Science has played a mixed role in guiding conservation and sustainability-oriented decision-making by individuals, policymakers, institutions, and governments. Not all science-based conservation and sustainability initiatives that address issues facing humanity and ecosystems and global problems have gained public support. Conservation decisions and policy prescriptions are and may be based on perceptions about and experiences with the environment, local land use, and ecosystems that may not align with or be grounded in science or evidence from experts in the field. Values, beliefs, and perceptions associated with nature play a critical role in how individuals view biodiversity conservation, sustainability, and natural resource management. This study first examines the gap between experts (scientists and other field experts) and the public (farmers and non-farmers) about the state of water and land resources, wildlife and associated habitats, and aquatic biodiversity in the Smoky Hill River Watershed in western Kansas. Second, the study examines the role that values and beliefs play in shaping environmental perceptions for farmers and non-farmers. Analysis confirms that a gap between experts and farmers/non-farmers does exist, especially with respect to the state of the Ogallala Aquifer, playas, rivers and streams, lakes and reservoirs, native grasslands, wildlife habitats, farmland, native fish populations, and wildlife species. Ordered-logistic regression analyses, meanwhile, indicate that farmer and non-farmer perceptions about the state of the local environment are influenced by traditional and self-interested values, as well as environmental values and beliefs, but less so by religiosity and political ideology. Despite broad takeaways, results exhibited heterogeneity across the farmer and non-farmer subpopulations. If environmental professionals cannot align ecological data, stakeholders’ values/perceptions, and policies, then the existing body of technical research and management on sustainability in natural and social sciences may be of little value.
Marbled murrelets (Brachyramphus marmoratus) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet federal- and state-mandated recovery efforts for this species. During June–August 2020 and 2021, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–present), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). The abundance estimated for the entire study area was 470 birds (95-percent confidence interval, 313–707 birds) in 2020 and 402 birds (95-percent confidence interval, 219–737 birds) in 2021. Estimated abundances for both years are comparable with most prior years of study. We estimated reproductive productivity (calculated as the hatch-year to after-hatch-year ratio) after date-correcting hatch-year and after-hatch-year counts to account for birds expected to be absent from the water while inland at nests. The date-corrected juvenile ratio was 0.018±0.011 standard error in 2020 and 0.041±0.024 standard error in 2021. We updated a comprehensive database of all Zone 6 marbled murrelet survey data since 1999 with 2020–21 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1157","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Felis, J.J., Adams, J., Horton, C.A., Kelsey, E.C., and White, L.M., 2022, Abundance and productivity of Marbled Murrelets (Brachyramphus marmoratus) off central California during the 2020 and 2021 breeding seasons: U.S. Geological Survey Data Report 1157, 12 p., https://doi.org/10.3133/dr1157.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-134849","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":400463,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.pdf","text":"Report","size":"6 MB"},{"id":400464,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1157/images"},{"id":400465,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.xml"},{"id":400466,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","text":"Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021","description":"Felis, J.J., Adams, J., Peery, M.Z., Henry, R.W., Henkel, L.A., Becker, B.H., and Halbert, P., 2022, Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021: U.S. Geological Survey data release, https://doi.org/10.5066/F75B01RW."},{"id":400473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1157/covrthb.jpg"},{"id":400472,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1157/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1157"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.59918212890626,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
A cooperative study led by the U.S. Geological Survey and Wake County Environmental Services was initiated to characterize the fractured-rock aquifer system and assess the sustainability of groundwater resources in and around Wake County. This report contributes to the development of a comprehensive groundwater budget for the study area, thereby helping to enable resource managers to make sound and sustainable water-supply and water-use decisions.
Construction information was used to analyze the well depth, casing depth, and reported well yield of more than 7,500 inventoried wells. The median well depth and casing depth were 265 feet (ft) below land surface (bls) and 68 ft bls, respectively, and the median well yield was 10 gallons per minute. Generally, well yield increased with depth to around 200 ft bls and then began to decrease with depth within the fractured-rock aquifer.
Borehole geophysical logging methods were used to characterize the fractured-rock aquifer by mapping the orientation of geologic structures within the subsurface. Structure measurements were made on resulting log data and mapped to observed general spatial trends within the regional groundwater system and more distinct hydrogeologic units. Many of the fractures observed within the borehole logs are steeply dipping across Wake County, although open fractures with shallow dip angles were also observed in most rock classes. Regional geologic structural trends were observed in proximity to the Jonesboro Fault.
Potential groundwater recharge in the study area was estimated using a Soil-Water-Balance (SWB) model, as well as using base flow hydrograph separation. The SWB model calculated net infiltration below the root zone for 1981 through 2019 for a 5,402-square-mile area that extends to the counties surrounding Wake County. The mean annual net infiltration rate for the 39-year period was about 8.6 inches per year for the study area. The mean annual net infiltration results from the SWB model were comparable to annual base flow estimates using the PART hydrograph-separation method at six U.S. Geological Survey streamgages within the study area. Mean annual base flow for all six drainage basins was near 7.5 inches per year and estimates ranged from 2.9 to 8.9 inches. Comparisons of mean annual potential recharge from the SWB model and base flow estimates were generally within 2 inches, except during high flows for most of the drainage basins in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225041","collaboration":"Prepared in cooperation with Wake County Environmental Services","usgsCitation":"Antolino, D.J., and Gurley, L.N., 2022, Assessment of well yield, dominant fractures, and groundwater recharge in Wake County, North Carolina (ver. 1.1, May 2022) : U.S. Geological Survey Scientific Investigations Report 2022–5041, 35 p., https://doi.org/10.3133/sir20225041.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Database","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115494","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":435852,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MO793B","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model data sets for the Greater Wake County area, North Carolina, 1981 - 2070"},{"id":399579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95XKK5V","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model datasets for the Greater Wake County area, North Carolina, 1981–2019"},{"id":399580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HHBIE","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2016 products (ver. 2.0, July 2020)"},{"id":399576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5041"},{"id":399577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.XML"},{"id":399582,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":399596,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225041/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":399575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5041/coverthb2.jpg"},{"id":399578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5041/images/"},{"id":399581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2J23X","text":"USGS data release","linkHelpText":"Groundwater well yield in Wake County, North Carolina"},{"id":502396,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112959.htm","linkFileType":{"id":5,"text":"html"}},{"id":400310,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5041/versionHist.txt","size":"508 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","edition":"Version 1.1: May 2022; Version 1.0: April 2022","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Norcross, GA 30093
Renewable energy production, mostly via wind, solar, and biofuels, is central to goals worldwide to reduce carbon emissions and mitigate anthropogenic climate change (IPCC, 2014; Pörtner et al., 2021). Nevertheless, adverse impacts to natural systems, especially fatalities of wildlife and alteration of habitat, are key challenges for renewable energy production (Allison et al., 2019; Katzner et al., 2019).
