In 2015–16, a comparison study of stream sediment collection techniques was done for a U.S. Geological Survey streamgage on the Nemadji River near South Superior, Wisconsin (U.S. Geological Survey station number 04024430) to provide an adjustment factor for comparing suspended-sediment rating curves for two historical periods 1973–86 and 2006–16. During 1973–1986, the U.S. Geological Survey used the equal-width-increment technique to collect suspended-sediment concentration data (EWI SSC). The Wisconsin Department of Natural Resources and Minnesota Pollution Control Agency collected grab samples for total suspended solids (grab TSS) concentration starting in 2006 and continuing beyond 2016. In addition to the comparison study of suspended-sediment concentrations, bedload and bed material samples were collected in 2015–16, and the modified Einstein procedure was run to further characterize total sediment loads. The 2015–16 study indicated that the EWI SSC and grab TSS concentrations were different, but not as much as expected, especially on the high end where grab TSS concentrations were sometimes higher than EWI SSC concentrations, possibly due to a combination of a high percentage of fines in suspension and higher concentrations in the center of the channel than the margins. The 2015–16 measured bedload made up a small percentage of total sediment load, and bedload and streambed particle sizes are 90 to 100 percent sand sized or smaller. The relative proportion of measured bedload to total load decreased with increased streamflow, and for streamflows greater than 1,800 cubic feet per second, the suspended load made up 98 percent of the total load. Calculated 2015–16 instantaneous total sediment loads from the modified Einstein procedure were up to 70 percent of the measured loads for flows less than 1,000 cubic feet per second and near or more than 100 percent for flows greater than 1,000 cubic feet per second. The sediment rating curve developed for the 2006–16 adjusted grab TSS data had a similar slope but a lower intercept than its 1973–86 EWI SSC counterpart, indicating that for a given streamflow, suspended-sediment concentrations were lower for 2006–16 compared to 1973–86. The negative offset equates to estimates of annual suspended-sediment loads in 2006–16 being on average 87 percent of the 1973–86 loads. Over the period 2009–16, annual suspended-sediment loads ranged from a low of about 21,000 tons per year in 2015 to a high of 167,000 tons per year in 2012 with a mean of 85,000 tons per year. However, reductions in suspended-sediment concentrations are likely obscured by large loads during years with flooding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211003","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., 2021, Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016: U.S. Geological Survey Open-File Report 2021–1003, 27 p., https://doi.org/10.3133/ofr20211003.","productDescription":"Report: viii, 27 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-085024","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FX0X6Y","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Selected sediment data and results from regression models, modified Einstein Procedure, and loads estimation for the Nemadji River, 1973–2016"},{"id":385360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1003/ofr20211003.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1003"},{"id":385359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1003/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Nemadji River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.55157470703125,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.38672781370433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Baker River (Washington, USA) sockeye salmon (Oncorhynchus nerka) are a recovering Puget Sound stock that are aided by trap-and-haul and hatchery programs to mitigate for the presence of a high head dam. The relative contribution of hatchery and natural adults to overall production of smolts and recruits is unknown. The ability to identify three different sockeye production groups (natural production, artificial incubation, and artificial spawning beach) within the Baker system is crucial to moving forward with management goals. The examination of otoliths was proposed as a technical tool for improved understanding and management of Baker sockeye rebuilding efforts. Otoliths were chosen as they provide a chronological record on an individual fish basis and have been shown to identify fish origin through both otolith microstructure and chemistry.
The goal of this pilot project was to determine the feasibility of assigning sockeye to their production source based on otolith analysis. A variety of methods were employed and compared for accuracy of group assignment. The maximum overall accuracy capable of attainment was 88.57 percent, however complete confidence (100 percent) in the separation of natural production from artificial production was reached through the analysis of trace elements alone. Some segregation of the two artificial production groups was reached through analysis of a few specific trace elements (magnesium, manganese, and zinc). This confidence in assignment for the artificial production groups was aided by a two-step process of combining trace elements with microstructure. The Sr isotope ratios supported the trace element findings but did not help to boost the overall level of confidence in the separation of production groups. Based upon the results from this preliminary investigation, one could choose a statistically sound, efficient, and cost-effective use of otoliths as a tool for discriminating between the sockeye production groups of the Baker Lake system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211032","collaboration":"A Report to the Upper Skagit Indian Tribe per agreement # 17WNYD00SIT5545","usgsCitation":"Larsen, K.A., Wetzel, L.A., Stenberg, K.D., and Lind-Null, A.M., 2021, Investigation of otolith microstructure and composition for identification of rearing strategies and associated Baker Lake sockeye salmon (Oncorhynchus nerka) smolt production, Washington, 2016–17: U.S. Geological Survey Open-File Report 2021–1032, 15 p., https://doi.org/10.3133/ofr20211032.","productDescription":"vii, 16 p.","onlineOnly":"Y","ipdsId":"IP-091287","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":385712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1032/coverthb.jpg"},{"id":385713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1032/ofr20211032.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1032"}],"country":"United States","state":"Washington","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.626757,48.288991],[-122.620748,48.282961],[-122.623779,48.269431],[-122.652639,48.265081],[-122.66921,48.240614],[-122.668385,48.223967],[-122.628352,48.222467],[-122.606406,48.208262],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571853,48.102143],[-122.54512,48.05255],[-122.513994,48.059077],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.358812,47.93742],[-122.376837,47.923703],[-122.380497,47.904023],[-122.397349,47.912401],[-122.431035,47.914732],[-122.445519,47.930226],[-122.44076,47.951845],[-122.446682,47.963155],[-122.47266,47.988449],[-122.501257,47.987089],[-122.521219,47.972997],[-122.546824,47.967215],[-122.552053,47.973644],[-122.542924,47.996404],[-122.58178,48.010386],[-122.607342,48.030992],[-122.593621,48.0472],[-122.594922,48.056318],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.677337,48.154587],[-122.693084,48.181509],[-122.763042,48.215342],[-122.770045,48.224395],[-122.752563,48.260061],[-122.732022,48.279425],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664928,48.374823],[-122.664659,48.401508],[-122.634991,48.404244],[-122.63582,48.395128],[-122.609715,48.411565],[-122.60198,48.409907],[-122.595351,48.3972],[-122.585038,48.395166],[-122.585162,48.353304],[-122.551334,48.342138],[-122.506568,48.310041],[-122.505828,48.297677],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460027,47.48686],[-122.433385,47.46643],[-122.439415,47.458633],[-122.437656,47.407424],[-122.395054,47.399277],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.469702,47.344623],[-122.493122,47.330253],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.497862,47.475915],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.644901,48.691389],[-122.618225,48.670721],[-122.609576,48.645018],[-122.635299,48.651846],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.722262,48.731624],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.028091,48.973943],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.804869,48.595932],[-122.801096,48.585425],[-122.770349,48.558106],[-122.788503,48.530393],[-122.787347,48.523012],[-122.777467,48.517799],[-122.779124,48.508911],[-122.817912,48.483888],[-122.81973,48.458843],[-122.803521,48.428748],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.913888,48.443231],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.067675,48.479497],[-123.119451,48.492576],[-123.141478,48.505291],[-123.163234,48.529544],[-123.16147,48.547618],[-123.176266,48.562131],[-123.173061,48.579086],[-123.184941,48.58697],[-123.197754,48.586216],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.098462,48.612834],[-123.101552,48.59782],[-123.074611,48.591816],[-123.048403,48.569216],[-123.015046,48.560821],[-122.987296,48.561895],[-122.98611,48.569984],[-122.995026,48.578162],[-123.016647,48.580244],[-123.034101,48.591767],[-123.023433,48.599477],[-123.04653,48.61149],[-123.048652,48.621002],[-123.023495,48.634001],[-123.009924,48.655064],[-122.949116,48.693398],[-122.942367,48.706723],[-122.894599,48.71503],[-122.833124,48.698173],[-122.800267,48.67962],[-122.743049,48.661991],[-122.755031,48.649512],[-122.792147,48.633502],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.186076,48.684917],[-123.14799,48.668001],[-123.106165,48.633473],[-123.134956,48.63724],[-123.215917,48.669352],[-123.237148,48.683466],[-123.236567,48.68895],[-123.212892,48.689713],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.007511,48.718863],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.03636,48.69008],[-123.070427,48.699971],[-123.040179,48.717296],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.610841,48.561146],[-122.578856,48.54813],[-122.572967,48.529028],[-122.599948,48.536904],[-122.635738,48.526021],[-122.649256,48.528769],[-122.654342,48.537956],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.694672,48.596602],[-122.670638,48.568812],[-122.68944,48.543903],[-122.722407,48.540606],[-122.73048,48.565602],[-122.73944,48.573893],[-122.739898,48.583949],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.676796,48.610055],[-122.699266,48.621115]]],[[[-122.334524,48.018916],[-122.321721,48.019977],[-122.303455,48.005603],[-122.326115,48.010295],[-122.334524,48.018916]]],[[[-122.418268,47.320614],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.361336,47.481421],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.370167,47.583087],[-122.342937,47.59122],[-122.339513,47.599113],[-122.344937,47.60912],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.393248,47.701602],[-122.38044,47.709119],[-122.37314,47.729219],[-122.382641,47.749119],[-122.380241,47.758519],[-122.396422,47.777927],[-122.394944,47.803318],[-122.33595,47.852306],[-122.328546,47.897917],[-122.311927,47.923703],[-122.307048,47.949117],[-122.249007,47.959507],[-122.230046,47.970917],[-122.226346,47.976417],[-122.232391,47.987713],[-122.224979,48.016626],[-122.231761,48.029876],[-122.281087,48.049793],[-122.326119,48.092877],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.372492,48.193022],[-122.395499,48.228551],[-122.433767,48.23655],[-122.449605,48.232598],[-122.45371,48.228859],[-122.449513,48.214736],[-122.441731,48.211776],[-122.45493,48.196639],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.358375,48.056133],[-122.377114,48.057568],[-122.400692,48.085255],[-122.4675,48.130353],[-122.489986,48.120617],[-122.512031,48.133931],[-122.53722,48.183745],[-122.538916,48.209683],[-122.530996,48.249821],[-122.503786,48.257045],[-122.480925,48.251706],[-122.463962,48.270541],[-122.406516,48.25183],[-122.395328,48.257187],[-122.392058,48.269628],[-122.371693,48.287839],[-122.408718,48.326413],[-122.442678,48.337934],[-122.475529,48.359912],[-122.507437,48.364666],[-122.533452,48.383409],[-122.539449,48.39719],[-122.554536,48.40604],[-122.558403,48.426758],[-122.551221,48.439465],[-122.557298,48.444438],[-122.575254,48.443333],[-122.581607,48.429244],[-122.61448,48.41488],[-122.649839,48.408526],[-122.674158,48.424726],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.664623,48.478128],[-122.689121,48.476849],[-122.700603,48.457632],[-122.712322,48.464143],[-122.712981,48.47879],[-122.701644,48.497622],[-122.684521,48.