Landslides in Minnesota have caused loss of life, damaged infrastructure, and negatively affected Minnesota’s natural resources. Landslides increase the amount of sediment contributed to lakes and rivers, with negative consequences for water quality and aquatic habitats. Recent mapping reveals that landslide susceptible areas within Minnesota primarily occur on steep slopes adjacent to rivers, lakes, and transportation corridors. Local variation in landslide susceptibility is related to the underlying geology and glacial history.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223007","collaboration":"Prepared in cooperation with the University of Minnesota Duluth; Freshwater Society; University of Minnesota Twin Cities; University of Wisconsin-Superior; Gustavus Adolphus College; Winona State University; Minnesota State University, Mankato; St. Thomas University; and North Dakota State University","usgsCitation":"DeLong, S.B., Jennings, C.E., and Gran, K.B., 2022, Landslides in Minnesota: U.S. Geological Survey Fact Sheet 2022-3007, 4 p., https://doi.org/10.3133/fs20223007.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-134166","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":396802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3007/covrthb.jpg"},{"id":396803,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3007/fs20223007.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Minnesota","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.204691,46.704041],[-92.205192,46.698341],[-92.183091,46.695241],[-92.176091,46.686341],[-92.204092,46.666941],[-92.201592,46.656641],[-92.207092,46.651941],[-92.242493,46.649241],[-92.256592,46.658741],[-92.270592,46.650741],[-92.274392,46.657441],[-92.286192,46.660342],[-92.287392,46.667342],[-92.291292,46.668142],[-92.292192,46.663308],[-92.294033,46.074377],[-92.332912,46.062697],[-92.35176,46.015685],[-92.372717,46.014198],[-92.410649,46.027259],[-92.428555,46.024241],[-92.442259,46.016177],[-92.453373,45.992913],[-92.464512,45.985038],[-92.461138,45.980216],[-92.469354,45.973811],[-92.527052,45.983245],[-92.548459,45.969056],[-92.551186,45.95224],[-92.60246,45.940815],[-92.614314,45.934529],[-92.638824,45.934166],[-92.638474,45.925971],[-92.659549,45.922937],[-92.676167,45.912072],[-92.675737,45.907478],[-92.707702,45.894901],[-92.734039,45.868108],[-92.739278,45.84758],[-92.765146,45.830183],[-92.757815,45.806574],[-92.776496,45.790014],[-92.784621,45.764196],[-92.809837,45.744172],[-92.869193,45.717568],[-92.870025,45.697272],[-92.875488,45.689014],[-92.887929,45.639006],[-92.882529,45.610216],[-92.886442,45.598679],[-92.883749,45.575483],[-92.871082,45.567581],[-92.823309,45.560934],[-92.770223,45.566939],[-92.726082,45.541112],[-92.726677,45.514462],[-92.702224,45.493046],[-92.680234,45.464344],[-92.653549,45.455346],[-92.646602,45.441635],[-92.650422,45.398507],[-92.664102,45.393309],[-92.676961,45.380137],[-92.678223,45.373604],[-92.70272,45.358472],[-92.698967,45.336374],[-92.709968,45.321302],[-92.737122,45.300459],[-92.761013,45.289028],[-92.760615,45.278827],[-92.751659,45.26591],[-92.760249,45.2496],[-92.751708,45.218666],[-92.763908,45.204866],[-92.767408,45.190166],[-92.764872,45.182812],[-92.752404,45.173916],[-92.757707,45.155466],[-92.739584,45.115598],[-92.744938,45.108309],[-92.791528,45.079647],[-92.803079,45.060978],[-92.793282,45.047178],[-92.770362,45.033803],[-92.76206,45.02432],[-92.771231,45.001378],[-92.769445,44.97215],[-92.754603,44.955767],[-92.750645,44.937299],[-92.758701,44.908979],[-92.774571,44.898084],[-92.773946,44.889997],[-92.764133,44.875905],[-92.769102,44.862167],[-92.765278,44.837186],[-92.78043,44.812589],[-92.785206,44.792303],[-92.805287,44.768361],[-92.807988,44.75147],[-92.787906,44.737432],[-92.737259,44.717155],[-92.700948,44.693751],[-92.660988,44.660884],[-92.632105,44.649027],[-92.619779,44.634195],[-92.621456,44.615017],[-92.601516,44.612052],[-92.586216,44.600088],[-92.569434,44.603539],[-92.549777,44.58113],[-92.549957,44.568988],[-92.540551,44.567258],[-92.518358,44.575183],[-92.493808,44.566063],[-92.481001,44.568276],[-92.455105,44.561886],[-92.433256,44.5655],[-92.399281,44.558292],[-92.361518,44.558935],[-92.336114,44.554004],[-92.314071,44.538014],[-92.302466,44.516487],[-92.302215,44.500298],[-92.291005,44.485464],[-92.232472,44.445434],[-92.195378,44.433792],[-92.124513,44.422115],[-92.111085,44.413948],[-92.078605,44.404869],[-92.056486,44.402729],[-92.038147,44.388731],[-91.970266,44.365842],[-91.941311,44.340978],[-91.92559,44.333548],[-91.918625,44.322671],[-91.913534,44.311392],[-91.924613,44.291815],[-91.896388,44.27469],[-91.896008,44.262871],[-91.88704,44.251772],[-91.892698,44.231105],[-91.877429,44.212921],[-91.872369,44.199167],[-91.829167,44.17835],[-91.808064,44.159262],[-91.751747,44.134786],[-91.721552,44.130342],[-91.710597,44.12048],[-91.708207,44.105186],[-91.69531,44.09857],[-91.68153,44.0974],[-91.667006,44.086964],[-91.647873,44.064109],[-91.638115,44.063285],[-91.610487,44.04931],[-91.59207,44.031372],[-91.507121,44.01898],[-91.48087,44.008145],[-91.463515,44.009041],[-91.432522,43.996827],[-91.407395,43.965148],[-91.385785,43.954239],[-91.366642,43.937463],[-91.357426,43.917231],[-91.347741,43.911964],[-91.338141,43.897664],[-91.320605,43.888491],[-91.310991,43.867381],[-91.284138,43.847065],[-91.262436,43.792166],[-91.244135,43.774667],[-91.255431,43.744876],[-91.255932,43.729849],[-91.268455,43.709824],[-91.273252,43.666623],[-91.271749,43.654929],[-91.262397,43.64176],[-91.268748,43.615348],[-91.232707,43.583533],[-91.232812,43.564842],[-91.243214,43.550722],[-91.243183,43.540309],[-91.232941,43.523967],[-91.218292,43.514434],[-91.217706,43.50055],[-96.453049,43.500415],[-96.453067,45.298115],[-96.489065,45.357071],[-96.521787,45.375645],[-96.562142,45.38609],[-96.617726,45.408092],[-96.680454,45.410499],[-96.692541,45.417338],[-96.731396,45.45702],[-96.76528,45.521414],[-96.857751,45.605962],[-96.844211,45.639583],[-96.835769,45.649648],[-96.760866,45.687518],[-96.745086,45.701576],[-96.662595,45.738682],[-96.641941,45.759871],[-96.627778,45.786239],[-96.583085,45.820024],[-96.574517,45.843098],[-96.561334,45.945655],[-96.57035,45.963595],[-96.57794,46.026874],[-96.559271,46.058272],[-96.554507,46.083978],[-96.557952,46.102442],[-96.56692,46.11475],[-96.563043,46.119512],[-96.571439,46.12572],[-96.56926,46.133686],[-96.579453,46.147601],[-96.577952,46.165843],[-96.587408,46.178164],[-96.584372,46.204155],[-96.59755,46.227733],[-96.598645,46.241626],[-96.590942,46.250183],[-96.59887,46.26069],[-96.595014,46.275135],[-96.60136,46.30413],[-96.599761,46.330386],[-96.619991,46.340135],[-96.618147,46.344295],[-96.629211,46.352654],[-96.644335,46.351908],[-96.646341,46.360982],[-96.655206,46.365964],[-96.658436,46.373391],[-96.666028,46.374566],[-96.669132,46.390037],[-96.680687,46.407383],[-96.688082,46.40788],[-96.701358,46.420584],[-96.703078,46.429467],[-96.718074,46.438255],[-96.715557,46.463232],[-96.73627,46.48138],[-96.737798,46.489785],[-96.733612,46.497224],[-96.737702,46.50077],[-96.738475,46.525793],[-96.744341,46.533006],[-96.743003,46.54294],[-96.74883,46.558127],[-96.744436,46.56596],[-96.746442,46.574078],[-96.772446,46.600129],[-96.774094,46.613288],[-96.78995,46.631531],[-96.790663,46.649112],[-96.798823,46.658071],[-96.792958,46.677427],[-96.784339,46.685054],[-96.790906,46.70297],[-96.779252,46.727429],[-96.784279,46.732993],[-96.781216,46.740944],[-96.787466,46.756753],[-96.784314,46.766973],[-96.796195,46.789881],[-96.795756,46.807795],[-96.801446,46.810401],[-96.80016,46.819664],[-96.787657,46.827817],[-96.789663,46.832306],[-96.779347,46.843672],[-96.781358,46.879363],[-96.768458,46.879563],[-96.767358,46.883663],[-96.773558,46.884763],[-96.776558,46.895663],[-96.759241,46.918223],[-96.761757,46.934663],[-96.78312,46.925482],[-96.79038,46.929398],[-96.791558,46.944464],[-96.797734,46.9464],[-96.798737,46.962399],[-96.821852,46.969372],[-96.82318,46.999965],[-96.834221,47.006671],[-96.829499,47.021537],[-96.818557,47.02778],[-96.821422,47.032842],[-96.819321,47.0529],[-96.824479,47.059682],[-96.818175,47.104193],[-96.827344,47.120144],[-96.824807,47.124968],[-96.831547,47.142017],[-96.822377,47.162744],[-96.829637,47.17497],[-96.826962,47.182802],[-96.838806,47.197894],[-96.832789,47.203911],[-96.838806,47.22502],[-96.832946,47.237588],[-96.83766,47.240876],[-96.835368,47.250428],[-96.841672,47.258164],[-96.838997,47.267