On February 9–10, 2022, the Pacific States Marine Fisheries Commission, U.S. Fish and Wildlife Service, U.S. Geological Survey, and Washington State University hosted a workshop to establish research priorities that support the implementation of action items listed in a current invasive species management plan, the Quagga and Zebra Mussel Action Plan (QZAP) 2.0, that are intended to limit the establishment and spread of quagga and zebra mussels in the western United States. The workshop focus was on developing research priorities for the thematic areas that are addressed in QZAP 2.0: 1) early detection monitoring, 2) prevention and containment, 3) control and management, and 4) rapid response. In addition, research priorities were developed for a fifth thematic area that addressed dreissenid mussel biology. Forty scientists participated in the two-day workshop. Prior to the workshop, participants were asked to review and rank research priorities that were established for a previous version of the QZAP and to offer suggestions on emerging research priorities. During the workshop, subject matter experts presented information describing current knowledge of research and information associated with the thematic areas of early detection monitoring, prevention and containment, rapid response, control and management, and biology in the context of strategies and actions listed in QZAP 2.0. The rankings of previous research priorities and suggestions of emerging priorities were then reviewed, and a revised list of research priorities was formed. The list of research priorities is presented by thematic area.
","language":"English","publisher":"Reabic","doi":"10.3391/mbi.2023.14.3.05","usgsCitation":"Counihan, T., DeBruyckere, L., Bollens, S., Phillips, S., Thom, T., and Shemai, B., 2023, Identifying research in support of the management and control of dreissenid mussels in the western United States: Management of Biological Invasions, v. 14, no. 3, p. 459-466, https://doi.org/10.3391/mbi.2023.14.3.05.","productDescription":"8 p.","startPage":"459","endPage":"466","ipdsId":"IP-144926","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":444381,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2023.14.3.05","text":"Publisher Index Page"},{"id":421067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Counihan, Timothy D. 0000-0003-4967-6514","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":207532,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":883831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeBruyckere, Lisa","contributorId":207531,"corporation":false,"usgs":false,"family":"DeBruyckere","given":"Lisa","email":"","affiliations":[{"id":37555,"text":"Creative Resource Strategies, LLC","active":true,"usgs":false}],"preferred":false,"id":883832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bollens, Stephen M.","contributorId":181850,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen M.","affiliations":[],"preferred":false,"id":883833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Stephen","contributorId":156280,"corporation":false,"usgs":false,"family":"Phillips","given":"Stephen","affiliations":[{"id":20304,"text":"Pacific States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":883834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thom, Theresa","contributorId":224436,"corporation":false,"usgs":false,"family":"Thom","given":"Theresa","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":883835,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shemai, Barak","contributorId":330000,"corporation":false,"usgs":false,"family":"Shemai","given":"Barak","email":"","affiliations":[{"id":78764,"text":"U.S. Fish and Wildlife Service - Southwest Region Aquatic Invasive Species Coordinator Box 1306. Albuquerque, NM 87103","active":true,"usgs":false}],"preferred":false,"id":883836,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241040,"text":"70241040 - 2023 - Incorporation of real-time earthquake magnitudes estimated via peak ground displacement scaling in the ShakeAlert Earthquake Early Warning system","interactions":[],"lastModifiedDate":"2023-05-25T15:50:57.475532","indexId":"70241040","displayToPublicDate":"2023-02-23T07:19:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Incorporation of real-time earthquake magnitudes estimated via peak ground displacement scaling in the ShakeAlert Earthquake Early Warning system","docAbstract":"The United States earthquake early warning (EEW) system, ShakeAlert®, currently employs two algorithms based on seismic data alone to characterize the earthquake source, reporting the weighted average of their magnitude estimates. Nonsaturating magnitude estimates derived in real time from Global Navigation Satellite System (GNSS) data using peak ground displacement (PGD) scaling relationships offer complementary information with the potential to improve EEW reliability for large earthquakes. We have adapted a method that estimates magnitude from PGD (Crowell et al., 2016) for possible production use by ShakeAlert. To evaluate the potential contribution of the modified algorithm, we installed it on the ShakeAlert development system for real‐time operation and for retrospective analyses using a suite of GNSS data that we compiled. Because of the colored noise structure of typical real‐time GNSS positions, observed PGD values drift over time periods relevant to EEW. To mitigate this effect, we implemented logic within the modified algorithm to control when it issues initial and updated PGD‐derived magnitude estimates (
The U.S. Geological Survey, in cooperation with the Macoupin County Soil and Water Conservation District and the American Farmland Trust, undertook a monitoring effort from 2017 to 2021 in the upper Macoupin Creek watershed. The monitoring effort was to determine and characterize nitrogen, phosphorus, and suspended-sediment concentrations, loads, and yields for a 566.7 square kilometer area of the Macoupin Creek watershed at two locations on upper Macoupin Creek bracketing a segment of the watershed where increased implementation of conservation land-use practices was planned. Two monitoring stations were established, consisting of an upstream site (Macoupin Creek at Highway 108 near Carlinville, Illinois; U.S. Geological Survey streamgage 05586647) and a downstream site (Macoupin Creek at Highway 111 near Summerville, Ill.; U.S. Geological Survey streamgage 05586745). Data collected at these stations included continuous stream discharge and periodic samples for nutrients and suspended sediment. A Weighted Regressions on Time, Discharge, and Season–Kalman model was implemented to estimate daily concentrations for nitrate plus nitrite, total phosphorus, and suspended sediment for both monitoring stations. These daily concentrations were used in conjunction with the continuous stream discharge data to derive estimates of constituent flux, loads, and yields.
During the study period, the study area subbasin of the upper Macoupin Creek watershed reduced downstream nitrate and total phosphorus cummulative yields by approximately 54 and 21 percent, respectively; however, the cummulative yield of suspended sediment increased by approximately 10 percent from inputs within the study area. These data indicate that nitrate and phosphorus transport is greater from the upstream subbasin and being diluted in the combined subbasin by lower transport from the study area, whereas suspended sediment is being contributed from the study area reach, presumably through surface runoff and streambank and streambed erosion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225131","collaboration":"Prepared in cooperation with the Macoupin County Soil and Water Conservation District and American Farmland Trust","usgsCitation":"Garcia, L.A., Terrio, P.J., and Manaster, A.E., 2023, Nutrient and suspended-sediment concentrations, loads, and yields in upper Macoupin Creek, Illinois, 2017–21: U.S. Geological Survey Scientific Investigations Report 2022–5131, 17 p., https://doi.org/10.3133/sir20225131.","productDescription":"Report: vii, 17 p.; Data Release; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-144304","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":413286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5131/images"},{"id":413285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":413284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5131/sir20225131.pdf","text":"Report","size":"2.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5131"},{"id":499487,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114379.htm","linkFileType":{"id":5,"text":"html"}},{"id":413345,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225131/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413289,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":413283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5131/coverthb.jpg"},{"id":413288,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IC7QS","text":"USGS data release","linkHelpText":"Nutrient and sediment concentrations, loads, and yields in the Upper Macoupin Creek watershed, water years 2018–2021"}],"country":"United States","state":"Illinois","otherGeospatial":"Upper Macoupin Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.666,\n 39.5\n ],\n [\n -90.666,\n 39\n ],\n [\n -89.5,\n 39\n ],\n [\n -89.5,\n 39.5\n ],\n [\n -90.666,\n 39.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The Drinking Water Protection Section of the Minnesota Department of Health conducted reconnaissance monitoring of selected public water systems in Minnesota. Funding was obtained primarily from the Environment and Natural Resources Trust Fund. Sampling was conducted in 2019 and 2021. Laboratory analysis of samples was conducted for a variety of different contaminants of emerging concern (CECs), including selected pharmaceuticals, pesticides, PFAS, wastewater indicators and other parameters chosen for the physical and land use setting surrounding the sampling points. Sampling site and parameter selection were designed with several goals, as follows: Characterize occurrence and distribution of selected CECs in settings where such chemicals are most likely to be present; Determine if any such occurrences represent a public health concern; Compare results from coupled source water and finished (i.e., treated) water samples at public water system sites where such sampling is feasible; Assess if results from geologically vulnerable (sensitive subject to rapid recharge) and geologically non-vulnerable settings differ significantly. 306 samples were collected as part of the study, from three networks of public water systems differentiated on the basis of source water type (i.e., surface water or groundwater) and land use environment (agricultural and wastewater influenced). This report provides a preliminary, qualitative evaluation of the results. Additionally, more rigorous research will be conducted on these water quality data to evaluate the below findings in more detail. High-level findings from this assessment include the following: Very few samples exceeded health-based guidance for CECs; o When this occurred, MDH staff conducted follow up sampling at the system and provided technical advice about managing the situation. Only a fraction of the CECs analyzed were detected; o Of the 522 different CECs analyzed in the water samples, 161 were detected in one or more samples; o Additionally, most detections were at low levels; Among the CEC classes included in the analytical work, pesticides and PFAS were generally detected at a greater frequency than other CECs; o See Executive Summary Figure 1. The ten most commonly detected individual compounds include: o Tribromomethane, or bromoform, (a disinfection by-product) (70% of sites where analyzed); o norgestrel (a pharmaceutical) (69% of sites where analyzed); o lithium (68% of sites where analyzed); o Metolachlor SA (52%), Deethylatrazine (49%), atrazine (45%), and deisopropylatrazine (31%) (pesticides); o PFBA (44%) and PFHxS (27%) (PFAS compounds); and o 5-methyl benzotriazole (29%) (a benzotriazole). Some CECs were detected more frequently in samples collected from surface waters than those collected from groundwater sources; CEC concentrations were generally higher in vulnerable settings compared to nonvulnerable settings; Whether CECs were detected more frequently in the source water or finished water varied by CEC class. For example, o Benzotriazoles and pharmaceuticals were more frequently detected in source water samples than finished water samples; and o Tribromomethane, or bromoform, a common disinfection by-product, was more frequently found in finished water samples than in source water samples. This work prompted a series of programmatic changes and innovations: A response framework was established for helping the program and public water systems manage detections of unregulated CECs in drinking water; Results were forwarded to the program within MDH responsible for developing healthbased guidance in order to nominate specific compounds found in drinking water but for which limited or no risk advice is available; MDH is seeking support from the Clean Water Council to support the establishment of permanent capacity within the Drinking Water Protection Section to continue sampling efforts of this type.