509123],[-122.671386,48.50398],[-122.606961,48.522152],[-122.599951,48.520946],[-122.598469,48.512169],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.46967,48.474975],[-122.483501,48.49243],[-122.485288,48.528106],[-122.498463,48.556206],[-122.504428,48.564775],[-122.531978,48.568644],[-122.534719,48.574246],[-122.495904,48.575927],[-122.478431,48.559303],[-122.44456,48.570115],[-122.425271,48.599522],[-122.448702,48.622624],[-122.46425,48.625717],[-122.500308,48.656163],[-122.519172,48.713095],[-122.495301,48.737328],[-122.490401,48.751128],[-122.510902,48.757728],[-122.535803,48.776128],[-122.567498,48.779185],[-122.596844,48.771492],[-122.637146,48.735708],[-122.626287,48.72093],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.630422,48.696625],[-122.673472,48.733082],[-122.647443,48.773998],[-122.646777,48.785011],[-122.693683,48.804475],[-122.699303,48.789063],[-122.709815,48.786205],[-122.709169,48.817829],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.821631,48.941369],[-122.817226,48.95597],[-122.774276,48.991038],[-122.756318,48.996881],[-122.75802,49.002357],[-121.751252,48.997399],[-117.032351,48.999188],[-117.042623,47.761223],[-117.039813,46.425425],[-117.034696,46.418318],[-117.046915,46.379577],[-117.062785,46.365287],[-117.062748,46.353624],[-117.055983,46.345531],[-117.023844,46.335976],[-117.020663,46.314793],[-116.986688,46.296662],[-116.991134,46.276342],[-116.966742,46.256923],[-116.955264,46.23088],[-116.965841,46.203417],[-116.92187,46.167808],[-116.950276,46.123464],[-116.955263,46.102237],[-116.976957,46.09667],[-116.982479,46.089389],[-116.978938,46.080007],[-116.957372,46.075449],[-116.942656,46.061],[-116.91718,45.996575],[-118.987129,45.999855],[-119.027056,45.969134],[-119.12612,45.932859],[-119.19553,45.92787],[-119.25715,45.939926],[-119.322509,45.933183],[-119.364396,45.921605],[-119.450256,45.917354],[-119.487829,45.906307],[-119.524632,45.908605],[-119.571584,45.925456],[-119.600549,45.919581],[-119.623393,45.905639],[-119.669877,45.856867],[-119.772927,45.845578],[-119.802655,45.84753],[-119.907461,45.828135],[-119.965744,45.824365],[-120.07015,45.785152],[-120.141352,45.773152],[-120.170453,45.761951],[-120.210754,45.725951],[-120.282156,45.72125],[-120.40396,45.699249],[-120.482362,45.694449],[-120.505863,45.700048],[-120.559465,45.738348],[-120.591166,45.746547],[-120.634968,45.745847],[-120.68937,45.715847],[-120.855674,45.671545],[-120.895575,45.642945],[-120.913476,45.640045],[-120.943977,45.656445],[-120.983478,45.648344],[-121.06437,45.652549],[-121.084933,45.647893],[-121.120064,45.623134],[-121.117052,45.618117],[-121.145534,45.607886],[-121.183841,45.606441],[-121.196556,45.616689],[-121.200367,45.649829],[-121.215779,45.671238],[-121.33777,45.704949],[-121.372574,45.703111],[-121.401739,45.692887],[-121.423592,45.69399],[-121.462849,45.701367],[-121.499153,45.720846],[-121.533106,45.726541],[-121.631167,45.704657],[-121.668362,45.705082],[-121.707358,45.694809],[-121.735104,45.694039],[-121.811304,45.706761],[-121.867167,45.693277],[-121.901855,45.670716],[-121.900858,45.662009],[-121.908267,45.654399],[-121.935149,45.644169],[-121.955734,45.643559],[-121.963547,45.632784],[-121.983038,45.622812],[-122.044374,45.609516],[-122.101675,45.583516],[-122.183695,45.577696],[-122.2017,45.564141],[-122.266701,45.543841],[-122.331502,45.548241],[-122.352802,45.569441],[-122.380302,45.575941],[-122.438674,45.563585],[-122.548149,45.596768],[-122.675008,45.618039],[-122.76381,45.657138],[-122.774511,45.680437],[-122.760108,45.734413],[-122.761451,45.759163],[-122.769532,45.780583],[-122.795605,45.81],[-122.785026,45.867699],[-122.81151,45.912725],[-122.806193,45.932416],[-122.813998,45.960984],[-122.837638,45.98082],[-122.856158,46.014469],[-122.878092,46.031281],[-122.884478,46.06028],[-122.904119,46.083734],[-122.962681,46.104817],[-123.004233,46.133823],[-123.041297,46.146351],[-123.115904,46.185268],[-123.166414,46.188973],[-123.280166,46.144843],[-123.371433,46.146372],[-123.430847,46.181827],[-123.427629,46.229348],[-123.474844,46.267831],[-123.501245,46.271004],[-123.547659,46.259109],[-123.547636,46.265595],[-123.613544,46.259988],[-123.669501,46.266832],[-123.679125,46.272502],[-123.680574,46.296025],[-123.700764,46.305278],[-123.724273,46.301161],[-123.727913,46.289661],[-123.741478,46.290274],[-123.766682,46.273499],[-123.806139,46.283588],[-123.875525,46.239787],[-123.919581,46.251217],[-123.954353,46.277001],[-123.974509,46.303063],[-124.001264,46.31326],[-124.020551,46.315737],[-124.029924,46.308312],[-124.044018,46.275925],[-124.060961,46.278761],[-124.080671,46.267239],[-124.064624,46.326899],[-124.057425,46.409315],[-124.057024,46.493338],[-124.068655,46.634879],[-124.062715,46.642582],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.050842,46.617421],[-124.023566,46.582559],[-124.031737,46.496375],[-124.026032,46.462978],[-123.990615,46.463019],[-123.99268,46.488617],[-123.983688,46.498542],[-123.968044,46.473497],[-123.943667,46.477197],[-123.921192,46.507731],[-123.896703,46.522665],[-123.894254,46.537028],[-123.920247,46.567343],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.87668,46.730657],[-123.898641,46.750205],[-123.916371,46.741322],[-123.91285,46.730647],[-123.916874,46.726739],[-123.948683,46.725369],[-123.968564,46.736106],[-123.974994,46.733391],[-123.979655,46.724658],[-123.966886,46.705184],[-123.994242,46.707929],[-124.003458,46.702337],[-124.063117,46.733664],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.110641,46.91252],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.046344,46.893972],[-124.01366,46.90363],[-123.985082,46.921916],[-123.957493,46.921261],[-123.86018,46.948556],[-123.898245,46.971927],[-123.939214,46.969739],[-123.959185,46.981759],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.017035,47.011717],[-124.026345,47.030187],[-124.065856,47.04114],[-124.122057,47.04165],[-124.141517,47.035142],[-124.151288,47.021112],[-124.138035,46.970959],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.25359,47.30248],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.336724,47.415996],[-124.355955,47.545698],[-124.382215,47.632302],[-124.412106,47.691199],[-124.425195,47.738434],[-124.453927,47.765334],[-124.47657,47.769671],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.67083,47.982366],[-124.682157,48.035987],[-124.696542,48.069274],[-124.695114,48.087096],[-124.687101,48.098657],[-124.733174,48.163393],[-124.731746,48.169997],[-124.704153,48.184422],[-124.696111,48.198599],[-124.690389,48.219745],[-124.705031,48.238774],[-124.684677,48.255228],[-124.676319,48.295143],[-124.665908,48.299324],[-124.65894,48.331057],[-124.670072,48.341341],[-124.696703,48.349748],[-124.727022,48.371101],[-124.731828,48.381157],[-124.716947,48.389776],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.250882,48.264773],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.880068,48.160621],[-123.858821,48.154273],[-123.778122,48.155466],[-123.728736,48.1628],[-123.71835,48.158713],[-123.702743,48.166783],[-123.651408,48.156952],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.288265,48.121036],[-123.239129,48.118217],[-123.21719,48.127203],[-123.1644,48.165894],[-123.133445,48.177276],[-123.143229,48.156633],[-123.116479,48.150208],[-123.085154,48.127137],[-123.06621,48.120469],[-123.038727,48.081138],[-122.979413,48.09594],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.918602,48.058238],[-122.877641,48.047025],[-122.849273,48.053808],[-122.857727,48.065774],[-122.878255,48.076072],[-122.882013,48.100779],[-122.876282,48.110877],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.778466,48.106135],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.698465,48.103102],[-122.68724,48.101662],[-122.69222,48.087081],[-122.682264,48.042723],[-122.668942,48.032026],[-122.669868,48.017217],[-122.686898,48.008305],[-122.70184,48.016106],[-122.723374,48.008095],[-122.718082,47.987739],[-122.701294,47.972979],[-122.6788,47.96793],[-122.676215,47.958743],[-122.68445,47.939593],[-122.657722,47.931156],[-122.651063,47.920985],[-122.655085,47.905058],[-122.646494,47.894771],[-122.610341,47.887343],[-122.631857,47.874815],[-122.63636,47.866186],[-122.69376,47.868002],[-122.681602,47.850405],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.880462,47.720643],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.917103,47.620743],[-122.856611,47.649615],[-122.804498,47.653363],[-122.754186,47.671612],[-122.740159,47.736228],[-122.722686,47.748827],[-122.714801,47.768176],[-122.690562,47.778372],[-122.682015,47.800882],[-122.623192,47.836199],[-122.608105,47.856728],[-122.573672,47.857582],[-122.573098,47.874081],[-122.588235,47.912923],[-122.620316,47.931553],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.527593,47.905882],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.485214,47.804128],[-122.495346,47.79704],[-122.495458,47.786692],[-122.471402,47.765965],[-122.470333,47.757109],[-122.471844,47.749819],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.53094,47.704814],[-122.511196,47.708715],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.500357,47.617816],[-122.49824,47.598242],[-122.493933,47.588963],[-122.479089,47.583654],[-122.518367,47.57408],[-122.543118,47.556326],[-122.546611,47.52355],[-122.52305,47.524],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.575985,47.32642],[-122.547521,47.285344],[-122.578211,47.254804],[-122.589454,47.227618],[-122.602541,47.217506],[-122.611464,47.2181],[-122.668571,47.270449],[-122.697378,47.283969],[-122.671256,47.343774],[-122.632463,47.376394],[-122.671486,47.366876],[-122.725738,47.33047],[-122.74525,47.297158],[-122.749621,47.276408],[-122.718124,47.250045],[-122.648941,47.214531],[-122.641802,47.205013],[-122.673925,47.174675],[-122.691771,47.141958],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.816633,47.276457],[-122.799025,47.289306],[-122.796646,47.341654],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.84586,47.298405],[-122.863732,47.270221],[-122.856171,47.233788],[-122.838298,47.208353],[-122.858735,47.167955],[-122.852046,47.164359],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.650634,47.132738],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.561957,47.244099],[-122.527586,47.291531],[-122.547747,47.316403],[-122.533338,47.31662],[-122.471652,47.277321],[-122.4442,47.266723],[-122.429605,47.269707],[-122.409199,47.288556],[-122.444635,47.300421],[-122.418268,47.320614]]]]},\"properties\":{\"name\":\"Washington\",\"nation\":\"USA \"}}]}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Evaporation-rate estimates at Lake Mead and Lake Mohave, Nevada and Arizona, were based on eddy covariance and available energy measurements from March 2010 through April 2019 at Lake Mead and May 2013 through April 2019 at Lake Mohave. The continuous data needed to compute monthly evaporation were collected from floating-platform and land-based measurement stations located at each reservoir. Collected data include latent- and sensible-heat fluxes, net radiation, air temperature, wind speed, humidity, and water-temperature profiles. Data collection, analysis methods, and monthly evaporation results for Lake Mead through February 2012 were documented in a U.S. Geological Survey (USGS) Scientific-Investigations Report, 2013–5229. Monthly evaporation and associated datasets for both reservoirs through April 2015 were published in a USGS Data Release (https://doi.org/10.5066/F79C6VG3). Average annual evaporation at Lake Mead was 1,896 millimeters (mm), which is a 10 percent difference from the 1,718 mm average annual evaporation at Lake Mohave; this was primarily due to differences in available energy. Average annual available energy at Lake Mead was 139 watts per square meter (W/m2), which is an 18 percent difference from the 116 W/m2 average annual available energy at Lake Mohave. Differences in available energy are driven by differences in advected heat between Lake Mead and Lake Mohave; advected heat at Lake Mohave is lower due to colder inflows and warmer outflows. Lake Mead monthly evaporation estimates for this study compare reasonably well to the Bureau of Reclamation’s 24-Month Study (24MS) evaporation coefficients, which are based on pioneering studies from the 1950s. Temporal trends in this study indicate that the effects of heat storage at Lake Mead were underestimated in the 24MS, particularly during the fall months when energy was released from the lake. Mean monthly evaporation rates at Lake Mead were greater than Lake Mohave from June through November during the study period. The seasonal pattern of evaporation at Lake Mohave in this study indicates that the effects of available energy were underestimated in the 24MS coefficients for this reservoir, and that evaporation was substantially overestimated from spring through summer
during the study period of 2013 through 2019.
Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Pursuant to Section 7002 (“Mineral Security”) of Title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Cong.), the Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked with reviewing and revising the methodology used to evaluate mineral criticality and the U.S. Critical Minerals List no less than every 3 years. The initial Critical Minerals List was published in the Federal Register on May 18, 2018, in response to Executive Order No. 13817, A Federal Strategy to Ensure Secure and Reliable Supplies of Critical Minerals (3 CFR, 2017 Comp, p. 397–399). This report documents the updated evaluation methodology and the resultant updated draft list of minerals recommended for inclusion in the Critical Minerals List.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211045","usgsCitation":"Nassar, N.T., and Fortier, S.M., 2021, Methodology and technical input for the 2021 review and revision of the U.S. Critical Minerals List: U.S. Geological Survey Open-File Report 2021–1045, 31 p., https://doi.org/10.3133/ofr20211045.","productDescription":"viii, 31 p.","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127319","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":384978,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1045/ofr20211045.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1045"},{"id":384977,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1045/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Due to high mortality in the first year or two of life, Lost River (Deltistes luxatus sp.) and Shortnose suckers (Chasmistes brevirostris sp.) in Upper Klamath Lake, Oregon rarely reach maturity. In 2015, the U.S. Fish and Wildlife Service began the Sucker Assisted Rearing Program (SARP) to improve early life survival before releasing the fish back into Upper Klamath Lake. Survival and growth rates were compared for fish in mesocosms among three potential release or in-lake rearing sites, and in a pond at the SARP rearing facility. Fish used in this study included a mix of Lost River, Shortnose, and Klamath largescale suckers reared at either U.S. Fish and Wildlife Service or Klamath Tribes fish rearing facilities. These sites were Shoalwater Bay (SWB), Rattlesnake Point (RPT), and Cove Point (CPT). Ninety-nine to 103 suckers tagged with passive integrated transponders (PIT) were placed into each mesocosm for up to 80 days and up to 103 days in the SARP pond. Cessation of movement, as determined by passive detection of tagged fish on remote antennas, indicated mortality. Dissolved-oxygen saturation, temperature, and pH were tracked hourly in each mesocosm. All the suckers placed into the SWB mesocosm died during an extreme hypoxia event. These fish were replaced with another 120 PIT-tagged and 2 untagged hatchery-reared Lost River suckers from the Klamath Tribes Fish Research Facility (KTFRF), of which, all but two died during a second extreme hypoxia event. It was determined that SWB was an unsuitable site for summertime release or rearing of juvenile suckers in 2018. The summer survival rate was ≥86 percent at CPT, RPT, and the SARP pond. Suckers in the SARP pond grew slightly slower and gained less weight relative to increases in length than suckers held at RPT and CPT. All suckers sampled at the start of the study from both the SARP facility and the KTFRF, when water temperatures averaged approximately 18–22 degrees Celsius (°C), were infected with low levels of the gill parasite Ichthyobodo sp. Ichthyobodo sp. was detected on only 1 of 16 suckers sampled from CPT, RPT, and the SARP pond in late September or early October when water temperatures were approximately 16–19 °C, indicating fish were able to shed the parasite in cooler temperatures. Water quality conditions at RPT and CPT were adequate for in-lake rearing of SARP suckers in 2018. Due to interannual differences in water quality conditions, these sites may not be suitable in all years. Future research focused on the suitability of RPT, CPT and other potential sites under in years with varying conditions would be beneficial for improving sucker in-lake rearing practices. Additional research could help to elucidate how size at entry into the mesocosms affects sucker survival.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211036","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., Conway, C.M., Ostberg, C.O., Bart, R.J., and Elliott, D.G., 2021, Survival and growth of suckers in mesocosms at three locations within Upper Klamath Lake, Oregon, 2018: U.S. Geological Survey Open-File Report 2021–1036, 18 p., https://doi.org/10.3133/ofr20211036.","productDescription":"v, 18 p.","onlineOnly":"Y","ipdsId":"IP-119761","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":385517,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1036/coverthb.jpg"},{"id":385518,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1036/ofr20211036.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1036"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.79031372070312,\n 42.24478535602799\n ],\n [\n -121.79855346679686,\n 42.39810802339276\n ],\n [\n -121.95098876953125,\n 42.6147595985433\n ],\n [\n -122.12265014648438,\n 42.48627657532139\n ],\n [\n -121.96884155273436,\n 42.34129022434778\n ],\n [\n -121.9207763671875,\n 42.261049162113856\n ],\n [\n -121.81365966796874,\n 42.22139878761366\n ],\n [\n -121.79031372070312,\n 42.24478535602799\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities supported the U.S. Geological Survey priorities of enabling integrated predictive science, producing FAIR (Findable, Accessible, Interoperable, Reusable) data, building modular and reusable tools, building authoritative national datasets for hazards or assets, and developing tools and methods for biosurveillance of emerging invasive species and health threats. Through these efforts, community members were informed of new and emerging technologies and data topics that helped them in their professional responsibilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211016","usgsCitation":"Hsu, L., and Liford, A.N., 2021, Community for Data Integration 2019 Annual Report: U.S. Geological Survey Open-File Report 2021–1016, 19 p., https://doi.org/10.3133/ofr20211016.","productDescription":"iv, 19 p.","onlineOnly":"Y","ipdsId":"IP-119547","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":385363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1016/ofr20211016.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1016"},{"id":385362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1016/coverthb.jpg"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey (USGS) formed the internal Research Grade Evaluation (RGE) Review Team in May 2017. The Team undertook a 2-year comprehensive review of RGE practices and policies at the USGS that included (1) the first-ever quantitative assessment of the USGS workforce evaluated under the RGE process, (2) a benchmarking meeting in March 2018 of the USGS and 11 other Federal science agencies to compare how each conducts research scientist evaluation, and (3) extensive surveys of four internal stakeholder groups. The Team recommends that the RGE review process emphasize the importance of outcomes resulting from a scientist’s efforts, rather than focusing on easily quantified outputs such as peer-reviewed papers, presentations, and posters. Thus, the Team recommends that a scientist’s work be assessed according to contributions and impacts in three areas: (1) scientific understanding, (2) the missions of the U.S. Geological Survey and the U.S. Department of the Interior, and (3) society more broadly. The Team developed (1) new formats for the Research Scientist Record (RSR) and Development Scientist Record (DSR) that match the Office of Personnel Management’s guidelines for factor scoring and (2) new findings templates to provide more meaningful feedback to scientists.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211035","usgsCitation":"U.S. Geological Survey Research Grade Evaluation Review Team, 2021, Final report on the assessment of the U.S. Geological Survey’s bureauwide Research Grade Evaluation (RGE) process: U.S. Geological Survey Open-File Report 2021–1035, 106 p., https://doi.org/10.3133/ofr20211035.","productDescription":"vi, 106 p.","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120198","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":385219,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1035/coverthb.jpg"},{"id":385220,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1035/ofr20211035.pdf","text":"Report","size":"2.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1035"}],"contact":"Office of Science Quality and Integrity
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 911
Reston, VA 20192
This study was conducted by the U.S. Geological Survey and Northeastern University in cooperation with the U.S. Fish and Wildlife Service and The Nature Conservancy. This report summarizes field investigation and analysis of waves, current patterns, and sediment deposition and erosion along the Gandys Beach, New Jersey, salt marsh vegetated shoreline and mudflat, where living shoreline structures (for example, oyster reefs) were constructed to protect the marsh shoreline and enhance habitat for oyster and other species. Constructed oyster reefs (CORs, also known as oyster castles) provide shoreline protection and habitat for fish and shellfish communities via wave energy attenuation. However, the processes and mechanism of CORs on wave attenuation and current circulation remain unclear, thus limiting the assessment of COR effectiveness for shoreline protection. This report presents the results of the field investigation on wave characteristics, current patterns, and marsh edge erosion along a shoreline with CORs in Delaware Bay. To measure the effectiveness of these CORs, six pressure transducers, six tilt current meters, multiple sediment traps, and marsh edge erosion pins were deployed from February to April 2018 in Gandys Beach in upper Delaware Bay. The spatial variations of wave heights measured on both sides of the CORs indicate a strong dependence of wave attenuation on the ratio between the freeboard of the CORs and the offshore wave heights. It was found that swell energy originating from the Atlantic Ocean can penetrate the CORs without any dampening even when the CORs are emergent, whereas the wind seas are more impacted by the CORs. Tidal current velocity and circulation patterns near the CORs (for example, the current velocity was higher than 10 centimeters per second [cm/s] and even up to 30 cm/s in the gaps between the CORs compared to less than 10 cm/s in the control area) differ from those in the control area without protection from the CORs and are greatly affected by the surrounding bathymetry. The combined effect of living shoreline structures on wave attenuation and changes in circulation patterns over the study period resulted in the reduction of shoreline erosion both vertically and laterally compared to that in the control area and also resulted in changes in the grain size distribution in both the water column and the salt marsh and mudflat areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211040","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and The Nature Conservancy
Prepared in collaboration with Northeastern University
Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st St.
Gainesville, FL 32653
Water, bed sediment, and invertebrate tissue were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the Clark Fork Basin. The sampling program was completed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin and monitor trace elements associated with historical mining and smelting activities. Sampling sites were on the river and tributaries of the Clark Fork. Water samples were collected periodically at 20 sites from October 2018 through September 2019. Bed-sediment and tissue samples were collected once at 13 sites during July 2019.
Water-quality data included concentrations of major ions, dissolved organic carbon, nitrogen (nitrate plus nitrite), trace elements, and suspended sediment. Daily values of turbidity were determined at four sites. Bed-sediment data included trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data included trace-element concentrations in whole-body tissue of aquatic benthic invertebrates. Statistical summaries of water-quality, bed-sediment, and invertebrate tissue trace-element data for sites in the Clark Fork Basin were provided for the period of record: March 1985–September 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211027","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Clark, G.D., Hornberger, M.I., Hepler, E.J., Cleasby, T.E., and Heinert, T.L., 2021, Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2018–September 2019: U.S. Geological Survey Open-File Report 2021–1027, 16 p., https://doi.org/10.3133/ofr20211027.","productDescription":"Report: vi, 16 p.; Data Release; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-122934","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":385286,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1027/coverthb.jpg"},{"id":385287,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1027/ofr20211027.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 1027–1027"},{"id":385288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GKHL8W","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2018–September 2019"},{"id":385289,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.13421630859374,\n 47.10565336099383\n ],\n [\n -114.39788818359375,\n 47.025206001585396\n ],\n [\n -114.25506591796875,\n 46.613601326659726\n ],\n [\n -114.00238037109375,\n 46.58718152732907\n ],\n [\n -113.15917968749999,\n 46.15890744507131\n ],\n [\n -112.69775390625,\n 45.84793427349226\n ],\n [\n -112.00836181640625,\n 46.15319980124842\n ],\n [\n -111.88201904296875,\n 46.428392162921234\n ],\n [\n -113.00262451171875,\n 46.848921470800455\n ],\n [\n -113.631591796875,\n 47.13368783277605\n ],\n [\n -114.13421630859374,\n 47.10565336099383\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, from October 2017 through September 2018 (water year 2018) and from October 2018 through September 2019 (water year 2019). Major findings for this period include the following:
Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Suite 500
Norcross, GA 30093
Coking coal, or metallurgical coal, has been produced in the United States for nearly 200 years. Coking coal is primarily used in the production of coke for use in the steel industry, and for other uses (for example, foundries, blacksmithing, heating buildings, and brewing). Currently, U.S. coking coal is produced in Alabama, Arkansas, Pennsylvania, Virginia , and West Virginia. Historically, coking coal has also been produced in 15 other states (Alaska, Colorado, Georgia, Illinois, Indiana, Kentucky, Maryland, Montana, New Mexico, Ohio, Oklahoma, Tennessee, Utah, Washington, and Wyoming), but currently is not. Coals from the Appalachian, Arkoma, and Illinois basins are Pennsylvanian in age, while coals in Alaska, Colorado, Montana, New Mexico, Utah, Washington, and Wyoming range in age from Early Cretaceous through Eocene.
This Open-File Report presents the geographic locations of current and historical coking coal deposits of the United States, with additional information about recent and historical mining and exploration activities. Chemical, rheological, petrographic, and other criteria for evaluating the coking potential of coals are discussed, and historical data for coking coals in the United States are presented. In addition, new coking coal samples from Alabama, Arkansas, Kentucky, and Oklahoma were collected and analyzed for this report, and the data are presented in multiple tables, including proximate and ultimate analyses; calorific value; sulfur forms; major-, minor-, and trace-element abundances; Free-Swelling Index; Gieseler Plastometer analyses; American Society for Testing and Materials (ASTM) dilatation; coal petrography; and predicted values of Coal Stability Factor and Coal Strength after Reaction with CO2 (pCSF and pCSR, respectively). Data from previously analyzed coking coal samples in Kentucky, Pennsylvania, Virginia, and West Virginia were supplied by three companies, including results from all the tests listed above, plus oxidation, Hardgrove Grindability Index, and ash fusion (in a reducing environment) temperatures are also presented in tables in the report.
Geographic Information System (GIS) data compiled for this project are available for download for public and private utilization and may be used to create maps for a variety of energy resource studies. These GIS data are in shapefile format, and metadata files are included describing all GIS processing. Additional geographic information about coking coal areas of the United States are also presented in tabular format in the report, including the following: names of coal basins, fields, regions, districts, and areas; coal beds or zones; geographic locations including States, counties, towns, rivers, mountains, etc.; stratigraphic hierarchy and age of the coal-bearing interval; coking characteristics including sulfur content, ash yield, volatile matter, moisture, calorific value, and Free-Swelling Index; coal rank; names of coal mines and coal-mining companies; current and past mining activity; and references for reports about the coal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201113","usgsCitation":"Trippi, M.H., Ruppert, L.F., Eble, C.F., and Hower, J.C., 2021, Coking coal of the United States—Modern and historical coking coal mining locations and chemical, rheological, petrographic, and other data from modern samples: U.S. Geological Survey Open-File Report 2020–1113, 112 p., https://doi.org/10.3133/ofr20201113.","productDescription":"Report: xi, 112 p.; Tables 1.1-21.1; Data Release; Metadata; Spatial Data","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111543","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":381899,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113_appendix_tables_csv.zip","text":"Tables","size":"88.9 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Zip file of tables in appendixes 1 through 21 in CSV format"},{"id":381894,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1113/coverthb.jpg"},{"id":381895,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":381896,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KFQOKM","text":"USGS data release","linkHelpText":"Coking coal of the United States: Modern and historical locations of coking coal mining locations and chemical, rheological, petrographic, and other data from modern samples"},{"id":381898,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113_appendix_tables_excel.zip","text":"Tables","size":"295 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Zip file of tables in appendixes 1 through 21 in Excel format"},{"id":382122,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113_shapefiles.zip","size":"466 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- GIS shapefiles of the coking coal resources in the United States"},{"id":381897,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2020/1113/ofr20201113_metadata.zip","size":"101 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- For spatial data"}],"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":"Geology, Energy & Minerals Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
954 National Center
Reston, VA 20192
The historic distribution of Mojave desert tortoises (Gopherus agassizii) was relatively continuous across the range, and the importance of tortoise habitat outside of designated tortoise conservation areas (TCAs) to recovery has long been recognized for its contributions to supporting gene flow between TCAs and to minimizing impacts and edge effects within TCAs. However, connectivity of Mojave desert tortoise populations has become a concern because of recent and proposed development of large tracts of desert tortoise habitat that cross, fragment, and surround designated conservation areas. This paper summarizes the underlying concepts and importance of connectivity for Mojave desert tortoise populations by reviewing current information on connectivity and providing information to managers for maintaining or enhancing desert tortoise population connectivity as they consider future proposals for development and management actions.