Because of the magnitude of these challenges, extensive effort has been invested in surveys and science to understand the environmental effects of renewable energy on species and systems. Nevertheless, these impacts have not been formally compared relative to counterfactual conditions (Bull et al., 2021; Coetzee and Gaston, 2021), i.e., those occurring in the absence of renewable energy. As such, cumulative ecological impact assessments required by many regulating agencies typically only consider the adverse impacts of renewables, without evaluating whether mitigative effects of current and planned build-out (e.g., Larson et al., 2020) will offset their adverse impacts to species and natural systems (Allison et al., 2014). Accordingly, these critical decision processes have an insufficient perspective to foster fully informed decisions, and, for some species or systems, renewable energy could lead to more profound impacts than those it is intended to prevent. Furthermore, because of this approach and, despite the well-studied benefits to society of renewable energy development (IPCC, 2014), the ecological value of renewable energy is often premised on the plausible but untested assumption that its negative effects to natural populations and systems are less consequential than the negative effects in alternative scenarios with less renewable energy and greater climate change.
A more comprehensive framing of the counterfactual in cumulative ecological impact assessments would evaluate, for each species or system, the incremental effects of renewables over their full life cycle against the incremental effects they provide by mitigating climate change. This framing is important because a given species or system may see net positive or net negative effects from either renewables or climate change. Furthermore, cumulative impact assessments could identify optimized tradeoffs that balance, for each species or system, the effects of both climate change and renewable energy.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2022.844286","usgsCitation":"Katzner, T., Allison, T.D., Diffendorfer, J.E., Hale, A., Lantz, E.J., and Veers, P., 2022, Counterfactuals to assess effects to species and systems from renewable energy development: Frontiers in Conservation Science, v. 3, 844286, 4 p., https://doi.org/10.3389/fcosc.2022.844286.","productDescription":"844286, 4 p.","ipdsId":"IP-131158","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2022.844286","text":"Publisher Index Page"},{"id":417251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2022-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":873250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allison, Taber D","contributorId":223428,"corporation":false,"usgs":false,"family":"Allison","given":"Taber","email":"","middleInitial":"D","affiliations":[{"id":39329,"text":"American Wind Wildlife Institute","active":true,"usgs":false}],"preferred":false,"id":873251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":873252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hale, Amanda","contributorId":219856,"corporation":false,"usgs":false,"family":"Hale","given":"Amanda","email":"","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":873253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lantz, Eric J.","contributorId":305585,"corporation":false,"usgs":false,"family":"Lantz","given":"Eric","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":873254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Veers, Paul","contributorId":305586,"corporation":false,"usgs":false,"family":"Veers","given":"Paul","email":"","affiliations":[],"preferred":false,"id":873255,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70231918,"text":"70231918 - 2022 - Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system","interactions":[],"lastModifiedDate":"2022-06-03T13:42:47.59382","indexId":"70231918","displayToPublicDate":"2022-05-10T08:42:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system","docAbstract":"Radium (Ra) is a geogenic radioactive contaminant that frequently occurs at elevated levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS). Geochemical indicators (e.g., redox conditions or total dissolved solids) can broadly characterize conditions associated with elevated Ra levels in groundwater, but do not consistently correlate to elevated Ra within specific stratigraphic horizons. A coupled geochemical and isotopic study of groundwater and aquifer solids for major and trace elements, Ra, and uranium (U) at discrete intervals in the MCOAS was used to elucidate processes that may be responsible for this disconnect, via analysis of groundwater as well as extracted and digested solid aquifer samples. We find that the potential for Ra mobilization varies by stratigraphic unit, as observed by whole-rock 226Ra/238U (dis)equilibrium. Overall, the examined aqueous geochemical characteristics (e.g., redox conditions, total dissolved solids) do not explain Ra concentrations within the system, suggesting that alternative factors, like solid-phase associations or the extent of alpha recoil damage, may be more important. A relation between aqueous 87Sr/86Sr and 226Ra suggests that minerals with radiogenic 87Sr/86Sr are more likely to release 226Ra to the aqueous system. Overall, the release of U and Ra due to water-rock interaction varies with discrete stratigraphy, depending on aqueous geochemistry and available mineral associations. Due to complex Ra-rock