Fossils in the order Sirenia (family Dugongidae) from Santa Rosa Island, part of Channel Islands National Park in southern California, provide rare temporal and spatial links between earlier and later evolutionary forms of dugongids, and add information about their dispersal into the northeastern Pacific region. Marine sedimentary rocks containing these fossils have characteristics of both the late Oligocene to middle Miocene Vaqueros Sandstone and the early to middle Miocene Rincon formation observed elsewhere. To determine a more precise age of the fossils, marine invertebrate shells were collected from the same exposures as the sirenian fossils for chronostratigraphic assessment using strontium isotope compositions and the well-calibrated seawater strontium evolution curve. Shells used for analysis were from bivalve mollusks (Pycnodonte sp. [oyster] and Lyropecten sp. [scallop]) and crustaceans (Balanus sp. [barnacle]). Results show a wide range of 87Sr/86Sr values, indicating that shell materials experienced varying degrees of diagenetic alteration. Strontium concentrations and 87Sr/86Sr values in subsamples of Pycnodonte shell show correlations between original shell material and a secondary component having lower strontium concentrations and less radiogenic (lower) 87Sr/86Sr. In contrast, all Lyropecten shell analyses yielded a uniform 87Sr/86Sr value (0.708440±0.000010 [2× standard deviation]) over a wide range of strontium concentrations (around 900 to 1,800 micrograms per gram [μg/g]). Results for Balanus shell subsamples show a range of strontium compositional behavior between the other two types of shell. Acetic acid leachates of sandy matrix confirm that diagenetic fluids had low 87Sr/86Sr values consistent with the least radiogenic values in Pycnodonte subsamples. A simple mixing model between two calcite end-members can explain observed Pycnodonte data, although actual diagenetic processes likely involved secondary dissolution/reprecipitation or strontium ion exchange between shell material and pore fluid. Data indicate that only Lyropecten subsamples have retained their original 87Sr/86Sr compositions, resulting in a best-estimate age of 20.08±0.11 million years ago (Ma) (±95-percent confidence interval [CI]). Although Dugongidae fossils have been found in Miocene and younger sediments along the west coast of North America, the Santa Rosa Island specimens represent some of the earliest and most accurately dated sirenian fossils in the region. Chronostratigraphic results also constrain the timing of the transgressional processes represented by shallow-water (Vaqueros Sandstone) to deep-water (Rincon formation) depositional environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235026","collaboration":"Prepared in cooperation with the U.S. National Park Service","usgsCitation":"Paces, J.B., Minor, S.A., Schmidt, K.M., and Hoffman, J., 2023, Strontium isotope chronostratigraphic age of a sirenian fossil site on Santa Rosa Island, Channel Islands National Park, California: U.S. Geological Survey Scientific Investigations Report 2023–5026, 27 p., https://doi.org/10.3133/sir20235026.","productDescription":"Report: vii, 27 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135728","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":415211,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GG6NB5","text":"USGS data release","linkHelpText":"Sr concentrations and 87Sr/86Sr data used to determine the Sr-chronostratigraphic age of sirenian fossils on Santa Rosa Island, Channel Islands National Park: California, USA"},{"id":415210,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5026/images/"},{"id":415208,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235026/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5026"},{"id":415206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5026/coverthb.jpg"},{"id":415207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5026/sir20235026.pdf","text":"Report","size":"42.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5026"},{"id":415209,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5026/sir20235026.XML"},{"id":500882,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114663.htm"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.27493358761777,\n 34.050843485499456\n ],\n [\n -120.27493358761777,\n 33.868674166486116\n ],\n [\n -119.93999465714583,\n 33.868674166486116\n ],\n [\n -119.93999465714583,\n 34.050843485499456\n ],\n [\n -120.27493358761777,\n 34.050843485499456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
In hopes of reversing or slowing the decline of the river delta, water diversions have been built and planned, and natural diversions have formed and been allowed to develop along the lower Mississippi River. In addition to the possibility of building land, these diversions allow for the storage of nutrients within the deposited sediments and provide a buffer from coastal storm surge flooding. Deposition from diversions reduces nutrient loading to the receiving waterbodies. Along the Mississippi River delta in Louisiana, modern planned diversions after 2017 (CPRA 2017) seek to bring sediment-laden water from the river to a receiving area that may once have been part of the historic delta floodplain. Many of the existing diversions discharge directly into open-water bays of the subaqueous delta, however some flood diversions outflow to the subaerial floodplain (Kroes et al. 2015). The effects of diversion outflows to bays are difficult to physically analyze and quantify due to the complex hydrodynamics of subaqueous sites, such as storm-driven resuspension, and tidal currents that mobilize deposited fine sediments downcoast or off the continental shelf. In contrast, flood diversions that outflow to subaerial floodplains offer clear and numerous sediment deposition measurement opportunities and clearly identifiable material to analyze. Flood diversions, while similar, may not exhibit identical depositional environments due to hydraulic gradient and vegetation differences. Because flood diversions draw water from the river at a greater height above the riverbed, they may entrain less bed sediment than non-flood diversions (Karmaker et al. 2010). Previous studies indicate that the large discharges through flood diversion control structures deposit large masses of sediment (Nittrouer et al. 2012) and nutrients and can provide depositional curves that may be extrapolated to other diversions (Kroes et al. 2015).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD2023: The sedimentation and hydrologic modeling conference","conferenceDate":"May 8-12, 2023","conferenceLocation":"St. Louis, MO","language":"English","publisher":"SEDHYD","usgsCitation":"Kroes, D., Noe, G.E., Ramirez, D., and Vosburg, B., 2023, Sediment and nutrient deposition over a reconnected floodplain during large-scale river diversions, the Bonnet Carré spillway in 2011, 2016, and 2019, in Proceedings of SEDHYD2023, St. Louis, MO, May 8-12, 2023, 11 p.","productDescription":"11 p.","ipdsId":"IP-151842","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":418678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418675,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2023Program/s68.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Bonnet Carré spillway, Lake Pontchartrain, Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.42757540318235,\n 30.082894344072514\n ],\n [\n -90.42757540318235,\n 30.01150844828244\n ],\n [\n -90.3745696787966,\n 30.01150844828244\n ],\n [\n -90.3745696787966,\n 30.082894344072514\n ],\n [\n -90.42757540318235,\n 30.082894344072514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":876812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":876813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez, David","contributorId":315549,"corporation":false,"usgs":false,"family":"Ramirez","given":"David","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":876814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vosburg, Brian","contributorId":315550,"corporation":false,"usgs":false,"family":"Vosburg","given":"Brian","email":"","affiliations":[{"id":68350,"text":"Grey Boat Group","active":true,"usgs":false}],"preferred":false,"id":876815,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243217,"text":"70243217 - 2023 - National-scale assessment of total gaseous mercury isotopes across the United States","interactions":[],"lastModifiedDate":"2023-05-04T11:44:41.794468","indexId":"70243217","displayToPublicDate":"2023-04-12T06:41:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5998,"text":"JGR Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"National-scale assessment of total gaseous mercury isotopes across the United States","docAbstract":"With the 2011 promulgation of the Mercury and Air Toxics Standards by the U.S. Environmental Protection Agency, and the successful negotiation by the United Nations Environment Program of the Minamata Convention, emissions of mercury (Hg) have declined in the United States. While the declines in atmospheric Hg concentrations in North America are encouraging, linking the declines to changing domestic and global source portfolios remains challenging. To address these research gaps, the U.S. Geological Survey initiated the first national-scale effort to establish a baseline of total gaseous mercury stable isotope values at 31 sites distributed across the United States. Results indicated that unique Hg sources, such as Hg evasion from an elemental Hg contaminated site or free tropospheric intrusions in high altitude sites, were distinguishable from background atmospheric values. Minor gradients were observed across the nation, with regions of heavy industrial activity demonstrating lower δ202Hg, but no consistent changes in other isotopes such as Δ199Hg and Δ200Hg were observed. Furthermore, δ202Hg was impacted by foliar uptake and senescence but trends varied between forested regions in the northeastern and midwestern United States. These data demonstrate regional emission sources and other environmental variables can impact total gaseous Hg (TGM) isotope values, highlighting the need to characterize atmospheric Hg isotopes over larger geographical areas to evaluate changes related to national and international Hg regulations.
