interactions as fixed effects and site as a random effect. Before herbicide application, expected mean counts did not differ between treatment and control survey locations. Three years post-treatment, we detected significant increases in expected mean counts at treatment compared to control survey locations for soras (</span><i>t</i><sub>193</sub><span> = −3.373,&nbsp;</span><i>P</i><span> = 0.020) and Virginia rails (</span><i>t</i><sub>193</sub><span> = −3.167,&nbsp;</span><i>P</i><span> = 0.037), and point estimates for all species except least bittern were higher at treatment survey locations. Overall, our results suggest that these marshbird species responded positively to herbicide control of invasive cattail and that breeding marshbirds in these and similar wetland systems may experience positive population response over a period of at least 3 years following treatment.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22484","usgsCitation":"Hill, N., Johnson, D., Cooper, T., Archer, A., and Andersen, D.E., 2023, Marshbird response to herbicide control of cattail in northwestern Minnesota: The Journal of Wildlife Management, v. 87, no. 8, e22484, 14 p., https://doi.org/10.1002/jwmg.22484.","productDescription":"e22484, 14 p.","ipdsId":"IP-131062","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22484","text":"Publisher Index Page"},{"id":480825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.2253684104991,\n              49.07382900749482\n            ],\n            [\n              -97.2253684104991,\n              47.098948093042196\n            ],\n            [\n              -95.09634908157517,\n              47.098948093042196\n            ],\n            [\n              -95.09634908157517,\n              49.07382900749482\n            ],\n            [\n              -97.2253684104991,\n              49.07382900749482\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hill, Nina M.","contributorId":349191,"corporation":false,"usgs":false,"family":"Hill","given":"Nina M.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":924132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":220516,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":924133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Thomas R.","contributorId":349193,"corporation":false,"usgs":false,"family":"Cooper","given":"Thomas R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":924134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Althea A.","contributorId":349197,"corporation":false,"usgs":false,"family":"Archer","given":"Althea A.","affiliations":[{"id":83459,"text":"St. Cloud University","active":true,"usgs":false}],"preferred":false,"id":924135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924136,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70249869,"text":"sir20235116 - 2023 - Assessment of post-wildfire geomorphic change in the North Fork Eagle Creek stream channel, New Mexico, 2017–21","interactions":[],"lastModifiedDate":"2026-03-13T15:35:00.059451","indexId":"sir20235116","displayToPublicDate":"2023-11-14T13:43:28","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5116","displayTitle":"Assessment of Post-Wildfire Geomorphic Change in the North Fork Eagle Creek Stream Channel, New Mexico, 2017–21","title":"Assessment of post-wildfire geomorphic change in the North Fork Eagle Creek stream channel, New Mexico, 2017–21","docAbstract":"<p>The 2012 Little Bear Fire caused substantial vegetation loss in the Eagle Creek Basin of south-central New Mexico. This loss was expected to alter the localized hydrologic response to precipitation by creating conditions that amplify surface runoff, which might alter the geomorphology of North Fork Eagle Creek, a major tributary to Eagle Creek. To monitor short-term geomorphic change, annual geomorphic surveys of North Fork Eagle Creek were conducted from 2017 to 2021. The surveys measured 14 cross sections, stream gradients, woody debris accumulations, and pools found within the study reach. During the 2017–21 study period, the study reach experienced multiple high-flow events that resulted from both monsoonal rainfall and snowmelt runoff. Comparisons of the cross-section and channel profile data for the repeat geomorphic surveys indicate localized erosion and deposition occurred as a result of the high-flow events but overall study reach geomorphology shower little change through the study period. Additionally, the number of woody debris accumulations and pools increased during the study period. Evidence from the 5-year geomorphic survey indicates that the North Fork Eagle Creek’s geomorphology did not change substantially during the study period. Wildfire severity and frequency within mountainous regions of the Southwest are projected to increase and their effect on fluvial systems remains uncertain; however, continued geomorphic studies can provide informative insight on watershed post-wildfire resiliency and recovery by establishing baselines that can be used in the event of a future severe wildfire within the Eagle Creek Basin.