","language":"English","publisher":"Minnesota Department of Health","collaboration":"Minnesota Department of Health, Minnesota Environment and Natural Resources Trust Fund","usgsCitation":"de Lambert, J., Overbo, A., Robertson, S., and Elliott, S.M., 2023, Data summary report: Unregulated contaminants monitoring project, 85 p.","productDescription":"85 p.","ipdsId":"IP-145896","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414813,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414798,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.health.state.mn.us/communities/environment/water/docs/ucmpreport.pdf"}],"country":"United States","state":"Minnesota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.204691,46.704041],[-92.205192,46.698341],[-92.183091,46.695241],[-92.176091,46.686341],[-92.204092,46.666941],[-92.201592,46.656641],[-92.207092,46.651941],[-92.242493,46.649241],[-92.256592,46.658741],[-92.270592,46.650741],[-92.274392,46.657441],[-92.286192,46.660342],[-92.287392,46.667342],[-92.291292,46.668142],[-92.292192,46.663308],[-92.294033,46.074377],[-92.332912,46.062697],[-92.35176,46.015685],[-92.372717,46.014198],[-92.410649,46.027259],[-92.428555,46.024241],[-92.442259,46.016177],[-92.453373,45.992913],[-92.464512,45.985038],[-92.461138,45.980216],[-92.469354,45.973811],[-92.527052,45.983245],[-92.548459,45.969056],[-92.551186,45.95224],[-92.60246,45.940815],[-92.614314,45.934529],[-92.638824,45.934166],[-92.638474,45.925971],[-92.659549,45.922937],[-92.676167,45.912072],[-92.675737,45.907478],[-92.707702,45.894901],[-92.734039,45.868108],[-92.739278,45.84758],[-92.765146,45.830183],[-92.757815,45.806574],[-92.776496,45.790014],[-92.784621,45.764196],[-92.809837,45.744172],[-92.869193,45.717568],[-92.870025,45.697272],[-92.875488,45.689014],[-92.887929,45.639006],[-92.882529,45.610216],[-92.886442,45.598679],[-92.883749,45.575483],[-92.871082,45.567581],[-92.823309,45.560934],[-92.770223,45.566939],[-92.726082,45.541112],[-92.726677,45.514462],[-92.702224,45.493046],[-92.680234,45.464344],[-92.653549,45.455346],[-92.646602,45.441635],[-92.650422,45.398507],[-92.664102,45.393309],[-92.676961,45.380137],[-92.678223,45.373604],[-92.70272,45.358472],[-92.698967,45.336374],[-92.709968,45.321302],[-92.737122,45.300459],[-92.761013,45.289028],[-92.760615,45.278827],[-92.751659,45.26591],[-92.760249,45.2496],[-92.751708,45.218666],[-92.763908,45.204866],[-92.767408,45.190166],[-92.764872,45.182812],[-92.752404,45.173916],[-92.757707,45.155466],[-92.739584,45.115598],[-92.744938,45.108309],[-92.791528,45.079647],[-92.803079,45.060978],[-92.793282,45.047178],[-92.770362,45.033803],[-92.76206,45.02432],[-92.771231,45.001378],[-92.769445,44.97215],[-92.754603,44.955767],[-92.750645,44.937299],[-92.758701,44.908979],[-92.774571,44.898084],[-92.773946,44.889997],[-92.764133,44.875905],[-92.769102,44.862167],[-92.765278,44.837186],[-92.78043,44.812589],[-92.785206,44.792303],[-92.805287,44.768361],[-92.807988,44.75147],[-92.787906,44.737432],[-92.737259,44.717155],[-92.700948,44.693751],[-92.660988,44.660884],[-92.632105,44.649027],[-92.619779,44.634195],[-92.621456,44.615017],[-92.601516,44.612052],[-92.586216,44.600088],[-92.569434,44.603539],[-92.549777,44.58113],[-92.549957,44.568988],[-92.540551,44.567258],[-92.518358,44.575183],[-92.493808,44.566063],[-92.481001,44.568276],[-92.455105,44.561886],[-92.433256,44.5655],[-92.399281,44.558292],[-92.361518,44.558935],[-92.336114,44.554004],[-92.314071,44.538014],[-92.302466,44.516487],[-92.302215,44.500298],[-92.291005,44.485464],[-92.232472,44.445434],[-92.195378,44.433792],[-92.124513,44.422115],[-92.111085,44.413948],[-92.078605,44.404869],[-92.056486,44.402729],[-92.038147,44.388731],[-91.970266,44.365842],[-91.941311,44.340978],[-91.92559,44.333548],[-91.918625,44.322671],[-91.913534,44.311392],[-91.924613,44.291815],[-91.896388,44.27469],[-91.896008,44.262871],[-91.88704,44.251772],[-91.892698,44.231105],[-91.877429,44.212921],[-91.872369,44.199167],[-91.829167,44.17835],[-91.808064,44.159262],[-91.751747,44.134786],[-91.721552,44.130342],[-91.710597,44.12048],[-91.708207,44.105186],[-91.69531,44.09857],[-91.68153,44.0974],[-91.667006,44.086964],[-91.647873,44.064109],[-91.638115,44.063285],[-91.610487,44.04931],[-91.59207,44.031372],[-91.507121,44.01898],[-91.48087,44.008145],[-91.463515,44.009041],[-91.432522,43.996827],[-91.407395,43.965148],[-91.385785,43.954239],[-91.366642,43.937463],[-91.357426,43.917231],[-91.347741,43.911964],[-91.338141,43.897664],[-91.320605,43.888491],[-91.310991,43.867381],[-91.284138,43.847065],[-91.262436,43.792166],[-91.244135,43.774667],[-91.255431,43.744876],[-91.255932,43.729849],[-91.268455,43.709824],[-91.273252,43.666623],[-91.271749,43.654929],[-91.262397,43.64176],[-91.268748,43.615348],[-91.232707,43.583533],[-91.232812,43.564842],[-91.243214,43.550722],[-91.243183,43.540309],[-91.232941,43.523967],[-91.218292,43.514434],[-91.217706,43.50055],[-96.453049,43.500415],[-96.453067,45.298115],[-96.489065,45.357071],[-96.521787,45.375645],[-96.562142,45.38609],[-96.617726,45.408092],[-96.680454,45.410499],[-96.692541,45.417338],[-96.731396,45.45702],[-96.76528,45.521414],[-96.857751,45.605962],[-96.844211,45.639583],[-96.835769,45.649648],[-96.760866,45.687518],[-96.745086,45.701576],[-96.662595,45.738682],[-96.641941,45.759871],[-96.627778,45.786239],[-96.583085,45.820024],[-96.574517,45.843098],[-96.561334,45.945655],[-96.57035,45.963595],[-96.57794,46.026874],[-96.559271,46.058272],[-96.554507,46.083978],[-96.557952,46.102442],[-96.56692,46.11475],[-96.563043,46.119512],[-96.571439,46.12572],[-96.56926,46.133686],[-96.579453,46.147601],[-96.577952,46.165843],[-96.587408,46.178164],[-96.584372,46.204155],[-96.59755,46.227733],[-96.598645,46.241626],[-96.590942,46.250183],[-96.59887,46.26069],[-96.595014,46.275135],[-96.60136,46.30413],[-96.599761,46.330386],[-96.619991,46.340135],[-96.618147,46.344295],[-96.629211,46.352654],[-96.644335,46.351908],[-96.646341,46.360982],[-96.655206,46.365964],[-96.658436,46.373391],[-96.666028,46.374566],[-96.669132,46.390037],[-96.680687,46.407383],[-96.688082,46.40788],[-96.701358,46.420584],[-96.703078,46.429467],[-96.718074,46.438255],[-96.715557,46.463232],[-96.73627,46.48138],[-96.737798,46.489785],[-96.733612,46.497224],[-96.737702,46.50077],[-96.738475,46.525793],[-96.744341,46.533006],[-96.743003,46.54294],[-96.74883,46.558127],[-96.744436,46.56596],[-96.746442,46.574078],[-96.772446,46.600129],[-96.774094,46.613288],[-96.78995,46.631531],[-96.790663,46.649112],[-96.798823,46.658071],[-96.792958,46.677427],[-96.784339,46.685054],[-96.790906,46.70297],[-96.779252,46.727429],[-96.784279,46.732993],[-96.781216,46.740944],[-96.787466,46.756753],[-96.784314,46.766973],[-96.796195,46.789881],[-96.795756,46.807795],[-96.801446,46.810401],[-96.80016,46.819664],[-96.787657,46.827817],[-96.789663,46.832306],[-96.779347,46.843672],[-96.781358,46.879363],[-96.768458,46.879563],[-96.767358,46.883663],[-96.773558,46.884763],[-96.776558,46.895663],[-96.759241,46.918223],[-96.761757,46.934663],[-96.78312,46.925482],[-96.79038,46.929398],[-96.791558,46.944464],[-96.797734,46.9464],[-96.798737,46.962399],[-96.821852,46.969372],[-96.82318,46.999965],[-96.834221,47.006671],[-96.829499,47.021537],[-96.818557,47.02778],[-96.821422,47.032842],[-96.819321,47.0529],[-96.824479,47.059682],[-96.818175,47.104193],[-96.827344,47.120144],[-96.824807,47.124968],[-96.831547,47.142017],[-96.822377,47.162744],[-96.829637,47.17497],[-96.826962,47.182802],[-96.838806,47.197894],[-96.832789,47.203911],[-96.838806,47.22502],[-96.832946,47.237588],[-96.83766,47.240876],[-96.835368,47.250428],[-96.841672,47.258164],[-96.838997,47.267716],[-96.842531,47.269531],[-96.844088,47.289981],[-96.832884,47.30449],[-96.841958,47.316907],[-96.835845,47.321014],[-96.835845,47.335914],[-96.852417,47.366241],[-96.848907,47.370565],[-96.852676,47.374973],[-96.846925,47.376891],[-96.840621,47.389881],[-96.845492,47.394179],[-96.844919,47.399815],[-96.863593,47.418775],[-96.85748,47.440457],[-96.859868,47.470926],[-96.85471,47.478281],[-96.85853,47.489934],[-96.851653,47.497098],[-96.851367,47.509037],[-96.866363,47.524893],[-96.85471,47.535973],[-96.859153,47.566355],[-96.853689,47.570381],[-96.856373,47.575749],[-96.851293,47.589264],[-96.856903,47.602329],[-96.855421,47.60875],[-96.873671,47.613654],[-96.871005,47.616832],[-96.879496,47.620576],[-96.882393,47.633489],[-96.888573,47.63845],[-96.882376,47.649025],[-96.88697,47.653049],[-96.887126,47.666369],[-96.895271,47.67357],[-96.899352,47.689473],[-96.908928,47.688722],[-96.907266,47.693976],[-96.920119,47.710383],[-96.923544,47.718201],[-96.919471,47.722515],[-96.932809,47.737139],[-96.928505,47.748037],[-96.934173,47.752412],[-96.939179,47.768397],[-96.9644,47.782995],[-96.957283,47.790147],[-96.966068,47.797297],[-96.975131,47.798326],[-96.980579,47.805614],[-96.979327,47.824533],[-96.986685,47.837639],[-96.998295,47.841724],[-96.998144,47.858882],[-97.005557,47.863977],[-97.002456,47.868677],[-97.023156,47.874978],[-97.019355,47.880278],[-97.024955,47.886878],[-97.019155,47.889778],[-97.024955,47.894978],[-97.020155,47.900478],[-97.024955,47.908178],[-97.017254,47.905678],[-97.015354,47.910278],[-97.023754,47.915878],[-97.018054,47.918078],[-97.035754,47.930179],[-97.036054,47.939379],[-97.054554,47.946279],[-97.052454,47.957179],[-97.061454,47.96358],[-97.053553,47.991