Maintaining an ecological network for the Mojave desert tortoise, with a system of core habitats (TCAs) connected by linkages, is necessary to support demographically viable populations and long-term gene flow within and between TCAs. There are four points for wildlife and land-management agencies to consider when making decisions that could affect connectivity of Mojave desert tortoise populations (for example, in updating actions in resource management plans or amendments that could help maintain or restore functional connectivity in light of the latest information):
Each TCA has unique strengths and weaknesses regarding its ability to support minimum sustainable populations based on areal extent and its ability to support population increases based on landscape connection with adjacent populations. Considering how proposed projects (inside or outside of TCAs) affect connectivity and the ability of TCAs to support at least 5,000 adult tortoises (the numerical goal for each TCA) could help managers to maintain the resilience of TCAs to population declines. The same project, in an alternative location, could have very different impacts on local and regional populations. For example, within the habitat matrix surrounding TCAs, narrowly delineated corridors may not allow for natural population dynamics if they do not accommodate overlapping home ranges along most of their widths so that tortoises reside, grow, find mates, and produce offspring that can replace older tortoises. In addition, most habitat outside TCAs may receive more surface disturbance than habitat within TCAs. Therefore, managing the entire remaining matrix of desert tortoise habitat for permeability may be better than delineating fixed corridors. These concepts apply, especially given uncertainty about long-term condition of habitat, within and outside of TCAs under a changing climate.
Ultimately, questions such as “What are the critical linkages that need to be protected?” could be better framed as “How can we manage the remaining habitat matrix in ways that sustain ecological processes and habitat suitability for special status species?” Land-management decisions made in the context of the latter question may be more conducive to maintenance of a functional ecological network.
In California, the Bureau of Land Management established 0.1–1.0 percent caps on new surface-disturbance for TCAs and mapped linkages that address the issues described in number 1 of this list.
Nevada, Utah, and Arizona currently do not have surface-disturbance limits. Limits comparable to those in the Desert Renewable Energy Conservation Plan (DRECP) would be 0.5 percent within TCAs and 1 percent within the linkages modeled by Averill-Murray and others (2013). Limits in some areas of California within the Desert Renewable Energy Conservation Plan, such as Ivanpah Valley, are more restrictive, at 0.1 percent. Continuity across the state line in Nevada could be achieved with comparable limits in the adjacent portion of Ivanpah Valley, as well as the Greater Trout Canyon Translocation Area and the Stump Springs Regional Augmentation Site. These more restrictive limits would help protect remaining habitat in the major interstate connectivity pathway through Ivanpah Valley and focal areas of population augmentation that provide additional population connectivity along the western flank of the Spring Mountains.
In a recent study that analyzed 13 years of desert tortoise monitoring data, nearly all desert tortoise observations were at sites in which 5 percent or less of the surrounding landscape within 1 kilometer was disturbed (Carter and others, 2020a). To help maintain tortoise habitability and permeability across all other non-conservation-designated tortoise habitat, all surface disturbance could be limited to less than 5-percent development per square kilometer because the 5-percent threshold for development is the point at which tortoise occupation drops precipitously (Carter and others, 2020a). However, although individual desert tortoises were observed at development levels up to 5 percent, we do not know the fitness or reproductive characteristics of these individuals. This level of development also may not allow for long-term persistence of healthy populations that are of adequate size needed for demographic or functional connectivity; therefore, a conservative interpretation suggests that, ideally, development could be lower. Lower development levels would be particularly useful in areas within the upper 5th percentile of connectivity values modeled by Gray and others (2019).
Reducing ancillary threats in places where connectivity is restricted to narrow strips of habitat, for example, narrow mountain passes or vegetated strips between solar development, could enhance the functionality of these vulnerable linkages. In such areas, maintaining multiple, redundant linkages could further enhance overall connectivity.
Minimization of mortality from roads and maximization of passage under roads. Roads pose a significant threat to the long-term persistence of local tortoise populations, and roads of high traffic volume lead to severe population declines, which ultimately fragments populations farther away from the roads. Three points (a.–c.) pertain to reducing direct mortality of tortoises on the many paved roads that cross desert tortoise habitat and to maintaining a minimal level of permeability across these roads:
Tortoise-exclusion fencing tied into culverts, underpasses, overpasses, or other passages below roads in desert tortoise habitat, would limit vehicular mortality of tortoises and provide opportunities for movement across the roads. Installation of shade structures on the habitat side of fences installed in areas with narrow population-depletion zones would limit overheating of tortoises that may pace the fence.
Passages below highways could be maintained or retrofitted to ensure safe tortoise access, for example, by filling eroded drop-offs or modifying erosion-control features such as rip-rap to make them safer and more passable for tortoises. Wildlife management agencies could work with transportation departments to develop construction standards that are consistent with hydrologic/erosion management goals, while also incorporating a design and materials consistent with tortoise survival and passage and make the standards widely available. The process would be most effective if the status of passages was regularly monitored and built into management plans.
Healthy tortoise populations along fenced highways could be supported by ensuring that land inside tortoise-exclusion fences is not so degraded that it leads to degradation of tortoise habitat outside the exclusion areas. For example, severe invasive plant infestations inside a highway exclusion could cause an increase of invasive plants outside the exclusion area and degrade habitat; therefore, invasive plants inside road rights of way could be mown or treated with herbicide to limit their spread into adjacent tortoise habitat and minimize the risk of these plants carrying wildfires into adjacent habitat.
Adaptation of management based on new information. Future research will continue to build upon and refine models related to desert tortoise population connectivity and develop new ones. New models could consider landscape levels of development and be constructed such that they share common foundations to support future synthesis efforts. If model development was undertaken in partnership with entities that are responsible for management of desert tortoise habitat, it would facilitate incorporation of current and future modeling results into their land management decisions. There are specific topics that may be clarified with further evaluation:
The effects of climate change on desert tortoise habitat, distribution, and population connectivity;
The effects of large-scale fires, especially within repeatedly burned habitat, on desert tortoise distribution and population connectivity;
The ability of solar energy facilities or similar developments to support tortoise movement and presence by leaving washes intact; leaving native vegetation intact whenever possible, or if not possible, mowing the site, allowing vegetation to re-sprout, and managing weeds; and allowing tortoises to occupy the sites; and
The design and frequency of underpasses necessary to maintain functional demographic and genetic connectivity across linear features, like highways.
Wildlife Program
Prepared in cooperation with the U.S. Fish and Wildlife Service
","usgsCitation":"Averill-Murray, R.C., Esque, T.C., Allison, L.J., Bassett, S., Carter, S.K., Dutcher, K.E., Hromada, S.J., Nussear, K.E., and Shoemaker, K., 2021, Connectivity of Mojave Desert tortoise populations—Management implications for maintaining a viable recovery network: U.S. Geological Survey Open-File Report 2021–1033, 23 p., https://doi.org/10.3133/ofr20211033.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-125269","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":385161,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1033/covrthb.jpg"},{"id":385162,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":385163,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1033/images"},{"id":385164,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1033/ofr20211033.xml"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.71923828124999,\n 33.669496972795535\n ],\n [\n -113.8623046875,\n 33.578014746143985\n ],\n [\n -112.69775390625,\n 33.50475906922609\n ],\n [\n -111.51123046875,\n 33.284619968887675\n ],\n [\n -111.73095703125,\n 34.10725639663118\n ],\n [\n -111.9287109375,\n 35.51434313431818\n ],\n [\n -113.00537109375,\n 36.24427318493909\n ],\n [\n -114.3896484375,\n 36.73888412439431\n ],\n [\n -115.86181640625001,\n 37.07271048132943\n ],\n [\n -117.42187500000001,\n 37.68382032669382\n ],\n [\n -118.27880859375001,\n 37.579412513438385\n ],\n [\n -117.7734375,\n 35.97800618085566\n ],\n [\n -117.72949218749999,\n 35.44277092585766\n ],\n [\n -118.76220703125001,\n 34.75966612466248\n ],\n [\n -117.99316406249999,\n 34.488447837809304\n ],\n [\n -116.74072265625,\n 34.288991865037524\n ],\n [\n -114.71923828124999,\n 33.669496972795535\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Red-throated loons (Gavia stellata) are a species of conservation concern in Alaska due to recent evidence of a population decline on the Arctic Coastal Plain (ACP) in northern Alaska. In 2019, the U.S. Geological Survey and the U.S. Fish and Wildlife Service conducted a pilot study to evaluate diet and use of nearshore foraging areas as possible drivers of the population decline. We collected fat biopsies to examine diet of breeding red-throated loons using previously outlined methods. We also deployed GPS-Ultra High Frequency transmitters on red-throated loons for an initial understanding of detailed offshore marine habitat use during the breeding season. A broader research project on marine habitat use and fish diet of breeding red-throated loons will begin in 2021 on the Canning River Delta and in Foggy Island Bay, Alaska.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211029","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Uher-Koch, B.D., Latty, C.J., and Schmutz, J.A., 2021, Red-throated loon (Gavia stellata) use of nearshore marine habitats—Results from a 2019 pilot study in Northern Alaska: U.S. Geological Survey Open-File Report 2021–1029, 4 p., https://doi.org/10.3133/ofr20211029.","productDescription":"iv, 4 p.","onlineOnly":"Y","ipdsId":"IP-125193","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":385133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1029/coverthb.jpg"},{"id":385134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1029/ofr20211029.pdf","text":"Report","size":"795 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1029"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.5081787109375,\n 70.0435668608635\n ],\n [\n -145.535888671875,\n 70.0435668608635\n ],\n [\n -145.535888671875,\n 70.29606309973389\n ],\n [\n -146.5081787109375,\n 70.29606309973389\n ],\n [\n -146.5081787109375,\n 70.0435668608635\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The U.S. Geological Survey (USGS) collected borehole geophysical and video logs in 17 open-hole wells in Northampton, Warminster, and Warwick Townships, Bucks County, Pennsylvania during 2017–19 to support detailed groundwater investigations at and near the former Naval Air Warfare Center (NAWC) Warminster, where groundwater contamination with per- and polyfluoroalkyl substances (PFAS) had become a concern since 2014. The area is underlain by the Triassic Stockton Formation, which forms a fractured-sedimentary-rock aquifer used for private, industrial, and public drinking-water supply. The geophysical and video logs were used to characterize the boreholes and identify potential water-bearing fractures for subsequent detailed investigations. Of the 17 wells that were logged, subsequent investigations were conducted by USGS in 15 wells and included hydraulic tests of discrete water-bearing zones using a straddle-packer system in 13 wells and depth-discrete point sampling in 2 wells. These 15 wells ranged in depth from about 210 to 604 feet (ft) below land surface (bls) and included six new 6-inch diameter wells drilled to initial depths of 600 ft bls on the former NAWC Warminster base property in 2018 and nine 8- to 12-inch diameter existing former production or unused test wells. Partial geophysical or video logs also were collected by USGS during 2018 in two other wells that were not included in subsequent detailed investigations.