716],[-96.842531,47.269531],[-96.844088,47.289981],[-96.832884,47.30449],[-96.841958,47.316907],[-96.835845,47.321014],[-96.835845,47.335914],[-96.852417,47.366241],[-96.848907,47.370565],[-96.852676,47.374973],[-96.846925,47.376891],[-96.840621,47.389881],[-96.845492,47.394179],[-96.844919,47.399815],[-96.863593,47.418775],[-96.85748,47.440457],[-96.859868,47.470926],[-96.85471,47.478281],[-96.85853,47.489934],[-96.851653,47.497098],[-96.851367,47.509037],[-96.866363,47.524893],[-96.85471,47.535973],[-96.859153,47.566355],[-96.853689,47.570381],[-96.856373,47.575749],[-96.851293,47.589264],[-96.856903,47.602329],[-96.855421,47.60875],[-96.873671,47.613654],[-96.871005,47.616832],[-96.879496,47.620576],[-96.882393,47.633489],[-96.888573,47.63845],[-96.882376,47.649025],[-96.88697,47.653049],[-96.887126,47.666369],[-96.895271,47.67357],[-96.899352,47.689473],[-96.908928,47.688722],[-96.907266,47.693976],[-96.920119,47.710383],[-96.923544,47.718201],[-96.919471,47.722515],[-96.932809,47.737139],[-96.928505,47.748037],[-96.934173,47.752412],[-96.939179,47.768397],[-96.9644,47.782995],[-96.957283,47.790147],[-96.966068,47.797297],[-96.975131,47.798326],[-96.980579,47.805614],[-96.979327,47.824533],[-96.986685,47.837639],[-96.998295,47.841724],[-96.998144,47.858882],[-97.005557,47.863977],[-97.002456,47.868677],[-97.023156,47.874978],[-97.019355,47.880278],[-97.024955,47.886878],[-97.019155,47.889778],[-97.024955,47.894978],[-97.020155,47.900478],[-97.024955,47.908178],[-97.017254,47.905678],[-97.015354,47.910278],[-97.023754,47.915878],[-97.018054,47.918078],[-97.035754,47.930179],[-97.036054,47.939379],[-97.054554,47.946279],[-97.052454,47.957179],[-97.061454,47.96358],[-97.053553,47.991612],[-97.064289,47.998508],[-97.066762,48.009558],[-97.063012,48.013179],[-97.072239,48.019107],[-97.068987,48.026267],[-97.072257,48.048068],[-97.097772,48.07108],[-97.103052,48.071669],[-97.099431,48.082106],[-97.105226,48.09044],[-97.104872,48.097851],[-97.109535,48.104723],[-97.123205,48.106648],[-97.120702,48.114987],[-97.131956,48.139563],[-97.141401,48.14359],[-97.138911,48.157793],[-97.146745,48.168556],[-97.141474,48.179099],[-97.146233,48.186054],[-97.134372,48.210434],[-97.136304,48.228984],[-97.141254,48.234668],[-97.135763,48.237596],[-97.138765,48.244991],[-97.127276,48.253323],[-97.131846,48.267589],[-97.11657,48.279661],[-97.12216,48.290056],[-97.128862,48.292882],[-97.122072,48.300865],[-97.132443,48.315489],[-97.127601,48.323319],[-97.134854,48.331314],[-97.131145,48.339722],[-97.147748,48.359905],[-97.140106,48.380479],[-97.145592,48.394195],[-97.135012,48.406735],[-97.142849,48.419471],[-97.1356,48.424369],[-97.139173,48.430528],[-97.134229,48.439797],[-97.137689,48.447583],[-97.132746,48.459942],[-97.144116,48.469212],[-97.141397,48.476256],[-97.144981,48.481571],[-97.140291,48.484722],[-97.138864,48.494362],[-97.148133,48.503384],[-97.153076,48.524148],[-97.150481,48.536877],[-97.163105,48.543855],[-97.160863,48.549236],[-97.152459,48.552326],[-97.158638,48.564067],[-97.149616,48.569876],[-97.14974,48.579516],[-97.142915,48.583733],[-97.143684,48.597066],[-97.137504,48.612268],[-97.132931,48.61338],[-97.130089,48.621166],[-97.125639,48.620919],[-97.125269,48.629694],[-97.108466,48.632658],[-97.111921,48.642918],[-97.100551,48.658614],[-97.102652,48.664793],[-97.097708,48.68395],[-97.118286,48.700573],[-97.116185,48.709348],[-97.136083,48.727763],[-97.139488,48.746611],[-97.151289,48.757428],[-97.147478,48.763698],[-97.154854,48.774515],[-97.157093,48.790024],[-97.163535,48.79507],[-97.165624,48.809627],[-97.180028,48.81845],[-97.177747,48.824815],[-97.181116,48.832741],[-97.173811,48.838309],[-97.175618,48.853105],[-97.187362,48.867598],[-97.185738,48.87222],[-97.197982,48.880341],[-97.197982,48.898332],[-97.210541,48.90439],[-97.211161,48.916649],[-97.217992,48.919735],[-97.218666,48.931781],[-97.224505,48.9341],[-97.232147,48.948955],[-97.230859,48.960891],[-97.239209,48.968684],[-97.237297,48.985696],[-97.230833,48.991303],[-97.229039,49.000687],[-95.153711,48.998903],[-95.15335,49.383079],[-95.126467,49.369439],[-95.058404,49.35317],[-95.014415,49.356405],[-94.988908,49.368897],[-94.957465,49.370186],[-94.854245,49.324154],[-94.816222,49.320987],[-94.824291,49.308834],[-94.82516,49.294283],[-94.797244,49.214284],[-94.797527,49.197791],[-94.773223,49.120733],[-94.750221,49.099763],[-94.750218,48.999992],[-94.718932,48.999991],[-94.683069,48.883929],[-94.684217,48.872399],[-94.692527,48.86895],[-94.693044,48.853392],[-94.685681,48.840119],[-94.701968,48.831778],[-94.704284,48.824284],[-94.694974,48.809206],[-94.694312,48.789352],[-94.690889,48.778066],[-94.651765,48.755913],[-94.645164,48.749975],[-94.645083,48.744143],[-94.61901,48.737374],[-94.58715,48.717599],[-94.549069,48.714653],[-94.533057,48.701262],[-94.452332,48.692444],[-94.438701,48.694889],[-94.416191,48.710948],[-94.384221,48.711806],[-94.342758,48.703382],[-94.308446,48.710239],[-94.290737,48.707747],[-94.260541,48.696381],[-94.251169,48.683514],[-94.254643,48.663888],[-94.250497,48.656654],[-94.224276,48.649527],[-94.091244,48.643669],[-94.065775,48.646104],[-94.035616,48.641018],[-94.006933,48.643193],[-93.944221,48.632294],[-93.91153,48.634673],[-93.840754,48.628548],[-93.824144,48.610724],[-93.806763,48.577616],[-93.811201,48.542385],[-93.818253,48.530046],[-93.794454,48.516021],[-93.656652,48.515731],[-93.643091,48.518294],[-93.628865,48.53121],[-93.612844,48.521876],[-93.60587,48.522472],[-93.594379,48.528793],[-93.547191,48.528684],[-93.467504,48.545664],[-93.460798,48.550552],[-93.456675,48.561834],[-93.465199,48.590659],[-93.438494,48.59338],[-93.405269,48.609344],[-93.395022,48.603303],[-93.371156,48.605085],[-93.362132,48.613832],[-93.35324,48.613378],[-93.349095,48.624935],[-93.254854,48.642784],[-93.207398,48.642474],[-93.178095,48.623339],[-93.088438,48.627597],[-92.984963,48.623731],[-92.954876,48.631493],[-92.95012,48.630419],[-92.949839,48.608269],[-92.929614,48.606874],[-92.909947,48.596313],[-92.894687,48.594915],[-92.728046,48.53929],[-92.657881,48.546263],[-92.634931,48.542873],[-92.625739,48.518189],[-92.631117,48.508252],[-92.627237,48.503383],[-92.636696,48.499428],[-92.654039,48.501635],[-92.661418,48.496557],[-92.698824,48.494892],[-92.712562,48.463013],[-92.687998,48.443889],[-92.656027,48.436709],[-92.507285,48.447875],[-92.475585,48.418793],[-92.456325,48.414204],[-92.456389,48.401134],[-92.47675,48.37176],[-92.469948,48.351836],[-92.437825,48.309839],[-92.416285,48.295463],[-92.369174,48.220268],[-92.336831,48.235383],[-92.269742,48.248241],[-92.273706,48.256747],[-92.294541,48.27156],[-92.292999,48.276404],[-92.301451,48.288608],[-92.294527,48.306454],[-92.306309,48.316442],[-92.304561,48.322977],[-92.295412,48.323957],[-92.288994,48.342991],[-92.26228,48.354933],[-92.222813,48.349203],[-92.216983,48.345114],[-92.206803,48.345596],[-92.203684,48.352063],[-92.178418,48.351881],[-92.177354,48.357228],[-92.145049,48.365651],[-92.143583,48.356121],[-92.083513,48.353865],[-92.077961,48.358253],[-92.055228,48.359213],[-92.045734,48.347901],[-92.046562,48.33474],[-92.037721,48.333183],[-92.030872,48.325824],[-92.000133,48.321355],[-92.01298,48.297391],[-92.006577,48.265421],[-91.989545,48.260214],[-91.976903,48.244626],[-91.971056,48.247667],[-91.971779,48.252977],[-91.954432,48.251678],[-91.952209,48.244394],[-91.957683,48.242683],[-91.957798,48.232989],[-91.941838,48.230602],[-91.915772,48.238871],[-91.89347,48.237699],[-91.884691,48.227321],[-91.867882,48.219095],[-91.864382,48.207031],[-91.815772,48.211748],[-91.809038,48.206013],[-91.79181,48.202492],[-91.789011,48.196549],[-91.756637,48.205022],[-91.749075,48.198844],[-91.741932,48.199122],[-91.742313,48.204491],[-91.714931,48.19913],[-91.711611,48.1891],[-91.721413,48.180255],[-91.724584,48.170657],[-91.705318,48.170775],[-91.70726,48.153661],[-91.698174,48.141643],[-91.699981,48.13184],[-91.712226,48.116883],[-91.703524,48.113548],[-91.682845,48.122118],[-91.687623,48.111698],[-91.676876,48.107264],[-91.665208,48.107011],[-91.653261,48.114137],[-91.653571,48.109567],[-91.640175,48.096926],[-91.559272,48.108268],[-91.552962,48.103012],[-91.569746,48.093348],[-91.575471,48.066294],[-91.575672,48.048791],[-91.567254,48.043719],[-91.488646,48.068065],[-91.45033,48.068806],[-91.437582,48.049248],[-91.429642,48.048608],[-91.391128,48.057075],[-91.370872,48.06941],[-91.365143,48.066968],[-91.340159,48.073236],[-91.332589,48.069331],[-91.26638,48