612],[-97.064289,47.998508],[-97.066762,48.009558],[-97.063012,48.013179],[-97.072239,48.019107],[-97.068987,48.026267],[-97.072257,48.048068],[-97.097772,48.07108],[-97.103052,48.071669],[-97.099431,48.082106],[-97.105226,48.09044],[-97.104872,48.097851],[-97.109535,48.104723],[-97.123205,48.106648],[-97.120702,48.114987],[-97.131956,48.139563],[-97.141401,48.14359],[-97.138911,48.157793],[-97.146745,48.168556],[-97.141474,48.179099],[-97.146233,48.186054],[-97.134372,48.210434],[-97.136304,48.228984],[-97.141254,48.234668],[-97.135763,48.237596],[-97.138765,48.244991],[-97.127276,48.253323],[-97.131846,48.267589],[-97.11657,48.279661],[-97.12216,48.290056],[-97.128862,48.292882],[-97.122072,48.300865],[-97.132443,48.315489],[-97.127601,48.323319],[-97.134854,48.331314],[-97.131145,48.339722],[-97.147748,48.359905],[-97.140106,48.380479],[-97.145592,48.394195],[-97.135012,48.406735],[-97.142849,48.419471],[-97.1356,48.424369],[-97.139173,48.430528],[-97.134229,48.439797],[-97.137689,48.447583],[-97.132746,48.459942],[-97.144116,48.469212],[-97.141397,48.476256],[-97.144981,48.481571],[-97.140291,48.484722],[-97.138864,48.494362],[-97.148133,48.503384],[-97.153076,48.524148],[-97.150481,48.536877],[-97.163105,48.543855],[-97.160863,48.549236],[-97.152459,48.552326],[-97.158638,48.564067],[-97.149616,48.569876],[-97.14974,48.579516],[-97.142915,48.583733],[-97.143684,48.597066],[-97.137504,48.612268],[-97.132931,48.61338],[-97.130089,48.621166],[-97.125639,48.620919],[-97.125269,48.629694],[-97.108466,48.632658],[-97.111921,48.642918],[-97.100551,48.658614],[-97.102652,48.664793],[-97.097708,48.68395],[-97.118286,48.700573],[-97.116185,48.709348],[-97.136083,48.727763],[-97.139488,48.746611],[-97.151289,48.757428],[-97.147478,48.763698],[-97.154854,48.774515],[-97.157093,48.790024],[-97.163535,48.79507],[-97.165624,48.809627],[-97.180028,48.81845],[-97.177747,48.824815],[-97.181116,48.832741],[-97.173811,48.838309],[-97.175618,48.853105],[-97.187362,48.867598],[-97.185738,48.87222],[-97.197982,48.880341],[-97.197982,48.898332],[-97.210541,48.90439],[-97.211161,48.916649],[-97.217992,48.919735],[-97.218666,48.931781],[-97.224505,48.9341],[-97.232147,48.948955],[-97.230859,48.960891],[-97.239209,48.968684],[-97.237297,48.985696],[-97.230833,48.991303],[-97.229039,49.000687],[-95.153711,48.998903],[-95.15335,49.383079],[-95.126467,49.369439],[-95.058404,49.35317],[-95.014415,49.356405],[-94.988908,49.368897],[-94.957465,49.370186],[-94.854245,49.324154],[-94.816222,49.320987],[-94.824291,49.308834],[-94.82516,49.294283],[-94.797244,49.214284],[-94.797527,49.197791],[-94.773223,49.120733],[-94.750221,49.099763],[-94.750218,48.999992],[-94.718932,48.999991],[-94.683069,48.883929],[-94.684217,48.872399],[-94.692527,48.86895],[-94.693044,48.853392],[-94.685681,48.840119],[-94.701968,48.831778],[-94.704284,48.824284],[-94.694974,48.809206],[-94.694312,48.789352],[-94.690889,48.778066],[-94.651765,48.755913],[-94.645164,48.749975],[-94.645083,48.744143],[-94.61901,48.737374],[-94.58715,48.717599],[-94.549069,48.714653],[-94.533057,48.701262],[-94.452332,48.692444],[-94.438701,48.694889],[-94.416191,48.710948],[-94.384221,48.711806],[-94.342758,48.703382],[-94.308446,48.710239],[-94.290737,48.707747],[-94.260541,48.696381],[-94.251169,48.683514],[-94.254643,48.663888],[-94.250497,48.656654],[-94.224276,48.649527],[-94.091244,48.643669],[-94.065775,48.646104],[-94.035616,48.641018],[-94.006933,48.643193],[-93.944221,48.632294],[-93.91153,48.634673],[-93.840754,48.628548],[-93.824144,48.610724],[-93.806763,48.577616],[-93.811201,48.542385],[-93.818253,48.530046],[-93.794454,48.516021],[-93.656652,48.515731],[-93.643091,48.518294],[-93.628865,48.53121],[-93.612844,48.521876],[-93.60587,48.522472],[-93.594379,48.528793],[-93.547191,48.528684],[-93.467504,48.545664],[-93.460798,48.550552],[-93.456675,48.561834],[-93.465199,48.590659],[-93.438494,48.59338],[-93.405269,48.609344],[-93.395022,48.603303],[-93.371156,48.605085],[-93.362132,48.613832],[-93.35324,48.613378],[-93.349095,48.624935],[-93.254854,48.642784],[-93.207398,48.642474],[-93.178095,48.623339],[-93.088438,48.627597],[-92.984963,48.623731],[-92.954876,48.631493],[-92.95012,48.630419],[-92.949839,48.608269],[-92.929614,48.606874],[-92.909947,48.596313],[-92.894687,48.594915],[-92.728046,48.53929],[-92.657881,48.546263],[-92.634931,48.542873],[-92.625739,48.518189],[-92.631117,48.508252],[-92.627237,48.503383],[-92.636696,48.499428],[-92.654039,48.501635],[-92.661418,48.496557],[-92.698824,48.494892],[-92.712562,48.463013],[-92.687998,48.443889],[-92.656027,48.436709],[-92.507285,48.447875],[-92.475585,48.418793],[-92.456325,48.414204],[-92.456389,48.401134],[-92.47675,48.37176],[-92.469948,48.351836],[-92.437825,48.309839],[-92.416285,48.295463],[-92.369174,48.220268],[-92.336831,48.235383],[-92.269742,48.248241],[-92.273706,48.256747],[-92.294541,48.27156],[-92.292999,48.276404],[-92.301451,48.288608],[-92.294527,48.306454],[-92.306309,48.316442],[-92.304561,48.322977],[-92.295412,48.323957],[-92.288994,48.342991],[-92.26228,48.354933],[-92.222813,48.349203],[-92.216983,48.345114],[-92.206803,48.345596],[-92.203684,48.352063],[-92.178418,48.351881],[-92.177354,48.357228],[-92.145049,48.365651],[-92.143583,48.356121],[-92.083513,48.353865],[-92.077961,48.358253],[-92.055228,48.359213],[-92.045734,48.347901],[-92.046562,48.33474],[-92.037721,48.333183],[-92.030872,48.325824],[-92.000133,48.321355],[-92.01298,48.297391],[-92.006577,48.265421],[-91.989545,48.260214],[-91.976903,48.244626],[-91.971056,48.247667],[-91.971779,48.252977],[-91.954432,48.251678],[-91.952209,48.244394],[-91.957683,48.242683],[-91.957798,48.232989],[-91.941838,48.230602],[-91.915772,48.238871],[-91.89347,48.237699],[-91.884691,48.227321],[-91.867882,48.219095],[-91.864382,48.207031],[-91.815772,48.211748],[-91.809038,48.206013],[-91.79181,48.202492],[-91.789011,48.196549],[-91.756637,48.205022],[-91.749075,48.198844],[-91.741932,48.199122],[-91.742313,48.204491],[-91.714931,48.19913],[-91.711611,48.1891],[-91.721413,48.180255],[-91.724584,48.170657],[-91.705318,48.170775],[-91.70726,48.153661],[-91.698174,48.141643],[-91.699981,48.13184],[-91.712226,48.116883],[-91.703524,48.113548],[-91.682845,48.122118],[-91.687623,48.111698],[-91.676876,48.107264],[-91.665208,48.107011],[-91.653261,48.114137],[-91.653571,48.109567],[-91.640175,48.096926],[-91.559272,48.108268],[-91.552962,48.103012],[-91.569746,48.093348],[-91.575471,48.066294],[-91.575672,48.048791],[-91.567254,48.043719],[-91.488646,48.068065],[-91.45033,48.068806],[-91.437582,48.049248],[-91.429642,48.048608],[-91.391128,48.057075],[-91.370872,48.06941],[-91.365143,48.066968],[-91.340159,48.073236],[-91.332589,48.069331],[-91.26638,48.078713],[-91.214428,48.10294],[-91.190461,48.124891],[-91.183207,48.122235],[-91.176181,48.125811],[-91.137733,48.14915],[-91.139402,48.154738],[-91.092258,48.173101],[-91.082731,48.180756],[-91.024208,48.190072],[-90.976955,48.219452],[-90.914971,48.230603],[-90.88548,48.245784],[-90.875107,48.237784],[-90.847352,48.244443],[-90.839176,48.239511],[-90.836313,48.176963],[-90.832589,48.173765],[-90.821115,48.184709],[-90.817698,48.179569],[-90.804207,48.177833],[-90.796596,48.159373],[-90.777917,48.163801],[-90.778031,48.148723],[-90.79797,48.136894],[-90.787305,48.134196],[-90.789919,48.129902],[-90.76911,48.116585],[-90.761555,48.100133],[-90.751608,48.090968],[-90.641596,48.103515],[-90.626886,48.111846],[-90.59146,48.117546],[-90.582217,48.123784],[-90.55929,48.121683],[-90.555845,48.117069],[-90.569763,48.106951],[-90.567482,48.101178],[-90.556838,48.096008],[-90.487077,48.099082],[-90.467712,48.108818],[-90.438449,48.098747],[-90.403219,48.105114],[-90.374542,48.090942],[-90.367658,48.094577],[-90.344234,48.094447],[-90.330052,48.102399],[-90.312386,48.1053],[-90.289337,48.098993],[-90.224692,48.108148],[-90.188679,48.107947],[-90.176605,48.112445],[-90.136191,48.112136],[-90.116259,48.104303],[-90.073873,48.101138],[-90.023595,48.084708],[-90.015057,48.067188],[-90.008446,48.068396],[-89.997852,48.057567],[-89.99305,48.028404],[-89.97718,48.023501],[-89.968255,48.014482],[-89.954605,48.011516],[-89.95059,48.015901],[-89.934489,48.015628],[-89.915341,47.994866],[-89.897414,47.987599],[-89.873286,47.985419],[-89.868153,47.989898],[-89.847571,47.992442],[-89.842568,48.001368],[-89.830385,48.000284],[-89.820483,48.014665],[-89.797744,48.014505],[-89.763967,48.022969],[-89.724048,48.018996],[-89.721038,48.017965],[-89.724044,48.013675],[-89.716114,48.016441],[-89.716417,48.010251],[-89.702528,48.006325],[-89.673798,48.01151],[-89.667128,48.007421],[-89.657051,48.009954],[-89.649057,48.003853],[-89.617867,48.010947],[-89.611678,48.017529],[-89.607821,48.006566],[-89.594749,48.004332],[-89.582117,47.996314],[-89.564288,48.00293],[-89.489226,48.014528],[-89.495344,48.002356],[-89.541521,47.992841],[-89.551555,47.987305],[-89.555015,47.974849],[-89.572315,47.967238],[-89.58823,47.9662],[-89.611412,47.980731],[-89.624559,47.983153],[-89.631825,47.980039],[-89.640129,47.96793],[-89.638285,47.954275],[-89.697619,47.941288],[-89.793539,47.891358],[-89.85396,47.873997],[-89.87158,47.874194],[-89.923649,47.862062],[-89.930844,47.857723],[-89.92752,47.850825],[-89.933899,47.84676],[-89.974296,47.830514],[-90.072025,47.811105],[-90.075559,47.803303],[-90.1168,47.79538],[-90.16079,47.792807],[-90.178755,47.786414],[-90.187636