Rapid population growth and development in the southeastern United States have resulted in substantial impairment to freshwater aquatic ecosystems. National or regional restoration policies strive to address impaired ecosystems but can suffer from inconsistent and opaque processes. The Clean Water Act, for example, establishes reallocation mechanisms to transfer ecosystem services from sites of disturbance to compensation sites to offset aquatic resource functions that are unavoidably lost through land development. However, planning for the prioritization of compensatory mitigation areas is often hampered by unstructured decision-making processes that are narrowly framed because they are not co-produced with stakeholders affected by, or having an interest in, the impacts and mitigation. This summary report represents the collaborative efforts of the U.S. Geological Survey and the North Carolina Department of Environmental Quality, Division of Mitigation Services, to co-develop an applied decision framework following the principles of structured decision-making for prioritizing watershed catchments by their potential for realizing a range of beneficial outcomes from future mitigation projects. The framework focuses on supporting the State’s nationally recognized stream and wetlands compensatory mitigation program by clarifying a discrete decision problem and specifying agency and stakeholder values to formulate fundamental and means objectives for prioritizing restoration sites. The co-development of this decision framework resulted in a number of useful insights from the perspective of the decision maker, including recognition (1) that the problem is a multi-objective decision driven by values beyond restoring lost functionality of ecosystems (that is, biogeophysical goals), (2) that the decision comprises a linked and sequential planning-to-implementation process, and (3) that future risk associated with land-use and climate change must be considered. The outcomes of this collaboration can serve as a systematic and transparent framework to prioritize a wide range of restoration, conservation, and resource-allocation activities in similar environmental contexts across the Nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221058","collaboration":"Prepared in cooperation with the North Carolina Department of Environmental Quality","usgsCitation":"García, A.M., Eaton, M., Sanchez, G.M., Keisman, J.L., Ullman, K., and Blackwell, J., 2023, Value-aligned planning objectives for restoring North Carolina aquatic resources: U.S. Geological Survey Open-File Report 2022–1058, 20 p., https://doi.org/10.3133/ofr20221058.","productDescription":"vi, 20 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125133","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":414972,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1058/ofr20221058.XML"},{"id":414969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1058/coverthb.jpg"},{"id":414970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1058/ofr20221058.pdf","text":"Report","size":"1.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1058"},{"id":499718,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114653.htm","linkFileType":{"id":5,"text":"html"}},{"id":414973,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1058/images/"}],"country":"United States","state":"North Carolina","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-75.753765,35.199612],[-75.718015,35.209377],[-75.684006,35.232913],[-75.664512,35.227514],[-75.630358,35.238487],[-75.599005,35.256253],[-75.596915,35.269491],[-75.581935,35.263917],[-75.535741,35.272856],[-75.529393,35.288272],[-75.487678,35.485056],[-75.487528,35.525889],[-75.47861,35.553069],[-75.48133,35.622896],[-75.487678,35.648287],[-75.507385,35.680564],[-75.515397,35.73038],[-75.533512,35.773577],[-75.522232,35.774178],[-75.496086,35.728515],[-75.458659,35.596597],[-75.471355,35.479615],[-75.486771,35.391652],[-75.52592,35.233839],[-75.533627,35.225825],[-75.560225,35.232048],[-75.610101,35.227514],[-75.769705,35.180359],[-75.944725,35.105091],[-76.013145,35.061855],[-76.013561,35.068832],[-75.99188,35.092395],[-75.989175,35.115165],[-75.98395,35.120042],[-75.9547,35.1196],[-75.893942,35.150433],[-75.801444,35.183079],[-75.785729,35.194244],[-75.753765,35.199612]]],[[[-75.675245,35.929024],[-75.65954,35.919564],[-75.662019,35.906522],[-75.64512,35.905788],[-75.62767,35.883149],[-75.616833,35.856331],[-75.619772,35.847606],[-75.614361,35.815659],[-75.620454,35.809253],[-75.63898,35.818639],[-75.667891,35.82354],[-75.675054,35.830204],[-75.660086,35.83861],[-75.663356,35.869835],[-75.67283,35.882423],[-75.681415,35.88398],[-75.697672,35.901639],[-75.696871,35.909556],[-75.702165,35.915428],[-75.723782,35.925569],[-75.727251,35.93362],[-75.718266,35.939714],[-75.705323,35.939403],[-75.675245,35.929024]]],[[[-76.12236,36.550621],[-75.867044,36.550754],[-75.818735,36.357579],[-75.773329,36.231529],[-75.71831,36.113674],[-75.658537,36.02043],[-75.569794,35.863301],[-75.533012,35.787377],[-75.536428,35.780118],[-75.543259,35.779691],[-75.573083,35.828867],[-75.588878,35.844926],[-75.619151,35.889415],[-75.620114,35.925288],[-75.648899,35.965758],[-75.668379,35.978394],[-75.678909,35.993925],[-75.723662,36.003139],[-75.727084,36.01051],[-75.722609,36.037362],[-75.737088,36.040784],[-75.74051,36.046839],[-75.73972,36.07527],[-75.75572,36.153922],[-75.783676,36.215949],[-75.811588,36.244014],[-75.808165,36.259545],[-75.814483,36.285344],[-75.822907,36.291662],[-75.837913,36.294558],[-75.845284,36.305614],[-75.841335,36.328517],[-75.831858,36.339047],[-75.831595,36.346418],[-75.836201,36.363135],[-75.85147,36.379456],[-75.85147,36.415785],[-75.864106,36.430527],[-75.888325,36.441583],[-75.899908,36.482124],[-75.907279,36.485809],[-75.924127,36.482124],[-75.935473,36.490601],[-75.972545,36.494671],[-76.003708,36.506235],[-76.023627,36.500778],[-76.031949,36.482496],[-76.012337,36.447462],[-75.98005,36.435464],[-75.962285,36.41724],[-75.940676,36.41885],[-75.928369,36.428588],[-75.923601,36.425788],[-75.916409,36.38901],[-75.923331,36.361863],[-75.895285,36.319615],[-75.882154,36.284674],[-75.864933,36.284674],[-75.86052,36.280607],[-75.867356,36.252483],[-75.864154,36.235522],[-75.858703,36.222628],[-75.848838,36.21657],[-75.838367,36.200129],[-75.839924,36.17711],[-75.823915,36.158332],[-75.822531,36.145957],[-75.800378,36.112728],[-75.791637,36.082267],[-75.793974,36.07171],[-75.836084,36.092616],[-75.867792,36.127262],[-75.863914,36.159226],[-75.882987,36.186807],[-75.910658,36.212157],[-75.922344,36.244122],[-75.94984,36.25787],[-75.96462,36.254433],[-75.957058,36.247903],[-75.945372,36.222468],[-75.956027,36.198065],[-75.936436,36.18088],[-75.904999,36.164188],[-75.939047,36.165518],[-76.016984,36.186367],[-76.029086,36.202036],[-76.043838,36.210126],[-76.054308,36.229162],[-76.08148,36.237935],[-76.132005,36.287773],[-76.184702,36.298166],[-76.188717,36.281242],[-76.171378,36.265806],[-76.149486,36.263902],[-76.115851,36.214219],[-76.080106,36.19944],[-76.05992,36.15514],[-76.064224,36.143775],[-76.092555,36.135794],[-76.178946,36.123424],[-76.206873,36.137521],[-76.254064,36.18419],[-76.273316,36.189062],[-76.27699,36.184952],[-76.247401,36.161823],[-76.228527,36.130647],[-76.191715,36.107197],[-76.216599,36.095409],[-76.265037,36.104886],[-76.329921,36.133396],[-76.373571,36.138208],[-76.3935,36.163251],[-76.447812,36.192514],[-76.454414,36.189901],[-76.456061,36.183577],[-76.375892,36.12042],[-76.346418,36.121023],[-76.334965,36.110903],[-76.298733,36.1012],[-76.303998,36.092776],[-76.323478,36.084879],[-76.355069,36.086458],[-76.410878,36.078034],[-76.420881,36.06066],[-76.451418,36.039073],[-76.459316,36.024331],[-76.491959,36.018013],[-76.514335,36.00564],[-76.547505,36.009852],[-76.580674,36.00722],[-76.60384,36.033018],[-76.615423,36.037757],[-76.653332,36.035124],[-76.676484,36.043612],[-76.721445,36.147838],[-76.719401,36.199441],[-76.675462,36.266882],[-76.693253,36.278357],[-76.744436,36.212725],[-76.7521,36.147328],[-76.722996,36.066585],[-76.679657,35.991951],[-76.70019,35.964573],[-76.692376,35.945342],[-76.667547,35.933509],[-76.528551,35.944039],[-76.473795,35.960888],[-76.460632,35.970365],[-76.398242,35.984317],[-76.38192,35.971681],[-76.381394,35.96273],[-76.362966,35.942197],[-76.340327,35.94325],[-76.317687,35.946935],[-76.272408,35.972734],[-76.213966,35.988002],[-76.176585,35.993267],[-76.093697,35.993001],[-76.083131,35.989845],[-76.062071,35.993004],[-76.024162,35.970891],[-76.014159,35.957202],[-76.01995,35.934036],[-76.014353,35.920746],[-76.063203,35.853433],[-76.050485,35.806689],[-76.046813,35.717935],[-76.036393,35.690344],[-76.046361,35.659067],[-76.04015,35.65131],[-76.029863,35.649443],[-76.013808,35.669103],[-75.9869,35.768194],[-75.987148,35.836967],[-75.97783,35.897181],[-75.962562,35.901393],[-75.94782,35.920347],[-75.927286,35.93193],[-75.92676,35.940354],[-75.943608,35.952464],[-75.947293,35.959835],[-75.899382,35.977209],[-75.84989,35.976156],[-75.80935,35.959308],[-75.800926,35.944566],[-75.782498,35.935615],[-75.778813,35.918241],[-75.751961,35.878227],[-75.748276,35.852428],[-75.734587,35.839266],[-75.727216,35.822703],[-75.726689,35.811361],[-75.739357,35.770994],[-75.724743,35.742892],[-75.71294,35.69849],[-75.713502,35.693993],[-75.741605,35.672073],[-75.742167,35.655212],[-75.729802,35.625985],[-75.747225,35.610248],[-75.778138,35.592262],[-75.775328,35.579335],[-75.837154,35.570904],[-75.859636,35.586641],[-75.895045,35.573152],[-75.916403,35.538305],[-75.950126,35.530998],[-75.964178,35.511326],[-75.963053,35.493903],[-75.987222,35.484348],[-75.995652,35.475355],[-75.997901,35.453435],[-76.009704,35.442194],[-76.01139,35.423084],[-76.020945,35.410719],[-76.025441,35.408471],[-76.050171,35.415778],[-76.059726,35.410157],[-76.063661,35.405099],[-76.059726,35.383741],[-76.069281,35.370813],[-76.132793,35.349455],[-76.14291,35.338776],[-76.14291,35.32866],[-76.149655,35.326411],[-76.182254,35.336528],[-76.20586,35.336528],[-76.235087,35.350017],[-76.253072,35.350017],[-76.257569,35.344397],[-76.265437,35.343273],[-76.282299,35.345521],[-76.304781,35.355638],[-76.327263,35.356762],[-76.335132,35.355638],[-76.340752,35.346645],[-76.349745,35.345521],[-76.382344,35.356762],[-76.399206,35.348893],[-76.408199,35.350017