.078713],[-91.214428,48.10294],[-91.190461,48.124891],[-91.183207,48.122235],[-91.176181,48.125811],[-91.137733,48.14915],[-91.139402,48.154738],[-91.092258,48.173101],[-91.082731,48.180756],[-91.024208,48.190072],[-90.976955,48.219452],[-90.914971,48.230603],[-90.88548,48.245784],[-90.875107,48.237784],[-90.847352,48.244443],[-90.839176,48.239511],[-90.836313,48.176963],[-90.832589,48.173765],[-90.821115,48.184709],[-90.817698,48.179569],[-90.804207,48.177833],[-90.796596,48.159373],[-90.777917,48.163801],[-90.778031,48.148723],[-90.79797,48.136894],[-90.787305,48.134196],[-90.789919,48.129902],[-90.76911,48.116585],[-90.761555,48.100133],[-90.751608,48.090968],[-90.641596,48.103515],[-90.626886,48.111846],[-90.59146,48.117546],[-90.582217,48.123784],[-90.55929,48.121683],[-90.555845,48.117069],[-90.569763,48.106951],[-90.567482,48.101178],[-90.556838,48.096008],[-90.487077,48.099082],[-90.467712,48.108818],[-90.438449,48.098747],[-90.403219,48.105114],[-90.374542,48.090942],[-90.367658,48.094577],[-90.344234,48.094447],[-90.330052,48.102399],[-90.312386,48.1053],[-90.289337,48.098993],[-90.224692,48.108148],[-90.188679,48.107947],[-90.176605,48.112445],[-90.136191,48.112136],[-90.116259,48.104303],[-90.073873,48.101138],[-90.023595,48.084708],[-90.015057,48.067188],[-90.008446,48.068396],[-89.997852,48.057567],[-89.99305,48.028404],[-89.97718,48.023501],[-89.968255,48.014482],[-89.954605,48.011516],[-89.95059,48.015901],[-89.934489,48.015628],[-89.915341,47.994866],[-89.897414,47.987599],[-89.873286,47.985419],[-89.868153,47.989898],[-89.847571,47.992442],[-89.842568,48.001368],[-89.830385,48.000284],[-89.820483,48.014665],[-89.797744,48.014505],[-89.763967,48.022969],[-89.724048,48.018996],[-89.721038,48.017965],[-89.724044,48.013675],[-89.716114,48.016441],[-89.716417,48.010251],[-89.702528,48.006325],[-89.673798,48.01151],[-89.667128,48.007421],[-89.657051,48.009954],[-89.649057,48.003853],[-89.617867,48.010947],[-89.611678,48.017529],[-89.607821,48.006566],[-89.594749,48.004332],[-89.582117,47.996314],[-89.564288,48.00293],[-89.489226,48.014528],[-89.495344,48.002356],[-89.541521,47.992841],[-89.551555,47.987305],[-89.555015,47.974849],[-89.572315,47.967238],[-89.58823,47.9662],[-89.611412,47.980731],[-89.624559,47.983153],[-89.631825,47.980039],[-89.640129,47.96793],[-89.638285,47.954275],[-89.697619,47.941288],[-89.793539,47.891358],[-89.85396,47.873997],[-89.87158,47.874194],[-89.923649,47.862062],[-89.930844,47.857723],[-89.92752,47.850825],[-89.933899,47.84676],[-89.974296,47.830514],[-90.072025,47.811105],[-90.075559,47.803303],[-90.1168,47.79538],[-90.16079,47.792807],[-90.178755,47.786414],[-90.187636,47.77813],[-90.248794,47.772763],[-90.323446,47.753771],[-90.332686,47.746387],[-90.437712,47.731612],[-90.441912,47.726404],[-90.458365,47.7214],[-90.537105,47.703055],[-90.551291,47.690266],[-90.735927,47.624343],[-90.86827,47.5569],[-90.907494,47.532873],[-90.914247,47.522639],[-90.939072,47.514532],[-91.032945,47.458236],[-91.045646,47.456525],[-91.097569,47.413888],[-91.128131,47.399619],[-91.146958,47.381464],[-91.156513,47.378816],[-91.188772,47.340082],[-91.238658,47.304976],[-91.262512,47.27929],[-91.288478,47.26596],[-91.326019,47.238993],[-91.357803,47.206743],[-91.418805,47.172152],[-91.477351,47.125667],[-91.497902,47.122579],[-91.518793,47.108121],[-91.573817,47.089917],[-91.591508,47.068684],[-91.626824,47.049953],[-91.644564,47.026491],[-91.666477,47.014297],[-91.704649,47.005246],[-91.780675,46.945881],[-91.806851,46.933727],[-91.841349,46.925215],[-91.883238,46.905728],[-91.914984,46.883836],[-91.952985,46.867037],[-92.094089,46.787839],[-92.088289,46.773639],[-92.06449,46.745439],[-92.025789,46.710839],[-92.01529,46.706469],[-92.020289,46.704039],[-92.03399,46.708939],[-92.08949,46.74924],[-92.10819,46.74914],[-92.13789,46.73954],[-92.14329,46.73464],[-92.141291,46.72524],[-92.146291,46.71594],[-92.167291,46.719941],[-92.189091,46.717541],[-92.204691,46.704041]]]},\"properties\":{\"name\":\"Minnesota\",\"nation\":\"USA \"}}]}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Species distributions are governed by processes occurring at multiple spatial scales. For species with complex life cycles, the needs of all life stages must be met within the dispersal limitations of the species. Multi-scale processes can be particularly important for these species, where small-scale patterns in specific habitat components can affect the distribution of one life stage, whereas large-scale patterns in land cover might better explain the distribution of other life stages. Using a conditional multi-scale model, we evaluated which aspects of the landscape and local environment are most strongly related to occupancy patterns of western spadefoots (Spea hammondii). In northern and central California, the proportion of grassland land cover within 2 km of a site was positively related to the occurrence of the northern clade of the western spadefoot. At the pond scale, we found that western spadefoots were more likely to breed in pools with lower pH. Our results indicate that protecting remaining grasslands for adult spadefoots and ensuring multiple pools with diverse characteristics and hydroperiods so at least some pools result in successful breeding will likely be necessary to conserve western spadefoots, especially with a changing climate. Considering the processes that affect species distributions at multiple life stages and spatial scales is an essential component of effective conservation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3960","usgsCitation":"Halstead, B., Rose, J.P., Clark, D., Kleeman, P.M., and Fisher, R., 2022, Multi-scale patterns in occurrence of an ephemeral pool-breeding amphibian: Ecosphere, v. 13, no. 3, e3960, 14 p., https://doi.org/10.1002/ecs2.3960.","productDescription":"e3960, 14 p.","ipdsId":"IP-127818","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":489146,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3960","text":"Publisher Index Page"},{"id":435933,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E1SP64","text":"USGS data release","linkHelpText":"Western Spadefoot Survey Data in Northern and Central California (2019)"},{"id":397856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.0244140625,\n 33.46810795527896\n ],\n [\n -119.091796875,\n 33.46810795527896\n ],\n [\n -119.091796875,\n 40.48038142908172\n ],\n [\n -125.0244140625,\n 40.48038142908172\n ],\n [\n -125.0244140625,\n 33.46810795527896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Denise 0000-0002-9688-2946 drclark@usgs.gov","orcid":"https://orcid.org/0000-0002-9688-2946","contributorId":213957,"corporation":false,"usgs":true,"family":"Clark","given":"Denise","email":"drclark@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":839226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229415,"text":"70229415 - 2022 - Comparison of electrofishing and PIT antennas for detection of hatchery-reared Roundtail Chub (Gila robusta) stocked into a desert stream","interactions":[],"lastModifiedDate":"2022-03-07T14:53:31.825137","indexId":"70229415","displayToPublicDate":"2022-03-07T08:39:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2530,"text":"Journal of the Arizona-Nevada Academy of Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of electrofishing and PIT antennas for detection of hatchery-reared Roundtail Chub (Gila robusta) stocked into a desert stream","title":"Comparison of electrofishing and PIT antennas for detection of hatchery-reared Roundtail Chub (Gila robusta) stocked into a desert stream","docAbstract":"Stocking of rare native fishes for conservation purposes is a common practice in the southwestern United States. Monitoring typically occurs after hatchery-reared fish are released to assess post-stocking movement and survival. We conducted a two-year study, in which tow-barge electrofishing and portable, flat-bed passive integrated transponder (PIT) antennas were used to monitor PIT-tagged, hatchery-reared roundtail chub (Gila robusta) following release into the upper Verde River in Arizona. Specifically, our study aimed to compare the performance of PIT antennas and electrofishing in detecting PIT tagged fish released in a small desert river and to examine the behavioral response of hatchery-reared roundtail chub after stocking. In both years, more fish were detected by antenna arrays (84%) than by electrofishing (30%). roundtail chub were significantly more likely to be detected by antennas than electrofishing each year; however, when antenna data were evaluated only during the few days in which electrofishing took place, there was no significant difference (Year 1, p=0.1784; Year 2, p=0.6295) in detection between gear types for the same time interval, suggesting that electrofishing and antennas are equally likely to detect fish during 48-72 hour time frames. Within 72 hours of release, antennas detected 100% of fish that moved upstream and 93.8% of fish that moved downstream from the stocking location. Overall, less than half (45.6% in Year 1; 41.1% in Year 2) of the stocked roundtail chub were detected using both methods in both years. Utilization of both active capture gear (electrofishing) and passive gear (antennae) had advantages over monitoring with a single method. PIT antennae can be especially useful for managers who lack the personnel or time to implement more intensive methods of capture but want to monitor post-stocking movement and survival of stocked fish.