,47.77813],[-90.248794,47.772763],[-90.323446,47.753771],[-90.332686,47.746387],[-90.437712,47.731612],[-90.441912,47.726404],[-90.458365,47.7214],[-90.537105,47.703055],[-90.551291,47.690266],[-90.735927,47.624343],[-90.86827,47.5569],[-90.907494,47.532873],[-90.914247,47.522639],[-90.939072,47.514532],[-91.032945,47.458236],[-91.045646,47.456525],[-91.097569,47.413888],[-91.128131,47.399619],[-91.146958,47.381464],[-91.156513,47.378816],[-91.188772,47.340082],[-91.238658,47.304976],[-91.262512,47.27929],[-91.288478,47.26596],[-91.326019,47.238993],[-91.357803,47.206743],[-91.418805,47.172152],[-91.477351,47.125667],[-91.497902,47.122579],[-91.518793,47.108121],[-91.573817,47.089917],[-91.591508,47.068684],[-91.626824,47.049953],[-91.644564,47.026491],[-91.666477,47.014297],[-91.704649,47.005246],[-91.780675,46.945881],[-91.806851,46.933727],[-91.841349,46.925215],[-91.883238,46.905728],[-91.914984,46.883836],[-91.952985,46.867037],[-92.094089,46.787839],[-92.088289,46.773639],[-92.06449,46.745439],[-92.025789,46.710839],[-92.01529,46.706469],[-92.020289,46.704039],[-92.03399,46.708939],[-92.08949,46.74924],[-92.10819,46.74914],[-92.13789,46.73954],[-92.14329,46.73464],[-92.141291,46.72524],[-92.146291,46.71594],[-92.167291,46.719941],[-92.189091,46.717541],[-92.204691,46.704041]]]},\"properties\":{\"name\":\"Minnesota\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Lambert, Jane","contributorId":303692,"corporation":false,"usgs":false,"family":"de Lambert","given":"Jane","affiliations":[{"id":65878,"text":"MN Department of Health","active":true,"usgs":false}],"preferred":false,"id":867799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Overbo, Alycia","contributorId":303694,"corporation":false,"usgs":false,"family":"Overbo","given":"Alycia","email":"","affiliations":[{"id":65878,"text":"MN Department of Health","active":true,"usgs":false}],"preferred":false,"id":867801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Steve","contributorId":303693,"corporation":false,"usgs":false,"family":"Robertson","given":"Steve","email":"","affiliations":[{"id":65878,"text":"MN Department of Health","active":true,"usgs":false}],"preferred":false,"id":867800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":867798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246686,"text":"70246686 - 2023 - Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","interactions":[],"lastModifiedDate":"2023-07-14T11:53:26.020041","indexId":"70246686","displayToPublicDate":"2023-02-23T06:50:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use","docAbstract":"Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (a) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios, (b) sensitivity, and (c) adaptive capacity. The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increases are expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Strong variation in predicted estuarine nutrient loads was observed as a function of climate model projections, while projected LULC changes were more consistently associated with elevated loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries.
Understanding plant community response to environmental change is a crucial aspect of biological conservation and restoration, but species-based approaches are limited in that they do not reveal the underlying mechanisms driving vegetation dynamics. An understanding of trait-environment relationships is particularly important in the case of invasive species which may alter abiotic conditions and available resources. This study is the first to measure the functional response of riparian plant communities to biocontrol of an invasive species. We focused on an invasive shrub, Tamarix (saltcedar), that is defoliated by a beetle that was released by the US Department of Agriculture along the Upper Colorado River (southwestern United States). We calculated community weighted means and functional dispersion of individual traits, multivariate functional dispersion and species diversity. We used linear mixed effect models (LME) to compare these metrics at paired vegetation patches dominated and not dominated by Tamarix during cycles of defoliation and refoliation over eight years. We found that community-weighted average trait values, species diversity and functional dispersion changed little in response to defoliation, and instead seemed to be responding to fluctuations in yearly precipitation. Average height and seed weight were greater in Tamarix-dominated patches relative to control patches. Functional dispersion followed a similar trajectory to species diversity, but was a more sensitive indicator of plant community change. We showed that riparian vegetation can be resilient to Tamarix biocontrol, and that defoliation might not necessarily always lead to substantial changes in ecosystem function.
Condit Dam was removed from river kilometer (rkm) 5.3 of the White Salmon River, Washington, in 2011 and 2012 after blocking upstream passage of anadromous fish for nearly 100 years. The dam removal opened habitat upstream and improved habitat downstream with addition of cobble and gravel to a reach depauperate of spawning and rearing habitat. We assessed juvenile anadromous salmonid abundance and distribution in the subbasin from 2016 through 2021 to evaluate the efficacy of natural recolonization. We sampled for outmigrant smolts and other life-history stages at a rotary screw trap at rkm 2.3 and for juvenile abundance at sites in Buck and Rattlesnake Creeks, two primary tributaries upstream from the former dam location.
We estimated smolt abundance of steelhead (Oncorhynchus mykiss) and coho salmon (O. kisutch) at the screw-trap site during most years of the study. High flow and missed trapping days in 2017 precluded estimates, and the trap was not fished during 2020 because of the onset of the COVID-19 pandemic. Steelhead smolt-abundance estimates ranged from 3,581 to 5,851 fish; coho salmon smolt-abundance estimates ranged from 1,093 to 1,773 fish, although in 2021, only 2 coho salmon smolt were captured and no estimate was made.
Other species and life stages also were captured in the screw trap. Steelhead and coho salmon fry and parr, and Chinook salmon (O. tshawytscha) fry were captured, indicating the presence and likely use of improved habitat downstream from the former dam site by multiple life stages and spawning success upstream from the screw-trap site. Chinook salmon fry were captured, indicating spawning success upstream from the screw-trap site. Fry numbers varied greatly by day and year. Yearly variation in Chinook and coho salmon fry numbers may have been influenced by high flows following spawning causing redd scour and egg-to-fry mortality. Three bull trout (Salvelinus confluentus) were caught in the screw trap, one in June 2018, one in June 2019, and one in June 2021. All three bull trout showed smolt characteristics and were tagged with passive integrated transponders (PITs). The bull trout captured in June 2018 was detected at Bonneville Dam Corner Collector several days later, indicating likely anadromy. We also captured lamprey in the screw trap: 44 during 2018, 31 during 2019, and 11 during 2021; we believe most were adult brook lamprey (Lampetra richardsoni), although some could have been Pacific lamprey (Entosphenus tridentatus) macropthalmia.
We confirmed the presence of juvenile steelhead (through smolt origin data) and coho salmon in Mill, Buck, and Rattlesnake Creeks, which are all upstream from the former site of Condit Dam. Juvenile salmonid abundance sampling at a site in Buck Creek during 2016–20 indicated the presence of juvenile coho salmon in all years except 2020. Total salmonid abundance (steelhead and coho salmon combined) at the Buck Creek site each year exceeded abundance in sampling prior to dam removal in 2009 and 2010. Juvenile salmonid abundance sampling in Rattlesnake Creek during 2016–20 indicated the presence of juvenile coho salmon in 2017, 2018, and 2019. Total juvenile salmonid abundance at the Rattlesnake Creek site was highly variable, sometimes exceeding and sometimes less than abundance prior to dam removal during 2001–05. During the period covered by this report, adult salmonid returns to the Columbia River were decreasing, largely because of marine survival. The extent to which this basin-wide decrease affected adult returns and juvenile populations in the White Salmon River subbasin is not known.
Despite a period of poor marine survival, PIT-tagged smolt and juvenile steelhead and coho salmon from the screw trap and tributaries returned to Bonneville Dam. Smolt-to-adult return rates from the screw trap to Bonneville Dam were similar to those in other nearby rivers during this period. However, data are still incomplete for some years and sample sizes were low. Future tagging and monitoring would be beneficial to track this valuable metric.
Genetic samples from steelhead smolt and parr collected at the screw trap and some main-stem electrofishing during 2016 were analyzed for Genetic Stock Identification (GSI) by CRITFC. Preliminary data showed that White Salmon River fish were the most common at about 42 percent, with 19 percent typing to Hood River, Oregon stock, and about 26 percent typing to Skamania stock, a common hatchery stock in the area. Winter and summer runs were represented in the samples.