interactions and the heterogeneous geology of the MCOAS, aqueous geochemistry does not fully predict the mobilization and concentration of Ra in groundwater. As sources and sinks of Ra within the MCOAS vary across stratigraphy, knowledge of aqueous geochemistry, available solid-phase associations, and nuclide leachability all are important to consider for understanding elevated Ra occurrence in aquifer systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2022.105300","usgsCitation":"Mathews, M.J., Scott, S.R., Gotkowitz, M.B., Hunt, R., and Ginder-Vogel, M., 2022, Isotopic analysis of radium geochemistry at discrete intervals in the Midwestern Cambrian-Ordovician aquifer system: Applied Geochemistry, v. 142, 105300, 11 p., https://doi.org/10.1016/j.apgeochem.2022.105300.","productDescription":"105300, 11 p.","ipdsId":"IP-135098","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":401679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.1865234375,\n 46.057985244793024\n ],\n [\n -92.30712890625,\n 46.042735653846506\n ],\n [\n -92.7685546875,\n 45.90529985724799\n ],\n [\n -92.8564453125,\n 45.5679096098613\n ],\n [\n -92.6806640625,\n 45.42929873257377\n ],\n [\n -92.79052734375,\n 44.793530904744074\n ],\n [\n -92.471923828125,\n 44.5435052132082\n ],\n [\n -91.9720458984375,\n 44.35527821160296\n ],\n [\n -91.702880859375,\n 44.09547572946637\n ],\n [\n -91.2689208984375,\n 43.88205730390537\n ],\n [\n -91.263427734375,\n 43.51270490464819\n ],\n [\n -91.2139892578125,\n 43.38508989465156\n ],\n [\n -91.07666015625,\n 43.28920196020127\n ],\n [\n -91.1700439453125,\n 43.137069765760344\n ],\n [\n -91.1590576171875,\n 42.92827401776912\n ],\n [\n -91.01074218749999,\n 42.69858589169842\n ],\n [\n -90.71411132812499,\n 42.64608143458068\n ],\n [\n -90.615234375,\n 42.500453028125584\n ],\n [\n -87.7972412109375,\n 42.48830197960227\n ],\n [\n -87.7532958984375,\n 42.75104599038353\n ],\n [\n -87.8631591796875,\n 43.04079076668198\n ],\n [\n -87.8631591796875,\n 43.32118142926661\n ],\n [\n -87.66540527343749,\n 43.79885402720353\n ],\n [\n -87.5006103515625,\n 44.19402066387343\n ],\n [\n -86.7864990234375,\n 45.463983441272724\n ],\n [\n -86.99523925781249,\n 45.413876460821086\n ],\n [\n -87.967529296875,\n 44.55524925971063\n ],\n [\n -88.04443359375,\n 44.59829048984011\n ],\n [\n -87.6434326171875,\n 44.99588261816546\n ],\n [\n -87.6214599609375,\n 45.10066901851988\n ],\n [\n -87.7313232421875,\n 45.21687321093267\n ],\n [\n -87.6104736328125,\n 45.40616374516014\n ],\n [\n -87.8631591796875,\n 45.36372498305678\n ],\n [\n -87.7972412109375,\n 45.625563438215984\n ],\n [\n -88.6981201171875,\n 44.465151013519616\n ],\n [\n -90.4779052734375,\n 45.556371735883125\n ],\n [\n -91.1865234375,\n 46.057985244793024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"142","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathews, Madeleine J","contributorId":292236,"corporation":false,"usgs":false,"family":"Mathews","given":"Madeleine","email":"","middleInitial":"J","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":844116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Sean R","contributorId":292237,"corporation":false,"usgs":false,"family":"Scott","given":"Sean","email":"","middleInitial":"R","affiliations":[{"id":17815,"text":"Wisconsin State Laboratory of Hygiene","active":true,"usgs":false}],"preferred":false,"id":844117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gotkowitz, Madeline B","contributorId":292239,"corporation":false,"usgs":false,"family":"Gotkowitz","given":"Madeline","email":"","middleInitial":"B","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":844118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ginder-Vogel, Matthew","contributorId":176769,"corporation":false,"usgs":false,"family":"Ginder-Vogel","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":844120,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248943,"text":"70248943 - 2022 - Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","interactions":[],"lastModifiedDate":"2023-09-27T12:16:30.658314","indexId":"70248943","displayToPublicDate":"2022-05-10T07:13:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","docAbstract":"The late Holocene Bonneville landslide, a 15.5 km2 rockslide-debris avalanche, descended 1000 m from the north side of the Columbia River Gorge and dammed the Columbia River where it bisects the Cascade Range of Oregon and Washington, USA. The landslide, inundation, and overtopping created persistent geomorphic, ecologic, and cultural consequences to the river corridor, reported by Indigenous narratives and explorer accounts, as well as scientists and engineers. From new dendrochronology and radiocarbon dating of three trees killed by the landslide, one entrained and buried by the landslide and two killed by rising water in the impounded Columbia River upstream of the blockage, we find (1) the two drowned trees and the buried tree died the same year, and (2) the age of tree death, and hence the landslide (determined by combined results of nine radiocarbon analyses of samples from the three trees), falls within AD 1421–1455 (3σ confidence interval). This result provides temporal context for the tremendous physical, ecological, and cultural effects of the landslide, as well as possible triggering mechanisms. The age precludes the last Cascadia Subduction Zone earthquake of AD 1700 as a landslide trigger, but not earlier subduction zone or local crustal earthquakes.