Most wells had numerous water-bearing fractures or openings throughout the depth of the open boreholes. Most of these water-bearing features appeared to be openings parallel to bedding or high-angle fractures approximately orthogonal to bedding. Casing lengths ranged from about 19 to 93 ft bls. Depth to the ambient water level at the time of logging ranged from about 1.8 ft above land surface in a flowing well to about 55 ft bls. Measured borehole flow was predominantly downward in most of the deepest wells (greater than 400 ft), which were commonly located at the highest land-surface elevations, and contained inflow from fractures at relatively shallow depths and outflow through fractures near or below depths of 500 ft bls. Borehole flow was predominantly upward in most wells less than 400 ft in depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211025","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Senior, L.A., Anderson, J.A., and Bird, P.H., 2021, Geophysical and video logs of selected wells at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania, 2017–19: U.S. Geological Survey Open-File Report 2021–1025, 92 p., https://doi.org/10.3133/ofr20211025.","productDescription":"x, 92 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118758","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":384970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1025/coverthb.jpg"},{"id":384971,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1025/ofr20211025.pdf","text":"Report","size":"12.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1025"}],"country":"United States","state":"Pennsylvania","county":"Bucks County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-75.1908,40.5916],[-75.1909,40.59],[-75.1922,40.5858],[-75.1929,40.5828],[-75.193,40.5805],[-75.193,40.5791],[-75.1903,40.5742],[-75.1851,40.5701],[-75.1801,40.5676],[-75.1761,40.5667],[-75.1719,40.5657],[-75.1664,40.565],[-75.1614,40.5655],[-75.1567,40.5673],[-75.1537,40.5691],[-75.1503,40.5711],[-75.1472,40.5729],[-75.1447,40.5742],[-75.1411,40.5756],[-75.1393,40.5759],[-75.1344,40.5763],[-75.126,40.5756],[-75.1181,40.5746],[-75.1175,40.5745],[-75.1096,40.5725],[-75.1037,40.5707],[-75.0996,40.5683],[-75.0968,40.5664],[-75.095,40.5649],[-75.0913,40.5618],[-75.0856,40.557],[-75.0798,40.5523],[-75.0755,40.5491],[-75.0725,40.5464],[-75.0682,40.5432],[-75.0662,40.5402],[-75.0651,40.5364],[-75.0645,40.5333],[-75.0651,40.5287],[-75.065,40.5264],[-75.065,40.5247],[-75.0655,40.5209],[-75.0656,40.5201],[-75.0656,40.5147],[-75.0649,40.5115],[-75.0644,40.5096],[-75.0641,40.5073],[-75.0636,40.4991],[-75.0636,40.491],[-75.0631,40.4855],[-75.0633,40.4824],[-75.0645,40.4783],[-75.0651,40.476],[-75.0672,40.4689],[-75.0682,40.4657],[-75.0694,40.463],[-75.0706,40.4598],[-75.0707,40.4571],[-75.0714,40.4544],[-75.0714,40.4529],[-75.0711,40.4512],[-75.0705,40.4478],[-75.0693,40.4444],[-75.0676,40.4416],[-75.0662,40.4385],[-75.0651,40.4358],[-75.0649,40.4353],[-75.0649,40.434],[-75.0637,40.4294],[-75.0627,40.4252],[-75.0616,40.4224],[-75.0606,40.4205],[-75.0581,40.4192],[-75.0551,40.4173],[-75.0527,40.4168],[-75.0492,40.4154],[-75.046,40.4136],[-75.0433,40.4116],[-75.0409,40.4102],[-75.0373,40.408],[-75.0332,40.4065],[-75.0296,40.4055],[-75.0266,40.4054],[-75.0217,40.4062],[-75.0186,40.4071],[-75.0134,40.4083],[-75.0068,40.4106],[-75.004,40.4113],[-75.001,40.4117],[-74.9982,40.412],[-74.9973,40.412],[-74.9948,40.4117],[-74.9907,40.4108],[-74.9868,40.4089],[-74.9844,40.408],[-74.983,40.4075],[-74.982,40.4071],[-74.9776,40.4054],[-74.9756,40.4045],[-74.9723,40.403],[-74.9692,40.4014],[-74.9688,40.401],[-74.9663,40.3989],[-74.9647,40.3965],[-74.9626,40.394],[-74.9606,40.391],[-74.9585,40.3876],[-74.9559,40.3832],[-74.9532,40.3786],[-74.9498,40.37],[-74.9473,40.3616],[-74.9463,40.3546],[-74.9448,40.3483],[-74.9437,40.3451],[-74.9411,40.3419],[-74.9372,40.3387],[-74.9339,40.3356],[-74.9314,40.3334],[-74.929,40.3311],[-74.9254,40.3279],[-74.9217,40.3248],[-74.9177,40.3222],[-74.9149,40.3201],[-74.9144,40.3199],[-74.9107,40.3183],[-74.9066,40.3173],[-74.9029,40.3168],[-74.9,40.3162],[-74.8976,40.3158],[-74.8939,40.3144],[-74.8916,40.3138],[-74.8887,40.3119],[-74.8863,40.3105],[-74.8836,40.3092],[-74.8787,40.3045],[-74.8735,40.2997],[-74.8697,40.2959],[-74.8671,40.2934],[-74.8655,40.2919],[-74.8607,40.2855],[-74.8584,40.2814],[-74.8558,40.276],[-74.854,40.2713],[-74.8521,40.2674],[-74.8498,40.2641],[-74.8485,40.2606],[-74.846,40.2575],[-74.8432,40.2538],[-74.8412,40.2511],[-74.8397,40.2496],[-74.8393,40.2493],[-74.8374,40.2478],[-74.8351,40.247],[-74.8279,40.2439],[-74.8208,40.2402],[-74.8165,40.2385],[-74.8115,40.2369],[-74.8061,40.235],[-74.8019,40.2331],[-74.7971,40.2307],[-74.7965,40.2304],[-74.7911,40.2278],[-74.7852,40.224],[-74.7822,40.2228],[-74.7782,40.2198],[-74.7759,40.2183],[-74.7748,40.2173],[-74.7723,40.2147],[-74.77,40.2114],[-74.7683,40.2087],[-74.7667,40.2055],[-74.7645,40.2023],[-74.7621,40.1996],[-74.7608,40.1973],[-74.7605,40.195],[-74.7592,40.1922],[-74.7583,40.1906],[-74.7566,40.1883],[-74.7541,40.1866],[-74.7512,40.1847],[-74.7488,40.1833],[-74.7464,40.1824],[-74.7421,40.181],[-74.741,40.1806],[-74.7391,40.1788],[-74.7365,40.1769],[-74.7358,40.1763],[-74.7322,40.174],[-74.7283,40.1702],[-74.7252,40.1661],[-74.7233,40.1618],[-74.7229,40.1562],[-74.7248,40.1529],[-74.7252,40.1521],[-74.7277,40.148],[-74.7324,40.1443],[-74.7372,40.1413],[-74.7415,40.1387],[-74.7458,40.1365],[-74.7489,40.1357],[-74.7522,40.1357],[-74.7567,40.1357],[-74.7615,40.1353],[-74.7645,40.1344],[-74.7652,40.1342],[-74.769,40.1329],[-74.7726,40.1311],[-74.7756,40.129],[-74.7787,40.1273],[-74.7812,40.1255],[-74.7816,40.1252],[-74.7842,40.1237],[-74.7867,40.1229],[-74.7894,40.1225],[-74.7924,40.1225],[-74.7932,40.1226],[-74.7963,40.1231],[-74.7997,40.1238],[-74.8052,40.126],[-74.8057,40.1262],[-74.8111,40.1278],[-74.8153,40.1287],[-74.8195,40.1287],[-74.8232,40.1278],[-74.8261,40.1269],[-74.8287,40.1251],[-74.8309,40.1228],[-74.8332,40.1199],[-74.8344,40.1164],[-74.8363,40.1128],[-74.8371,40.1088],[-74.8382,40.1056],[-74.8405,40.1033],[-74.8435,40.1015],[-74.8471,40.0996],[-74.8513,40.0979],[-74.8542,40.0963],[-74.8566,40.0946],[-74.8588,40.0927],[-74.8604,40.0907],[-74.8621,40.0888],[-74.8644,40.0869],[-74.8662,40.0855],[-74.8699,40.0843],[-74.8734,40.0831],[-74.877,40.0819],[-74.8806,40.0805],[-74.8851,40.0792],[-74.8905,40.0778],[-74.8954,40.0765],[-74.8985,40.0754],[-74.9021,40.0745],[-74.9063,40.0737],[-74.91,40.0729],[-74.9136,40.072],[-74.9172,40.0718],[-74.9239,40.0713],[-74.9274,40.0714],[-74.9287,40.0714],[-74.9335,40.0706],[-74.9382,40.0685],[-74.9478,40.0635],[-74.9601,40.0573],[-74.9676,40.0544],[-74.9736,40.0516],[-74.9751,40.0506],[-74.9857,40.0567],[-74.9838,40.0585],[-74.982,40.0603],[-74.9824,40.0648],[-74.9811,40.0675],[-74.9768,40.0697],[-74.9743,40.0737],[-74.9706,40.0759],[-74.9663,40.0786],[-74.9632,40.0812],[-74.9606,40.0852],[-74.9586,40.0915],[-74.9602,40.0984],[-74.9636,40.1039],[-74.9652,40.1085],[-74.9651,40.1134],[-74.9661,40.118],[-74.9679,40.1189],[-74.9714,40.1199],[-74.9762,40.1205],[-74.981,40.121],[-75.0153,40.1394],[-75.0943,40.1867],[-75.1032,40.1923],[-75.1339,40.2106],[-75.1906,40.2439],[-75.1989,40.2486],[-75.2013,40.25],[-75.2592,40.2855],[-75.3001,40.3084],[-75.3007,40.3089],[-75.3084,40.3131],[-75.3433,40.3341],[-75.3487,40.3378],[-75.3534,40.3406],[-75.3629,40.3462],[-75.383,40.3584],[-75.3985,40.3672],[-75.402,40.3696],[-75.4032,40.37],[-75.4068,40.3724],[-75.4216,40.3812],[-75.4257,40.3845],[-75.4299,40.3873],[-75.4465,40.3975],[-75.4518,40.4008],[-75.4643,40.4082],[-75.4833,40.4194],[-75.4759,40.4266],[-75.4734,40.4292],[-75.4672,40.4346],[-75.4548,40.4457],[-75.451,40.4493],[-75.4492,40.4511],[-75.4454,40.4547],[-75.4113,40.4872],[-75.4094,40.4881],[-75.4026,40.4925],[-75.4008,40.4938],[-75.3909,40.5],[-75.3879,40.5018],[-75.3551,40.5239],[-75.3354,40.5372],[-75.3101,40.5535],[-75.2743,40.5756],[-75.2553,40.5839],[-75.1981,40.611],[-75.1977,40.6097],[-75.1953,40.607],[-75.1934,40.6025],[-75.1921,40.598],[-75.1908,40.5936],[-75.1908,40.5916]]]},\"properties\":{\"name\":\"Bucks\",\"state\":\"PA\"}}]}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service (FWS), began a study in 2019 to complete the compilation and quality assurance of water-resource threats and needs data for the 117 National Wildlife Refuges (NWRs) in the FWS Legacy Mountain-Prairie Region (LMPR) and to characterize the water-resource threats and needs of each refuge and of the LMPR itself. The LMPR encompasses the states of Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, and Wyoming. This report includes the compilation and quality assurance of current (April 2020) water-resource threats and needs data for the refuges in the LMPR and a statistical, graphical, and spatial characterization, including the ranking and prioritization of threat types, threat causes, and needs by the number of occurrences in the LMPR as a whole and by refuges, states, and select U.S. Environmental Protection Agency Level III Ecoregions.
A total of 540 unique threat occurrences were identified for 109 refuges in the LMPR. No threats were identified for eight refuges. About 43 percent of the threat occurrences, for 59 refuges, had a high-severity threat rating. Of the 10 most common threat types, 8 were also among the most common high-severity threat types. Water-resource threats had 72 different causes. About 83 percent of the overall common causes for threats and for high-severity threats were the same. The most common threat types overall and the most common high-severity threat types were compromised water management capability, habitat shifting/alteration, and altered flow regimes. The 20 water-resource threat types for Long Lake NWR were the most for refuges in the LMPR. Other refuges with the greatest number of threat types included Marais des Cygnes NWR (18) and Arapaho and Lee Metcalf NWRs (16 each). About 54 percent of refuges with threats had high-severity threats. Arapaho and Quivira NWRs each had 10 high-severity threat types, the maximum number of high-severity threat types for LMPR refuges.
A total of 637 unique need occurrences were identified for 114 refuges. No needs were reported for three refuges. The most common need type, a Water Resource Inventory and Assessment, was reported for 78 refuges. Two of the most common need types, repair and replace water management infrastructure and water supply/quantity monitoring, were the most common high-priority need types. Bear River Migratory Bird Refuge had the most (39) unique water-resource need types for refuges in the LMPR. Other refuges with the greatest number of need types were Baca (38), Alamosa (36), and Monte Vista (36) NWRs. The most high-priority need types for a refuge was 23, at Monte Vista NWR. Alamosa (22), Baca (22), and Lake Andes (19) NWRs were also among the top 4 refuges with the greatest number of high-priority need types.
An overall ranking scheme was developed to identify refuges that have the highest-ranking priority for conservation efforts to fulfill refuges’ statutory purposes. The count of occurrences of high-severity threats and high-priority needs were summed to determine the overall ranking value for a refuge. The 10 refuges with the highest overall ranking values, in order of ranking from higher to lower, were Alamosa, Baca, and Monte Vista NWRs (tied for highest); Lake Andes NWR, Ouray and Quivira NWRs, Bear River Migratory Bird Refuge and Flint Hills NWR, Cokeville Meadows NWR, and Arapaho NWR.