],[-76.431805,35.362383],[-76.436301,35.37812],[-76.448666,35.383741],[-76.462156,35.380368],[-76.472273,35.371375],[-76.485762,35.371375],[-76.540292,35.410657],[-76.586349,35.508957],[-76.476706,35.511707],[-76.456427,35.550546],[-76.471207,35.55742],[-76.48358,35.538172],[-76.55679,35.528892],[-76.600441,35.538516],[-76.634468,35.510332],[-76.601472,35.460838],[-76.580187,35.387113],[-76.606041,35.387113],[-76.710083,35.427155],[-76.759234,35.418906],[-76.830897,35.447949],[-76.942022,35.473529],[-77.023912,35.514802],[-77.026638,35.490569],[-76.967214,35.438296],[-76.891938,35.433649],[-76.664027,35.345696],[-76.500375,35.321915],[-76.482389,35.314046],[-76.467776,35.276951],[-76.467776,35.261213],[-76.477893,35.243228],[-76.490258,35.233111],[-76.494755,35.212877],[-76.521733,35.192643],[-76.536346,35.174657],[-76.539719,35.166788],[-76.536346,35.142058],[-76.546463,35.122948],[-76.557704,35.116204],[-76.568945,35.097094],[-76.60042,35.067867],[-76.631895,35.056626],[-76.801426,34.964369],[-76.982904,35.060607],[-76.989778,35.045484],[-76.977404,35.004926],[-76.89354,34.957495],[-76.762931,34.920374],[-76.635072,34.989116],[-76.588055,34.991428],[-76.566697,34.998173],[-76.502623,35.007166],[-76.491382,35.017283],[-76.490258,35.034144],[-76.474521,35.070116],[-76.463468,35.076411],[-76.435762,35.057941],[-76.425461,35.001464],[-76.395625,34.975179],[-76.332044,34.970917],[-76.326361,34.976245],[-76.329557,34.986901],[-76.364367,35.034853],[-76.318546,35.020645],[-76.288354,35.005726],[-76.296524,34.976245],[-76.275567,34.960971],[-76.277698,34.940014],[-76.347673,34.872171],[-76.368274,34.872881],[-76.379641,34.86258],[-76.400242,34.855476],[-76.463016,34.785076],[-76.524712,34.681964],[-76.586236,34.698805],[-76.582421,34.767757],[-76.604796,34.787482],[-76.620606,34.784389],[-76.616567,34.714059],[-76.673619,34.71491],[-76.673537,34.70757],[-76.523303,34.652271],[-76.383827,34.807906],[-76.322808,34.86116],[-76.233672,34.925926],[-76.093349,35.048705],[-76.069906,35.075701],[-76.043621,35.070017],[-76.035933,35.058987],[-76.137269,34.987858],[-76.233088,34.905477],[-76.31021,34.852309],[-76.386804,34.784579],[-76.494068,34.66197],[-76.524199,34.615416],[-76.535946,34.588577],[-76.555196,34.615993],[-76.549343,34.645585],[-76.579467,34.660174],[-76.642939,34.677618],[-76.676312,34.693151],[-76.770044,34.696899],[-76.817453,34.693722],[-76.990262,34.669623],[-77.136843,34.632926],[-77.209161,34.605032],[-77.322524,34.535574],[-77.462922,34.471354],[-77.556943,34.417218],[-77.661673,34.341868],[-77.740136,34.272546],[-77.829209,34.162618],[-77.878161,34.067963],[-77.915536,33.971723],[-77.946568,33.912261],[-77.960172,33.853315],[-77.970606,33.844517],[-78.009973,33.861406],[-78.018689,33.888289],[-78.095429,33.906031],[-78.17772,33.914272],[-78.276147,33.912364],[-78.383964,33.901946],[-78.509042,33.865515],[-78.541087,33.851112],[-79.358317,34.545358],[-79.675299,34.804744],[-80.797543,34.819786],[-80.782042,34.935782],[-80.93495,35.107409],[-81.041489,35.044703],[-81.057648,35.062433],[-81.058029,35.07319],[-81.052078,35.096276],[-81.032806,35.108049],[-81.038968,35.126299],[-81.05042,35.131048],[-81.044391,35.147918],[-81.239358,35.159974],[-82.27492,35.200071],[-82.314863,35.191089],[-82.32335,35.184789],[-82.344554,35.193115],[-82.361469,35.190831],[-82.36899,35.181747],[-82.379712,35.186884],[-82.378744,35.198053],[-82.390439,35.215395],[-82.403348,35.204473],[-82.417597,35.200131],[-82.439595,35.165863],[-82.448969,35.165037],[-82.455609,35.177425],[-82.460092,35.178143],[-82.483937,35.173798],[-82.495506,35.164312],[-82.516044,35.163442],[-82.529973,35.155617],[-82.550508,35.159498],[-82.556168,35.151736],[-82.563767,35.151575],[-82.578316,35.142104],[-82.609706,35.139039],[-82.629031,35.126155],[-82.642237,35.129215],[-82.662381,35.118123],[-82.683625,35.125833],[-82.694898,35.098456],[-82.72701,35.094142],[-82.738379,35.079453],[-82.749491,35.078487],[-82.757704,35.068019],[-82.777376,35.064143],[-82.781973,35.066817],[-82.776357,35.081349],[-82.787867,35.085024],[-83.108535,35.000771],[-83.620185,34.992091],[-83.619985,34.986592],[-84.321869,34.988408],[-84.29024,35.225572],[-84.28322,35.226577],[-84.223718,35.269078],[-84.211818,35.266078],[-84.202879,35.255772],[-84.200117,35.244679],[-84.188417,35.239979],[-84.170416,35.245779],[-84.12889,35.243679],[-84.12115,35.250644],[-84.097508,35.247382],[-84.081117,35.261146],[-84.052612,35.269982],[-84.02141,35.301383],[-84.02651,35.309283],[-84.03501,35.311983],[-84.029377,35.333197],[-84.038081,35.348363],[-84.024756,35.353896],[-84.007586,35.371661],[-84.008207,35.389683],[-84.021782,35.407418],[-84.00225,35.422548],[-83.992568,35.438065],[-83.973057,35.448921],[-83.971439,35.455145],[-83.966656,35.454941],[-83.961054,35.462838],[-83.949389,35.461164],[-83.937015,35.471511],[-83.911773,35.476028],[-83.905612,35.48906],[-83.880074,35.518745],[-83.859261,35.521851],[-83.848502,35.519259],[-83.827428,35.524653],[-83.802434,35.541588],[-83.780129,35.550387],[-83.771736,35.562118],[-83.749894,35.561146],[-83.735669,35.565455],[-83.723459,35.561874],[-83.707199,35.568533],[-83.676268,35.570289],[-83.640498,35.566075],[-83.608889,35.579451],[-83.582,35.562684],[-83.56609,35.565993],[-83.498335,35.562981],[-83.485527,35.568204],[-83.479317,35.582764],[-83.455722,35.598045],[-83.445802,35.611803],[-83.421576,35.611186],[-83.396626,35.62272],[-83.388602,35.632352],[-83.366941,35.638728],[-83.35156,35.659858],[-83.334965,35.665471],[-83.321101,35.662815],[-83.312757,35.654809],[-83.297154,35.65775],[-83.290682,35.672638],[-83.258117,35.691924],[-83.255489,35.714974],[-83.251247,35.719916],[-83.240669,35.72676],[-83.214501,35.724434],[-83.18837,35.729798],[-83.159208,35.764892],[-83.120183,35.766234],[-83.07403,35.790016],[-83.036209,35.787405],[-83.001473,35.773752],[-82.992053,35.773948],[-82.964088,35.78998],[-82.961724,35.800491],[-82.945515,35.824662],[-82.920171,35.841664],[-82.918312,35.863977],[-82.901301,35.872593],[-82.901843,35.890274],[-82.911936,35.921618],[-82.901577,35.931446],[-82.898506,35.9451],[-82.874159,35.952698],[-82.860724,35.94743],[-82.852554,35.949089],[-82.826045,35.929721],[-82.82257,35.922531],[-82.804997,35.927168],[-82.805771,35.935316],[-82.800431,35.944155],[-82.787465,35.952163],[-82.785356,35.96253],[-82.774905,35.971978],[-82.785558,35.977795],[-82.785267,35.987927],[-82.776001,36.000103],[-82.750065,36.006004],[-82.688865,36.038604],[-82.684765,36.045004],[-82.637165,36.065805],[-82.618664,36.056105],[-82.618164,36.047005],[-82.609663,36.044906],[-82.596177,36.03188],[-82.595525,36.026012],[-82.614362,36.003506],[-82.613028,35.994],[-82.604239,35.987319],[-82.610889,35.967409],[-82.581003,35.965557],[-82.576678,35.959255],[-82.557874,35.953901],[-82.549682,35.964275],[-82.507068,35.977475],[-82.483498,35.996284],[-82.460658,36.007809],[-82.409458,36.083409],[-82.355157,36.115609],[-82.336756,36.114909],[-82.321448,36.119551],[-82.289455,36.13571],[-82.270954,36.12761],[-82.260353,36.13371],[-82.247521,36.130865],[-82.213852,36.159112],[-82.182549,36.143714],[-82.147948,36.149516],[-82.136547,36.128817],[-82.137974,36.119576],[-82.127146,36.104417],[-82.105444,36.108119],[-82.080303,36.105728],[-82.061342,36.113121],[-82.054142,36.126821],[-82.033141,36.120422],[-81.908137,36.302013],[-81.879382,36.313767],[-81.857333,36.334787],[-81.841268,36.343321],[-81.800812,36.358073],[-81.766102,36.338517],[-81.730976,36.341187],[-81.707438,36.335171],[-81.707785,36.346007],[-81.721334,36.353101],[-81.732865,36.376502],[-81.729813,36.388033],[-81.737952,36.39719],[-81.739648,36.406686],[-81.720734,36.422537],[-81.715229,36.436532],[-81.71489,36.45722],[-81.695311,36.467912],[-81.697829,36.507544],[-81.707573,36.526101],[-81.707963,36.536209],[-81.699962,36.536829],[-81.69003,36.552154],[-81.690236,36.568718],[-81.677036,36.570718],[-81.677535,36.588117],[-81.003802,36.563629],[-80.837954,36.559131],[-80.704831,36.562319],[-80.295243,36.543973],[-80.122183,36.542646],[-78.529722,36.540981],[-77.16966,36.547315],[-77.152691,36.544078],[-76.916048,36.543815],[-76.916989,36.550742],[-76.12236,36.550621]]]]},\"properties\":{\"name\":\"North Carolina\",\"nation\":\"USA \"}}]}","contact":"South Atlantic Water Science Center
U.S. Geological Survey
3916 Sunset Ridge Road
Raleigh, NC 27607
Many households lack the necessary food and water supplies to sustain themselves for more than three days during a disaster. Community vulnerability assessments can be used to identify households with more pressing needs for emergency food and water resources. It is critical that these assessments include the interaction between physical impacts to lifeline infrastructure and the social vulnerabilities of food and water insecurity to prioritize, allocate, and distribute emergency resources. In this paper, we review and synthesize relevant literature to propose a new multidisciplinary conceptual framework of community vulnerability assessment for estimating initial emergency food and water resource requirements in a developed country. Using the framework as a guide, we illustrate its practical application through a simplified, deterministic model of initial resource requirements in disaster response, and offer a quantitative, comprehensive description of its application within the geophysical hazard context of the “ShakeOut” scenario—a major Mw 7.8 earthquake on California's San Andreas fault, occurring within the Los Angeles Basin, CA (USA) region. Model results estimate that 999,027 households (2,947,130 residents) will require initial emergency food and water resource requirements. Estimates include about 6 million meals and 9 million liters of water, concentrated in Lancaster-Palmdale, El Monte-Baldwin Park, East Los Angeles-Downey in Los Angeles County, the Coachella Valley (Riverside County), and in populated areas of San Bernardino County. A sensitivity analysis of social vulnerability interactions with utility service outages investigates the influence of food insecurity on the amplification of resource needs. This study establishes fundamental knowledge at the nexus of natural hazards, critical infrastructure disruptions, and social vulnerability by providing initial estimates of emergency resource demand while advancing the understanding of social inequity in emergency resource access.