Juvenile salmonid sampling in the White Salmon River, Washington, following removal of Condit Dam, demonstrated that anadromous salmonids are using newly opened habitat upstream from the former dam site and improved lower river habitat. Steelhead and coho salmon smolts are being produced upstream from the former dam site, and some have returned to Bonneville Dam as adults. Chinook salmon spawning upstream from our smolt trap site are producing fry. These results are encouraging for success of the strictly natural recolonization strategy. However, declines in anadromous runs to the larger Columbia River Basin also likely have affected the White Salmon runs and our data may not reflect full capacity of the White Salmon River subbasin juvenile production. Continued abundance, distribution, and GSI monitoring will help to track the evolution of anadromous fish in the White Salmon River under a natural recolonization strategy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221117","collaboration":"Prepared in cooperation with Yakama Nation Fisheries and Mid-Columbia Fisheries Enhancement Group","usgsCitation":"Jezorek, I.G., and Hardiman, J.M., 2023, Juvenile salmonid monitoring to assess natural recolonization following removal of Condit Dam on the White Salmon River, Washington, 2016–21: U.S. Geological Survey Open-File Report 2022–1117, 23 p., https://doi.org/10.3133/ofr20221117.","productDescription":"vi, 23 p.","onlineOnly":"Y","ipdsId":"IP-137364","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":413140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1117/coverthb.jpg"},{"id":413143,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1117/images"},{"id":413142,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221117/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1117"},{"id":413141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1117/ofr20221117.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1117"},{"id":499726,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114378.htm","linkFileType":{"id":5,"text":"html"}},{"id":413144,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1117/ofr20221117.XML"}],"country":"United States","state":"Washington","otherGeospatial":"White Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.78283038944755,\n 46.100301136884156\n ],\n [\n -121.78283038944755,\n 45.67990372212273\n ],\n [\n -121.22276550358751,\n 45.67990372212273\n ],\n [\n -121.22276550358751,\n 46.100301136884156\n ],\n [\n -121.78283038944755,\n 46.100301136884156\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Integrated Information Dissemination Division
Water Resource Mission Area
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Email: water-science-school@usgs.gov
The U.S. Geological Survey (USGS) launched the Earth Mapping Resources Initiative (Earth MRI) to modernize the surface and subsurface geologic mapping of the United States, with a focus on identifying areas that may have the potential to contain critical mineral resources. EarthMRI can inform strategies to ensure secure and reliable domestic critical mineral supplies for the United States as mandated by Executive Order 13817 and the Infrastructure and Jobs Act of 2021 (Public Law 117–58, 135 Stat. 529). Earth MRI is a collaborative effort between the USGS and the State geological surveys as represented by the Association of American State Geologists to identify, prioritize, and acquire new geoscience data for geographic areas, or focus areas, across the Nation that have potential to host critical mineral resources. Mapping of focus areas was based on a framework of mineral systems and their associated mineral deposit types that could possibly host critical minerals. Using readily available geologic, geophysical, geochemical, and mineral deposit data, teams of USGS scientists worked with representatives of State geological surveys in a series of workshops to outline focus areas that contain evidence of key features for one or more mineral systems. These areas can be used to guide future efforts to collect new geologic, geophysical, geochemical, and topographic data that focus on critical minerals through Earth MRI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233007","collaboration":"Prepared in cooperation with the Association of American State Geologists","usgsCitation":"Hammarstrom, J.M., Kreiner, D.C., Dicken, C.L., and Woodruff, L.G., 2023, National map of focus areas for potential critical mineral resources in the United States: U.S. Geological Survey Fact Sheet 2023–3007, 4 p., https://doi.org/10.3133/fs20233007.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-147615","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":499567,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114381.htm","linkFileType":{"id":5,"text":"html"}},{"id":413202,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3007/fs20233007.pdf","text":"Report","size":"4.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3007"},{"id":413201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3007/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","contact":"Earth Mapping Resources Initiative (Earth MRI)
Mineral Resources Program
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: minerals@usgs.gov
Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse (Centrocercus urophasianus), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity—twice the amount of connectivity as random—and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rsos.220437","usgsCitation":"Cross, T.B., Tack, J.D., Naugle, D., Schwartz, M.D., Doherty, K., Oyler-McCance, S.J., Pritchert, R.D., and Fedy, B.C., 2023, The ties that bind the sagebrush biome: Integrating genetic connectivity into range-wide conservation of greater sage-grouse: Royal Society Open Science, v. 10, no. 2, 220437, 15 p., https://doi.org/10.1098/rsos.220437.","productDescription":"220437, 15 p.","ipdsId":"IP-136470","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":444387,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.220437","text":"Publisher Index Page"},{"id":435437,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HI7OGR","text":"USGS data release","linkHelpText":"Greater sage-grouse network-prioritized functional connectivity cumulative current map (raster)"},{"id":413667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.07007462178439,\n 48.995456978554444\n ],\n [\n -119.8990141514297,\n 48.995456978554444\n ],\n [\n -119.8990141514297,\n 36.393670817249514\n ],\n [\n -103.07007462178439,\n 36.393670817249514\n ],\n [\n -103.07007462178439,\n 48.995456978554444\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Cross, Todd B.","contributorId":189267,"corporation":false,"usgs":false,"family":"Cross","given":"Todd","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":865592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tack, Jason D. jtack@usgs.gov","contributorId":302682,"corporation":false,"usgs":false,"family":"Tack","given":"Jason","email":"jtack@usgs.gov","middleInitial":"D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":865593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naugle, David E.","contributorId":255114,"corporation":false,"usgs":false,"family":"Naugle","given":"David E.","affiliations":[{"id":51432,"text":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, 59812, USA","active":true,"usgs":false}],"preferred":false,"id":865594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwartz, Michael D.","contributorId":174566,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":865595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":865596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":865597,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pritchert, Ronald D.","contributorId":218059,"corporation":false,"usgs":false,"family":"Pritchert","given":"Ronald","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":865598,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fedy, Brad C.","contributorId":140877,"corporation":false,"usgs":false,"family":"Fedy","given":"Brad","email":"","middleInitial":"C.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":865599,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70244045,"text":"70244045 - 2023 - Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","interactions":[],"lastModifiedDate":"2023-05-31T14:30:11.069748","indexId":"70244045","displayToPublicDate":"2023-02-22T09:26:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)","docAbstract":"Study region
The Southern Hills aquifer system in the Louisiana Capital Area Groundwater Conservation District (CAGCD), USA.
Study focus
The Southern Hills aquifer system provides abundant groundwater for public and industrial supplies in the CAGCD. Groundwater depletion, saltwater intrusion, and land subsidence are potential concerns due to prolonged excessive groundwater withdrawals. This study develops a high-fidelity groundwater flow model utilizing a complex unstructured grid to investigate groundwater flow and storage responses to excessive groundwater withdrawals for the Southern Hills aquifer system in the CAGCD. The groundwater model incorporates the Mississippi River alluvial aquifer down to the Miocene sands extending to depths around 1 km.
New hydrological insights
Groundwater modeling results indicate large cones of depression in the Evangeline and Jasper formations in the Baton Rouge area due to prolonged groundwater withdrawals. Low-permeability faults are inferred by significant groundwater level difference across the faults. While local groundwater storage depletion in deeper aquifers is evident, overall estimated groundwater storage changes of the Southern Hills aquifer system in the CAGCD are close to zero in the past two decades, indicating insignificant groundwater storage changes. This is attributed to dominant interactions between the major rivers and the shallower alluvial aquifer. In addition, the simulated groundwater storage changes exhibit patterns similar to those derived by the Gravity Recovery and Climate Experiment (GRACE) model that has been used in evaluation of groundwater depletion in many regional studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2023.101342","usgsCitation":"Chen, Y., Vahdat-Aboueshagh, H., Tsai, F.T., Dausman, A., and Runge, M.C., 2023, Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA): Journal of Hydrology: Regional Studies, v. 46, 101342, 22 p., https://doi.org/10.1016/j.ejrh.2023.101342.","productDescription":"101342, 22 p.","ipdsId":"IP-137603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444389,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2023.101342","text":"Publisher Index Page"},{"id":417579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Southern Hills aquifer system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.91720564327883,\n 31.007470903702682\n ],\n [\n -91.91720564327883,\n 30.261535321867598\n ],\n [\n -90.71125532149338,\n 30.261535321867598\n ],\n [\n -90.71125532149338,\n 31.007470903702682\n ],\n [\n -91.91720564327883,\n 31.007470903702682\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Ye-Hong","contributorId":305936,"corporation":false,"usgs":false,"family":"Chen","given":"Ye-Hong","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vahdat-Aboueshagh, Hamid","contributorId":305937,"corporation":false,"usgs":false,"family":"Vahdat-Aboueshagh","given":"Hamid","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsai, Frank T.-C.","contributorId":305938,"corporation":false,"usgs":false,"family":"Tsai","given":"Frank","email":"","middleInitial":"T.-C.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":874255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dausman, Alyssa","contributorId":223766,"corporation":false,"usgs":false,"family":"Dausman","given":"Alyssa","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":874256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240217,"text":"ofr20221121 - 2023 - Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","interactions":[],"lastModifiedDate":"2023-02-23T11:58:55.644522","indexId":"ofr20221121","displayToPublicDate":"2023-02-22T09:06:04","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1121","displayTitle":"Observations of Coastal Circulation, Waves, and Sediment Transport Along West Maui, Hawaiʻi (November 2017– March 2018), and Modeling Effects of Potential Watershed Restoration on Decreasing Sediment Loads to Adjacent Coral Reefs","title":"Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017– March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs","docAbstract":"Terrestrial sediment discharging from watersheds off West Maui, Hawaiʻi, has been documented as a primary stressor to local coral reefs, causing coral reef health to decline. The U.S. Geological Survey acquired and analyzed physical oceanographic and sedimentologic field data off the coast of West Maui to calibrate and validate physics-based, numerical hydrodynamic and sediment transport models of the study area developed by Deltares. These models simulated terrestrial sediment transport and dispersal from West Maui watersheds into coastal waters and how terrestrial sediment affects nearby coral reefs under different oceanographic forcing and watershed restoration scenarios.
Wave energy and near-bed turbidity are positively correlated in the field observations, illustrating a process not captured by the model simulations in which sediment already deposited on the seabed is resuspended by wave action and subsequently transported by prevailing currents. In the model simulations, large waves during flood events led to a decrease in suspended-sediment concentrations. Notably, however, the model results only consider sediment entering coastal waters from five stream sources and do not simulate sediment already present on the seabed.
The model simulations project that the Honokeana and Māhinahina coral reefs would experience the greatest reduction in sediment impacts from theoretical watershed restoration. Additionally, when large waves coincide with flood events, post-storm sedimentation generally decreases in the nearshore region, but increases in the region offshore of the reefs. The measured and modeled sediment dynamics demonstrate a demarcation between the coral reefs sheltered within embayments (Honolua reef) or behind points (Wahikuli reef) and those along the relatively open coastline between Kapalua and Kāʻanapali (Kapalua, Honokeana, Māhinahina, and Honokōwai reefs). The sheltered sites are affected by terrestrial sediment from single stream mouths, where most sediment is delivered within hours of a flood (rain) event. Once this sediment enters the nearshore, it settles out and remains within the reef area for a prolonged period owing to a lack of wave or current-driven bed shear stress. Thus, the primary effect of sediment on the reefs within these sheltered areas is sedimentation. In contrast, coral reefs along the unsheltered (or “open”) section of coastline (between Kapalua and Kāʻanapali) are more exposed to waves and terrestrial sediment from multiple stream sources. At these reefs, fine-grained terrestrial sediment can rarely settle but instead remains in suspension. Thus, even long after a flood event has occurred, these sites chronically experience light attenuation from suspended sediment.