About 33 percent of overall threat occurrences were reported as under the control of the FWS to mitigate, as were 37 percent of all threat occurrences with a high-severity rating. The most common overall threat types and high-severity threat types under FWS control were compromised water management capability; habitat shifting/alteration; altered flow regimes; loss/alteration of wetland habitat; and legal challenges or fines for non-compliance with water policy, law, or regulation. A total of 68 percent of overall need occurrences and 67 percent of all high-priority need occurrences were under the control of the FWS. The most common overall need types and high-priority needs types under control were repair or replace water management infrastructure, water supply/quantity monitoring, water quality baseline monitoring, and protect habitat from invasive species. A Water Resource Inventory and Assessment was also a common overall need under FWS control, as was the high-priority need of water level monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211007","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Bauch, N.J., Kohn, M.S., and Caruso, B.S., 2021, Characterization of water-resource threats and needs for U.S. Fish and Wildlife Service National Wildlife Refuges in the Legacy Mountain-Prairie Region, 2020: U.S. Geological Survey Open-File Report 2021–1007, 46 p., https://doi.org/10.3133/ofr20211007.","productDescription":"viii, 46 p.","onlineOnly":"Y","ipdsId":"IP-119415","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":384940,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1007/coverthb.jpg"},{"id":384941,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1007/ofr20211007.pdf","text":"Report","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1007"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, Utah, Wyoming","otherGeospatial":"Legacy Mountain Prairie Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.0283203125,\n 36.96744946416934\n ],\n [\n -94.63623046875,\n 37.00255267215955\n ],\n [\n -94.63623046875,\n 39.095962936305476\n ],\n [\n -95.00976562499999,\n 39.62261494094297\n ],\n [\n -94.81201171875,\n 39.85915479295669\n ],\n [\n -95.64697265625,\n 40.51379915504413\n ],\n [\n -96.1083984375,\n 41.60722821271717\n ],\n [\n -96.6357421875,\n 42.66628070564928\n ],\n [\n -96.50390625,\n 43.48481212891603\n ],\n [\n -96.416015625,\n 45.36758436884978\n ],\n [\n -96.85546875,\n 45.61403741135093\n ],\n [\n -96.52587890625,\n 45.9511496866914\n ],\n [\n -96.85546875,\n 46.81509864599243\n ],\n [\n -96.85546875,\n 47.62097541515849\n ],\n [\n -97.20703125,\n 48.1367666796927\n ],\n [\n -97.20703125,\n 48.99463598353405\n ],\n [\n -116.01562499999999,\n 49.03786794532644\n ],\n [\n -116.08154296875001,\n 48.004625021133904\n ],\n [\n -115.4443359375,\n 47.27922900257082\n ],\n [\n -114.36767578124999,\n 46.51351558059737\n ],\n [\n -114.521484375,\n 45.66012730272194\n ],\n [\n -114.14794921875,\n 45.521743896993634\n ],\n [\n -113.99414062499999,\n 45.61403741135093\n ],\n [\n -113.48876953125,\n 44.94924926661153\n ],\n [\n -112.69775390625,\n 44.38669150215206\n ],\n [\n -111.26953125,\n 44.69989765840318\n ],\n [\n -111.11572265625,\n 44.574817404670306\n ],\n [\n -111.0498046875,\n 41.983994270935625\n ],\n [\n -114.01611328125,\n 42.00032514831621\n ],\n [\n -114.06005859375,\n 36.94989178681327\n ],\n [\n -109.0283203125,\n 36.96744946416934\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
This document was prepared in cooperation with Gwinnett County, Georgia, to supplement the journal article “Microbial and Viral Indicators of Pathogens and Human Health Risks from Recreational Exposure to Waters Impaired by Fecal Contamination” (published in Journal of Sustainable Water in the Built Environment). The document includes an executive summary of the article, project ideas for Gwinnett County to enhance its bacterial monitoring program, and an annotated bibliography of selected references from the article. Although tailored to Gwinnett County, the project ideas are based on the state of the science of monitoring for fecal-associated pathogens and pathogen indicators in impaired surface waters and may be of interest to water resources divisions of other municipalities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211028","collaboration":"Prepared in cooperation with Gwinnett County, Georgia","usgsCitation":"McKee, A.M., and Cruz, M.A., 2021, Executive summary and annotated bibliography of selected references from “Microbial and viral indicators of pathogens and human health risks from recreational exposure to waters impaired by fecal contamination” with related project ideas for Gwinnett County, Georgia: U.S. Geological Survey Open-File Report 2021–1028, 10 p., https://doi.org/10.3133/ofr20211028.","productDescription":"v, 10 p.","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123061","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":384887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1028/coverthb.jpg"},{"id":384888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1028/ofr20211028.pdf","text":"Report","size":"1.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1028"}],"country":"United States","state":"Georgia","county":"Gwinnett County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-83.8178,34.1273],[-83.8649,34.0133],[-83.8665,34.0092],[-83.867,34.0083],[-83.8676,34.0074],[-83.8681,34.0065],[-83.8687,34.0051],[-83.8692,34.0047],[-83.8686,34.0042],[-83.8681,34.0042],[-83.8675,34.0042],[-83.867,34.0042],[-83.8664,34.0038],[-83.8659,34.0033],[-83.8653,34.0029],[-83.8647,34.0024],[-83.8642,34.0015],[-83.8636,34.001],[-83.8631,34.0006],[-83.8625,34.0001],[-83.8619,33.9997],[-83.8619,33.9988],[-83.8614,33.9983],[-83.8608,33.9974],[-83.8602,33.9965],[-83.8597,33.9965],[-83.8591,33.9961],[-83.8586,33.9956],[-83.8569,33.9943],[-83.8552,33.9929],[-83.8547,33.9925],[-83.853,33.992],[-83.8519,33.9911],[-83.8502,33.9907],[-83.8496,33.9902],[-83.848,33.9898],[-83.8474,33.9893],[-83.8457,33.9885],[-83.843,33.9862],[-83.8424,33.9858],[-83.8413,33.9853],[-83.8407,33.9849],[-83.8391,33.9844],[-83.8379,33.9831],[-83.8374,33.9822],[-83.8374,33.9808],[-83.8368,33.9794],[-83.8362,33.979],[-83.8357,33.9781],[-83.8357,33.9772],[-83.8351,33.9767],[-83.8351,33.9758],[-83.8351,33.9749],[-83.8345,33.974],[-83.834,33.9735],[-83.8345,33.9731],[-83.8345,33.9722],[-83.8339,33.9717],[-83.8328,33.9704],[-83.8328,33.9695],[-83.8328,33.9686],[-83.8328,33.9676],[-83.8322,33.9667],[-83.8317,33.9663],[-83.8311,33.9663],[-83.83,33.9658],[-83.8261,33.965],[-83.825,33.9645],[-83.8239,33.9641],[-83.8228,33.9623],[-83.8217,33.9623],[-83.8205,33.9614],[-83.82,33.9605],[-83.8194,33.96],[-83.8188,33.9586],[-83.8183,33.9582],[-83.8177,33.9577],[-83.8172,33.9573],[-83.8149,33.955],[-83.8138,33.9546],[-83.8133,33.9537],[-83.8127,33.9528],[-83.8132,33.9514],[-83.8127,33.951],[-83.8132,33.9491],[-83.8115,33.9473],[-83.811,33.9469],[-83.8099,33.9469],[-83.8087,33.9464],[-83.8082,33.946],[-83.8082,33.9446],[-83.8076,33.9442],[-83.8071,33.9433],[-83.806,33.9428],[-83.8054,33.9428],[-83.8043,33.9415],[-83.8043,33.9406],[-83.8048,33.9397],[-83.8054,33.9383],[-83.8059,33.9378],[-83.8053,33.9369],[-83.8037,33.936],[-83.8031,33.9347],[-83.8031,33.9338],[-83.8031,33.9328],[-83.802,33.9319],[-83.8014,33.9315],[-83.8009,33.9319],[-83.8003,33.932],[-83.7997,33.9306],[-83.7992,33.9301],[-83.8008,33.9288],[-83.8299,33.9054],[-83.8343,33.9017],[-83.8442,33.8939],[-83.8551,33.8852],[-83.8952,33.8535],[-83.9023,33.848],[-83.9089,33.8425],[-83.9094,33.8425],[-83.9324,33.8246],[-83.933,33.8246],[-83.9593,33.8044],[-83.9642,33.8007],[-83.9822,33.7864],[-83.9998,33.7722],[-84.0058,33.7676],[-84.0276,33.7501],[-84.0318,33.7471],[-84.0326,33.7473],[-84.0353,33.7482],[-84.0359,33.7482],[-84.0359,33.7491],[-84.0359,33.75],[-84.0365,33.75],[-84.0365,33.7514],[-84.0382,33.7518],[-84.0393,33.7523],[-84.0393,33.7532],[-84.0399,33.7564],[-84.041,33.7582],[-84.0416,33.7586],[-84.0421,33.7595],[-84.0427,33.7604],[-84.0433,33.7609],[-84.0438,33.7618],[-84.0433,33.7622],[-84.0438,33.7627],[-84.0444,33.7627],[-84.0455,33.7636],[-84.0466,33.7645],[-84.0472,33.7654],[-84.0483,33.7658],[-84.0488,33.7658],[-84.0494,33.7654],[-84.0499,33.7654],[-84.0505,33.7663],[-84.0511,33.7667],[-84.0516,33.7667],[-84.0522,33.7667],[-84.0527,33.7672],[-84.0533,33.7681],[-84.0538,33.7685],[-84.055,33.7699],[-84.0555,33.7703],[-84.0561,33.7708],[-84.0567,33.7717],[-84.0572,33.7721],[-84.0578,33.7721],[-84.0583,33.7726],[-84.06,33.773],[-84.0617,33.773],[-84.0633,33.7734],[-84.0644,33.7739],[-84.0655,33.7743],[-84.0683,33.7747],[-84.0711,33.7752],[-84.0716,33.7752],[-84.0722,33.7756],[-84.0738,33.7761],[-84.075,33.777],[-84.0772,33.7788],[-84.08,33.7815],[-84.0806,33.7824],[-84.0822,33.7842],[-84.0845,33.7869],[-84.0862,33.7882],[-84.0867,33.7896],[-84.0873,33.7896],[-84.0884,33.79],[-84.0895,33.7909],[-84.0906,33.7914],[-84.0912,33.7923],[-84.0918,33.7927],[-84.0923,33.7941],[-84.0929,33.7941],[-84.0934,33.795],[-84.094,33.7959],[-84.0957,33.7963],[-84.0968,33.7972],[-84.0979,33.799],[-84.0985,33.7995],[-84.099,33.7999],[-84.1007,33.8008],[-84.1013,33.8008],[-84.1024,33.8013],[-84.1029,33.8013],[-84.1035,33.8012],[-84.104,33.8017],[-84.1052,33.8026],[-84.1057,33.8035],[-84.1068,33.8039],[-84.1079,33.8048],[-84.1085,33.8053],[-84.1091,33.8053],[-84.1096,33.8053],[-84.1102,33.8057],[-84.1107,33.8057],[-84.1113,33.8057],[-84.1118,33.8066],[-84.1124,33.8071],[-84.113,33.8075],[-84.1135,33.8075],[-84.1141,33.8075],[-84.1146,33.8084],[-84.1158,33.8098],[-84.1169,33.8111],[-84.118,33.8125],[-84.1186,33.8129],[-84.1191,33.8138],[-84.1197,33.8143],[-84.1202,33.8152],[-84.1208,33.8156],[-84.1208,33.8165],[-84.1214,33.8174],[-84.1225,33.8188],[-84.1231,33.8188],[-84.1248,33.8206],[-84.1259,33.8215],[-84.1264,33.8224],[-84.127,33.8237],[-84.1281,33.8256],[-84.1287,33.8256],[-84.1304,33.8274],[-84.1315,33.8287],[-84.1326,33.8296],[-84.1332,33.8305],[-84.1338,33.831],[-84.1338,33.8319],[-84.1338,33.8332],[-84.1343,33.8346],[-84.1349,33.835],[-84.1355,33.8355],[-84.136,33.8359],[-84.1366,33.8364],[-84.1371,33.8364],[-84.1383,33.8373],[-84.1416,33.8391],[-84.1461,33.8413],[-84.1466,33.8417],[-84.15,33.8453],[-84.1511,33.8462],[-84.1517,33.8467],[-84.1522,33.8476],[-84.1534,33.8485],[-84.1539,33.8485],[-84.1567,33.8526],[-84.1573,33.853],[-84.1584,33.8534],[-84.1595,33.8534],[-84.1606,33.8539],[-84.1612,33.8539],[-84.164,33.8552],[-84.1656,33.8557],[-84.1667,33.8565],[-84.1673,33.8565],[-84.1684,33.857],[-84.169,33.857],[-84.1706,33.857],[-84.1712,33.8574],[-84.1717,33.8574],[-84.1729,33.8578],[-84.1734,33.8578],[-84.174,33.8583],[-84.1745,33.8592],[-84.1751,33.8601],[-84.1762,33.861],[-84.1785,33.8633],[-84.1802,33.8646],[-84.1901,33.8668],[-84.1907,33.8672],[-84.1946,33.8694],[-84.1957,33.8699],[-84.1963,33.8703],[-84.1968,33.8708],[-84.1979,33.8712],[-84.1991,33.8717],[-84.1996,33.8717],[-84.2002,33.8717],[-84.2013,33.8721],[-84.2018,33.8721],[-84.2024,33.8721],[-84.2029,33.8721],[-84.2035,33.8725],[-84.2046,33.8734],[-84.2057,33.8748],[-84.2069,33.8761],[-84.2142,33.8833],[-84.2147,33.8838],[-84.2153,33.8842],[-84.2164,33.8842],[-84.2164,33.8851],[-84.217,33.886],[-84.2192,33.8883],[-84.2198,33.8892],[-84.2215,33.891],[-84.2226,33.8923],[-84.2243,33.8928],[-84.2248,33.8932],[-84.2254,33.8937],[-84.226,33.8946],[-84.2265,33.8955],[-84.2271,33.8959],