Water nutrient management efforts are frequently coordinated across thousands of water bodies, leading to a need for spatially extensive information to facilitate decision making. Here we explore potential applications of a machine learning model of river low-flow total phosphorus (TP) concentrations to support landscape nutrient management. The model was trained, validated, and then applied for all rivers of Michigan, USA to identify potential drivers of nutrient variation, predict alteration in nutrient concentrations from minimally disturbed conditions, and explore reach specific sensitivity to riparian agricultural change. A boosted regression tree model of low-flow TP concentrations trained on natural and anthropogenic landscape predictors accounted for 53 % of variation in cross-validation data, had good accuracy, little bias, and plausible relationships between predictors and response. Percent riparian agricultural cover accounted for the greatest root mean square error reduction in the modeled response (33.2 %), followed by riparian soil permeability (12.9 %), watershed slope (9.6 %), and percent urban cover (9.6 %). An apparent non-linear relationship between TP concentrations and percent riparian agricultural cover suggested steep positive increases in stream TP concentrations between 10 and 30 % upstream riparian agricultural cover. Predicted minimally disturbed TP concentrations were spatially variable and ranged from 7.0 to 48.5 μg l−1, with the highest concentrations in watersheds draining low-permeability lake plain soils. Comparison of minimally disturbed predictions to those from the early 2000s suggested that much of northern Michigan existed close to the reference condition, while lower Michigan streams were often substantially enriched. Our predicted values of minimally disturbed condition generally agree with previous studies but offer greater geographic specificity. Expanded application of machine learning modeling with landscape predictor data have great potential to inform large scale strategy development in landscapes with sparse reference data.
Arctic freshwater ecosystems and fish populations are largely shaped by seasonal and long-term watershed hydrology. In this paper, we hypothesize how changing air temperature and precipitation will alter freeze and thaw processes, hydrology, and instream habitat to assess potential indirect effects, such as the change to the foraging and behavioral ecology, on Arctic fishes, using Broad Whitefish Coregonus nasus as an indicator species. Climate change is expected to continue to alter hydrologic pathways, flow regimes, and, therefore, habitat suitability, connectivity, and availability for fishes. Warming and lengthening of the growing season will likely increase fish growth rates; however, the exceedance of threshold stream temperatures will likely increase physiological stress and alter life histories. We expect these changes to have mixed effects on Arctic subsistence fishes and fisheries. Management and conservation approaches focused on preserving the processes that create heterogeneity in aquatic habitats, genes, and communities will help maintain the resilience of Broad Whitefish and other important subsistence fisheries. Long-term effects are uncertain, so filling scientific knowledge gaps, such as identifying important habitats or increasing knowledge of abiotic variables in priority watersheds, is key to understanding and potentially mitigating likely impacts to Arctic fishes in a rapidly changing landscape.
No abstract available.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.3c02351","usgsCitation":"Schmidt, T., Fuller, C.C., Qi, S.L., and Gellis, A.C., 2023, Rebuttal to correspondence on “sediment sources and sealed-pavement area drive polycyclic aromatic hydrocarbon and metal occurrence in urban streams: Environmental Science and Technology, v. 57, no. 16, p. 6756-6758, https://doi.org/10.1021/acs.est.3c02351.","productDescription":"3 p.","startPage":"6756","endPage":"6758","ipdsId":"IP-148532","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":422068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"16","noUsgsAuthors":false,"publicationDate":"2023-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":886694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":886695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qi, Sharon L. 0000-0001-7278-4498 slqi@usgs.gov","orcid":"https://orcid.org/0000-0001-7278-4498","contributorId":1130,"corporation":false,"usgs":true,"family":"Qi","given":"Sharon","email":"slqi@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886702,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70244206,"text":"70244206 - 2023 - Effects of nitrate and conductivity on embryo-larval fathead minnows","interactions":[],"lastModifiedDate":"2023-07-11T16:09:11.855672","indexId":"70244206","displayToPublicDate":"2023-04-10T07:08:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effects of nitrate and conductivity on embryo-larval fathead minnows","docAbstract":"Nitrate concentrations have been rising in surface waters over the last century and now frequently exceed drinking water standards and environmental safety benchmarks globally. Health-wise, these trends are concerning because nitrate has been shown to disrupt endocrine function and developmental outcomes. The present study investigated potential sublethal effects of nitrate on developing fathead minnows. Fish were exposed from fertilization through 21 days postfertilization (dpf) to environmentally relevant concentrations of nitrate (0, 2, 5, 10, 25, or 100 mg/L NO3-N as NaNO3). Nitrate effects on hatch timing, heart rate and rhythm at 3 dpf, growth through 21 dpf, swim bladder inflation timing and size, scoliosis, pericardial edema, and mortality were assessed. Because adding NaNO3 increases water conductivity, two conductivity controls were included to match the ionic strength of the 10- and 100-mg/L NO3-N treatments. Increasing nitrate delayed posterior swim bladder (PSB) inflation in a dose-dependent manner, with possible inhibition of anterior swim bladder (ASB) inflation at higher doses, although nitrate did not affect swim bladder size. Conversely, nitrate did not affect hatch timing or cardiac endpoints at 3 dpf or induce pericardial edema or scoliosis, although there was a noted brood effect on these latter defects. As was observed with increasing nitrate, higher ion concentrations in the conductivity controls caused dose-dependent increases in fish body size at 21 dpf. Increased ionic strength also hastened ASB inflation independently of nitrate. As in other published studies, the observed delay in PSB inflation suggests that nitrate disrupts the thyroid axis and warrants further investigation. In addition, the present study supports the need for conductivity controls in nitrate toxicity studies to distinguish nitrate-specific effects. Environ Toxicol Chem 2023;00:1–13. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.
Kings Bay in northwest Florida, USA, is an important winter home of the largest aggregation of Florida manatee (Trichechus manatus latirostris), and the only location in the United States where visitors legally swim and interact with manatees. In addition to ambient conditions, visitors to the area and management actions have the potential to influence manatee behaviors. We tracked 32 manatees with satellite-linked global position system (GPS) telemetry tags in Kings Bay from 2006 to 2018. Also, personnel at Crystal River National Wildlife Refuge collected manatee counts at Three Sisters Springs from 2014 to 2017. Our objectives were to document the use of springs and other habitat components in Kings Bay relative to ambient water temperature, time of day, tide stage, and management actions within Three Sisters Springs and other manatee sanctuaries in the bay. Manatees that we tagged in Kings Bay spent a median 87% of the winter within the local study area, compared to 47% for animals that we tagged in the Florida Panhandle. Manatees showed preferences for King and Magnolia springs basins at low tide, indicating that they function as tidal refuges, when other locations may be less accessible; we also recorded within spring basin movements. Magnolia Spring Basin showed a significant diel pattern overall, and within basins, King Spring, Tarpon Hole, and Three Sisters Springs were used more during the night than during the day. All areas outside Kings Bay were used more at warmer ambient gulf water temperatures, while all of the springs basins were used more when gulf temperature was colder, especially Three Sisters Springs Basin. Management of Three Sisters Springs had an influence on manatee use during times of cold ambient gulf water temperatures; manatees used the springs more when the spring was closed to visitors, versus when the springs were completely open or when the spring lobes alone were closed. Manatee decisions were consistent with avoiding human interactions.