","language":"English","publisher":"Arizona-Nevada Academy of Sciences","doi":"10.2181/036.049.0209","usgsCitation":"Tennant, L.A., Ward, D., and Gibb, A.C., 2022, Comparison of electrofishing and PIT antennas for detection of hatchery-reared Roundtail Chub (Gila robusta) stocked into a desert stream: Journal of the Arizona-Nevada Academy of Science, v. 49, no. 2, p. 116-126, https://doi.org/10.2181/036.049.0209.","productDescription":"11 p.","startPage":"116","endPage":"126","ipdsId":"IP-099559","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448570,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2181/036.049.0209","text":"Publisher Index Page"},{"id":435935,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99PGQGL","text":"USGS data release","linkHelpText":"Hatchery-reared Roundtail Chub Data, Arizona USA"},{"id":396785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.47227668762206,\n 34.85346724741666\n ],\n [\n -112.39751815795898,\n 34.85346724741666\n ],\n [\n -112.39751815795898,\n 34.87565098440711\n ],\n [\n -112.47227668762206,\n 34.87565098440711\n ],\n [\n -112.47227668762206,\n 34.85346724741666\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tennant, Laura A. 0000-0003-0062-7287 ltennant@usgs.gov","orcid":"https://orcid.org/0000-0003-0062-7287","contributorId":5984,"corporation":false,"usgs":true,"family":"Tennant","given":"Laura","email":"ltennant@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":837338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, David 0000-0002-3355-0637","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":216231,"corporation":false,"usgs":true,"family":"Ward","given":"David","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":837339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibb, Alice C.","contributorId":207521,"corporation":false,"usgs":false,"family":"Gibb","given":"Alice","email":"","middleInitial":"C.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":837340,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229393,"text":"70229393 - 2022 - Deep learning detection and recognition of spot elevations on historic topographic maps","interactions":[],"lastModifiedDate":"2022-03-07T14:39:01.222238","indexId":"70229393","displayToPublicDate":"2022-03-07T08:33:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Deep learning detection and recognition of spot elevations on historic topographic maps","docAbstract":"Some information contained in historical topographic maps has yet to be captured digitally, which limits the ability to automatically query such data. For example, U.S. Geological Survey’s historical topographic map collection (HTMC) displays millions of spot elevations at locations that were carefully chosen to best represent the terrain at the time. Although research has attempted to reproduce these data points, it has proven inadequate to automatically detect and recognize spot elevations in the HTMC. We propose a deep learning workflow pretrained using large benchmark text datasets. To these datasets we add manually crafted training image/label pairs, and test how many are required to improve prediction accuracy. We find that the initial model, pretrained solely with benchmark data, fails to predict any HTMC spot elevations correctly, whereas the addition of just 50 custom image/label pairs increases the predictive ability by ~50%, and the inclusion of 350 data pairs increased performance by ~80%. Data augmentation in the form of rotation, scaling and translation (offset) expanded the size and diversity of the training dataset and vastly improved recognition accuracy up to ~95%. Visualization methods, such as heat map generation and salient feature detection are recommended to better understand why some predictions fail.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2022.804155","usgsCitation":"Arundel, S., Morgan, T.P., and Thiem, P.T., 2022, Deep learning detection and recognition of spot elevations on historic topographic maps: Frontiers in Environmental Science, v. 10, p. 1-10, https://doi.org/10.3389/fenvs.2022.804155.","productDescription":"804155, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-129409","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":448574,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.804155","text":"Publisher Index Page"},{"id":396784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"editors":[{"text":"Chiang, Yao-Yi","contributorId":288084,"corporation":false,"usgs":false,"family":"Chiang","given":"Yao-Yi","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":837350,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":837265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Trenton P.","contributorId":287989,"corporation":false,"usgs":false,"family":"Morgan","given":"Trenton","email":"","middleInitial":"P.","affiliations":[{"id":61682,"text":"Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":837341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiem, Philip T. 0000-0002-3324-2589","orcid":"https://orcid.org/0000-0002-3324-2589","contributorId":287990,"corporation":false,"usgs":true,"family":"Thiem","given":"Philip","email":"","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":837342,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230446,"text":"70230446 - 2022 - Warming in the upper San Francisco Estuary: Patterns of water temperature change from five decades of data","interactions":[],"lastModifiedDate":"2022-06-01T15:16:59.494274","indexId":"70230446","displayToPublicDate":"2022-03-07T06:34:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Warming in the upper San Francisco Estuary: Patterns of water temperature change from five decades of data","docAbstract":"Temperature is a key controlling variable from subcellular to ecosystem scales. Thus, climatic warming is expected to have broad impacts, especially in economically and ecologically valuable systems such as estuaries. The heavily managed upper San Francisco Estuary supplies water to millions of people and is home to fish species of high conservation, commercial, and recreational interest. Despite a long monitoring record (> 50 yr), we do not yet know how water temperatures have already changed or how trends vary spatially or seasonally. We fit generalized additive models on an integrated database of discrete water temperature observations to estimate long-term trends with spatio-seasonal variability. We found that water temperatures have increased 0.017°C yr−1 on average over the past 50 yr. Rates of temperature change have varied over time, but warming was predominant. Temperature increases were most widespread in the late-fall to winter (November to February) and mid-spring (April to June), coinciding with the winter development of juvenile Chinook salmon and spring spawning window of the endangered delta smelt. Warming was fastest in the northern regions, a key fish migration corridor with important tidal wetland habitat. However, no long-term temperature trends were detected in October and were only observed in some regions in May, July, and August. These results can help identify optimal areas for restoration or refugia to buffer the effects of a warming climate, and the methods can be leveraged to understand the spatiotemporal variability in climate warming patterns in other aquatic systems.