Sirenian social and reproductive behaviors lack much complexity or diversity. Whereas sirenians are usually sighted as solitary, or as cows with single calves, aggregations of many individuals can occur. Persistent social groupings are unknown. Home ranges are widely overlapping. Mating systems of dugongs (Dugong dugon) have been variously described as leks or as scramble promiscuity (mating herds ) and lone mating pairs have been observed in areas of low density, but further research into the hypothesized leks is needed (especially because scramble promiscuity has been observed in the same region). Dugongs and all manatees (Trichechus) show scramble promiscuity, wherein males form groups that escort single females with much physical contact for many days. The strongest social bonds are between females and nursing calves. Florida manatees (Trichechus manatus latirostris) show natal philopatry for years after weaning. Socially transmitted knowledge (tradition) appears important to Florida manatees and perhaps all species of sirenians, particularly in regions where seasonal movements during winter are necessary for survival, such as in winter for Florida manatees, and dugongs at the high latitude limits of their range. Some populations of Antillean, Amazonian, and African manatees have regular movements in response to seasonal flooding and access to food, which also may be learned through tradition . Dugongs may rely on group movements based on traditional knowledge in response to regional loss of food supply from extreme weather events. Communication is most obvious through vocalizations, which can show individual distinctiveness. Vocal communication is most prevalent between mothers and calves. Allomaternal care occurs in Florida manatees at shared aggregation sites. Florida manatees occupying a given region can consist of multiple matrilines that develop through the early bonding of calves to mothers and subsequent natal philopatry. Population genetics research supports male-biased dispersal and possible female-based philopatry in other trichechids, but perhaps not as strongly in dugongids. Considerable further research is needed on these and related topics to more comprehensively understand sirenian social and reproductive behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ethology and Behavioral Ecology of Sirenia","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-90742-6_4","usgsCitation":"O'Shea, T., Beck, C., Hodgson, A.J., Keith-Diagne, L., and Marmontel, M., 2022, Social and reproductive behaviors, chap. 4 of Ethology and Behavioral Ecology of Sirenia, p. 101-154, https://doi.org/10.1007/978-3-030-90742-6_4.","productDescription":"54 .","startPage":"101","endPage":"154","ipdsId":"IP-109802","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447848,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-030-90742-6_4","text":"Publisher Index Page"},{"id":400856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Shea, Thomas J.","contributorId":291933,"corporation":false,"usgs":false,"family":"O'Shea","given":"Thomas J.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":843410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Cathy 0000-0002-5388-5418 cbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-5418","contributorId":168987,"corporation":false,"usgs":true,"family":"Beck","given":"Cathy","email":"cbeck@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":843411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodgson, Amanda J.","contributorId":291934,"corporation":false,"usgs":false,"family":"Hodgson","given":"Amanda","email":"","middleInitial":"J.","affiliations":[{"id":62787,"text":"Aquatic Megafauna Research Unit, Murdoch University, Western Australia","active":true,"usgs":false}],"preferred":false,"id":843412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith-Diagne, Lucy W","contributorId":261440,"corporation":false,"usgs":false,"family":"Keith-Diagne","given":"Lucy W","affiliations":[{"id":36882,"text":"African Aquatic Conservation Fund","active":true,"usgs":false}],"preferred":false,"id":843413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marmontel, Miriam","contributorId":291935,"corporation":false,"usgs":false,"family":"Marmontel","given":"Miriam","affiliations":[{"id":62788,"text":"Mamiraua Institute for Sustainable Development, Amazonia, Brazil","active":true,"usgs":false}],"preferred":false,"id":843414,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231552,"text":"70231552 - 2022 - A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages","interactions":[],"lastModifiedDate":"2022-06-01T15:35:32.750509","indexId":"70231552","displayToPublicDate":"2022-05-10T06:39:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"A new indicator approach to reconstruct agricultural land use in Europe from sedimentary pollen assemblages","docAbstract":"The reconstruction of human impact is pivotal in palaeoecological studies, as humans are among the most important drivers of Holocene vegetation and ecosystem change. Nevertheless, separating the anthropogenic footprint on vegetation dynamics from the impact of climate and other environmental factors (disturbances such as fire, erosion, floods, landslides, avalanches, volcanic eruptions) is a challenging and still largely open issue. For this purpose, palynologists mostly rely on cultural indicator pollen types and related indices that consist of sums or ratios of these pollen types. However, the high environmental and biogeographical specificity of cultural indicator plants hinders the application of the currently available indices to wide geographical settings. Furthermore, the achievable taxonomic resolution of cultural indicator pollen types may hamper their indicative capacity. In this study, we propose the agricultural land use probability (LUP) index, a novel approach to quantify human impact intensity on European ecosystems based on cultural indicator pollen types. From the ‘classic’ cultural indicators, we construct the LUP index by selecting those with the best indicator capacity based on bioindication criteria. We first train the LUP index using twenty palynological sequences along a broad environmental gradient, spanning from treeless alpine to subtropical mediterranean evergreen plant communities. We then validate the LUP index using independent pollen datasets and archaeological proxies. Finally, we discuss the suitability of the selected pollen types and the potential of the LUP index for quantifying Holocene human impact in Europe, concluding that careful application of the LUP index may significantly contribute to refining pollen-based land-use reconstructions.
Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.
Debris flows pose a significant hazard to communities in mountainous areas, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. In certain situations, such as scenarios following wildfire, where there could be an abrupt increase in the likelihood and size of debris flows that necessitates a rapid hazard assessment, the computational demands of inundation models play a role in their utility. The inability to efficiently determine the downstream effects of anticipated debris-flow events remains a critical gap in our ability to understand, mitigate, and assess debris-flow hazards. To better understand the downstream effects of debris flows, we introduce a computationally efficient, reduced-complexity inundation model, which we refer to as the Progressive Debris-Flow routing and inundation model (ProDF). We calibrate ProDF against mapped inundation from five watersheds near Montecito, CA, that produced debris flows shortly after the 2017 Thomas Fire. ProDF reproduced 70% of mapped deposits across a 40 km2 study area. While this study focuses on a series of post-wildfire debris flows, ProDF is not limited to simulating debris-flow inundation following wildfire and could be applied to any scenario where it is possible to estimate a debris-flow volume. However, given its ability to reproduce mapped debris-flow deposits downstream of the 2017 Thomas Fire burn scar, and the modest run time associated with a simulation over this 40 km2 study area, results suggest ProDF may be particularly promising for post-wildfire hazard assessment applications.