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235116","issn":"2328-0328","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Nichols, J.R., Chavarria, S.B., and Graziano, A.P., 2023, Assessment of post-wildfire geomorphic change in the North Fork Eagle Creek stream channel, New Mexico, 2017–21: U.S. Geological Survey Scientific Investigations Report 2023–5116, 48 p., https://doi.org/10.3133/sir20235116.","productDescription":"Report: vi, 48 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-145308","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":501156,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115637.htm","linkFileType":{"id":5,"text":"html"}},{"id":422345,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94ZQHKU","text":"USGS data release","linkHelpText":"Data supporting the 2018 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":422344,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7TX3","text":"USGS data release","linkHelpText":"Data supporting the 2017 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":422346,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97ALYNZ","text":"USGS data release","linkHelpText":"Data supporting the 2019 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":422347,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BGPRN9","text":"USGS data release","linkHelpText":"Data supporting the 2020 and 2021 geomorphic surveys of North Fork Eagle Creek, New Mexico"},{"id":422340,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5116/sir20235116.pdf","size":"7.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5116 pdf"},{"id":422341,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235116/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5116 HTML"},{"id":422338,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5116/coverthb.jpg"},{"id":422339,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5116/images"},{"id":422342,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5116/sir20235116.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5116 XML"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek Stream Channel","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.5,\n              33.4\n            ],\n            [\n              -105.5,\n              33.00\n            ],\n            [\n              -105.1,\n              33.0\n            ],\n            [\n              -105.1,\n              33.4\n            ],\n            [\n              -105.5,\n              33.4\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a> <br>U.S. Geological Survey&nbsp;<br><span class=\"HQEo7\" role=\"link\" data-markjs=\"true\" data-mce-tabindex=\"0\">6700 Edith Blvd. NE <br>Albuquerque, NM 87113</span>&nbsp;</p><p><a data-mce-href=\"../\" href=\"../\"><span class=\"ContentPasted3\">Contact Pubs Warehouse</span></a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods </li><li>Results </li><li>Geomorphic Survey of North Fork Eagle Creek From 2017 to 2021 </li><li>Discussion </li><li>Summary </li><li>Acknowledgments </li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-11-14","noUsgsAuthors":false,"publicationDate":"2023-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols, Justin R. 0000-0003-0846-6430 jrnichols@usgs.gov","orcid":"https://orcid.org/0000-0003-0846-6430","contributorId":331348,"corporation":false,"usgs":true,"family":"Nichols","given":"Justin","email":"jrnichols@usgs.gov","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chavarria, Shaleene B. 0000-0001-8792-1010","orcid":"https://orcid.org/0000-0001-8792-1010","contributorId":223376,"corporation":false,"usgs":true,"family":"Chavarria","given":"Shaleene","email":"","middleInitial":"B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graziano, Alexander P. 0000-0003-1978-0986","orcid":"https://orcid.org/0000-0003-1978-0986","contributorId":211607,"corporation":false,"usgs":true,"family":"Graziano","given":"Alexander","email":"","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":887468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250126,"text":"70250126 - 2023 - Biological responses of Pacific herring embryos to crude oil are quantifiable at exposure levels below conventional limits of quantitation for PAHs in water and tissues","interactions":[],"lastModifiedDate":"2023-12-21T14:48:24.642867","indexId":"70250126","displayToPublicDate":"2023-11-14T10:07:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Biological responses of Pacific herring embryos to crude oil are quantifiable at exposure levels below conventional limits of quantitation for PAHs in water and tissues","docAbstract":"<p><span>Pacific herring (</span><i>Clupea pallasii</i><span>), a cornerstone of marine food webs, generally spawn on marine macroalgae in shallow nearshore areas that are disproportionately at risk from oil spills. Herring embryos are also highly susceptible to toxicity from chemicals leaching from oil stranded in intertidal and subtidal zones. The water-soluble components of crude oil trigger an adverse outcome pathway that involves disruption of the physiological functions of cardiomyocytes in the embryonic herring heart. In previous studies, impaired ionoregulation (calcium and potassium cycling) in response to specific polycyclic aromatic hydrocarbons (PAHs) corresponds to lethal embryolarval heart failure or subtle chamber malformations at the high and low ends of the PAH exposure range, respectively. Sublethal cardiotoxicity, which involves an abnormal outgrowth (ballooning) of the cardiac ventricular chamber soon after hatching, subsequently compromises juvenile heart structure and function, leading to pathological hypertrophy of the ventricle and reduced individual fitness, measured as cardiorespiratory performance. Previous studies have not established a threshold for these sublethal and delayed-in-time effects, even with total (∑)PAH exposures as low as 29 ng/g of wet weight (tissue dose). Here, we extend these earlier findings showing that (1)&nbsp;</span><i>cyp1a</i><span>&nbsp;gene expression provides an oil exposure metric that is more sensitive than typical quantitation of PAHs via GC–MS and (2) heart morphometrics in herring embryos provide a similarly sensitive measure of toxic response. Early life stage injury to herring (impaired heart development) thus occurs below the quantitation limits for PAHs in both water and embryonic tissues as a conventional basis for assessing oil-induced losses to coastal marine ecosystems.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.3c04122","usgsCitation":"Incardona, J.P., Linbo, T.L., Cameron, J.R., French, B.L., Bolton, J.L., Gregg, J.L., Donald, C.E., Hershberger, P., and Scholz, N.L., 2023, Biological responses of Pacific herring embryos to crude oil are quantifiable at exposure levels below conventional limits of quantitation for PAHs in water and tissues: Environmental Science and Technology, v. 57, no. 48, p. 19214-19222, https://doi.org/10.1021/acs.est.3c04122.","productDescription":"9 p.","startPage":"19214","endPage":"19222","ipdsId":"IP-154190","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":441596,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/11250/3111017","text":"Publisher Index Page"},{"id":422839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"48","noUsgsAuthors":false,"publicationDate":"2023-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Incardona, John P.","contributorId":331691,"corporation":false,"usgs":false,"family":"Incardona","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":79266,"text":"Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA USA.","active":true,"usgs":false}],"preferred":false,"id":888485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linbo, Tiffany L.","contributorId":192166,"corporation":false,"usgs":false,"family":"Linbo","given":"Tiffany","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":888486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cameron, James R.","contributorId":331692,"corporation":false,"usgs":false,"family":"Cameron","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":79267,"text":"Ocean Associates, Inc., under contract to Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA USA.","active":true,"usgs":false}],"preferred":false,"id":888487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"French, Barbara L.","contributorId":331693,"corporation":false,"usgs":false,"family":"French","given":"Barbara","email":"","middleInitial":"L.","affiliations":[{"id":79266,"text":"Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA USA.","active":true,"usgs":false}],"preferred":false,"id":888488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bolton, Jennie L.","contributorId":331694,"corporation":false,"usgs":false,"family":"Bolton","given":"Jennie","email":"","middleInitial":"L.","affiliations":[{"id":79266,"text":"Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA USA.","active":true,"usgs":false}],"preferred":false,"id":888489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donald, Carey E.","contributorId":331695,"corporation":false,"usgs":false,"family":"Donald","given":"Carey","email":"","middleInitial":"E.","affiliations":[{"id":79268,"text":"Institute of Marine Research, Bergen, Norway","active":true,"usgs":false}],"preferred":false,"id":888491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":888492,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scholz, Nathaniel L.","contributorId":331696,"corporation":false,"usgs":false,"family":"Scholz","given":"Nathaniel","email":"","middleInitial":"L.","affiliations":[{"id":79266,"text":"Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA USA.","active":true,"usgs":false}],"preferred":false,"id":888493,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250954,"text":"70250954 - 2023 - A global ecological signal of extinction risk in marine ray-finned fishes (class Actinopterygii)","interactions":[],"lastModifiedDate":"2024-01-13T14:54:49.450263","indexId":"70250954","displayToPublicDate":"2023-11-14T08:52:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17122,"text":"Cambridge Prisms: Extinction","active":true,"publicationSubtype":{"id":10}},"title":"A global ecological signal of extinction risk in marine ray-finned fishes (class Actinopterygii)","docAbstract":"<div class=\"abstract-content\"><div class=\"abstract\" data-abstract-type=\"normal\"><p>Many marine fish species are experiencing population declines, but