Grasslands and shrublands exhibit pronounced spatial and temporal variability in structure and function with differences in phenology that can be difficult to observe. Unpiloted aerial vehicles (UAVs) can measure vegetation spectral patterns relatively cheaply and repeatably at fine spatial resolution. We tested the ability of UAVs to measure phenological variability within vegetation functional groups and to improve classification accuracy at two sites in Montana, U.S.A. We tested four flight frequencies during the growing season. Classification accuracy based on reference data increased by 5–10% between a single flight and scenarios including all conducted flights. Accuracy increased from 50.6% to 61.4% at the drier site, while at the more mesic/densely vegetated site, we found an increase of 59.0% to 64.4% between a single and multiple flights over the growing season. Peak green-up varied by 2–4 weeks within the scenes, and sparse vegetation classes had only a short detectable window of active phtosynthesis; therefore, a single flight could not capture all vegetation that was active across the growing season. The multi-temporal analyses identified differences in the seasonal timing of green-up and senescence within herbaceous and sagebrush classes. Multiple UAV measurements can identify the fine-scale phenological variability in complex mixed grass/shrub vegetation.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14051290","usgsCitation":"Wood, D.J., Preston, T.M., Powell, S., and Stoy, P.C., 2022, Multiple UAV flights across the growing season can characterize fine scale phenological heterogeneity within and among vegetation functional groups: Remote Sensing, v. 14, 1290, 28 p., https://doi.org/10.3390/rs14051290.","productDescription":"1290, 28 p.","ipdsId":"IP-135792","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":448580,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14051290","text":"Publisher Index Page"},{"id":435936,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96848FL","text":"USGS data release","linkHelpText":"UAV based vegetation classification results and input NDVI, vegetation height, and texture datasets for two Montana rangeland sites in 2018"},{"id":401978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.07403564453124,\n 44.78573392716592\n ],\n [\n -111.49749755859375,\n 44.78573392716592\n ],\n [\n -111.49749755859375,\n 45.592900208269825\n ],\n [\n -113.07403564453124,\n 45.592900208269825\n ],\n [\n -113.07403564453124,\n 44.78573392716592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2022-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, David J. A. 0000-0003-4315-5160 dwood@usgs.gov","orcid":"https://orcid.org/0000-0003-4315-5160","contributorId":177588,"corporation":false,"usgs":true,"family":"Wood","given":"David","email":"dwood@usgs.gov","middleInitial":"J. A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":844385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":844386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Scott","contributorId":192347,"corporation":false,"usgs":false,"family":"Powell","given":"Scott","affiliations":[],"preferred":false,"id":844387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoy, Paul C.","contributorId":204157,"corporation":false,"usgs":false,"family":"Stoy","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":844388,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242758,"text":"70242758 - 2022 - Shallow faulting and folding in the epicentral area of the 1886 Charleston, South Carolina, earthquake","interactions":[],"lastModifiedDate":"2023-04-17T11:49:27.421928","indexId":"70242758","displayToPublicDate":"2022-03-06T06:44:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Shallow faulting and folding in the epicentral area of the 1886 Charleston, South Carolina, earthquake","docAbstract":"The moment magnitude (
Annual bank erosion was measured at multiple cross sections along the free-flowing meandering Powder River in the western United States from 1979 through 2019. Bank erosion was separated into two components—above water and underwater erosion. Above water erosion was measured as the annual bank retreat rate (0–15.4 m y−1). Underwater erosion rate (0–47 m3 m−1 y−1) was calculated as the volume eroded below the water level corresponding to the dominant annual peak discharge, Qp. This paper focuses primarily on the underwater erosion. A total of 491 annual erosion rates were calculated for 23 bank sites along a 90-km study reach in southeastern Montana. Sites were not just hotspots for bank erosion but represent the spectra of variables such as the radius of curvature divided by channel width, R/w (2–86), the peak discharge, Qp (22.7–314 m3 s−1), and the bank orientation (0–360°).
Local annual bank erosion was extremely variable in time and space. It was episodic and unsynchronized along the study reach with the maximum annual bank erosion occurring in different years at different bank sites. The composite probability distribution of all 491 annual bank erosion rates was best modeled by a zero-adjusted Weibull distribution. Individual probability distributions for each of the 23 sites were all different from each other and from the composite distribution highlighting the extreme variability. The correlation of the annual underwater erosion with channel geometry and bank variables was low (R2 < 0.31) but the correlation was higher for peak discharge with 25% of the sites having R2 > 0.50.
Time-averaging reduced the variability at each site and when grouped into five peak-discharge classes each class was correlated with R/w as a power law with an exponent of about −1. Reach-averaging also reduced the variability for each year, and when grouped by bank orientation (north-, east-, south-, and west-facing), bank erosion was linearly related to Qp with south- and west-facing orientations having about twice as much erosion per unit discharge (0.030 m3 m−1 y−1/m3 s−1) than north- and east-facing orientations.
Bank erosion was found to be not just a multi-variate complex process with little correlation and high variability that suggests randomness, but also a process that was a function of a different combinations of variables at different sites at the same time. However, this high variability was reduced by time- and reach-averaging, which produced predictable results analogous to the central limit theorem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2022.108134","usgsCitation":"Moody, J.A., 2022, The effects of discharge and bank orientation on the annual riverbank erosion along Powder River in Montana, USA: Geomorphology, v. 403, 108134, 17 p., https://doi.org/10.1016/j.geomorph.2022.108134.","productDescription":"108134, 17 p.","ipdsId":"IP-128404","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":409321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.1060780230682,\n 44.99730993309305\n ],\n [\n -105.34780716843096,\n 44.99730993309305\n ],\n [\n -105.34780716843096,\n 45.476708847648894\n ],\n [\n -106.1060780230682,\n 45.476708847648894\n ],\n [\n -106.1060780230682,\n 44.99730993309305\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"403","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":856974,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70255136,"text":"70255136 - 2022 - Many avenues for spatial personality research: a response to comments on Stuber et al. (2022)","interactions":[],"lastModifiedDate":"2024-06-12T23:35:34.384006","indexId":"70255136","displayToPublicDate":"2022-03-04T18:34:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":981,"text":"Behavioral Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Many avenues for spatial personality research: a response to comments on Stuber et al. (2022)","docAbstract":"We are grateful for the thought-provoking and forward-looking commentaries (Dingemanse et al. 2022; Mabry 2022; Spiegel and Pinter-Wollman 2022; Vander Wal et al. 2022) in response to our meta-analysis of evidence for consistent among-individual differences in animals’ spatial behaviors (Stuber et al. 2022). A clear consensus is that our demonstration of the prevalence of repeatability across spatial behaviors, and taxa, is only the first step towards identifying the mechanisms and consequences of variation in spatial behavior. Here, we take the opportunity to emphasize key future directions pertaining to uncovering mechanisms, disentangling apparent personality from spatial constraints, and examining additional metrics of variation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/beheco/arac018","usgsCitation":"Stuber, E.F., Carlson, B., and Jesmer, B., 2022, Many avenues for spatial personality research: a response to comments on Stuber et al. (2022): Behavioral Ecology, v. 33, no. 3, p. 492-493, https://doi.org/10.1093/beheco/arac018.","productDescription":"2 p.","startPage":"492","endPage":"493","ipdsId":"IP-136443","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arac018","text":"Publisher Index Page"},{"id":430056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":903509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Ben","contributorId":338737,"corporation":false,"usgs":false,"family":"Carlson","given":"Ben","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":903510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett","contributorId":338738,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":903511,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229369,"text":"70229369 - 2022 - Leveraging rangeland monitoring data for wildlife: From concept to practice","interactions":[],"lastModifiedDate":"2022-03-04T15:45:24.688257","indexId":"70229369","displayToPublicDate":"2022-03-04T09:31:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging rangeland monitoring data for wildlife: From concept to practice","docAbstract":"Available rangeland data, from field-measured plots to remotely sensed landscapes, provide much needed information for mapping and modeling wildlife habitats.