An accretionary tectonic model for the Mesoproterozoic ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin is presented. The tectonic model incorporates key observations about the nature and timing of Mesoproterozoic deposition, magmatism, regional metamorphism, and deformation across the 5000-km-long southern Laurentian margin. This time period was one of transition in the supercontinent cycle and occurred between the breakup of Columbia and the formation of Rodinia, and the southern Laurentian margin was a significant component of a much greater accretionary margin extending into Baltica and Amazonia and possibly parts of Antarctica and Australia. However, fundamental questions and contradictions remain in our understanding of the tectonic evolution of Laurentia and paleogeography during this time interval.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Laurentia: Turning points in the evolution of a continent","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.1220(08)","usgsCitation":"Daniel, C.G., Aronoff, R., Indares, A., and Jones, J.V., 2022, Laurentia in transition during the Mesoproterozoic: Observations and speculation on the ca. 1500–1340 Ma tectonic evolution of the southern Laurentian margin, chap. of Laurentia: Turning points in the evolution of a continent, https://doi.org/10.1130/2022.1220(08).","ipdsId":"IP-134080","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":400620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Daniel, Christopher G.","contributorId":195246,"corporation":false,"usgs":false,"family":"Daniel","given":"Christopher","email":"","middleInitial":"G.","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":843031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronoff, Ruth 0000-0001-5320-6596","orcid":"https://orcid.org/0000-0001-5320-6596","contributorId":291773,"corporation":false,"usgs":false,"family":"Aronoff","given":"Ruth","email":"","affiliations":[{"id":62750,"text":"Furman University","active":true,"usgs":false}],"preferred":false,"id":843032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Indares, Aphrodite 0000-0002-9604-079X","orcid":"https://orcid.org/0000-0002-9604-079X","contributorId":291774,"corporation":false,"usgs":false,"family":"Indares","given":"Aphrodite","email":"","affiliations":[{"id":62751,"text":"Memorial University Newfoundland","active":true,"usgs":false}],"preferred":false,"id":843033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":843034,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70234285,"text":"70234285 - 2022 - Water-use data in the United States: Challenges and future directions","interactions":[],"lastModifiedDate":"2022-08-08T11:38:57.659502","indexId":"70234285","displayToPublicDate":"2022-05-10T06:32:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Water-use data in the United States: Challenges and future directions","docAbstract":"In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data.
Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Streams in the Loup River Basin are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water. The U.S. Geological Survey, in cooperation with the Upper Loup and Lower Loup Natural Resources Districts, and the Nebraska Environmental Trust, studied the age and water-quality characteristics of groundwater near the South Loup River to assess the possible effects of a multiyear drought on streamflow.
Groundwater sampled in wells screened in Quaternary-age deposits displayed a wide range of mean ages (27 to 2,100 years), fraction modern, and susceptibility index values. Groundwater with higher concentrations of chloride and higher specific conductance was indicative of younger groundwater with a narrower age distribution and is more sensitive to climatic disturbances such as short-term drought conditions, based on the calculated susceptibility index. Groundwater samples from wells and springs in Pliocene-age deposits were categorized into two groups with different geochemical and age characteristics. One sample group of springs and wells, called the Western Pliocene, had higher concentrations of chloride and nitrate with young mean ages (18 to 77 years) and narrow age distributions. Groundwater in the Western Pliocene sample group is susceptible to short-term drought. In contrast, the other sample group from Pliocene-age deposits to the east (called Pliocene) had lower concentrations of nitrate, chloride, and mean groundwater ages ranging from 1,900 to 2,900 years old and is less likely to be affected by short-term drought conditions. Groundwater sampled from three wells screened in the Ogallala Formation was shown to have the oldest mean ages ranging from 8,700 to 23,000 years and the lowest calculated susceptibility index values observed in this study. Strong upward hydraulic gradients measured in wells indicated that groundwater from the Ogallala Formation is likely contributing to streamflow of the South Loup River.
Continuously measured gage height and specific conductance data indicated groundwater discharge from Quaternary-age deposits was highly responsive to precipitation events. In contrast, groundwater discharge from Pliocene-age deposits (Pliocene sample group) was far less responsive, indicating groundwater discharge from Pliocene-age deposits is likely more resilient to short-term drought conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225042","collaboration":"Prepared in cooperation with the Upper Loup and Lower Loup Natural Resources Districts and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., and Solder, J.E., 2022, Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5042, 57 p., https://doi.org/10.3133/sir20225042.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-129114","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":400241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5042"},{"id":502397,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112991.htm","linkFileType":{"id":5,"text":"html"}},{"id":400244,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6B4XE","text":"USGS data release","linkHelpText":"Lumped parameter models of groundwater age, South Loup River, Nebraska"},{"id":400243,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5042/images"},{"id":400242,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.XML"},{"id":400333,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5042/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.8599853515625,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 41.075210270566636\n ],\n [\n -98.5089111328125,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 42.07376224008719\n ],\n [\n -100.8599853515625,\n 41.075210270566636\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
A study was conducted to compile and evaluate data used to identify groundwater sources that are under the direct influence of surface water (GUDI) in Pennsylvania. In the early 1990s, the Pennsylvania Department of Environmental Protection (PADEP) implemented the Surface Water Identification Protocol (SWIP) for the identification of GUDI sources. Since the establishment of the SWIP, PADEP has classified more than 500 individual sources across Pennsylvania as GUDI, but Pennsylvania’s complex geology and physiography provide a challenge for a uniform method of GUDI determination. Components used in this study to compile and evaluate data associated with GUDI determination include: (1) a preliminary review of file information for 43 public water-supply wells, (2) quality control and addition of data to PADEP’s database for public water-supply systems to prepare data for analysis, and (3) exploratory evaluation of existing GUDI sources in the database with respect to hydrogeologic and source-construction characteristics that are currently utilized in the assessment methodology.