[-84.2282,33.8977],[-84.2288,33.8986],[-84.2299,33.9005],[-84.2311,33.9013],[-84.2316,33.9018],[-84.2327,33.9027],[-84.2333,33.9031],[-84.2339,33.9031],[-84.2366,33.9045],[-84.2378,33.9049],[-84.2394,33.9063],[-84.2406,33.9072],[-84.2417,33.9071],[-84.2428,33.9076],[-84.2439,33.9076],[-84.2444,33.9085],[-84.2467,33.9098],[-84.2478,33.9103],[-84.2484,33.9103],[-84.2495,33.9107],[-84.25,33.9107],[-84.2511,33.9111],[-84.2523,33.9116],[-84.2562,33.9143],[-84.2596,33.9192],[-84.2601,33.9192],[-84.2653,33.931],[-84.2676,33.936],[-84.2699,33.9396],[-84.2716,33.9423],[-84.2727,33.945],[-84.2711,33.9459],[-84.2672,33.9473],[-84.2656,33.9482],[-84.2707,33.955],[-84.2668,33.956],[-84.268,33.9582],[-84.268,33.9605],[-84.2658,33.9623],[-84.2636,33.9633],[-84.262,33.9656],[-84.2626,33.9674],[-84.2643,33.9692],[-84.2654,33.971],[-84.2605,33.9738],[-84.2599,33.9765],[-84.26,33.9792],[-84.2611,33.9824],[-84.2617,33.9847],[-84.2607,33.9865],[-84.259,33.9874],[-84.2568,33.9874],[-84.254,33.9875],[-84.2518,33.9879],[-84.2496,33.9902],[-84.248,33.9935],[-84.2464,33.9953],[-84.2437,33.998],[-84.2409,33.9999],[-84.2376,34.0008],[-84.2338,34.0027],[-84.2299,34.0046],[-84.2249,34.0051],[-84.2194,34.0051],[-84.2133,34.0038],[-84.2088,34.0011],[-84.2049,33.9985],[-84.2021,33.9967],[-84.2015,33.9935],[-84.202,33.9912],[-84.197,33.9899],[-84.1909,33.99],[-84.1854,33.9923],[-84.1816,33.9964],[-84.18,34.0033],[-84.1796,34.0101],[-84.178,34.016],[-84.1753,34.0197],[-84.1736,34.021],[-84.1726,34.0238],[-84.1715,34.0256],[-84.1665,34.0284],[-84.1632,34.0298],[-84.1605,34.0298],[-84.1577,34.0312],[-84.1533,34.0308],[-84.1488,34.029],[-84.1449,34.0286],[-84.1411,34.0287],[-84.1333,34.0301],[-84.1272,34.0315],[-84.1245,34.0325],[-84.1217,34.0334],[-84.1179,34.0362],[-84.1157,34.038],[-84.1119,34.0426],[-84.1075,34.0453],[-84.1036,34.0472],[-84.1009,34.049],[-84.1043,34.0522],[-84.1071,34.0549],[-84.1099,34.0571],[-84.1121,34.0607],[-84.1172,34.0639],[-84.1183,34.0652],[-84.1173,34.0703],[-84.114,34.0771],[-84.1141,34.0835],[-84.112,34.0885],[-84.1098,34.094],[-84.1104,34.0971],[-84.1083,34.0999],[-84.1039,34.1026],[-84.1028,34.1058],[-84.1023,34.1108],[-84.1018,34.1149],[-84.0996,34.1186],[-84.0986,34.1213],[-84.0964,34.1241],[-84.0936,34.1259],[-84.0926,34.13],[-84.0921,34.1328],[-84.0894,34.1373],[-84.0861,34.1424],[-84.0823,34.1488],[-84.0785,34.1529],[-84.0702,34.1593],[-84.0686,34.1607],[-84.0642,34.1617],[-84.0631,34.168],[-84.052,34.164],[-84.0481,34.1627],[-84.0258,34.1547],[-84.0001,34.1454],[-83.868,34.0983],[-83.8178,34.1273]]]},\"properties\":{\"name\":\"Gwinnett\",\"state\":\"GA\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
The Kansas River provides drinking water to about 800,000 people in northeastern Kansas. Water-treatment facilities that use the Kansas River as a water-supply source use chemical and physical processes during water treatment to remove contaminants before public distribution. Advanced notification of changing water-quality conditions near water-supply intakes allows water-treatment facilities to proactively adjust treatment. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas Water Plan), the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, and Johnson County WaterOne, collected water-quality data at the Kansas River at Wamego (USGS site 06887500; hereafter referred to as the “Wamego site”) and De Soto (USGS site 06892350; hereafter referred to as the “De Soto site”) monitoring sites to update previously published regression models relating continuous water-quality sensor measurements, streamflow, and seasonal components to discretely sampled water-quality constituent concentrations or densities. Linear regression analysis was used to update and develop models for total dissolved solids, major ions, hardness as calcium carbonate, nutrients (nitrogen and phosphorus species), chlorophyll a, total suspended solids, suspended sediment, and fecal indicator bacteria at the Wamego and De Soto monitoring sites using data collected during July 2012 through September 2019. The water-quality information documented in this report can be used as guidance for water-treatment processes and to characterize changes in water-quality conditions in the Kansas River over time that would not be otherwise possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211018","collaboration":"Prepared in cooperation with the Kansas Water Office, the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, and Johnson County WaterOne","usgsCitation":"Williams, T.J., 2021, Linear regression model documentation and updates for computing water-quality constituent concentrations or densities using continuous real-time water-quality data for the Kansas River, Kansas, July 2012 through September 2019: U.S. Geological Survey Open-File Report 2021–1018, 18 p., https://doi.org/10.3133/ofr20211018.","productDescription":"Report: vii, 18 p.; Appendixes: 1–32; Dataset","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120556","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":384812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2021/1018/downloads","text":"Appendixes 1–32","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1018 Appendixes 1–32"},{"id":384811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1018/ofr20211018.pdf","text":"Report","size":"1.16 MB","description":"OFR 2021–1018"},{"id":384810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1018/coverthb.jpg"},{"id":384813,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.66845703124999,\n 38.151837403006766\n ],\n [\n -94.5703125,\n 38.151837403006766\n ],\n [\n -94.5703125,\n 39.977120098439634\n ],\n [\n -97.66845703124999,\n 39.977120098439634\n ],\n [\n -97.66845703124999,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Emergent late Pliocene and Pleistocene shoreline deposits, morphologically identifiable Pleistocene shoreline units, and seaward-facing scarps characterize the easternmost Atlantic Coastal Plain (ACP) of the United States of America. In some areas of the ACP, these deposits, units, and scarps have been studied in detail. Within these areas, temporal and spatial data are sufficient for time-depositional frameworks for shoreline-evolution to have been developed and published. For other areas, such as the southeastern Atlantic Coastal Plain (SEACP), available data are conflicting and (or) insufficient to develop such a framework, or to make shoreline correlations. Differential epeirogenic uplift and shoreline deformation, resulting from mantle-flow and climate-induced isostatic adjustments, complicate regional shoreline correlations. In the SEACP, the topographically prominent Orangeburg Scarp (hereafter, the Scarp) rises tens of meters in elevation from southeastern Georgia to southeastern North Carolina. The degree to which the Scarp and shoreline units seaward of the Scarp are deformed continues to be debated, but there is general agreement that the lower Savannah River area (LSRA) of Georgia and South Carolina is the least deformed area of the SEACP.
This paper synthesizes published and previously unpublished numerical age and stratigraphic data for emergent Pliocene and younger shoreline deposits in the LSRA in Georgia. Age data are applied to these shoreline deposits as they are delineated (map units) on the 1976 geologic map of Georgia by Lawton and others. Age assignments are based on stratigraphic position, fossil content, soil and weathering diagnostic properties, and numerical ages as determined by meteoric Beryllium‑10 paleosol residence time (10BePRT), optically stimulated luminescence (OSL), uranium disequilibrium series (U-series), amino acid racemization (AAR), and radiocarbon (14C) analyses. These data provide a preliminary Pliocene-Pleistocene geochronology for the Orangeburg Scarp and shoreline deposits seaward of the Scarp in the LSRA of Georgia. Minimum ages and age ranges indicate the following:
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
The National Cooperative Geologic Mapping Program (NCGMP) is publishing a strategic plan titled Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge (Brock and others, in press). The plan provides a vision, mission, and goals for the program during the years 2020–2030, which are:
In order to achieve the goals outlined in the strategic plan, the NCGMP has developed an implementation plan. This plan will guide the annual review of projects carried out by USGS staff (FEDMAP) described in the plan and the development of the annual FEDMAP prospectus that will ensure the effective application of the NCGMP strategy.
This publication describes the implementation plan of the NCGMP strategy for the southern Pacific Border and Sierra-Cascade Mountains provinces, as defined by Fenneman (1917, 1928, and 1946). This implementation plan focuses on the geology of California and a sliver of Nevada surrounding Lake Tahoe. The southern Pacific Border and Sierra-Cascade Mountains provinces encompass the varied landscapes of the high Sierra Nevada, the Central Valley, and Coast Ranges in northern and central California and the Peninsular Ranges, Continental Borderland, Los Angeles Basin-San Gabriel-San Bernardino valleys, western and central Transverse Ranges, and northernmost Salton Trough in southern California. Societal demands create a need for earth-science data in each of these landscapes. The broader San Francisco Bay area, Central Valley, Los Angeles-San Gabriel-San Bernardino lowlands, and the coastal lowlands that border the Peninsular Ranges are densely populated (about 30 million people) areas at high risk of natural hazards. The mountains of the Sierra Nevada, Peninsular Ranges, and Transverse Ranges, and the coast all provide numerous recreational opportunities that attract visitors from around the world, whereas previously these ranges attracted people to mine their resources. The agricultural capacity of the Central Valley is a critical resource for the Nation that is increasingly water limited.
The southern. Pacific Border and Sierra-Cascade Mountains provinces, at the edge of the North American continent, were profoundly influenced by subduction zone tectonics during the Mesozoic and early Cenozoic (ongoing in northernmost California) and subsequently by the inception, development, and present activity of the San Andreas transform margin system. Although the geology of this region is the poster child of fundamental conceptual models of subduction zone complexes, forearc basins, ophiolite obductions, magmatic arcs, and suspect terranes, as well as hosting one of Earth’s most notorious continental transform faults—the San Andreas Fault—important questions that have important societal consequences remain to be answered. Most of California’s population reside in these provinces and live within 30 miles of an active fault (according to www.earthquakeauthority.com) yet new faults continue to be discovered, highlighting the importance of deformation off the main San Andreas Fault. Bedrock, surficial, and three-dimensional (3D) geologic maps depicting stratigraphic structure and depth to crystalline basement rocks provide critical context and information for understanding fault rupture, distributed deformation, fault connectivity, and history in addition to providing crucial data that enable forecasting of shaking amplitude and length from hypothetical earthquake scenarios.