Wastewater treatment plant effluent can increase stream water temperature from near freezing to 5°C–12°C in winter months. Recent research in the South Platte River Basin in Colorado showed that this warming alters the reproductive timing of some fishes. However, the spatial extent and magnitude of this warming are unknown. Thus, we created winter water temperature models both upstream and downstream of effluent inputs for two urban tributaries of the South Platte River, the Big Thompson River, and St. Vrain Creek. We examined the influence of air temperature, discharge, effluent temperature, and distance downstream on water temperature over the winter period (December–February). The models were also used to predict water temperature in the absence of effluent and based on air temperature predictions in 2052 and 2082. Effluent temperature was the largest driver of water temperature downstream of the effluent, while the impact of air temperature was comparatively small. Streams cooled after an initially sharp temperature increase, though were still predicted to be ∼2°C greater than they would be in the absence of effluent at ∼0.5 km. Predicted air temperatures in 2052 and 2082 had a negligible effect on water temperature, suggesting that mitigating effluent temperature is key to protecting the winter thermal regimes of effluent-impacted rivers. Our models can be used to gain insight into the magnitude and downstream extent of the impact of effluent temperature on small urban streams in winter and provide a baseline for models in other watersheds and at larger scales.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1120412","usgsCitation":"Adams, C., Winkelman, D.L., and Fitzpatrick, R., 2023, Impact of wastewater treatment plant effluent on the winter thermal regime of two urban Colorado South Platte tributaries: Frontiers in Enviornmental Science, v. 11, 1120412, 10 p., https://doi.org/10.3389/fenvs.2023.1120412.","productDescription":"1120412, 10 p.","ipdsId":"IP-149443","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":443916,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1120412","text":"Publisher Index Page"},{"id":430205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Big Thompson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.47113160280938,\n 40.490008852821404\n ],\n [\n -105.47113160280938,\n 40.37392612322179\n ],\n [\n -105.18090980925777,\n 40.37392612322179\n ],\n [\n -105.18090980925777,\n 40.490008852821404\n ],\n [\n -105.47113160280938,\n 40.490008852821404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Catherine M.","contributorId":338827,"corporation":false,"usgs":false,"family":"Adams","given":"Catherine M.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Ryan M.","contributorId":338828,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Ryan M.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":903629,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242136,"text":"70242136 - 2023 - Predicted aquatic exposure effects from a national urban stormwater study","interactions":[],"lastModifiedDate":"2023-12-04T16:57:15.989156","indexId":"70242136","displayToPublicDate":"2023-04-07T08:18:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13794,"text":"Environmental Science: Water Research and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Predicted aquatic exposure effects from a national urban stormwater study","docAbstract":"A multi-agency study of 438 organic and 62 inorganic chemicals measured in urban stormwater during 50 total runoff events at 21 sites across the United States demonstrated that stormwater discharges can generate localized, aquatic exposures to extensive contaminant mixtures, including organics suspected to cause adverse aquatic-health effects. The aggregated risks to multiple aquatic trophic levels (fish, invertebrates, plants) of the stormwater mixture exposures, which were documented in the national study, were explored herein by calculating cumulative ratios of organic-contaminant in vitro exposure–activity cutoffs (∑EAR) and health-benchmark-weighted cumulative toxicity quotients (∑TQ). Both risk assessment approaches indicated substantial (moderate to high) risk for acute adverse effects to aquatic organisms across multiple trophic levels (fish, macroinvertebrates, non-vascular/vascular plants) at or near stormwater discharge points across the United States. The results are interpreted as potential orders of magnitude underestimates of actual aquatic risk in stormwater control wetlands or in the immediate vicinity of such discharges to surface-water receptors, because the 438 organic-compound analytical space assessed in this study is orders of magnitude less than the 350 000 parent compounds estimated to be in current commercial use globally and the incalculable chemical-space of potential metabolites and degradates.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00933A","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Masoner, J.R., Kolpin, D., and Gordon, S.E., 2023, Predicted aquatic exposure effects from a national urban stormwater study: Environmental Science: Water Research and Technology, v. 9, p. 3191-3199, https://doi.org/10.1039/D2EW00933A.","productDescription":"9 p.","startPage":"3191","endPage":"3199","ipdsId":"IP-124205","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":443921,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1039/d2ew00933a","text":"Publisher Index Page"},{"id":415409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-66.28243,18.51476],[-65.7713,18.42668],[-65.591,18.22803],[-65.84716,17.97591],[-66.59993,17.98182],[-67.18416,17.94655],[-67.24243,18.37446],[-67.10068,18.5206],[-66.28243,18.51476]]],[[[-155.54211,19.08348],[-155.68817,18.91619],[-155.93665,19.05939],[-155.90806,19.33888],[-156.07347,19.70294],[-156.02368,19.81422],[-155.85008,19.97729],[-155.91907,20.17395],[-155.86108,20.26721],[-155.78505,20.2487],[-155.40214,20.07975],[-155.22452,19.99302],[-155.06226,19.8591],[-154.80741,19.50871],[-154.83147,19.45328],[-155.22217,19.23972],[-155.54211,19.08348]]],[[[-156.07926,20.64397],[-156.41445,20.57241],[-156.58673,20.783],[-156.70167,20.8643],[-156.71055,20.92676],[-156.61258,21.01249],[-156.25711,20.91745],[-155.99566,20.76404],[-156.07926,20.64397]]],[[[-156.75824,21.17684],[-156.78933,21.06873],[-157.32521,21.09777],[-157.25027,21.21958],[-156.75824,21.17684]]],[[[-157.65283,21.32217],[-157.70703,21.26442],[-157.7786,21.27729],[-158.12667,21.31244],[-158.2538,21.53919],[-158.29265,21.57912],[-158.0252,21.71696],[-157.94161,21.65272],[-157.65283,21.32217]]],[[[-159.34512,21.982],[-159.46372,21.88299],[-159.80051,22.06533],[-159.74877,22.1382],[-159.5962,22.23618],[-159.36569,22.21494],[-159.34512,21.982]]],[[[-94.81758,49.38905],[-94.64,48.84],[-94.32914,48.67074],[-93.63087,48.60926],[-92.61,48.45],[-91.64,48.14],[-90.83,48.27],[-89.6,48.01],[-89.27292,48.01981],[-88.37811,48.30292],[-87.43979,47.94],[-86.46199,47.55334],[-85.65236,47.22022],[-84.87608,46.90008],[-84.77924,46.6371],[-84.54375,46.53868],[-84.6049,46.4396],[-84.3367,46.40877],[-84.14212,46.51223],[-84.09185,46.27542],[-83.89077,46.11693],[-83.61613,46.11693],[-83.46955,45.99469],[-83.59285,45.81689],[-82.55092,45.34752],[-82.33776,44.44],[-82.13764,43.57109],[-82.43,42.98],[-82.9,42.43],[-83.12,42.08],[-83.142,41.97568],[-83.02981,41.8328],[-82.69009,41.67511],[-82.43928,41.67511],[-81.27775,42.20903],[-80.24745,42.3662],[-78.93936,42.86361],[-78.92,42.965],[-79.01,43.27],[-79.17167,43.46634],[-78.72028,43.62509],[-77.73789,43.62906],[-76.82003,43.62878],[-76.5,44.01846],[-76.375,44.09631],[-75.31821,44.81645],[-74.867,45.00048],[-73.34783,45.00738],[-71.50506,45.0082],[-71.405,45.255],[-71.08482,45.30524],[-70.66,45.46],[-70.305,45.915],[-69.99997,46.69307],[-69.23722,47.44778],[-68.905,47.185],[-68.23444,47.35486],[-67.79046,47.06636],[-67.79134,45.70281],[-67.13741,45.13753],[-66.96466,44.8097],[-68.03252,44.3252],[-69.06,43.98],[-70.11617,43.68405],[-70.64548,43.09024],[-70.81489,42.8653],[-70.825,42.335],[-70.495,41.805],[-70.08,41.78],[-70.185,42.145],[-69.88497,41.92283],[-69.96503,41.63717],[-70.64,41.475],[-71.12039,41.49445],[-71.86,41.32],[-72.295,41.27],[-72.87643,41.22065],[-73.71,40.9311],[-72.24126,41.11948],[-71.945,40.93],[-73.345,40.63],[-73.982,40.628],[-73.95232,40.75075],[-74.25671,40.47351],[-73.96244,40.42763],[-74.17838,39.70926],[-74.90604,38.93954],[-74.98041,39.1964],[-75.20002,39.24845],[-75.52805,39.4985],[-75.32,38.96],[-75.07183,38.78203],[-75.05673,38.40412],[-75.37747,38.01551],[-75.94023,37.21689],[-76.03127,37.2566],[-75.72205,37.93705],[-76.23287,38.31921],[-76.35,39.15],[-76.54272,38.71762],[-76.32933,38.08326],[-76.99,38.23999],[-76.30162,37.91794],[-76.25874,36.9664],[-75.9718,36.89726],[-75