Case files for 43 wells from PADEP’s Northcentral and Southcentral regions were reviewed to: (1) provide a better understanding of how the SWIP was applied in practice, (2) verify and compile missing data, and (3) find additional attributes not previously available that might explain a well’s categorization as GUDI. Review of file information showed that the SWIP outlined in PADEP technical guidance was usually followed, but for some sources, the GUDI determination was more complex and could not be easily summarized.
Data compiled for study analyses provided by PADEP include source data derived from public water-supply system case files, a source-information database for public water-supply systems, and Microscopic Particulate Analysis (MPA) results and associated water-quality data for public water-supply system groundwater sources. Data from the Pennsylvania Drinking Water Information System (PADWIS), which is PADEP’s database for public water-supply systems, were also used for this study. The PADWIS database originally included data for 12,147 groundwater sources (11,812 groundwater sources not under the direct influence of surface water (non-GUDI) wells and 335 GUDI wells). A subset (4,018 wells consisting of 3,842 non-GUDI wells and 175 GUDI wells) of the PADWIS database was created for an analysis and includes only community wells evaluated in accordance with the SWIP. MPA results for 631 community and noncommunity wells were compiled, along with associated water-quality data (alkalinity, chloride, Escherichia coli, fecal coliform, nitrate, pH, sodium, specific conductance, sulfate, total coliform, total dissolved solids, total residue, and turbidity) populated from the PADEP Bureau of Laboratories Sample Information System. Data compiled from sources other than PADEP include spatial data, both naturogenic (for example, average precipitation or distance to closest hydrologic feature) and anthropogenic (for example, percentage of developed or agricultural land cover within a specific vicinity of a public water-supply system well) data representing spatially derived variables.
Comparison among wells in the PADWIS dataset subset using the nonparametric Kruskal-Wallis test showed that GUDI wells had significantly older median construction years, shallower depths, and static water levels closer to the land surface than non-GUDI wells and that carbonate aquifers had the highest percentages of wells designated as GUDI (12 percent; 57 wells). Further comparison of wells in the PADWIS database subset using the Spearman’s rho monotonic correlation test illustrated that public water-supply wells designated as GUDI largely occur in unconfined aquifers and have high average yield and shallow static water levels. Assessment of the MPA database subset using the Kruskal-Wallis test showed wells with MPA total risk-factor scores that exceeded zero had older median construction years and shallower casing depths than wells with MPA total risk-factor scores of zero and that carbonate aquifers had the highest percentages of wells with MPA total risk-factor scores exceeding zero (30 percent; 63 wells). Spearman’s rho correlations showed that wells completed in aquifers with depths to major water-bearing zones closer to the land-surface had higher total risk-factor scores resulting from MPA samples.
Based on the results of the analyses described in this report, broad conclusions can be drawn regarding site-specific well characteristics as well as anthropogenic and naturogenic factors that could be responsible for a well being designated as GUDI, but the accuracy of these results is dependent on the quality of the data being analyzed. Ultimately, study results serve as an added resource for initial desktop screening of wells to determine if additional site-specific investigation is warranted and underscore the need for field evaluation.
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\"}}]}","edition":"Version 1.0: May 2022; Version 2.0: June 2023","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Although declines in grassland birds have been documented, national initiatives to conserve grasslands and their biota have fallen short in part because the non-market values of natural ecosystems and species are often not recognized in political decision making. Identifying shared, anthropogenic threats faced by market-valued and non-market-valued species may generate additional support for grassland conservation. We quantify the relationship between the market value of grasslands to commercial beekeepers and the importance of grasslands for birds of conservation concern in North and South Dakota. Our models estimated beekeeping annual revenue increased by $7525 USD and grassland bird abundances increased 2 to 7% per 10-km2 increase in grassland area. We estimated grassland conversion from 2006 to 2012 resulted in a $2.0 to $2.8 M USD decrease in annual revenue for beekeepers in the Dakotas. Through this study we demonstrate both the market value of grasslands to commercial beekeepers and the non-market benefits of grasslands in supporting migratory birds and discuss the implications of future land-use change. As grassland conversion and subsequent biodiversity loss continue, understanding the co-benefits of grassland conservation may be necessary to illuminate their contributions to society.
The U.S. Geological Survey (USGS) maintains an archive of 189,180 digitized scans of analog seismic records from the World‐Wide Standardized Seismograph Network (WWSSN). Although these scans have been made public, the archive is too large to manually review, and few researchers have utilized large numbers of these records. To facilitate further research using this historical dataset, we develop a simple convolutional neural network (CNN) that rapidly (∼4.75 s/film chip) classifies scanned film chip images (called “chips,” because they are individually cut segments of 70 mm film) into four categories of “interestingness” to earthquake seismologists based on the presence of earthquakes and other seismic signals in the record: “no interest,” “little interest,” “interest,” and “high interest.” The CNN, dubbed “Seismic Analog Record Network” (SARNet), can identify four types of seismic traces (“no events,” “minor events,” “major events,” and “errors”) in 200 × 200 pixel subcrops with an accuracy of 92% using a confidence threshold of 85%. SARNet then converts 100 random subcrops from each film chip into the overall classification of interestingness. In this task, SARNet performed as well as expert human classifiers in determining the film chip’s overall interest grade. Applying SARNet to 34,000 film chips in the WWSSN archive found that 21% of the images were of “high interest” and had an “indeterminate” rate of only 4%. Thus, the need for the manual review of images was reduced by 79%. Sorting of film chips derived from SARNet will expedite further exploration of the archive of digitized analog seismic records stored at the USGS.