These analyses underscore the importance of understanding how coastal ocean waves and circulation can lead to different sediment dynamics and stressors for coral reefs along the same region of the West Maui coastline. These differing factors indicate that the most effective watershed restoration and mitigation strategies may vary among the different coral reefs and streams. An important next step is to determine how the science of this study can support management goals for these coral reefs: what are target reductions of sedimentation, suspended-sediment concentrations, or the resulting light attenuation? Then, using the coupled hydrodynamic-sediment model, we can examine which watershed restoration scenarios in each stream will best achieve those targets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221121","collaboration":"Prepared in cooperation with the Deltares Impacts of Extreme Weather Strategic Research Program","programNote":"Coastal and the Marine Hazards and Resources Program","usgsCitation":"Storlazzi, C.D., Cheriton, O.M., Cronin, K.M., van der Heijden, L.H., Winter, G., Rosenberger, K.J., Logan, J.B., and McCall, R.T., 2023, Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017–March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs: U.S. Geological Survey Open-File Report 2022–1121, 73 p., https://doi.org/10.3133/ofr20221121.","productDescription":"Report: ix, 73 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-138761","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":412766,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914LMK2","text":"USGS data release","description":"USGS data release","linkHelpText":"Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii"},{"id":412765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DK9O60","text":"USGS data release","description":"USGS data release","linkHelpText":"Time series data of oceanographic conditions from West Maui, Hawaii, 2017-2018 Coral Reef Circulation and Sediment Dynamics Experiment"},{"id":412764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1121/ofr20221121.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1121"},{"id":412763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1121/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.72475140864907,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 20.922050876041368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission Street
Santa Cruz, CA 95060
Wildfire is a growing concern as climate shifts. The hydrologic effects of wildfire, which include elevated hazards and changes in water quantity and quality, are increasingly assessed using numerical models. Post-wildfire application of physically based distributed models provides unique insight into the underlying processes that affect water resources after wildfire. This work reviews and synthesizes post-wildfire applications of physically based distributed models by examining the scales and geographic/ecohydrologic distribution of model applications, hydrologic response process representation, model parameterization, and model performance metrics. Highlighted gaps and opportunities for advancing physically based distributed hydrologic response modeling after wildfire include the following: (a) applying models in under-represented geographic (S. America, Africa, Asia) and ecohydrologic regions (arid or dry subhumid climates), (b) incorporating all four major streamflow generation mechanisms (infiltration excess, saturation excess, subsurface storm flow, and groundwater flow), (c) representing integrated vadose zone and saturated zone processes to better capture subsurface streamflow generation, (d) building new remotely sensed model parameterization methods for precipitation interception, infiltration, and overland flow that account for burn severity and recovery, (e) incorporating distributed state variables (e.g., soil moisture, groundwater levels) in model performance assessment, (f) designing model intercomparison studies, including field datasets specifically for post-wildfire model development and validation, (g) linking mechanistic vegetation regrowth models with hydrologic models to improve simulation of process shifts as ecosystems recover, and (h) creating a new community modeling framework to integrate modeling advances across the wildfire science community.
Growing demand for renewable energy has resulted in expansion of energy infrastructure across sagebrush ecosystems of western North America. Geothermal power is an increasingly popular renewable energy source, especially within remote areas, but little is known about the impacts it may have on local wildlife populations. Investigations are warranted given similarities to more conventional surface disturbance activities with well-documented impacts. Using a novel 2-pronged analytical approach, we estimated effects of geothermal energy production activities (hereafter, geothermal) on populations of greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse), a species of high conservation concern. First, we applied a before-after-control-impact paired series design at two geothermal sites in Nevada, USA, to estimate absence rates of male sage-grouse from lek sites (breeding grounds) and changes in predicted apparent abundance (
“The Bay Connects us, the Bay reflects us” writes Tom Horton in the book “Turning the Tide—Saving the Chesapeake Bay”. The Chesapeake Bay watershed contains the largest estuary in the United States. The watershed stretches north to Cooperstown, New York, south to Lynchburg and Virginia Beach, Virginia, west to Pendleton County, West Virginia, and east to Seaford, Delaware, and Scranton, Pennsylvania. The watershed is more than 64,000 square miles that contain 150 major rivers and streams, hereafter referred to collectively as streams, that total more than 100,000 miles in length. The watershed contains thousands of smaller creeks and tributaries, large numbers of plants and animals, and, in 2020, more than 18.4 million people. As changes occur in population, land use, and climate within the watershed, so too do the diversity and health of the Bay's ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233003","usgsCitation":"Austin, S.H., Cashman, M.J., Clune, J., Colgin, J.E., Fanelli, R.M., Krause, K.P., Majcher, E.H., Maloney, K.O., Mason, C.A., Moyer, D.L., and Zimmerman, T.M., 2023, Tracking status and trends in seven key indicators of stream health in the Chesapeake Bay watershed: U.S. Geological Survey Fact Sheet 2023–3003, 6 p., https://doi.org/10.3133/fs20233003.","productDescription":"Report: 6 p.; 2 Data Releases","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-139165","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":435438,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98O2HQJ","text":"USGS data release","linkHelpText":"Compilation of multi-agency specific conductance observations for streams within the Chesapeake Bay watershed"},{"id":418602,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92SHG66","text":"USGS data release","linkHelpText":"Compilation of multi-agency water temperature observations for streams within the Chesapeake Bay watershed"},{"id":418601,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3003/images/"},{"id":418600,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3003/fs20233003.XML"},{"id":418599,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233003/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3003"},{"id":418598,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3003/fs20233003.pdf","text":"Report","size":"2.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3003"},{"id":418597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3003/coverthb3.jpg"},{"id":499563,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114382.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
Introduction: Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes.
Methods: This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions.
Results: Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges.
Discussion: As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore.
Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (Laterallus jamaicensis jamaicensis), Yellow Rails (Coterminous noveboracensis), and Mottled Ducks (Anas fulvigula; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their magnitude, relevance for decision making, and reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2824","usgsCitation":"Stantial, M.L., Lawson, A.J., Fournier, A., Kappes, P.J., Kross, C.S., Runge, M.C., Woodrey, M.S., and Lyons, J.E., 2023, Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty: Ecological Applications, v. 33, no. 4, e2824, 15 p., https://doi.org/10.1002/eap.2824.","productDescription":"e2824, 15 p.","ipdsId":"IP-138568","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444400,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2824","text":"Publisher Index Page"},{"id":435440,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95OCH4K","text":"USGS data release","linkHelpText":"Qualitative value of information for the effects of prescribed fire in Gulf of Mexico marshes: Expert judgment scores from a 2020 adaptive management workshop"},{"id":413613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Stantial, Michelle L 0000-0003-1112-2903","orcid":"https://orcid.org/0000-0003-1112-2903","contributorId":291453,"corporation":false,"usgs":true,"family":"Stantial","given":"Michelle","email":"","middleInitial":"L","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":865361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fournier, Auriel 0000-0002-8530-9968","orcid":"https://orcid.org/0000-0002-8530-9968","contributorId":261669,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":865363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kappes, Peter J.","contributorId":275193,"corporation":false,"usgs":false,"family":"Kappes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":865364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kross, Chelsea S. 0000-0003-4959-2556","orcid":"https://orcid.org/0000-0003-4959-2556","contributorId":302753,"corporation":false,"usgs":false,"family":"Kross","given":"Chelsea","email":"","middleInitial":"S.","affiliations":[{"id":65542,"text":"Forbes Biological Station–Bellrose Waterfowl Research Center, Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":865365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woodrey, Mark S.","contributorId":259212,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":865367,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":865368,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70243283,"text":"70243283 - 2023 - An examination of soil crusts on the floor of Jezero crater, Mars","interactions":[],"lastModifiedDate":"2023-10-11T15:24:01.859907","indexId":"70243283","displayToPublicDate":"2023-02-21T07:11:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5718,"text":"Journal of Geophysical Research: Planets","onlineIssn":"2169-9100","active":true,"publicationSubtype":{"id":10}},"title":"An examination of soil crusts on the floor of Jezero crater, Mars","docAbstract":"Martian soils are critically important for understanding the history of Mars, past potentially habitable environments, returned samples, and future human exploration. This paper examines soil crusts on the floor of Jezero crater encountered during initial phases of the Mars 2020 mission. Soil surface crusts have been observed on Mars at other locations, starting with the two Viking Lander missions. Rover observations show that soil crusts are also common across the floor of Jezero crater, revealed in 45 of 101 locations where rover wheels disturbed the soil surface, 2 out of 7 helicopter flights that crossed the wheel tracks, and 4 of 8 abrasion/drilling sites. Most soils measured by the SuperCam laser-induced breakdown spectroscopy (LIBS) instrument show high hydrogen content at the surface, and fine-grained soils also show a visible/near infrared (VISIR) 1.9 µm H2O absorption feature. The Planetary Instrument for X-ray Lithochemistry (PIXL) and SuperCam observations suggest the presence of salts at the surface of rocks and soils. The correlation of S and Cl contents with H contents in SuperCam LIBS measurements suggests that the salts present are likely hydrated. On the “Naltsos” target, magnesium and sulfur are correlated in PIXL measurements, and Mg is tightly correlated with H at the SuperCam points, suggesting hydrated Mg-sulfates. Mars Environmental Dynamics Analyzer (MEDA) observations indicate possible frost events and potential changes in the hydration of Mg-sulfate salts. Jezero crater soil crusts may therefore form by salts that are hydrated by changes in relative humidity and frost events, cementing the soil surface together.
To constrain fault processes and hazard, fault slip rates may be extrapolated over different fault lengths or time intervals. Here, we investigate slip rates for the Cucamonga Fault (CF). The CF is located at the junction of the Transverse Range fault system with the San Andreas and San Jacinto Faults, and it is hypothesized to connect with these faults, promoting the propagation of large, multi-fault earthquakes. Previous work has shown that CF displacements on late Quaternary alluvial fan surfaces are highly variable along strike. We present two new 10Be surface exposure ages from depth profiles on the alluvial fans. Slip rates are consistent with a rate of 1.4 ± 0.3 m/kyr over time intervals of ∼20, ∼30, and ∼40 kyr. If the CF participates in multi-fault ruptures, then these earthquakes occur either rarely or with sufficient regularity to maintain apparently steady rates over multiple intervals. We also explore along-strike fault displacement variability using a calibrated morphological model. The model successfully reproduces scarp profiles and indicates that fault displacement variability can be explained in part by scarp age but not uplift rate. We infer that both erosion by ephemeral gullying and distributed deformation contribute to fault displacement variability, although both are difficult to detect confidently without excavations across the scarp. These investigations show that better characterization of cumulative-slip variability along strike may improve accuracy and precision of slip rates. Slip rates that do not consider epistemic uncertainties may not be suitable for extrapolation over longer fault sections.