The tectonic evolution of California produced not only stunning mountains, with associated hazards from landslides and active volcanoes, but also fertile valleys that make California the top agricultural producer in the country in terms of cash receipts (according to www.ers.usda.gov/faqs). These valleys lie atop large basins that not only store groundwater but, in many cases, host oil and gas fields, contributing to the fourth highest hydrocarbon production by State in the country in 2016 (according to https://www.aei.org/carpe-diem/animated-chart-of-us-oil-production-by-state-1981-2017). Water is a key resource increasingly stressed by growing agricultural, industrial, and residential needs. Warmer and drier conditions have led to an increased reliance on extracting groundwater resources, whose availability and quality are dictated at the first order by the 3D spatial distribution of bedrock and Quaternary surficial deposits. Thus, assessment of this critical resource is inextricably tied to knowledge of the surficial and subsurface geologic structure and material types.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211012","usgsCitation":"Langenheim, V.E., Graymer, R.W., Powell, R.E., Schmidt, K.M., and Sweetkind, D.S., 2021, Implementation plan for the southern Pacific Border and Sierra-Cascade Mountains provinces: U.S. Geological Survey Open-File Report 2021–1012, 11 p., https://doi.org/10.3133/ofr20211012.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-121693","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":384840,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1012/ofr20211012.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1012/covrthb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.26855468749999,\n 32.69486597787505\n ],\n [\n -117.20214843749999,\n 34.415973384481866\n ],\n [\n -116.806640625,\n 36.491973470593685\n ],\n [\n -119.35546875000001,\n 38.34165619279595\n ],\n [\n -119.3115234375,\n 39.30029918615029\n ],\n [\n -120.10253906249999,\n 40.212440718286466\n ],\n [\n -121.86035156249999,\n 42.06560675405716\n ],\n [\n -124.3212890625,\n 42.06560675405716\n ],\n [\n -124.541015625,\n 40.51379915504413\n ],\n [\n -123.70605468750001,\n 38.71980474264237\n ],\n [\n -122.607421875,\n 37.19533058280065\n ],\n [\n -121.59667968749999,\n 35.817813158696616\n ],\n [\n -120.58593749999999,\n 34.45221847282654\n ],\n [\n -117.94921874999999,\n 33.54139466898275\n ],\n [\n -117.2900390625,\n 32.54681317351514\n ],\n [\n -115.26855468749999,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Incorporating spatial and temporal scales into greater sage-grouse (Centrocercus urophasianus) population monitoring strategies is challenging and rarely implemented. Sage-grouse populations experience fluctuations in abundance that lead to temporal oscillations, making trend estimation difficult. Accounting for stochasticity is critical to reliably estimate population trends and investigate variation related to deterministic factors on the landscape, which are amenable to management action. Here, we describe a novel, range-wide hierarchical monitoring framework for sage-grouse centered on four objectives: (1) create a standardized database of lek counts, (2) develop spatial population structures by clustering leks, (3) estimate spatial trends at different temporal extents based on abundance nadirs (troughs), and (4) develop a targeted annual warning system to help inform management decisions. Using automated and repeatable methods (software), we compiled a lek database (as of 2019) that contained 262,744 counts and 8,421 unique lek locations from disparate state data. The hierarchical population units (clusters) included 13 nested levels, identifying biologically relevant units and population structure that minimized inter-cluster sage-grouse movements. With these products, we identified spatiotemporal variation in trends in population abundance using Bayesian state-space models. We estimated 37.0, 65.2, and 80.7-percent declines in abundance range-wide during short (17 years), medium (33 years), and long (53 years) temporal scales, respectively. However, some areas exhibited evidence of increasing trends in abundance in recent decades. Models predicted 12.3, 19.2, and 29.6 percent of populations (defined as clusters of neighboring leks) consisted of over 50-percent probability of extirpation at 19, 38, and 56-year projections from 2019, respectively, based on averaged annual rate of change in apparent abundance across two, four, and six oscillations (average period of oscillation is 9.4 years). At the lek level, models predicted 45.7, 60.1, and 78.0 percent of leks with over 50-percent extirpation probabilities over the same time periods, respectively, mostly located on the periphery of the species’ range. The targeted annual warning system automates annual identification of local populations exhibiting asynchronous decline relative to regional population patterns using simulated management actions and an optimization algorithm for evaluating range-wide stabilization of population abundance. In 2019, approximately 3.2 percent of leks and 2.0 percent of populations were identified by the targeted annual warning system for management intervention range-wide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201154","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the Bureau of Land Management","usgsCitation":"Coates, P.S., Prochazka, B.G., O’Donnell, M.S., Aldridge, C.L., Edmunds, D.R., Monroe, A.P., Ricca, M.A., Wann, G.T., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2021, Range-wide greater sage-grouse hierarchical monitoring framework—Implications for defining population boundaries, trend estimation, and a targeted annual warning system: U.S. Geological Survey Open-File Report 2020–1154, 243 p., https://doi.org/10.3133/ofr20201154.","productDescription":"Report: vi, 243 p.; 1 Table","numberOfPages":"243","onlineOnly":"Y","ipdsId":"IP-123421","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384766,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154_table8.csv","text":"Table 8","size":"80 KB","linkFileType":{"id":7,"text":"csv"}},{"id":384765,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154_table8.xlsx","text":"Table 8","size":"60 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":384760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1154/ofr20201154.pdf","text":"Report","size":"310 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1154/covrthb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.32226562500001,\n 35.67514743608467\n ],\n [\n -103.447265625,\n 35.67514743608467\n ],\n [\n -103.447265625,\n 48.69096039092549\n ],\n [\n -120.32226562500001,\n 48.69096039092549\n ],\n [\n -120.32226562500001,\n 35.67514743608467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This document presents the renewed vision, mission, and goals for the National Cooperative Geologic Mapping Program (NCGMP). The NCGMP, as authorized by the National Cooperative Geologic Mapping Act of 1992 (Public Law 102-285, 106 Stat. 166 and its reauthorizations), is tasked with expediting the production of a geologic database for the Nation based on modern geologic maps and their supporting data. In addition to highlighting the benefits of geologic maps for economic prosperity, national security, and environmental quality, the report describes the NCGMP structure and components. A renewed vision and mission for the NCGMP are stated, and three goals for guiding the program toward that vision for the next ten years are established. The vision of creating an integrated, three-dimensional, digital geologic map of the United States and its territories to address the changing needs of the Nation by 2030 is thereby defined to drive the activities of all NCGMP components for the next ten years. The strategic actions required to realize the NCGMP vision are identified for each of its components.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211013","usgsCitation":"Brock, J., Berry, K., Faulds, J., Berg, R., House, K., Marketti, M., McPhee, D., Schmidt, K., Schmitt, J., Soller, D., Spears, D., Thompson, R., Thorleifson, H., and Walsh, G., 2021, Renewing the National Cooperative Geologic Mapping Program as the Nation’s authoritative source for modern geologic knowledge: U.S. Geological Survey Open-File Report 2021–1013, 10 p., https://doi.org/10.3133/ofr20211013.","productDescription":"vi, 10 p.","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115733","costCenters":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"links":[{"id":384680,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1013/ofr20211013.pdf","text":"Report","size":"0.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1013"},{"id":384679,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1013/coverthb.jpg"}],"contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Water-quality activities and water-level measurements conducted by the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office coincide with the USGS mission of appraising the quantity and quality of the Nation’s water resources. The activities are conducted in cooperation with the U.S. Department of Energy’s (DOE) Idaho Operations Office. Results of water-quality and hydraulic head investigations are presented in various USGS publications or in refereed scientific journals, and the data are stored in the National Water Information System (NWIS) database. The results of the studies are used by researchers, regulatory and managerial agencies, and civic groups.
In its broadest sense, “quality assurance” refers to doing the job right the first time. It includes the functions of planning for products, review and acceptance of the products, and an audit designed to evaluate the system that produces the products. Quality control and quality assurance differ in that quality control ensures that things are done correctly given the “state-of-the-art” technology, and quality assurance ensures that quality control is maintained within specified limits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211004","collaboration":"DOE/ID-22253Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Sand dune ecosystems are highly dynamic landforms found along coastlines and riverine deltas where a supply of sand-sized material is available to be delivered by aquatic and wind environments. These unique ecosystems provide habitat for a variety of endemic and rare plant and animal species. Sand dunes have been affected by human development, sand mining, and shoreline stabilization from invasive weeds. This report provides a summary of a comprehensive literature review, field survey, and genomic analysis for the Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii, hereafter howellii), an endemic species to the San Francisco Bay-Delta, California, which was listed as a federally endangered subspecies in 1978. Howellii is found on a historic dune sheet (the Antioch sand sheet) near the confluence of the Sacramento and San Joaquin Rivers. The Antioch sand sheet has been greatly altered by sand mining and land conversion into agriculture and urban development. In chapter A, we describe results of the literature review and field survey. We found howellii at eight locations with over 90 percent of the adult population and nearly 99 percent of juveniles observed on the Antioch Dunes National Wildlife Refuge. We measured a negative relationship between howellii numbers and invasive weed cover, illustrating the importance of mobilized open sand for this species. In chapter B, we describe the genomic study results. We surveyed genomic diversity by using double-digest restriction-site associated sequencing to estimate population genetic structure and levels of diversity across all surveyed occurrences. The genomic analyses included outgroup samples of the closely related Oenothera deltoides subsp. cognata and three occurrences of an unknown taxon with intermediate morphology to cognata and howellii, which also occurs on the Antioch sand sheet, east of the Antioch Dunes National Wildlife Refuge. These three morphologically distinctive groups formed genetically distinctive clusters and well-supported monophyletic clades in clustering and phylogenetic analyses, respectively. There was no indication of recent hybridization among any of the groups. Among howellii occurrences, the Antioch Dunes National Wildlife Refuge contained the greatest genetic diversity. Our approach, which combined field surveys, habitat assessments, and genetic analyses, can provide useful information for the conservation and management of rare and at-risk plant species and highlights the uniqueness of the Antioch sand sheet floral diversity through the discovery of a putative new taxon within the bird-cage evening primrose species complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211017","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Friends of San Pablo Bay National Wildlife Refuge","usgsCitation":"Thorne, K.M., and Vandergast, A.G., 2021, Distribution, abundance, and genomic diversity of the endangered Antioch Dunes evening-primrose (Oenothera deltoides subsp. howellii) surveyed in 2019: U.S. Geological Survey Open-File Report 2021–1017, 40 p., https://doi.org/10.3133/ofr20211017.","productDescription":"vi, 40 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-124754","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436447,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93VYTF5","text":"USGS data release","linkHelpText":"Oenothera deltoides Genotype Data from Contra Costa County, California in 2019"},{"id":384604,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017_chB_app2.csv","text":"Chapter B Appendix 2","size":"4 KB","linkFileType":{"id":7,"text":"csv"}},{"id":384550,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017.xml"},{"id":384549,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1017/images"},{"id":384548,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1017/ofr20211017.pdf","text":"Report","size":"35 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384547,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1017/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.89605712890624,\n 37.97018468810549\n ],\n [\n -121.6241455078125,\n 37.97018468810549\n ],\n [\n -121.6241455078125,\n 38.11727165830543\n ],\n [\n -121.89605712890624,\n 38.11727165830543\n ],\n [\n -121.89605712890624,\n 37.97018468810549\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Navajo (N) aquifer is the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in the Black Mesa area because of continued water requirements for industrial and municipal use by a growing population and because of its arid climate. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year depending on location.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from November 2016 to December 2018. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater and surface-water chemistry.
In calendar year 2017, total groundwater withdrawals were 3,710 acre-feet (acre-ft), industrial withdrawals were 1,110 acre-ft, and municipal withdrawals were 2,600 acre-ft. In calendar year 2018, total groundwater withdrawals were 3,670 acre-ft, industrial withdrawals were 1,170 acre-ft, and municipal withdrawals were 2,500 acre-ft. Total withdrawals during 2017 and 2018 were about 49 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline.
From the prestress period (prior to 1965) to 2018, measured water levels available for comparison in wells completed in the unconfined areas of the N aquifer within the Black Mesa area declined in 8 of 14 wells, the changes ranged from +12.1 feet to −39.4 feet, and the median change was -0.6 feet. Water levels also declined in 15 of 18 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was −40.2 feet (ft), with changes ranging from +14.2 ft to −189.0 ft. From the prestress period to 2018, the median water-level change for all 32 wells in both the confined and unconfined areas was −9.4 ft.
Spring flow was measured at four springs in 2017 and 2018. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Pasture Canyon Spring has fluctuated for the period of record.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2018), Dinnebito Wash near Sand Springs 09401110 (1993 to 2018), Polacca Wash near Second Mesa 09400568 (1994 to 2018), and Pasture Canyon Springs 09401265 (2004 to 2018). Median winter flows (November through February) of each water year were used as an index of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Dinnebito Wash and Polacca Wash, whereas a decreasing trend was indicated at Moenkopi Wash and Pasture Canyon Springs.
In 2017 and 2018, water samples collected from two wells, four springs, and three streams in the Black Mesa area were analyzed for selected chemical constituents. The results from wells and springs were compared with previous analyses from the same wells and springs. At the Peabody 2 well, a significant (p<0.05) decreasing trend in dissolved solids over time was found, while concentrations of dissolved solids have not varied significantly (p>0.05) at the Kykotsmovi PM2 well. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Baseflow water chemistry samples were collected from Moenkopi, Dinnebito, and Polacca washes in 2017. Samples from all three washes had total-dissolved solids concentrations higher than is typically found in the N aquifer water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211124","collaboration":"Prepared in cooperation with the Navajo Nation and Peabody Western Coal Company","usgsCitation":"Mason, J.P., 2021, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2016–2018: U.S. Geological Survey Open-File Report 2021–1124, 50 p., https://doi.org/10.3133/ofr20211124.","productDescription":"vii, 50 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-110021","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":384543,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181193","text":"Open-File Report 2018-1193","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona—2015–2016"},{"id":384455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1124/ofr20211124.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1124/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.76391601562499,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 35.32633026307483\n ],\n [\n -109.171142578125,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 36.99377838872517\n ],\n [\n -111.76391601562499,\n 35.32633026307483\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. At the time of this report, the work is conducted by the Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2020 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased twelvefold to approximately 9.6 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few unexplained high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2020, but with increasing numbers at all sites and the highest number of abalone counted and measured island-wide since 1993. Recruitment rates have fallen since a peak in 2017, but 2020 continued to show moderate levels of additional recruitment. The distance between adjacent black abalone has decreased substantially since it was first consistently measured in 2005, potentially indicating that the abalone are close enough to one another to reproduce successfully. Sand burial can have devastating localized consequences to black abalone, but there is evidence suggesting that they may be able to escape periodic sand inundation if suitable refugia exist. These data suggest that monitoring can inform adaptive management of the resource by base resource managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211023","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2021, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report: U.S. Geological Survey Open-File Report 2021–1023, 33 p., https://doi.org/10.3133/ofr20211023.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-125069","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1023/covrthb.jpg"},{"id":384508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384509,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.xml"},{"id":384510,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1023/images"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59442138671875,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.20996748987798\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819