Many species around the world are declining precipitously as a result of multiple threats and changing climate. Managers tasked with protecting species often face difficult decisions in regard to identifying which threats should be addressed, given limited resources and uncertainty in the success of any identified management action. On Kaua‘i Island, Hawai‘i, USA, forest bird species have experienced accelerated declines over the last 20 years, and 2 species, the ‘akikiki (Oreomystis bairdi) and ‘akeke‘e (Loxops caeruleirostris), are now at the brink of extinction. Both species face multiple threats, and managers face difficult decisions on whether to mitigate threats in the wild, establish a captive population as insurance against extinction, translocate birds to novel locations, or some combination of these actions. Each set of actions (alternatives) would require substantial resources with considerable uncertainty in success. In 2014, we brought together 14 experts representing biologists and managers familiar with the species and island to develop a conservation strategy under a structured decision making (SDM) framework, an approach for making complex decisions under uncertainty. The group's challenge was to identify a set of alternatives that reduces the risk of extinction, set the foundation for one or more genetically viable, reproducing, stable to increasing populations in 10 years, and promote conditions for long-term persistence in the wild. Multiple alternatives were evaluated, via expert judgement, in terms of the probability they would achieve the objectives concerning immediate extinction risk, near-term viability, and adequacy of habitat. Factors that might impede the success of each action were also evaluated. The process identified the establishment of a captive population and efforts to stabilize the existing wild population as the approach most likely to meet the objectives of preventing imminent extinction and ensuring long-term viability.
Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (Tympanuchus phasianellus: 9 exposed, 18 unexposed and greater prairie chickens (T. cupido; 11, 11). Exposure to crop production had greater effect on microbiota richness (t = 6.675, P < 0.001) and composition (PERMANOVA r2 = 0.212, P = 0.001) than did the host species (t = 4.762, P < 0.001; r2 = 0.070, P = 0.001) or their interaction (t = 3.449; r2 = 0.072, both P = 0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (T. cupido chao1 = 152.8 ± 20.5; T. phasianellus 115.3 ± 17.1) than in unexposed (102.9 ± 15.1 and 101.1 ± 17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean ± standard deviation; T. cupido 24.8 ± 10.0 and 10.1 ± 5.5, respectively; T. phasianellus 13.4 ± 6.8/4.9 ± 2.8) and resistome (T. cupido 46.8 ± 11.7/28.9 ± 10.2, T. phasianellus 38.3 ± 16.7/18.9 ± 14.2) than unexposed birds (T. cupido virulome: 14.2 ± 13.5, 4.5 ± 4.2; T. cupido resistome: 31.6 ± 20.2 and 13.1 ± 12.0; T. phasianellus virulome: 5.2 ± 4.7 and 1.4 ± 1.5; T. phasianellus resistome: 13.7 ± 16.1 and 4.0 ± 6.4).
This study examined the association of air, land, and water variables with the first historical occurrence and current distribution of toxic Prymnesium parvum blooms in reservoirs of the Brazos River and Colorado River, Texas (USA). One impacted and one reference reservoir were selected per basin. Land cover and use variables were estimated for the whole watershed (WW) and a 0.5-km zone on either side of streams (near field, NF). Variables were expressed in annual values. Principal component and trend analyses were used to determine (1) differences in environmental conditions before and after the 2001 onset of toxic blooms in impacted reservoirs (study period, 1992–2017), and (2) traits that uniquely discriminate impacted from reference reservoirs (2001–2017). Of thirty-three variables examined, two positively aligned with the reoccurring appearance of blooms in impacted reservoirs (air CO2 and herbicide Glyphosate) and another two negatively aligned (insecticides Terbufos and Malathion). Glyphosate use was observed throughout the study period but a turning point for an upward trend occurred near the year of first bloom occurrence. While the relevance of the decreased use of insecticides is uncertain, prior experimental studies reported that increasing concentrations of air CO2 and water Glyphosate can enhance P. parvum growth. Consistent with prior findings, impacted reservoirs were of higher salinity than reference reservoirs. In addition, their watersheds had far lower wetland cover at NF and WW scales. The value of wetlands in reducing harmful algal bloom incidence by reducing nutrient inputs has been previously recognized, but wetlands can also capture pesticides. Therefore, a diminished wetland cover could magnify Glyphosate loads flowing into impacted reservoirs. These observations are consistent with a scenario where rising levels of air CO2 and Glyphosate use contributed to the establishment of P. parvum blooms in reservoirs of relatively high salinity and minimal wetland cover over their watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.155567","usgsCitation":"Tabora-Sarmientoa, S., Patino, R., Portillo-Quintero, C., and Coldren, C., 2022, Air, land, and water variables associated with the first appearance and current spatial distribution of toxic Prymnesium parvum blooms in reservoirs of the Southern Great Plains, USA: Science of the Total Environment, v. 836, 155567, 11 p., https://doi.org/10.1016/j.scitotenv.2022.155567.","productDescription":"155567, 11 p.","ipdsId":"IP-135673","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.79055428065931,\n 33.96150939341686\n ],\n [\n -102.79055428065931,\n 30.40651030229435\n ],\n [\n -95.3521242635305,\n 30.40651030229435\n ],\n [\n -95.3521242635305,\n 33.96150939341686\n ],\n [\n -102.79055428065931,\n 33.96150939341686\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"836","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tabora-Sarmientoa, Shisbeth","contributorId":341529,"corporation":false,"usgs":false,"family":"Tabora-Sarmientoa","given":"Shisbeth","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Portillo-Quintero, Carlos","contributorId":341530,"corporation":false,"usgs":false,"family":"Portillo-Quintero","given":"Carlos","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coldren, Cade","contributorId":341531,"corporation":false,"usgs":false,"family":"Coldren","given":"Cade","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908568,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237696,"text":"70237696 - 2022 - The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","interactions":[],"lastModifiedDate":"2022-10-19T12:09:20.689887","indexId":"70237696","displayToPublicDate":"2022-05-07T07:03:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3275,"text":"Review