Better integration of wildlife habitat characteristics into rangeland monitoring schemes is needed for most rangeland wildlife species at varying spatial and temporal scales.
Here, we aim to stimulate use of and inspire ideas about rangeland monitoring data in the context of wildlife habitat modeling and species conservation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.09.005","usgsCitation":"Pilliod, D., Beck, J.L., Duchardt, C.J., Rachlow, J.L., and Veblen, K.E., 2022, Leveraging rangeland monitoring data for wildlife: From concept to practice: Rangelands, v. 44, no. 1, p. 87-98, https://doi.org/10.1016/j.rala.2021.09.005.","productDescription":"12 p.","startPage":"87","endPage":"98","ipdsId":"IP-125490","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.09.005","text":"Publisher Index Page"},{"id":396752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Utah, Wyoming","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.6865234375,\n 49.023461463214126\n ],\n [\n -112.87353515625,\n 48.019324184801185\n ],\n [\n -112.7197265625,\n 47.3834738721015\n ],\n [\n -109.18212890625,\n 45.058001435398275\n ],\n [\n -111.09374999999999,\n 45.058001435398275\n ],\n [\n -111.11572265625,\n 42.049292638686836\n ],\n [\n -114.10400390625,\n 42.049292638686836\n ],\n [\n -114.10400390625,\n 36.98500309285596\n ],\n [\n -109.05029296875,\n 36.96744946416934\n ],\n [\n -109.0283203125,\n 40.94671366508002\n ],\n [\n -106.85302734374999,\n 41.0130657870063\n ],\n [\n -106.171875,\n 40.863679665481676\n ],\n [\n -105.35888671875,\n 40.43022363450862\n ],\n [\n -105.40283203124999,\n 39.842286020743394\n ],\n [\n -104.9853515625,\n 38.71980474264237\n ],\n [\n -105.18310546875,\n 38.51378825951165\n ],\n [\n -104.87548828125,\n 37.54457732085582\n ],\n [\n -105.0732421875,\n 36.2265501474709\n ],\n [\n -105.40283203124999,\n 35.44277092585766\n ],\n [\n -106.06201171875,\n 35.137879119634185\n ],\n [\n -105.556640625,\n 33.687781758439364\n ],\n [\n -105.5126953125,\n 32.58384932565662\n ],\n [\n -102.94189453125,\n 29.267232865200878\n ],\n [\n -102.54638671875,\n 29.76437737516313\n ],\n [\n -101.7333984375,\n 29.82158272057499\n ],\n [\n -101.14013671875,\n 29.554345125748267\n ],\n [\n -100.52490234375,\n 28.65203063036226\n ],\n [\n -99.755859375,\n 27.761329874505233\n ],\n [\n -94.59228515625,\n 31.55981453201843\n ],\n [\n -94.482421875,\n 33.65120829920497\n ],\n [\n -94.59228515625,\n 36.58024660149866\n ],\n [\n -94.54833984375,\n 39.027718840211605\n ],\n [\n -94.81201171875,\n 39.9602803542957\n ],\n [\n -95.09765625,\n 39.90973623453719\n ],\n [\n -95.4052734375,\n 40.16208338164617\n ],\n [\n -95.7568359375,\n 40.74725696280421\n ],\n [\n -95.8447265625,\n 41.261291493919884\n ],\n [\n -96.04248046875,\n 41.85319643776675\n ],\n [\n -96.56982421875,\n 42.779275360241904\n ],\n [\n -96.39404296875,\n 43.14909399920127\n ],\n [\n -96.48193359375,\n 43.46886761482925\n ],\n [\n -96.39404296875,\n 45.3521452458518\n ],\n [\n -96.78955078125,\n 45.62940492064501\n ],\n [\n -96.52587890625,\n 45.85941212790755\n ],\n [\n -96.52587890625,\n 46.34692761055676\n ],\n [\n -96.767578125,\n 46.70973594407157\n ],\n [\n -96.83349609375,\n 47.60616304386874\n ],\n [\n -97.0751953125,\n 48.07807894349862\n ],\n [\n -97.1630859375,\n 48.58932584966975\n ],\n [\n -97.05322265625,\n 48.705462895790546\n ],\n [\n -97.18505859374999,\n 49.05227025601607\n ],\n [\n -113.6865234375,\n 49.023461463214126\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Jeffrey L.","contributorId":287806,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey","middleInitial":"L.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":837218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duchardt, Courtney Jean 0000-0003-4563-0199","orcid":"https://orcid.org/0000-0003-4563-0199","contributorId":264471,"corporation":false,"usgs":true,"family":"Duchardt","given":"Courtney","email":"","middleInitial":"Jean","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":837219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rachlow, Janet L.","contributorId":69298,"corporation":false,"usgs":true,"family":"Rachlow","given":"Janet","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":837220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Veblen, Kari E.","contributorId":76872,"corporation":false,"usgs":false,"family":"Veblen","given":"Kari","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":837221,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229387,"text":"70229387 - 2022 - Power analysis for detecting the effects of best management practices on reducing nitrogen and phosphorus fluxes to the Chesapeake Bay watershed, USA","interactions":[],"lastModifiedDate":"2022-03-04T15:17:53.244939","indexId":"70229387","displayToPublicDate":"2022-03-04T09:06:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Power analysis for detecting the effects of best management practices on reducing nitrogen and phosphorus fluxes to the Chesapeake Bay watershed, USA","docAbstract":"In 2010 the U.S. Environmental Protection Agency established the Total Maximum Daily Load (TMDL) which is a “pollution diet” that aims to reduce the amount of nitrogen and phosphorus entering the Chesapeake Bay, the largest estuary in the United States, by 25 and 24% percent, respectively. To achieve this goal the TMDL requires the implementation of Best Management Practices (BMPs), which are accepted land management practices for reducing pollutant runoff to nearby bodies of water. While the TMDL requires that the necessary management actions be in place by 2025 to eventually reach targeted nutrient loads, the ability to detect an effect of BMPs while assuming that one has occurred (i.e. statistical power) is still not well understood. The goal of this study was to investigate the power and required timelines to detect nutrient reductions in streams and rivers as the result of BMP implementation at the Chesapeake Watershed scale. Power estimates were produced using SPAtially Referenced Regression On Watershed attributes (SPARROW) models, which offer a flexible statistical framework and were recently extended to allow for modeling multiple time steps. Nitrogen and phosphorus focused models were calibrated to estimate the power to detect reductions in flux from numerous constituent sources. To confidently detect a decrease in constituent flux reaching the Chesapeake Bay’s tidal waters from a specific constituent source, reductions ranging from 30–60% were required for the nitrogen model. In contrast, reductions of up to 80% were not detectable under the phosphorus model. The timelines necessary to detect reductions in nitrogen flux ranged from 11 to several hundred years under different rates-of-change and management scenarios. The approach proposed here can help better understand the ability to detect the effects of BMPs on a regional scale and help guide future management actions and monitoring programs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.108713","usgsCitation":"McLaughlin, P., Alexander, R., Blomquist, J.D., Devereux, O.H., Noe, G.E., Wagner, T., and Smalling, K., 2022, Power analysis for detecting the effects of best management practices on reducing nitrogen and phosphorus fluxes to the Chesapeake Bay watershed, USA: Ecological Indicators, v. 136, p. 1-12, https://doi.org/10.1016/j.ecolind.2022.108713.","productDescription":"108713, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-136202","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":448593,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.108713","text":"Publisher Index Page"},{"id":396750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"136","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McLaughlin, Paul","contributorId":275082,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Paul","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":837243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard","contributorId":219089,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":837262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devereux, Olivia H.","contributorId":97238,"corporation":false,"usgs":true,"family":"Devereux","given":"Olivia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":837245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":837246,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837248,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837247,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229392,"text":"70229392 - 2022 - Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","interactions":[],"lastModifiedDate":"2022-03-04T15:06:26.624931","indexId":"70229392","displayToPublicDate":"2022-03-04T08:56:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","docAbstract":"The Alto Guaporé gold province, southwestern Amazon craton, contains gold deposits that have been mined since the beginning of the 18th century and these deposits, together, have modern-day, pre-mining gold resources of at least 1.8 Moz. The ore is associated with quartz vein systems along the southeastern part of the Aguapei belt, a ~35-km-wide and ~500-km-long, NNW-trending shear zone formed due to reactivation of a terrane-bounding suture. The Aguapei belt evolved by ca. 1150 to 1100 Ma rifting and deposition of siliciclastic sediments in an aulacogen basin, followed by deformation and low-grade metamorphism of the sedimentary sequences during 1100 to 900 Ma terrane collision along the craton margin. The deformation was characterized by a compressional regime until ca. 950 Ma and transition to a transpressional setting during the final 50 m.y.