.86804,36.55125],[-75.72749,35.55074],[-76.36318,34.80854],[-77.39763,34.51201],[-78.05496,33.92547],[-78.55435,33.86133],[-79.06067,33.49395],[-79.20357,33.15839],[-80.30132,32.50935],[-80.86498,32.0333],[-81.33629,31.44049],[-81.49042,30.72999],[-81.31371,30.03552],[-80.98,29.18],[-80.53558,28.47213],[-80.53,28.04],[-80.05654,26.88],[-80.08801,26.20576],[-80.13156,25.81677],[-80.38103,25.20616],[-80.68,25.08],[-81.17213,25.20126],[-81.33,25.64],[-81.71,25.87],[-82.24,26.73],[-82.70515,27.49504],[-82.85526,27.88624],[-82.65,28.55],[-82.93,29.1],[-83.70959,29.93656],[-84.1,30.09],[-85.10882,29.63615],[-85.28784,29.68612],[-85.7731,30.15261],[-86.4,30.4],[-87.53036,30.27433],[-88.41782,30.3849],[-89.18049,30.31598],[-89.59383,30.15999],[-89.41373,29.89419],[-89.43,29.48864],[-89.21767,29.29108],[-89.40823,29.15961],[-89.77928,29.30714],[-90.15463,29.11743],[-90.88022,29.14854],[-91.62678,29.677],[-92.49906,29.5523],[-93.22637,29.78375],[-93.84842,29.71363],[-94.69,29.48],[-95.60026,28.73863],[-96.59404,28.30748],[-97.14,27.83],[-97.37,27.38],[-97.38,26.69],[-97.33,26.21],[-97.14,25.87],[-97.53,25.84],[-98.24,26.06],[-99.02,26.37],[-99.3,26.84],[-99.52,27.54],[-100.11,28.11],[-100.45584,28.69612],[-100.9576,29.38071],[-101.6624,29.7793],[-102.48,29.76],[-103.11,28.97],[-103.94,29.27],[-104.45697,29.57196],[-104.70575,30.12173],[-105.03737,30.64402],[-105.63159,31.08383],[-106.1429,31.39995],[-106.50759,31.75452],[-108.24,31.75485],[-108.24194,31.34222],[-109.035,31.34194],[-111.02361,31.33472],[-113.30498,32.03914],[-114.815,32.52528],[-114.72139,32.72083],[-115.99135,32.61239],[-117.12776,32.53534],[-117.29594,33.04622],[-117.944,33.62124],[-118.4106,33.74091],[-118.51989,34.02778],[-119.081,34.078],[-119.43884,34.34848],[-120.36778,34.44711],[-120.62286,34.60855],[-120.74433,35.15686],[-121.71457,36.16153],[-122.54747,37.55176],[-122.51201,37.78339],[-122.95319,38.11371],[-123.7272,38.95166],[-123.86517,39.76699],[-124.39807,40.3132],[-124.17886,41.14202],[-124.2137,41.99964],[-124.53284,42.76599],[-124.14214,43.70838],[-124.02053,44.6159],[-123.89893,45.52341],[-124.07963,46.86475],[-124.39567,47.72017],[-124.68721,48.18443],[-124.5661,48.37971],[-123.12,48.04],[-122.58736,47.096],[-122.34,47.36],[-122.5,48.18],[-122.84,49],[-120,49],[-117.03121,49],[-116.04818,49],[-113,49],[-110.05,49],[-107.05,49],[-104.04826,48.99986],[-100.65,49],[-97.22872,49.0007],[-95.15907,49],[-95.15609,49.38425],[-94.81758,49.38905]]],[[[-153.00631,57.11584],[-154.00509,56.73468],[-154.5164,56.99275],[-154.67099,57.4612],[-153.76278,57.81657],[-153.22873,57.96897],[-152.56479,57.90143],[-152.14115,57.59106],[-153.00631,57.11584]]],[[[-165.57916,59.90999],[-166.19277,59.75444],[-166.84834,59.94141],[-167.45528,60.21307],[-166.46779,60.38417],[-165.67443,60.29361],[-165.57916,59.90999]]],[[[-171.73166,63.78252],[-171.11443,63.59219],[-170.49111,63.69498],[-169.68251,63.43112],[-168.68944,63.29751],[-168.77194,63.1886],[-169.52944,62.97693],[-170.29056,63.19444],[-170.67139,63.37582],[-171.55306,63.31779],[-171.79111,63.40585],[-171.73166,63.78252]]],[[[-155.06779,71.14778],[-154.34417,70.69641],[-153.90001,70.88999],[-152.21001,70.82999],[-152.27,70.60001],[-150.73999,70.43002],[-149.72,70.53001],[-147.61336,70.21403],[-145.68999,70.12001],[-144.92001,69.98999],[-143.58945,70.15251],[-142.07251,69.85194],[-140.98599,69.712],[-140.9925,66.00003],[-140.99777,60.3064],[-140.013,60.27684],[-139.039,60.00001],[-138.34089,59.56211],[-137.4525,58.905],[-136.47972,59.46389],[-135.47583,59.78778],[-134.945,59.27056],[-134.27111,58.86111],[-133.35555,58.41029],[-132.73042,57.69289],[-131.70781,56.55212],[-130.00778,55.91583],[-129.97999,55.285],[-130.53611,54.80275],[-131.08582,55.17891],[-131.96721,55.49778],[-132.25001,56.37],[-133.53918,57.17889],[-134.07806,58.12307],[-135.03821,58.18771],[-136.62806,58.21221],[-137.80001,58.5],[-139.86779,59.53776],[-140.82527,59.72752],[-142.57444,60.08445],[-143.95888,59.99918],[-145.92556,60.45861],[-147.11437,60.88466],[-148.22431,60.67299],[-148.01807,59.97833],[-148.57082,59.91417],[-149.72786,59.70566],[-150.60824,59.36821],[-151.71639,59.15582],[-151.85943,59.74498],[-151.40972,60.7258],[-150.34694,61.03359],[-150.62111,61.28442],[-151.89584,60.7272],[-152.57833,60.06166],[-154.01917,59.35028],[-153.28751,58.86473],[-154.23249,58.14637],[-155.30749,57.72779],[-156.30833,57.42277],[-156.5561,56.97998],[-158.11722,56.46361],[-158.43332,55.99415],[-159.60333,55.56669],[-160.28972,55.64358],[-161.22305,55.36473],[-162.23777,55.02419],[-163.06945,54.68974],[-164.78557,54.40417],[-164.94223,54.57222],[-163.84834,55.03943],[-162.87,55.34804],[-161.80417,55.89499],[-160.5636,56.00805],[-160.07056,56.41806],[-158.68444,57.01668],[-158.4611,57.21692],[-157.72277,57.57],[-157.55027,58.32833],[-157.04167,58.91888],[-158.19473,58.6158],[-158.51722,58.78778],[-159.05861,58.42419],[-159.71167,58.93139],[-159.98129,58.57255],[-160.35527,59.07112],[-161.355,58.67084],[-161.96889,58.67166],[-162.05499,59.26693],[-161.87417,59.63362],[-162.51806,59.98972],[-163.81834,59.79806],[-164.66222,60.26748],[-165.34639,60.5075],[-165.35083,61.0739],[-166.12138,61.50002],[-165.73445,62.075],[-164.91918,62.63308],[-164.56251,63.14638],[-163.75333,63.21945],[-163.06722,63.05946],[-162.26056,63.54194],[-161.53445,63.45582],[-160.77251,63.76611],[-160.95834,64.2228],[-161.51807,64.40279],[-160.77778,64.7886],[-161.39193,64.77724],[-162.45305,64.55944],[-162.75779,64.33861],[-163.54639,64.55916],[-164.96083,64.44695],[-166.42529,64.68667],[-166.845,65.0889],[-168.11056,65.67],[-166.70527,66.08832],[-164.47471,66.57666],[-163.65251,66.57666],[-163.7886,66.07721],[-161.67777,66.11612],[-162.48971,66.73557],[-163.71972,67.11639],[-164.43099,67.61634],[-165.39029,68.04277],[-166.76444,68.35888],[-166.20471,68.88303],[-164.43081,68.91554],[-163.16861,69.37111],[-162.93057,69.85806],[-161.9089,70.33333],[-160.9348,70.44769],[-159.03918,70.89164],[-158.11972,70.82472],[-156.58082,71.35776],[-155.06779,71.14778]]]]},\"properties\":{\"name\":\"United States\"}}]}","volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":868977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":868979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256510,"text":"70256510 - 2023 - Hypoxia and anoxia tolerance in diploid and triploid eastern oysters at high temperature","interactions":[],"lastModifiedDate":"2024-08-20T22:55:32.64562","indexId":"70256510","displayToPublicDate":"2023-04-06T17:52:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Hypoxia and anoxia tolerance in diploid and triploid eastern oysters at high temperature","docAbstract":"Increasing reliance on the use of triploid oysters to support aquaculture production relies on their generally superior growth rate and meat quality over that of diploid oysters. Reports of elevated triploid mortality have generated questions about potential trade-offs between growth and tolerance to environmental stressors. These questions are particularly relevant as climate change, coastal activities, and river management impact water salinity, temperature, nutrients, pH, and oxygen levels within key estuarine oyster growing areas. In particular, the co-occurrence of warm water temperatures and low dissolved oxygen concentration (DO) events are increasingly reported in estuaries, with potentially lethal impacts on sessile, oyster resources. To investigate potential differences in DO tolerance, diploid and triploid market-sized or seed oysters were exposed to continuous normoxia (DO > 5.0 mg L–1), hypoxia (DO < 2.0 mg L–1), and anoxia (DO < 0.5 mg L–1) at 28°C and their mortalities were monitored. The hemolymph of the market-sized oysters was collected to measure cellular and biochemical changes in response to hypoxia and anoxia, whereas their valve movements were also measured. In general, about half of market-sized oysters died within about 1 wk under anoxia (LT50: 5.7–8.9 days) and within about 2 wk under hypoxia (LT50: 11.9–19.4 days) with diploid oysters tending to die faster than triploid oysters. Seed oysters took longer to die than market-sized oysters under both anoxia (LT50: 9.5–12.1 days) and hypoxia (LT50: 21.8–25.0 days) with diploid oysters (LT50: 9.5–11.8 days) dying slightly faster than triploid oysters (LT50: 11.8–12.1 days) under anoxia. Hemolymph pH decreased and plasma calcium and glutathione concentrations increased with decreasing DO, with values under anoxia being different than those under normoxia. Hemocyte density was also lower under anoxia than under either normoxia or hypoxia. Overall, few differences in physiological responses to hypoxia and anoxia were found between diploid and triploid oysters suggesting that ploidy (2N versus 3N) had limited effect on the tolerance and response of eastern oysters to low DO.