their extinction risk profiles are largely understudied in comparison to their terrestrial vertebrate counterparts. Selective extinction of marine fish species may result in rapid alteration of the structure and function of ocean ecosystems. In this study, we compiled an ecological trait dataset for 8,185 species of marine ray-finned fishes (class Actinopterygii) from FishBase and used phylogenetic generalized linear models to examine which ecological traits are associated with increased extinction risk, based on the International Union for the Conservation of Nature Red List. We also assessed which threat types may be driving these species toward greater extinction risk and whether threatened species face a greater average number of threat types than non-threatened species. We found that larger body size and/or fishes with life histories involving movement between marine, brackish, and freshwater environments are associated with elevated extinction risk. Commercial harvesting threatens the greatest number of species, followed by pollution, development, and then climate change. We also found that threatened species, on average, face a significantly greater number of threat types than non-threatened species. These results can be used by resource managers to help address the heightened extinction risk patterns we found.</p></div></div>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/ext.2023.23.pr1","usgsCitation":"Bak, T.M., Camp, R.J., Heim, N.A., McCauley, D., Payne, J.L., and Knope, M.L., 2023, A global ecological signal of extinction risk in marine ray-finned fishes (class Actinopterygii): Cambridge Prisms: Extinction, v. 1, e25, 12 p., https://doi.org/10.1017/ext.2023.23.pr1.","productDescription":"e25, 12 p.","ipdsId":"IP-145291","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":441599,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/ext.2023.23.pr1","text":"Publisher Index Page"},{"id":424416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bak, Trevor M.","contributorId":317824,"corporation":false,"usgs":false,"family":"Bak","given":"Trevor","email":"","middleInitial":"M.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":892400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":892401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heim, Noel A. 0000-0002-4528-345X","orcid":"https://orcid.org/0000-0002-4528-345X","contributorId":333307,"corporation":false,"usgs":false,"family":"Heim","given":"Noel","email":"","middleInitial":"A.","affiliations":[{"id":79842,"text":"Department of Earth & Ocean Sciences, Tufts University","active":true,"usgs":false}],"preferred":false,"id":892402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCauley, Douglas J.","contributorId":287056,"corporation":false,"usgs":false,"family":"McCauley","given":"Douglas J.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":892403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Payne, Jonathan L. 0000-0002-9601-3310","orcid":"https://orcid.org/0000-0002-9601-3310","contributorId":333308,"corporation":false,"usgs":false,"family":"Payne","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":64472,"text":"Department of Geological Sciences, Stanford University","active":true,"usgs":false}],"preferred":false,"id":892404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knope, Matthew L 0000-0002-1372-6308","orcid":"https://orcid.org/0000-0002-1372-6308","contributorId":333309,"corporation":false,"usgs":false,"family":"Knope","given":"Matthew","email":"","middleInitial":"L","affiliations":[{"id":37485,"text":"University of Hawai‘i - Hilo","active":true,"usgs":false}],"preferred":false,"id":892405,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250252,"text":"70250252 - 2023 - Assessing the ecological risk of heavy metal sediment contamination from Port Everglades Florida USA","interactions":[],"lastModifiedDate":"2023-11-30T13:03:24.940594","indexId":"70250252","displayToPublicDate":"2023-11-14T06:57:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the ecological risk of heavy metal sediment contamination from Port Everglades Florida USA","docAbstract":"<div class=\"abstract\"><p>Port sediments are often contaminated with metals and organic compounds from anthropogenic sources. Remobilization of sediment during a planned expansion of Port Everglades near Fort Lauderdale, Florida (USA) has the potential to harm adjacent benthic communities, including coral reefs. Twelve sediment cores were collected from four Port Everglades sites and a control site; surface sediment was collected at two nearby coral reef sites. Sediment cores, sampled every 5 cm, were analyzed for 14 heavy metals using inductively coupled plasma-mass spectrometry. Results for all three locations yielded concentration ranges (µg/g): As (0.607–223), Cd (n/d–0.916), Cr (0.155–56.8), Co (0.0238–7.40), Cu (0.004–215), Pb (0.0169–73.8), Mn (1.61–204), Hg (n/d–0.736), Mn (1.61–204), Ni (0.232–29.3), Se (n/d–4.79), Sn (n/d–140), V (0.160–176), and Zn (0.112–603), where n/d = non-detected. The geo-accumulation index shows moderate-to-strong contamination of As and Mo in port sediments, and potential ecological risk indicates moderate-to-significantly high overall metal contamination. All four port sites have sediment core subsamples with As concentrations above both threshold effect level (TEL, 7.24 µg/g) and probable effect level (PEL, 41.6 µg/g), while Mo geometric mean concentrations exceed the background continental crust level (1.5 µg/g) threshold. Control site sediments exceed TEL for As, while the reef sites has low to no overall heavy metal contamination. Results of this study indicate there is a moderate to high overall ecological risk from remobilized sediment due to metal contamination. Due to an imminent dredging at Port Everglades, this could have the potential to harm the threatened adjacent coral communities and surrounding protected habitats.