The gold deposits are hosted in a variety of structures that are second-order to the main Aguapei shear zone. The Ernesto and Pau-a-Pique deposits are located ~40 km apart and at jogs along the Aguapei belt. They are marginal to pre-ore igneous rocks, with Ernesto hosted in the basal part of the metasedimentary Fortuna Formation that overlies tonalite and Pau-a-Pique at the contact between metasedimentary rocks and diorite. Three deformational phases comprise the compressional (D1 to D2) to transpressional (D3) tectonic events. In the Pau-a-Pique deposit and the deeper level of the Ernesto deposit, the ore-bearing veins are bedding parallel and follow D2 strike-slip and reverse fault zones, respectively. However, the veins formed during D3 reactivation of the older structures by an array of oblique accommodation faults. In contrast, ores at shallower levels of Ernesto, both in discordant and bedding-parallel veins, are hosted within a ~20-m-thick rigid metaconglomerate with associated dilation due to the structural complexity as sedimentary rocks of the Aguapei Group were folded around the dome-shaped roof of the pre-ore tonalite. The ores in both deposits, as well as in many other deposits of the province, are characterized by disseminated and vein-hosted pyrite. Gold occurs mainly as inclusions in the pyrite, with other hydrothermal phases comprising muscovite, Fe-Ti oxides, and minor apatite, chalcopyrite, and galena.
Fluid inclusion data, coupled with stable isotope geochemistry and geothermometry, indicate that gold precipitated from a low-salinity, CO2-rich fluid at ~300°C and ~2.5 kbar. The source for the fluid and gold was the interbedded pelites during devolatilization of the Aguapei Group sequence. The aqueous-carbonic fluid inclusions and the narrow range of δ18O values of quartz (12 ± 1‰) from many auriferous veins from the central part of the province represent a regional ore-forming fluid. The broad range of δD for hydrous minerals (–116 to –55‰) reflects influx of small amounts of meteoric water into the steeply dipping shear zones during postgold exhumation. The 40Ar/39Ar geochronology from hydrothermal muscovite indicates a widespread hydrothermal event along the belt between 928 and 920 Ma. Collectively, the geological, geochronological, and geochemical data suggest that metamorphic fluids migrated laterally into and then upward along the Aguapei belt and deposited gold in lower-order structures where strain gradients existed between lithounits. The province has many characteristics of large orogenic gold provinces worldwide and represents a highly prospective and underexplored target region for early Neoproterozoic gold, a time period that generally is not well endowed in gold ores.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4852","usgsCitation":"de Melo, R.P., de Oliveira, M.A., Goldfarb, R.J., Johnson, C.A., Marsh, E.E., Xavier, R.P., de Oliveira, L.R., and Morgan, L.E., 2022, Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil: Economic Geology, v. 117, no. 1, p. 127-163, https://doi.org/10.5382/econgeo.4852.","productDescription":"37 p.","startPage":"127","endPage":"163","ipdsId":"IP-121052","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488405,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11449/222995","text":"External Repository"},{"id":396749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Alto Guaporé gold province, Amazon craton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.7314453125,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -20.756113874762068\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Melo, Rodrigo Prudente","contributorId":287985,"corporation":false,"usgs":false,"family":"de Melo","given":"Rodrigo","email":"","middleInitial":"Prudente","affiliations":[{"id":61677,"text":"Faculdade de Ciência e Tecnologia, Univ. Federal de Goiás, R. Mucuri S/N, Aparecida de Goiânia, GO, CEP 74968-755, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Oliveira, Marcos Aurelio Farias","contributorId":287986,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Marcos","email":"","middleInitial":"Aurelio Farias","affiliations":[{"id":61678,"text":"Instituto de Geociências e Ciências Exatas, Univ. Estadual Paulista, R. 24A 1515, Rio Claro, SP, CEP 13506-900, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldfarb, Richard J. goldfarb@usgs.gov","contributorId":210729,"corporation":false,"usgs":false,"family":"Goldfarb","given":"Richard","email":"goldfarb@usgs.gov","middleInitial":"J.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":837256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":837257,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marsh, Erin E. 0000-0001-5245-9532 emarsh@usgs.gov","orcid":"https://orcid.org/0000-0001-5245-9532","contributorId":1250,"corporation":false,"usgs":true,"family":"Marsh","given":"Erin","email":"emarsh@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837258,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xavier, Roberto Perez","contributorId":287987,"corporation":false,"usgs":false,"family":"Xavier","given":"Roberto","email":"","middleInitial":"Perez","affiliations":[{"id":61679,"text":"Departamento de Geologia e Recursos Naturais, Instituto de Geociências, Universidade de Campinas, Campinas, SP, CEP 13083-970, Brazil","active":true,"usgs":false}],"preferred":false,"id":837259,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de Oliveira, Leandro Rocha","contributorId":287988,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Leandro","email":"","middleInitial":"Rocha","affiliations":[{"id":61680,"text":"Yamana Desenvolvimento Mineral, R. Ministro Orozimbo Nonato 272/19º andar, Belo Horizonte, MG, CEP 34006-053, Brazil","active":true,"usgs":false}],"preferred":false,"id":837260,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837261,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229391,"text":"70229391 - 2022 - Adaptive monitoring in support of adaptive management in rangelands","interactions":[],"lastModifiedDate":"2022-03-04T15:51:02.822444","indexId":"70229391","displayToPublicDate":"2022-03-04T08:56:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive monitoring in support of adaptive management in rangelands","docAbstract":"Monitoring supports iterative learning about the effectiveness of management actions, information that can help managers plan future actions, facilitate decision-making, and improve outcomes.
Adaptive monitoring is the evolution of a monitoring program in response to new management questions; new or changing environmental or socioeconomic conditions, improved monitoring methods, models, and tools; and experience implementing the monitoring program.
Adaptive monitoring is connected to research and management through the exchange of data; analytical, methodological, and technological developments; information; and understanding.