The Kirtland’s Warbler (Setophaga kirtlandii) is a formerly endangered habitat specialist that breeds mainly in young jack pine (Pinus banksiana) forests in northern Lower Michigan, USA. The species is conservation-reliant and depends on habitat management. Management actions have primarily focused on creating jack pine plantations, but the species also breeds in red pine (Pinus resinosa) plantations in central Wisconsin, USA. However, the plantations were not intended as breeding habitat and have suboptimal pine densities. While nesting success is similar between low-density red pine plantations and optimal jack pine habitat, it is not clear if low-density red pine plantations support high fledging survival. If high-quality nesting and post-fledging habitat are not synonymous, fledgling survival and breeding population recruitment may be low. We characterized survival, habitat use, and movement patterns of dependent Kirtland’s Warbler fledglings in Wisconsin red pine plantations and compared fledgling survival between Wisconsin and Michigan. Mayfield cumulative survival estimates at 30 days post-fledging were 0.20 for Wisconsin fledglings and 0.43–0.78 for Michigan fledglings. Logistic exposure cumulative survival estimates for Wisconsin fledglings were 0.23–0.34 at 30 days post-fledging. Fledglings in Wisconsin used areas where vegetation cover and density of red and jack pine were high relative to available areas but not at greater proportions than what was available. Our findings demonstrate that red pine plantations with low pine densities were not equally suitable as nesting and post-fledging habitat, as fledgling survival rates were low. We hypothesize that reduced habitat structure, and not particular pine species, likely contributed to reduced fledgling survival in Wisconsin. Thus, we recommend including red pine as a component in managed Kirtland’s Warbler habitat only if tree densities approach optimal levels.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad007","usgsCitation":"Olah, A., Ribic, C., Grveles, K., Sarah Warner, Lopez, D., and Pidgeon, A., 2023, Low Kirtland’s Warbler fledgling survival in Wisconsin plantations relative to Michigan plantations: Ornithological Applications, v. 125, no. 2, duad007, 14 p., https://doi.org/10.1093/ornithapp/duad007.","productDescription":"duad007, 14 p.","ipdsId":"IP-112246","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502487,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":497500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UnitedStates","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.8647407408813,\n 46.932668741089174\n ],\n [\n -92.99728980951639,\n 45.271242799734125\n ],\n [\n -90.7763900544374,\n 42.51884657701703\n ],\n [\n -87.9367256610007,\n 42.480677770787175\n ],\n [\n -87.40779088771117,\n 41.730422434317475\n ],\n [\n -83.06900912932046,\n 41.73440594813022\n ],\n [\n -82.1865330449237,\n 43.461406990458656\n ],\n [\n -83.90901134263669,\n 46.70834799532852\n ],\n [\n -87.92805157633859,\n 47.84390383588131\n ],\n [\n -91.8647407408813,\n 46.932668741089174\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"125","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Olah, Ashley","contributorId":363795,"corporation":false,"usgs":false,"family":"Olah","given":"Ashley","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":952031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":952030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grveles, Kim","contributorId":348828,"corporation":false,"usgs":false,"family":"Grveles","given":"Kim","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":952032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sarah Warner","contributorId":363797,"corporation":false,"usgs":false,"family":"Sarah Warner","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":952033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lopez, Davin","contributorId":363798,"corporation":false,"usgs":false,"family":"Lopez","given":"Davin","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":952034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pidgeon, Anna M.","contributorId":298926,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Anna M.","affiliations":[{"id":64735,"text":"Univ of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":952035,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240758,"text":"70240758 - 2023 - The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption","interactions":[],"lastModifiedDate":"2023-02-21T01:45:59.585247","indexId":"70240758","displayToPublicDate":"2023-02-20T19:36:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption","docAbstract":"Sabancaya volcano is the youngest and second most active volcano in Peru. It is part of the Ampato-Sabancaya volcanic complex which sits to the south of the ancient Hualca Hualca volcano and several frequently active faults, thus resulting in complex volcano-tectonic interactions. After 15 years of repose, in 2013, a series of 4 earthquakes with magnitude >4.5 occurred within 24 h, marking the beginning of a new episode of unrest. Several additional swarms of earthquakes occurred in the following years until magmatic eruptive activity started on 6 November 2016. This activity is ongoing as of this writing, with an average of 50 explosions per day. In this study, we present results of multiparametric monitoring of Sabancaya's activity observed during 2013–2020. Seismic data are used to create a one-dimensional seismic velocity model, to catalog, locate, and characterize earthquakes, to detect repeating earthquake families, and to monitor seismic velocity variations by ambient noise cross-correlation. These analyses are complemented by visual and remote sensing observations and ground deformation measurements. All monitored parameters showed significant changes on 6 November 2016, the day of eruption onset, thus dividing the eruptive activity into pre-eruptive and eruptive stages.
The unrest is characterized by high levels of seismic activity with hundreds of events detected per day. Volcano-tectonic (VT) earthquakes were dominant during the pre-eruptive period while long-period (LP) events and explosions have been most numerous since the eruption onset. Earthquake locations highlight long-lasting seismogenic zones along multiple previously active regional faults, as well as along newly identified faults. This VT seismicity is mainly distributed in a sector from the northwest to the east of the volcanic complex at distances of up to 30 km from the crater. We focus our analysis on two eruptive episodes: the eruption onset and subsequent crater migration from south to north, and the increase of lava dome extrusion rate in 2019. Both episodes are accompanied by seismic velocity decreases of up to 0.2% and are preceded by a few weeks by bursts of distal VT activity, including numerous repeating earthquakes. These repeated events were located on several remote tectonic faults (5–25 km from the vent). We suggest that these phenomena could be due to the injection of a batch of magma in the deep reservoir and/or conduit, which would generate 1) a pressure wave propagating in the hydrothermal system, triggering the bursts of seismic activity and 2) slow rising of magma by melting old material filling the conduit that eventually produced the eruptive and dome growth acceleration events.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107767","usgsCitation":"Machacca, R., Lesage, P., Tavera, H., Pesicek, J., Caudron, C., Torres, J., Puma, N., Vargas, K., Lazarte, I., Rivera, M., and Burgisser, A., 2023, The 2013−2020 seismic activity at Sabancaya Volcano (Peru): Long lasting unrest and eruption: Journal of Volcanology and Geothermal Research, v. 435, 107767, 21 p., https://doi.org/10.1016/j.jvolgeores.2023.107767.","productDescription":"107767, 21 p.","ipdsId":"IP-149045","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2023.107767","text":"Publisher Index Page"},{"id":413229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Andes Mountains, Sabancaya Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.88759125278847,\n -15.796325861968512\n ],\n [\n -71.87969027972629,\n -15.806737845832032\n ],\n [\n -71.86380245345819,\n -15.818058204597975\n ],\n [\n -71.82223646473676,\n -15.826238215481283\n ],\n [\n -71.81244612854955,\n -15.800540300892976\n ],\n [\n -71.82300938601416,\n -15.781120098585575\n ],\n [\n -71.84559586335715,\n -15.77459118709939\n ],\n [\n -71.87101638538533,\n -15.778971366114547\n ],\n [\n -71.88759125278847,\n -15.796325861968512\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"435","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Machacca, Roger","contributorId":302572,"corporation":false,"usgs":false,"family":"Machacca","given":"Roger","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesage, P.","contributorId":302573,"corporation":false,"usgs":false,"family":"Lesage","given":"P.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":864725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tavera, H.","contributorId":302574,"corporation":false,"usgs":false,"family":"Tavera","given":"H.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pesicek, J.D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":72233,"corporation":false,"usgs":true,"family":"Pesicek","given":"J.D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":864727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caudron, C.","contributorId":302575,"corporation":false,"usgs":false,"family":"Caudron","given":"C.","affiliations":[{"id":65511,"text":"Université libre de Bruxelles","active":true,"usgs":false}],"preferred":false,"id":864728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torres, J.L.","contributorId":302576,"corporation":false,"usgs":false,"family":"Torres","given":"J.L.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864729,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Puma, N.","contributorId":302577,"corporation":false,"usgs":false,"family":"Puma","given":"N.","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864730,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vargas, K.","contributorId":302578,"corporation":false,"usgs":false,"family":"Vargas","given":"K.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864731,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lazarte, I.","contributorId":302579,"corporation":false,"usgs":false,"family":"Lazarte","given":"I.","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864732,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rivera, M.","contributorId":302580,"corporation":false,"usgs":false,"family":"Rivera","given":"M.","email":"","affiliations":[{"id":65510,"text":"Instituto Geofísico del Perú","active":true,"usgs":false}],"preferred":false,"id":864733,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Burgisser, Alain","contributorId":152269,"corporation":false,"usgs":false,"family":"Burgisser","given":"Alain","email":"","affiliations":[{"id":18894,"text":"Universite de Savoie- CNRS, ISTerre","active":true,"usgs":false}],"preferred":false,"id":864753,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70240759,"text":"70240759 - 2023 - Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator","interactions":[],"lastModifiedDate":"2023-06-09T15:08:17.577235","indexId":"70240759","displayToPublicDate":"2023-02-20T19:24:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator","docAbstract":"A series of species introductions, overexploitation, and habitat modification preceded the extirpation of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi; LCT), historically the apex predator, from Lake Tahoe, California-Nevada, USA. Studies evaluating limiting factors for LCT emphasise the need to elucidate food web interactions, yet important knowledge gaps regarding trophic interactions among nonnative pelagic fishes and invertebrates remain. We quantified the abundance and consumption demand of planktivores with an emphasis on kokanee (Oncorhynchus nerka) and Mysis diluviana. We synthesised this new information with existing information for lake trout (Salvelinus namaycush). The seasonal supply of copepods satisfied the consumption demand of kokanee, but only supported low feeding and growth rates. Kokanee relied heavily on Mysis as prey, an unusual result. Mysis exhibited a high degree of herbivory initially followed by heavier consumption on copepods by larger individuals. Consumption demand for Mysis on copepods exceeded that of kokanee during all seasons. Mysis contributed to over 50% of the annual energy budget for lake trout up to 625 mm. Consumption of Mysis by lake trout and kokanee represented a significant source of mortality when compared to the production of Mysis. Predation on kokanee was sustainable, only involved lake trout >625 mm, and was focused on prespawning aggregations. Despite the presence of Mysis-fueled lake trout, kokanee have persisted; a noteworthy pattern when considering the negative responses of kokanee to nonnative lake trout and Mysis observed elsewhere. This pattern suggests that there may still be an effective niche for LCT in the invaded Lake Tahoe ecosystem.
","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1111/eff.12706","usgsCitation":"Hansen, A.G., McCoy, A., Thiede, G., and Beauchamp, D., 2023, Pelagic food web interactions in a large invaded ecosystem: Implications for reintroducing a native top predator: Ecology of Freshwater Fish, v. 32, no. 3, p. 552-570, https://doi.org/10.1111/eff.12706.","productDescription":"19 p.","startPage":"552","endPage":"570","ipdsId":"IP-147438","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499263,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12706","text":"Publisher Index Page"},{"id":413228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.9928593695287,\n 38.91420593218916\n ],\n [\n -119.94067431093485,\n 38.9505270086465\n ],\n [\n -119.9420476019504,\n 38.99003174862847\n ],\n [\n -119.93655443788818,\n 39.05404664405532\n ],\n [\n -119.92831469179416,\n 39.065776420173194\n ],\n [\n -119.9310612738256,\n 39.10521681856693\n ],\n [\n -119.94479418398184,\n 39.1148070943255\n ],\n [\n -119.92144823671603,\n 39.15102524650783\n ],\n [\n -119.91870165468492,\n 39.17977344901294\n ],\n [\n -119.92419481874748,\n 39.245743362733606\n ],\n [\n -119.99560595155981,\n 39.25850457367247\n ],\n [\n -120.00933886171606,\n 39.23829825056396\n ],\n [\n -120.02169848085674,\n 39.243616268460954\n ],\n [\n -120.06976366640359,\n 39.245743362733606\n ],\n [\n -120.09585619570052,\n 39.22553336277909\n ],\n [\n -120.10684252382566,\n 39.19893238916717\n ],\n [\n -120.15078783632549,\n 39.174450594299515\n ],\n [\n -120.15353441835695,\n 39.15528498086624\n ],\n [\n -120.17413378359132,\n 39.13504894619777\n ],\n [\n -120.16726732851319,\n 39.11587259996395\n ],\n [\n -120.17413378359132,\n 39.096691033476816\n ],\n [\n -120.16314745546619,\n 39.068975111804775\n ],\n [\n -120.13156176210668,\n 39.060444945335746\n ],\n [\n -120.13293505312258,\n 39.041248302223124\n ],\n [\n -120.12606859804447,\n 39.00710805468577\n ],\n [\n -120.10684252382566,\n 38.99323386992151\n ],\n [\n -120.10272265077865,\n 38.96761284332854\n ],\n [\n -120.12606859804447,\n 38.951594994011174\n ],\n [\n -120.09722948671609,\n 38.924890532506595\n ],\n [\n -120.07113695741916,\n 38.93557352390823\n ],\n [\n -120.03543139101299,\n 38.9291639221442\n ],\n [\n -120.01620531679418,\n 38.91741148121298\n ],\n [\n -119.9928593695287,\n 38.91420593218916\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":864734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Allison","contributorId":302581,"corporation":false,"usgs":false,"family":"McCoy","given":"Allison","email":"","affiliations":[{"id":65512,"text":"Washington Cooperative Fish and Wildlife Research Unit, School of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, Washington 98195, USA","active":true,"usgs":false}],"preferred":false,"id":864735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiede, Gary P.","contributorId":302582,"corporation":false,"usgs":false,"family":"Thiede","given":"Gary P.","affiliations":[{"id":65513,"text":"Department of Watershed Science and The Ecology Center, Utah State University, Logan, Utah 84322, USA","active":true,"usgs":false}],"preferred":false,"id":864736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":864737,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240761,"text":"70240761 - 2023 - Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","interactions":[],"lastModifiedDate":"2023-11-07T14:56:20.584618","indexId":"70240761","displayToPublicDate":"2023-02-20T16:04:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows","docAbstract":"Regulation of river flow regimes by dams and diversions impacts aquatic biota and ecosystems globally. However, our understanding of the ecological consequences of flow alteration and ecological benefits of flow restoration lags behind our ability to manipulate flows, and there is a need for broader development of flow–ecology relationships. Approaches for establishing flow–ecology relationships have recently shifted away from state-based methods that analyze snapshots of ecological conditions and towards rate-based methods focused on mechanisms that link hydrology with dynamics of important ecological components and processes.