of Palaeobotany and Palynology","active":true,"publicationSubtype":{"id":10}},"title":"The effect of diagenesis and acetolysis on the preservation of morphology and ultrastructural features of pollen","docAbstract":"Pollen morphology on its own and in conjunction with other characteristics has elucidated the origin and evolution of various plant groups. Previous studies of fossil pollen rarely discuss the effects of diagenesis and sample preparation on pollen characteristics, i.e., variability in staining, pollen morphology, and pollen wall ultrastructural characteristics. This paper examines the effect of acetolysis on reflectance and spectral epi-fluorescence measurements. Based on empirical studies, different species under similar experimental conditions display different reflectance values, indicating individual species respond differently to similar post-depositional thermal events. The quantitative pollen fluorescence spectra showed significant variability, but there is an overall increase in the mean wavelength of maximum emission with acetolysis. Increases in these spectral parameters are used to infer thermal maturation and diagenetic pathways in fossil pollen. The paper also discusses observations made on fossil pollen of a known thermal maturity using Pearson's Pollen/Spore Color Standard. Assessment of pollen thermal maturity using this color standard can be an indicator of the quality of morphological and ultrastructural information that can be extracted from fossil pollen. Increasing thermal maturity of pollen may have an effect on staining variability. Based on observations, staining for brightfield or electron microscopy in fossil pollen, although useful for improving contrast in the specimen, must be used with caution when interpreting pollen wall structure. Although single fossil pollen investigations are useful, replication of these studies on similar or the same specimens from the same locality or various localities will collectively provide more information for elucidation of the morphology and ultrastructure of the once living pollen, and is helpful in sorting out characteristics that may be artifacts from post-depositional diagenesis.
A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.
","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13206","usgsCitation":"Shapiro, A.M., Day-Lewis, F., Kappel, W.M., and Williams, J., 2022, Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration: Groundwater, v. 60, no. 6, p. 721-746, https://doi.org/10.1111/gwat.13206.","productDescription":"26 p.","startPage":"721","endPage":"746","ipdsId":"IP-130903","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":447877,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13206","text":"Publisher Index Page"},{"id":435854,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MRGR88","text":"USGS data release","linkHelpText":"Algorithms for model parameter estimation and state estimation applied to a state-space model for one-dimensional vertical infiltration incorporating snowmelt rate as a system input"},{"id":400497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":842636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":842637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231264,"text":"dr1156 - 2022 - U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","interactions":[],"lastModifiedDate":"2026-03-18T19:28:05.893773","indexId":"dr1156","displayToPublicDate":"2022-05-06T11:45:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1156","displayTitle":"U.S. Geological Survey National Shoreline Change— Summary Statistics for Updated Vector Shorelines (1800s–2010s) and Associated Shoreline Change Data for the Georgia and Florida Coasts","title":"U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts","docAbstract":"Rates of shoreline change have been updated for the open-ocean sandy coastlines of Georgia and Florida as part of the U.S. Geological Survey’s Coastal Change Hazards programmatic focus. This work was formerly within the National Assessment of Shoreline Change project. Shorelines were compiled from the original report published in 2005, recent update reports, and additional light detection and ranging (lidar) shorelines which were extracted from lidar data collected prior to and following Hurricane Irma, which made landfall in September 2017. These shorelines were used to compute long- and short-term rates that incorporate the proxy-datum bias on a transect-by-transect basis. The proxy-datum bias accounts for the unidirectional onshore bias of proxy-based high water line shorelines relative to datum-based mean high water shorelines. In this study, the coast of Georgia exhibited the highest average rates of erosion and accretion in both the long term (approximately 150 years) and the short term (approximately 30 years). Shoreline positions from the mid-1800s through 2018 were used to update the shoreline change rates for Florida and Georgia using the Digital Shoreline Analysis System (DSAS) software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1156","usgsCitation":"Kratzmann, M.G., 2022, U.S. Geological Survey national shoreline change— Summary statistics for updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida coasts: U.S. Geological Survey Data Report 1156, 8 p., https://doi.org/10.3133/dr1156.","productDescription":"Report: vi, 8 p.; Data Release","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132897","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400139,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.XML"},{"id":400294,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/dr1156/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1156"},{"id":400136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J3CVN4","text":"USGS data release","linkHelpText":"USGS national shoreline change—A GIS compilation of updated vector shorelines (1800s–2010s) and associated shoreline change data for the Georgia and Florida Coasts"},{"id":400134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1156/coverthb.jpg"},{"id":400135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1156/dr1156.pdf","text":"Report","size":"1.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1156"},{"id":400138,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1156/images/"},{"id":501269,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112990.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.71484375,\n 24.287026865376436\n ],\n [\n -78.486328125,\n 24.287026865376436\n ],\n [\n -78.486328125,\n 32.69486597787505\n ],\n [\n -87.71484375,\n 32.69486597787505\n ],\n [\n -87.71484375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598