Here we show how ultra-high resolution seabed mapping using new technology can help to understand processes that sculpt submarine canyons. Time-lapse seafloor surveys were conducted in the axis of Monterey Canyon, ∼50 km from the canyon head (∼1,840 m water depth) over an 18-month period. These surveys comprised 5-cm resolution multibeam bathymetry, 1-cm resolution lidar bathymetry, and 2-mm resolution stereophotographic imagery. Bathymetry data reveal centimeter-scale textures that would be undetectable by more traditional survey methods. Upward-looking Acoustic Doppler Current Profilers at the site recorded the flow character of internal tides and the passage of three turbidity currents, while sediment cores collected from the site record flow deposits. Combined with flow and core data, the bathymetry shows how turbidity currents and internal tides modify the seabed. The turbidity currents drape sediment across the site, infilling bedform troughs and smoothing erosional features carved by the internal tides (e.g., rippled scours). Turbidity currents with speeds of 0.9–3.3 m/s failed to cause notable bedform movement, which is surprising given that flows with similar speeds produced rapid bedform migration elsewhere, including the upper Monterey Canyon. The lack of migration may be related to the character of the underlying substrate or indicate that turbidity currents at the site lack dense, near-bed layers. The scale of scours produced by the internal tides (≤0.7 m/s) approaches the scale of features recorded in the ancient rock record. Thus, these results illustrate how the scale gap between seabed mapping technology and the rock record may eventually be bridged.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF006705","usgsCitation":"Wolfson-Schwehr, M., Paull, C.K., Caress, D.W., Gwiazda, R., Nieminski, N.M., Talling, P.J., Carvajal, C., Simmons, S.M., and Troni, G., 2023, Time-lapse seafloor surveys reveal how turbidity currents and internal tides in Monterey Canyon interact with the seabed at centimeter-scale: Journal of Geophysical Research: Earth Surface, v. 128, no. 4, e2022JF006705, 22 p., https://doi.org/10.1029/2022JF006705.","productDescription":"e2022JF006705, 22 p.","ipdsId":"IP-136210","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443928,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jf006705","text":"Publisher Index Page"},{"id":417402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.095833,\n 36.704167\n ],\n [\n -122.095833,\n 36.7\n ],\n [\n -122.0875,\n 36.7\n ],\n [\n -122.0875,\n 36.704167\n ],\n [\n -122.095833,\n 36.704167\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Wolfson-Schwehr, Monica","contributorId":175112,"corporation":false,"usgs":false,"family":"Wolfson-Schwehr","given":"Monica","email":"","affiliations":[],"preferred":false,"id":873579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":873580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":873581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gwiazda, Roberto","contributorId":147193,"corporation":false,"usgs":false,"family":"Gwiazda","given":"Roberto","email":"","affiliations":[{"id":13620,"text":"Monterey Bay Aquarium Research Institute, Moss Landing, California","active":true,"usgs":false}],"preferred":false,"id":873582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nieminski, Nora Maria 0000-0002-4465-8731","orcid":"https://orcid.org/0000-0002-4465-8731","contributorId":279764,"corporation":false,"usgs":true,"family":"Nieminski","given":"Nora","email":"","middleInitial":"Maria","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":873583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talling, Peter J.","contributorId":195515,"corporation":false,"usgs":false,"family":"Talling","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":873584,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carvajal, Cristian","contributorId":204133,"corporation":false,"usgs":false,"family":"Carvajal","given":"Cristian","email":"","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":873585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Simmons, Stephen M.","contributorId":305699,"corporation":false,"usgs":false,"family":"Simmons","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":40174,"text":"University of Hull","active":true,"usgs":false}],"preferred":false,"id":873586,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Troni, Giancarlo","contributorId":305700,"corporation":false,"usgs":false,"family":"Troni","given":"Giancarlo","email":"","affiliations":[{"id":66274,"text":"Pontifica Universidad Catolica de Chile","active":true,"usgs":false}],"preferred":false,"id":873587,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70242689,"text":"70242689 - 2023 - Planktic foraminifera","interactions":[],"lastModifiedDate":"2023-04-18T13:28:58.734306","indexId":"70242689","displayToPublicDate":"2023-04-06T08:27:29","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Planktic foraminifera","docAbstract":"Planktic foraminifera are single-celled marine organisms that secrete calcium carbonate tests. They live in the ocean's photic zone, and when they die, their tests, each about the size of a grain of sand, collect on the ocean floor. The geographic distribution of planktic foraminifera is mostly governed by the temperature and salinity of the ocean surface, and species assemblages are generally arranged in latitudinal bands from polar to tropical, with more species occupying warmer waters. Their ubiquity in the world's oceans since the Cretaceous Period makes them ideal biostratigraphic markers, and their sensitivity to environmental changes makes them excellent proxies of past ecological, oceanographic and climatic history.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-323-99931-1.00041-6","usgsCitation":"Dowsett, H., and Robinson, M., 2023, Planktic foraminifera, chap. of Reference module in earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-323-99931-1.00041-6.","productDescription":"HTML Document","ipdsId":"IP-149364","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":415912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dowsett, Harry J. 0000-0003-1983-7524","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":261665,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":869378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":261664,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":869379,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242657,"text":"70242657 - 2023 - Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate","interactions":[],"lastModifiedDate":"2023-10-11T15:17:00.654848","indexId":"70242657","displayToPublicDate":"2023-04-06T06:58:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate","docAbstract":"Scientists, resource managers, and decision-makers increasingly use knowledge co-production to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley, USA to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We co-produced scenario narratives, spatially-explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We document our co-production process, and using the co-produced models, we ask: “when and where do management actions make a difference?” and “when does climate override these actions?” The outcomes of this process provide lessons learned on how to co-create usable information and how to increase climate adaptive capacity in a highly managed landscape. We found that: 1) actions to restore wetlands and prioritize their water supply create habitat outcomes resilient to climate change impacts particularly in March, when habitat is most limited, 2) land protection combined with management can increase the ecosystem's resilience to climate change, and 3) the uptake and use of this information was influenced by the roles of different stakeholders, plus rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. While a broad stakeholder group contributed knowledge to scenario narratives and model development, to co-produce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped to build legitimacy, yet broad-scale use of climate adaptation knowledge will depend on state and local policies, engagement with decision-makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.14089","usgsCitation":"Byrd, K.B., Matchett, E., Mengelt, C., Wilson, T., DiPietro, D., Moritsch, M., Conlisk, E., Veloz, S., Casazza, M.L., and Reiter, M., 2023, Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate: Conservation Biology, v. 37, no. 5, e14089, 12 p., https://doi.org/10.1111/cobi.14089.","productDescription":"e14089, 12 p.","ipdsId":"IP-145413","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":499259,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/cobi.14089","text":"Publisher Index Page"},{"id":415649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.5,\n 39.75\n ],\n [\n -122.5,\n 35.5\n ],\n [\n -118.5,\n 35.5\n ],\n [\n -118.5,\n 39.75\n ],\n [\n -122.5,\n 39.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":869233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mengelt, Claudia 0000-0001-7869-5170","orcid":"https://orcid.org/0000-0001-7869-5170","contributorId":304087,"corporation":false,"usgs":true,"family":"Mengelt","given":"Claudia","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":869234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":869235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiPietro, Deanne","contributorId":304089,"corporation":false,"usgs":false,"family":"DiPietro","given":"Deanne","email":"","affiliations":[{"id":38279,"text":"Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":869236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moritsch, Monica","contributorId":304091,"corporation":false,"usgs":false,"family":"Moritsch","given":"Monica","affiliations":[{"id":65966,"text":"EDF","active":true,"usgs":false}],"preferred":false,"id":869237,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conlisk, Erin","contributorId":304092,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":869238,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Veloz, Sam","contributorId":304093,"corporation":false,"usgs":false,"family":"Veloz","given":"Sam","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":869239,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":869240,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reiter, Matthew","contributorId":304094,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":869241,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70243009,"text":"70243009 - 2023 - Paired Air and Stream Temperature Analysis (PASTA) to evaluate groundwater influence on streams","interactions":[],"lastModifiedDate":"2023-04-26T11:44:11.020493","indexId":"70243009","displayToPublicDate":"2023-04-06T06:42:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Paired Air and Stream Temperature Analysis (PASTA) to evaluate groundwater influence on streams","docAbstract":"Groundwater is critical for maintaining stream baseflow and thermal stability; however, the influence of groundwater on streamflow has been difficult to evaluate at broad spatial scales. Techniques such as baseflow separation necessitate streamflow records and do not directly indicate whether groundwater inflow may be sourced from more dynamic shallow flowpaths. We present a web tool application PASTA (Paired Air and Stream Temperature Analysis; https://cuahsi.shinyapps.io/pasta/) that capitalizes on increased public stream temperature data availability and large-scale, gridded climate observations to provide new and efficient insights regarding relative groundwater influence on streams. PASTA analyzes paired air and stream water temperature signals to evaluate spatiotemporal patterns in stream thermal sensitivity and relative groundwater influence, including inference regarding the dominant source groundwater depth (shallow or deep (i.e., approximately >6 m depth)). The tool is linked to publicly available stream temperature datasets and accepts user-uploaded datasets. As local air temperature is not often monitored, PASTA pulls daily air temperature data from the comprehensive Daymet products when directly measured data are unavailable, allowing the repurposing of existing stream temperature data. After data are selected or uploaded, the tool (a) fits sinusoidal curves of daily stream and air temperatures by year (water or calendar) to indicate groundwater influence characteristics and (b) performs linear regressions for stream versus air temperatures to indicate stream thermal sensitivity. Results are exported in ASCII file format, creating an efficient and approachable analysis tool for the adoption of newly developed heat tracing analysis from stream reach to landscape scales.
The presence of taliks (perennially unfrozen zones in permafrost areas) adversely affects the thermal stability of infrastructure in cold regions, including roads. The role of heat advection on talik development and feedback on permafrost degradation has not been quantified methodically in this context. We incorporate a surface energy balance model into a coupled groundwater flow and energy transport numerical model (SUTRA-ice). The model, calibrated with long-term observations (1997–2018 on the Alaska Highway), is used to investigate and quantify the role of heat advection on talik initiation and development under a road embankment. Over the 25-year simulation period, the new model is driven by reconstructed meteorological data and has a good agreement with near surface soil temperatures. The model successfully reproduces the increasing depth to the permafrost table (mean absolute error <0.2 m), and talik development. The results demonstrate that heat advection provides an additional energy source that expedites the rate of permafrost thaw and roughly doubles the rate of permafrost table deepening, compared to purely conductive thawing. Talik initially formed and grew over time under the combined effect of water flow, snow insulation, road construction and climate warming. Talik formation creates a new thermal state under the road embankment, resulting in acceleration of underlying permafrost degradation, due to the positive feedback of heat accumulation created by trapped unfrozen water. In a changing climate, mobile water flow will play a more important role in permafrost thaw and talik development under road embankments, and is likely to significantly increase maintenance costs and reduce the long-term stability of the infrastructure.
Acoustic telemetry is a commonly used technology to monitor animal occupancy and infer movement in aquatic environments. The information that acoustic telemetry provides is vital for spatial planning and management decisions concerning aquatic and coastal environments by characterizing behaviors and habitats such as spawning aggregations, migrations, corridors, and nurseries, among others. However, performance of acoustic telemetry equipment and resulting detection ranges and efficiencies can vary as a function of environmental conditions, leading to potentially biased interpretations of telemetry data. Here, we characterize variation in detection performance using an acoustic telemetry receiver array deployed in Wellfleet Harbor, Massachusetts, USA from 2015 to 2017. The array was designed to study benthic invertebrate movements and provided an in situ opportunity to identify factors driving variation in detection probability.
The near-shore location proximate to environmental monitoring allowed for a detailed examination of factors influencing detection efficiency in a range-testing experiment. Detection ranges varied from < 50 to 1,500 m and efficiencies varied from 0 to 100% within those detection ranges. Detection efficiency was affected by distance, wind speed and direction, wave height and direction, water temperature, water depth, and water quality.