</p></div>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.16152","usgsCitation":"Giarikos, D.G., White, L., Daniels, A., Santos, R.G., Baldauf, P.E., and Hirons, A.C., 2023, Assessing the ecological risk of heavy metal sediment contamination from Port Everglades Florida USA: PeerJ, v. 11, 35 p., https://doi.org/10.7717/peerj.16152.","productDescription":"35 p.","ipdsId":"IP-157548","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441601,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.16152","text":"Publisher Index Page"},{"id":423086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Port Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.15552129212654,\n              26.104742380968872\n            ],\n            [\n              -80.15552129212654,\n              25.999255489563083\n            ],\n            [\n              -80.08685639930893,\n              25.999255489563083\n            ],\n            [\n              -80.08685639930893,\n              26.104742380968872\n            ],\n            [\n              -80.15552129212654,\n              26.104742380968872\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Giarikos, Dimitrios G.","contributorId":331918,"corporation":false,"usgs":false,"family":"Giarikos","given":"Dimitrios","email":"","middleInitial":"G.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Laura","contributorId":331919,"corporation":false,"usgs":false,"family":"White","given":"Laura","email":"","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889106,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniels, Andre 0000-0003-4172-2344","orcid":"https://orcid.org/0000-0003-4172-2344","contributorId":204035,"corporation":false,"usgs":true,"family":"Daniels","given":"Andre","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889107,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Santos, Radleigh G.","contributorId":331920,"corporation":false,"usgs":false,"family":"Santos","given":"Radleigh","email":"","middleInitial":"G.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889108,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldauf, Paul E.","contributorId":331923,"corporation":false,"usgs":false,"family":"Baldauf","given":"Paul","email":"","middleInitial":"E.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hirons, Amy C.","contributorId":331925,"corporation":false,"usgs":false,"family":"Hirons","given":"Amy","email":"","middleInitial":"C.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889110,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250121,"text":"70250121 - 2023 - Data mining reveals tissue-specific expression and host lineage-associated forms of Apis mellifera filamentous virus","interactions":[],"lastModifiedDate":"2023-11-21T12:54:38.707121","indexId":"70250121","displayToPublicDate":"2023-11-14T06:53:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Data mining reveals tissue-specific expression and host lineage-associated forms of Apis mellifera filamentous virus","docAbstract":"<p>Apis mellifera filamentous virus (AmFV) is a large double-stranded DNA virus of uncertain phylogenetic position that infects honey bees (<i>Apis mellifera</i>). Little is known about AmFV evolution or molecular aspects of infection. Accurate annotation of open-reading frames (ORFs) is challenged by weak homology to other known viruses. This study was undertaken to evaluate ORFs (including coding-frame conservation, codon bias, and purifying selection), quantify genetic variation within AmFV, identify host characteristics that covary with infection rate, and examine viral expression patterns in different tissues.</p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.16455","usgsCitation":"Cornman, R.S., 2023, Data mining reveals tissue-specific expression and host lineage-associated forms of Apis mellifera filamentous virus: PeerJ, https://doi.org/10.7717/peerj.16455.","ipdsId":"IP-154830","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":441603,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.16455","text":"Publisher Index Page"},{"id":435122,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XT6GBE","text":"USGS data release","linkHelpText":"Occurrences of Apis mellifera filamentous virus (AmFV) sequences in public accessions of Apis mellifera and Varroa destructor"},{"id":422779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":888468,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}