We used a rate-based approach to validate environmental flow standards developed for the lower Brazos River, Texas, by analyzing the relationship between flow regime components and recruitment strength of imperiled Shoal Chub Macrhybopsis hyostoma, a fluvial specialist and pelagic-broadcast-spawning fish. We collected 254 age-0 Shoal Chub (9–40 mm total length), extracted their otoliths to estimate age in days, and used a generalized additive model to regress the number of captured recruits that hatched on a calendar date against flow regime metrics, such as pulse magnitude, flow rate of change, and pulse timing in relation to environmental flow standards proposed by a science advisory committee (Brazos Basin and Bay Area Expert Science Team).
The model revealed that flow magnitude, rate of change, and timing were all significant predictors that collectively explained 60% of variation in the recruitment strength index. Hindcasting for 1919–2020 showed a general reduction in recruitment strength following commencement of flow regulation in the lower Brazos River and revealed that high recruitment correlated with years in which most or all proposed flow tiers were attained, whereas low recruitment correlated with years when less than half of the targeted tiers were attained.
Our work represents an effective validation method for environmental flow recommendations and reveals specific flow regimes that benefit an imperiled fish species.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10837","usgsCitation":"Perkin, J., Acre, M.R., Ellard, J.K., Rodger, A.W., Trungale, J., Winemiller, K.O., and Yancy, L.E., 2023, Flow–recruitment relationships for Shoal Chub and implications for managing environmental flows: North American Journal of Fisheries Management, v. 43, no. 5, p. 1260-1275, https://doi.org/10.1002/nafm.10837.","productDescription":"16 p.","startPage":"1260","endPage":"1275","ipdsId":"IP-137319","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":413226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Brazos River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.55664204856129,\n 34.891337132196966\n ],\n [\n -103.67919574341136,\n 34.90431733940822\n ],\n [\n -103.67460945809466,\n 33.88709425240866\n ],\n [\n -100.07733765481305,\n 32.32672893624452\n ],\n [\n -97.58389153733157,\n 30.525918073387786\n ],\n [\n -96.49599579297191,\n 28.1805962671085\n ],\n [\n -95.17251974775999,\n 28.869046167859096\n ],\n [\n -96.08662137570019,\n 30.375252554772146\n ],\n [\n -96.7579178547347,\n 31.664902948076772\n ],\n [\n -99.43674912606912,\n 33.62884152650054\n ],\n [\n -101.21968168739465,\n 34.14353705447044\n ],\n [\n -103.55664204856129,\n 34.891337132196966\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Perkin, Joshuah S.","contributorId":238286,"corporation":false,"usgs":false,"family":"Perkin","given":"Joshuah S.","affiliations":[{"id":47708,"text":"Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX","active":true,"usgs":false}],"preferred":false,"id":864741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":864742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellard, Johnathan K.","contributorId":302585,"corporation":false,"usgs":false,"family":"Ellard","given":"Johnathan","email":"","middleInitial":"K.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodger, Anthony W.","contributorId":302586,"corporation":false,"usgs":false,"family":"Rodger","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":864744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trungale, Joe","contributorId":302587,"corporation":false,"usgs":false,"family":"Trungale","given":"Joe","email":"","affiliations":[{"id":65515,"text":"Texas Conservation Science","active":true,"usgs":false}],"preferred":false,"id":864745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winemiller, Kirk O.","contributorId":265134,"corporation":false,"usgs":false,"family":"Winemiller","given":"Kirk","email":"","middleInitial":"O.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yancy, Lauren E.","contributorId":302588,"corporation":false,"usgs":false,"family":"Yancy","given":"Lauren","email":"","middleInitial":"E.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":864747,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240754,"text":"70240754 - 2023 - Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region","interactions":[],"lastModifiedDate":"2023-02-20T22:04:07.85217","indexId":"70240754","displayToPublicDate":"2023-02-20T15:55:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region","docAbstract":"Accurate mapping of streams that maintain surface flow during annual baseflow periods in mountain headwater streams is important for informing water availability for human consumption and is a fundamental determinant of in-channel conditions for stream-dwelling organisms. Yet accurate mapping that captures local spatial variability and associated local controls on surface flow presence is limited. An empirical random-forest model was developed to predict streamflow permanence (late summer surface-flow presence) for Mount Rainier National Park and the surrounding mountainous area in western Washington, USA. This model was developed to improve upon the existing multi-state, regional-scale probability of stream permanence developed for the greater Pacific Northwest Region (PROSPERPNW). The model was trained on 544 wet/dry observations collected during the late summer, baseflow period from 2018 to 2020 using the crowd-source mobile application, FLOwPER. Final model accuracy was 0.74 with drainage area and covariates describing geology, topography, and land cover as top predictors of streamflow permanence compared to coarser resolution climatic covariates. The prevalence of static covariates over climatic covariates as top ranked important covariates highlights the importance of scale when evaluating controls on streamflow permanence. Cross validation of the model indicates that streamflow permanence probabilities from this model is an improvement over the regional-scale PROSPERPNW model demonstrating the utility of relatively simple, crowd-sourced data to address water resource needs, and that determination of important predictors of streamflow permanence is influenced by the spatial and temporal resolution of analysis.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14813","usgsCitation":"Jaeger, K.L., Sando, R., Dunn, S., and Gendaszek, A.S., 2023, Predicting probabilities of late summer surface flow presence in a glaciated mountainous headwater region: Hydrological Processes, v. 37, no. 2, e14813, 20 p., https://doi.org/10.1002/hyp.14813.","productDescription":"e14813, 20 p.","ipdsId":"IP-141066","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":444412,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14813","text":"Publisher Index Page"},{"id":435442,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P942QL23","text":"USGS data release","linkHelpText":"Supporting data for and predictions from streamflow permanence modeling in Mount Rainier National Park and surrounding area, Washington, 2018-2020"},{"id":413225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mt. Rainier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.91425095542269,\n 47.01752002020956\n ],\n [\n -122.78795134745224,\n 46.62862820386181\n ],\n [\n -122.55339493264981,\n 46.550098584041734\n ],\n [\n -122.65563747243549,\n 46.34497384739839\n ],\n [\n -122.89620815428425,\n 46.09474739160191\n ],\n [\n -122.7909584809756,\n 45.92766699262768\n ],\n [\n -122.74585147812789,\n 45.67282216496895\n ],\n [\n -122.66766600652696,\n 45.61185277936909\n ],\n [\n -122.30380285023114,\n 45.54239311283217\n ],\n [\n -121.81664721948816,\n 45.70223191477319\n ],\n [\n -121.67531194390217,\n 45.68332742209245\n ],\n [\n -121.45879833023858,\n 45.69383070693286\n ],\n [\n -121.1580849779278,\n 45.630781413305954\n ],\n [\n -120.98066410006487,\n 45.679125555918176\n ],\n [\n -121.06185670518839,\n 46.012189334319174\n ],\n [\n -121.07388523928094,\n 46.11234505718508\n ],\n [\n -120.77317188697053,\n 46.28718041984081\n ],\n [\n -120.78219328754065,\n 46.50050734721816\n ],\n [\n -120.60477240967734,\n 46.628693092975396\n ],\n [\n -120.65589367957018,\n 46.69473497860815\n ],\n [\n -120.90548576198775,\n 46.88004533998597\n ],\n [\n -121.37760572511556,\n 47.1445446352175\n ],\n [\n -122.05120363429107,\n 47.246711543948805\n ],\n [\n -122.36695265421739,\n 47.369052224585346\n ],\n [\n -122.54136639855736,\n 47.309956252224225\n ],\n [\n -122.67368027357409,\n 47.14249929055501\n ],\n [\n -122.9052295548532,\n 47.16294919605744\n ],\n [\n -122.91425095542269,\n 47.01752002020956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":864708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Sarah B. 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":291768,"corporation":false,"usgs":false,"family":"Dunn","given":"Sarah B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":864709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70254725,"text":"70254725 - 2023 - Survival rates of band-tailed pigeons estimated using passive integrated transponder tags","interactions":[],"lastModifiedDate":"2024-06-07T12:23:07.129432","indexId":"70254725","displayToPublicDate":"2023-02-20T07:20:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Survival rates of band-tailed pigeons estimated using passive integrated transponder tags","docAbstract":"Obtaining survival estimates on the Interior population of band-tailed pigeons (Patagioenas fasciata) is challenging because they are trap shy, but the joint use of passive integrated transponder (PIT) tags and bands is a potential solution. We investigated the use of PIT tags to passively recapture band-tailed pigeon at 3 locations in New Mexico, USA, to estimate survival. From 2013–2015, we captured, banded, and marked >600 individual band-tailed pigeons with PIT tags. To estimate annual survival rates, we used a Barker multi-state joint live and dead encounters and resighting model. Survival models excluding transience had survival estimates across site, sex, and year of 0.86 (95% CI = 0.84–0.88) for after hatch year birds and 0.63 (95% CI = 0.48–0.76) for hatch year birds. These results are consistent with other survival estimates reported for the Interior population of band-tailed pigeons using band return data and potentially provide an effective alternative method of monitoring survival of this population.