Performance of acoustic telemetry systems is strongly contingent on environmental conditions. Our study found that wind, waves, water temperature, water quality, and depth all affected performance to an extent that could seriously compromise a study if these effects were not taken into consideration. Other unmeasured factors may also be important, depending on the characteristics of each site. This information can help guide future telemetry study designs by helping researchers anticipate the density of receivers required to achieve study objectives. Researchers can further refine and document the reliability of their data by incorporating continuously deployed range-testing tags and prior knowledge on varying detection efficiency into movement and occupancy models.
","language":"English","publisher":"Springer","doi":"10.1186/s40317-023-00317-2","usgsCitation":"Long, M., Jordaan, A., and Castro-Santos, T.R., 2023, Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation: Animal Biotelemetry, v. 11, 18, 13 p., https://doi.org/10.1186/s40317-023-00317-2.","productDescription":"18, 13 p.","ipdsId":"IP-141767","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-023-00317-2","text":"Publisher Index Page"},{"id":416951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.12152378095689,\n 41.97721573790295\n ],\n [\n -70.12152378095689,\n 41.80349781857885\n ],\n [\n -69.90189169540182,\n 41.80349781857885\n ],\n [\n -69.90189169540182,\n 41.97721573790295\n ],\n [\n -70.12152378095689,\n 41.97721573790295\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Michael 0000-0001-6735-6878","orcid":"https://orcid.org/0000-0001-6735-6878","contributorId":261905,"corporation":false,"usgs":false,"family":"Long","given":"Michael","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":872227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":872228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":872229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242660,"text":"70242660 - 2023 - Observed and projected functional reorganization of riverine fish assemblages from global change","interactions":[],"lastModifiedDate":"2023-06-09T15:14:17.319867","indexId":"70242660","displayToPublicDate":"2023-04-06T06:34:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Observed and projected functional reorganization of riverine fish assemblages from global change","docAbstract":"Climate and land-use/land-cover change (‘global change’) are restructuring biodiversity, globally. Broadly, environmental conditions are expected to become warmer, potentially drier (particularly in arid regions), and more anthropogenically developed in the future, with spatiotemporally complex effects on ecological communities. We used functional traits to inform Chesapeake Bay Watershed fish responses to future climate and land-use scenarios (2030, 2060, and 2090). We modelled the future habitat suitability of focal species representative of key trait axes (substrate, flow, temperature, reproduction, and trophic) and used functional and phylogenetic metrics to assess variable assemblage responses across physiographic regions and habitat sizes (headwaters through large rivers). Our focal species analysis projected future habitat suitability gains for carnivorous species with preferences for warm water, pool habitats, and fine or vegetated substrates. At the assemblage level, models projected decreasing habitat suitability for cold-water, rheophilic, and lithophilic individuals but increasing suitability for carnivores in the future across all regions. Projected responses of functional and phylogenetic diversity and redundancy differed among regions. Lowland regions were projected to become less functionally and phylogenetically diverse and more redundant while upland regions (and smaller habitat sizes) were projected to become more diverse and less redundant. Next, we assessed how this model projected assemblage changes 2005-2030 related to observed time-series trends (1999–2016). Halfway through the initial projecting period (2005–2030), we found observed trends broadly followed modelled patterns of increasing proportions of carnivorous and lithophilic individuals in lowland regions but showed opposing patterns for functional and phylogenetic metrics. Leveraging observed and predicted analyses simultaneously helps elucidate the instances and causes of discrepancies between model predictions and ongoing observed changes. Collectively, results highlight the complexity of global change impacts across broad landscapes that likely relate to differences in assemblages’ intrinsic sensitivities and external exposure to stressors.
Salinity is known to affect drinking-water supplies and damage irrigated agricultural lands. Selenium in high concentrations is harmful to fish and other wildlife. Land managers, water providers, and agricultural producers in the lower Gunnison River Basin in western Colorado expend resources mitigating the effects of these constituents. The U.S. Geological Survey revised existing salinity (total dissolved solids) and selenium models for the lower Gunnison River Basin in an attempt to better identify areas of greatest salinity and selenium yield. This effort developed maps of yields predicted from multiple linear regression (MLR) models for the lower Gunnison River Basin. The models included data for irrigation and nonirrigation seasons and two periods, 1992–2004 and 2005–13.
Concentrations of salinity and selenium and discharge measurements made at the time of sampling were used to compute loads for subbasins (component drainages of the larger lower Gunnison River Basin study area), which were adjusted for inflows and outflows of canal loads. Load regression equations were determined from explanatory basin characteristics that included physical properties, precipitation, land use and cover, surficial deposits (soil and unconsolidated geologic materials), and bedrock geology. Loads of salinity and selenium were converted to yields by using the subbasin drainage areas, and an empirical Bayesian kriging procedure was used to produce robust grids of yields for salinity and selenium.
Salinity yields ranged from 0.00667 to 6.564 tons per year per acre. The highest salinity yields, greater than about 5.0 tons per year per acre, are predicted on the western side of the Uncompahgre River upstream from Delta, Colorado, an area with a high density of irrigated land. The selenium yield map shows a similar pattern, but the highest yields are somewhat more confined to the eastern side of the lower Uncompahgre River and south of the Gunnison River near the confluence with the Uncompahgre River at Delta, Colorado. Selenium yields ranged from 2.6888 x 10-10 to 0.000445 pounds per day per acre. The highest predicted selenium yields, greater than 0.0003 pounds per day per acre, were in the area downstream from Montrose, Colorado, on the eastern side of the Uncompahgre River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20235013","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Colorado Water Conservation Board","usgsCitation":"Williams, C.A., Gidley, R.G., and Stevens, M.R., 2023, Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013: U.S. Geological Survey Scientific Investigations Report 2023–5013, 37 p., https://doi.org/10.3133/sir20235013.","productDescription":"Report: vi, 37 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-127438","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":415136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CW7Q1N","text":"USGS data release","linkHelpText":"Basin Characteristics and Salinity and Selenium Loads and Yields for Selected Subbasins in the Lower Gunnison River Basin, Western Colorado, 1992─2013"},{"id":415232,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5013/images"},{"id":415233,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5013/sir20235013.xml"},{"id":415255,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235013/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5013"},{"id":415135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5013/sir20235013.pdf","text":"Report","size":"13.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5013"},{"id":415134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5013/coverthb.jpg"},{"id":415137,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"},{"id":500707,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114651.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.66041487616633,\n 38.99638415429618\n ],\n [\n -108.6616273692395,\n 39.00186401594732\n ],\n [\n -108.6616273692395,\n 38.9967055439632\n ],\n [\n -108.6881779535584,\n 38.77194822283556\n ],\n [\n -108.58197561628282,\n 38.556862390281765\n ],\n [\n -108.19035825380965,\n 38.16912358075567\n ],\n [\n -108.12730061605224,\n 37.915589610235415\n ],\n [\n -107.96135946405924,\n 37.80029529902727\n ],\n [\n -107.76886772774775,\n 37.81078405090291\n ],\n [\n -107.61846017361093,\n 38.26998042097301\n ],\n [\n -107.25524694190712,\n 38.623585049765126\n ],\n [\n -107.0055365452011,\n 38.85181039167898\n ],\n [\n -106.90464345562309,\n 38.99114000809618\n ],\n [\n -106.95004534593326,\n 39.07538965450817\n ],\n [\n -107.02178619634307,\n 39.241636232003856\n ],\n [\n -107.71852594996861,\n 39.17165133541914\n ],\n [\n -108.1185061789019,\n 39.03147242299278\n ],\n [\n -108.37655793950398,\n 38.98134099584442\n ],\n [\n -108.55719417192573,\n 39.05652481206508\n ],\n [\n -108.66041487616633,\n 38.99638415429618\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Submersed aquatic vegetation (SAV) plays an important role in ecosystems. Inventories of SAV spatial distribution and composition are important for monitoring changes in SAV. In this study, we compared three common SAV sampling methods to quantify SAV in western Lake Erie. Aerial imagery of near-shore areas in western Lake Erie was classified using object-based image analysis (OBIA) and evaluated against field-based surveys using single-beam sonar or rake samples. To assess variation among methods, data were assigned either vegetation ‘presence’ or ‘absence’ and compared for simple correspondence and agreement (Cohen’s Kappa, κ). The two field-based methods had the highest correspondence at 78% (n = 782) and the highest κ = 0.545. Correspondence between OBIA and rake surveys was 69% (n = 245) and κ = 0.36. Correspondence between OBIA and hydroacoustics was the lowest of 54% (n = 30,768) with an agreement of κ = 0.17. Environmental factors such as water turbidity may have played a role in reduced agreement between OBIA and field methods. Determining the optimal method or combination of methods will depend upon research goals, effort, and cost, but each method can provide reliable SAV information for resource management.
To inform responsible energy development, it is important to understand the ecological effects of contamination events. Wastewaters, a common byproduct of oil and gas extraction, often contain high concentrations of sodium chloride (NaCl) and heavy metals (e.g., strontium and vanadium). These constituents can negatively affect aquatic organisms, but there is scarce information for how wastewaters influence potentially distinct microbiomes in wetland ecosystems. Additionally, few studies have concomitantly investigated effects of wastewaters on the habitat (water and sediment) and skin microbiomes of amphibians or relationships among these microbial communities. We sampled microbiomes of water, sediment, and skin of four larval amphibian species across a gradient of chloride contamination (0.04–17,500 mg/L Cl) in the Prairie Pothole Region of North America. We detected 3129 genetic phylotypes and 68 % of those phylotypes were shared among the three sample types. The most common shared phylotypes were Proteobacteria, Firmicutes, and Bacteroidetes. Salinity of wastewaters increased dissimilarity within all three microbial communities, but not the diversity or richness of water and skin microbial communities. Strontium was associated with lower diversity and richness of sediment microbial communities, but not those of water or amphibian skin, likely because metal deposition occurs in sediment when wetlands dry. Based on Bray Curtis distance matrices, sediment microbiomes were similar to those of water, but neither had substantial overlap with amphibian microbiomes. Species identity was the strongest predictor of amphibian microbiomes; frog microbiomes were similar but differed from that of the salamander, whose microbiome had the lowest richness and diversity. Understanding how effects of wastewaters on the dissimilarity, richness, and diversity of microbial communities also influence the ecosystem function of communities will be an important next step. However, our study provides novel insight into the characteristics of, and associations among, different wetland microbial communities and effects of wastewaters from energy production.