We review recent advances in adaptive monitoring and discuss new opportunities for both the research and management communities to improve monitoring in the years ahead.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.07.003","usgsCitation":"McCord, S.E., and Pilliod, D., 2022, Adaptive monitoring in support of adaptive management in rangelands: Rangelands, v. 44, no. 1, p. 1-7, https://doi.org/10.1016/j.rala.2021.07.003.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-127736","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.07.003","text":"Publisher Index Page"},{"id":396753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837253,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231766,"text":"70231766 - 2022 - Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","interactions":[],"lastModifiedDate":"2022-05-27T13:45:52.178121","indexId":"70231766","displayToPublicDate":"2022-03-04T08:40:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","title":"Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","docAbstract":"Investigating the long-term fluctuations of the feeding ecology of megaherbivores such as sirenians is important, as any changes could be indicative of shifts in resource availability. The Indian River Lagoon (IRL), eastern Florida, USA, is a critical habitat for the Florida manatee (Trichechus manatus latirostris). However, the IRL has experienced a substantial decline in seagrass due to the persistence of several harmful algal blooms. Using microhistological analysis, we examined the diet of manatees over a discontinuous sampling period spanning over 38 years using stomach contents collected from carcasses recovered in the IRL. Samples collected between 2013–2015 (post-seagrass die-off, n = 90) were compared to archived stomach samples collected between 1977–1989 (pre-seagrass die-off, n = 103). Samples analyzed from 1977–1989 contained primarily seagrasses (61.7%), followed by algae (28.4%) and vascular plants (1.7%). In contrast, stomach samples from the post-seagrass die-off primarily contained algae (49.5%), followed by seagrasses (34%) and vascular plants (2.7%). Between 1977–1989 and 2013–2015, manatees in the IRL experienced a 44.9% decline in seagrass consumption, and a 74.3% increase in algal consumption. This dietary shift was not influenced by body length, a proxy of age, or sex. Our results indicate that the dietary shift experienced by manatees is due to the decline of available seagrass forage in the IRL, and highlight the dietary plasticity of manatees in the face of changes in resource availability. However, the individual health and population-level consequences of this dietary shift are unknown. An increase in mortality due to undetermined causes in this region since 2012 can be associated with deteriorating body conditions of manatees in the IRL, possibly resulting from a lack of seagrass diet. Future research should further investigate behavioral changes affecting manatees in relation to seagrass decline in the IRL, including the energetic costs of this dietary change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2022.107788","usgsCitation":"Allen, A.C., Beck, C., Sattelberger, D.C., and Kiszka, J.J., 2022, Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses: Estuarine, Coastal and Shelf Science, v. 268, 107788, 7 p., https://doi.org/10.1016/j.ecss.2022.107788.","productDescription":"107788, 7 p.","ipdsId":"IP-134570","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":401296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Indian River Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.26611328125,\n 27.176469131898898\n ],\n [\n -80.0738525390625,\n 27.244862521497282\n ],\n [\n -80.57373046875,\n 28.65203063036226\n ],\n [\n -80.85937499999999,\n 28.844673680771795\n ],\n [\n -80.9088134765625,\n 28.7965462417692\n ],\n [\n -80.7989501953125,\n 28.36723539252299\n ],\n [\n -80.4913330078125,\n 27.727298422724655\n ],\n [\n -80.37597656249999,\n 27.391278222579277\n ],\n [\n -80.26611328125,\n 27.176469131898898\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"268","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Aarin Conrad","contributorId":139671,"corporation":false,"usgs":false,"family":"Allen","given":"Aarin","email":"","middleInitial":"Conrad","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":843744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Cathy 0000-0002-5388-5418 cbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-5418","contributorId":168987,"corporation":false,"usgs":true,"family":"Beck","given":"Cathy","email":"cbeck@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":843745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sattelberger, Danielle C.","contributorId":292060,"corporation":false,"usgs":false,"family":"Sattelberger","given":"Danielle","email":"","middleInitial":"C.","affiliations":[{"id":62815,"text":"Environmental Resource Program, Florida Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":843746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiszka, Jeremy J.","contributorId":292061,"corporation":false,"usgs":false,"family":"Kiszka","given":"Jeremy","email":"","middleInitial":"J.","affiliations":[{"id":62816,"text":"Institute of Environment, Department of Biological Sciences, Florida International University","active":true,"usgs":false}],"preferred":false,"id":843747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255537,"text":"70255537 - 2022 - Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","interactions":[],"lastModifiedDate":"2024-06-21T11:53:57.84801","indexId":"70255537","displayToPublicDate":"2022-03-04T06:51:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","docAbstract":"Compensatory recruitment can facilitate the persistence of populations experiencing high adult mortality. Because early life-stages of many taxa, including amphibians, are difficult to mark and recapture, sources of variation in survival at these stages often are unknown, which creates barriers to improving in situ recruitment rates. We leveraged count data and open N-mixture models to examine the environmental factors associated with the hatching of egg clutches, tadpole survival, and probability of metamorphosis in Boreal Toads (Anaxyrus boreas boreas) that inhabit pastures leased for cattle grazing in western Wyoming, USA. We conducted weekly surveys and measured a suite of environmental variables at 20 breeding ponds during May–September 2018. The hatching of egg clutches was most strongly related to pond surface area, as clutches often desiccated at smaller ponds. Weekly tadpole survival was lowest in ponds with high abundance of aquatic predators. Predation did not preclude metamorphosis, which was more strongly associated with higher dissolved oxygen and vegetation cover. Cattle grazing reduced vegetation cover in and around breeding ponds, which resulted in lower levels of dissolved oxygen. Grazing-induced habitat changes are therefore likely to negatively influence tadpole metamorphosis both via indirect effects on dissolved oxygen, and direct effects on vegetation cover, which also serves as feeding sites and escape cover from predators. We demonstrate the success of three critical phases in early life-stage development (egg hatching, tadpole survival, metamorphosis) was associated with different environmental factors. The inclusion of stage-specific responses in demographic analyses is therefore critical for a thorough understanding of what limits populations.
The goal of the Louisiana Barrier Island Comprehensive Monitoring (BICM) program is to provide long-term data on coastal Louisiana for monitoring change and assisting in coastal management. This study (carried out under Coastal Protection and Restoration Authority contract number 2000339324, BICM2—Chenier TopoBathy DEM) builds upon the previous BICM physical assessment of the Chenier Plain region using bathymetric data from three periods (1930, 2007, and 2017) to develop digital elevation models for historical and current periods. In addition to bathymetric datasets, the study includes light detection and ranging elevation measurements along the coastline to produce elevation datasets for the 2007 and 2017 periods. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221014","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chenier Plain region bathymetric and topographic datasets: Methodology report: U.S. Geological Survey Open-File Report 2022–1014, 21 p., https://doi.org/10.3133/ofr20221014.","productDescription":"vii, 21 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122902","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501759,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112530.htm","linkFileType":{"id":5,"text":"html"}},{"id":396683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1014"},{"id":396682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1014/coverthb.jpg"},{"id":396685,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1014/images/"},{"id":396684,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.XML"},{"id":396704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221014/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chenier Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85620117187499,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.439597566602902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
We use a suite of historical earthquakes to quantitatively determine earthquake early warning (EEW) alert threshold strategies for a range of shaking intensity targets for EEW in the U.S. West Coast. The current method for calculating alert regions for the ShakeAlert EEW System does not take into account variabilities and uncertainties in shaking distribution. As a result, if the modified Mercalli intensity (MMI) level used to determine the extent of the alert region (the alert threshold) is the same as the target intensity threshold, the alert region will be too small to include all locations that require alerts even if earthquake source parameters are estimated accurately. Missed alerts can be reduced by using a lower alert threshold than the target threshold. This expands the alert region, increasing the number of precautionary alerts issued to people who experience shaking below the target level. We determine alert thresholds that optimize this tradeoff between missed and precautionary alerts for target thresholds of MMI 4.0-6.0 using a ShakeMap catalog of 143 M5.0-7.3 earthquakes as ground truth. We examine the quality of each alerting strategy relative to the target MMI, where we define alert quality metrics in terms of both the area and population alerted. Optimal alert thresholds maximize correct alerts while limiting most precautionary alerts to regions that are likely to still feel some shaking. We find these optimal alert thresholds also maximize warning times. This analysis presents a quantitative framework ShakeAlert can use to communicate alerting strategies and performance expectations to ShakeAlert users.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002515","usgsCitation":"Saunders, J.K., Minson, S.E., and Baltay Sundstrom, A.S., 2022, How low should we alert? Quantifying intensity threshold alerting strategies for earthquake early warning in the United States: Earth's Future, v. 10, no. 3, e2021EF002515, 20 p., https://doi.org/10.1029/2021EF002515.","productDescription":"e2021EF002515, 20 p.","ipdsId":"IP-130454","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002515","text":"Publisher Index Page"},{"id":482033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders, Jessie Kate 0000-0001-5340-6715","orcid":"https://orcid.org/0000-0001-5340-6715","contributorId":290634,"corporation":false,"usgs":true,"family":"Saunders","given":"Jessie","email":"","middleInitial":"Kate","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229816,"text":"70229816 - 2022 - Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","interactions":[],"lastModifiedDate":"2022-03-18T14:39:48.68884","indexId":"70229816","displayToPublicDate":"2022-03-03T09:34:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","docAbstract":"Conservation translocations are increasingly used to help recover imperiled species. However, success of establishing populations remains low, especially for amphibians. Identifying factors associated with translocation success can help increase efficiency and efficacy of recovery efforts. Since the 1990s, several captive and semi-captive facilities have produced Chiricahua Leopard Frogs (Rana chiricahuensis) to establish or augment wild populations in Arizona and New Mexico, USA. During this same time, personnel associated with several programs surveyed translocation and non-translocation sites for presence of amphibians. We used 25 years (1995–2019) of survey and translocation data for the federally threatened Chiricahua Leopard Frog to identify factors linked with population persistence. Our dataset included approximately 40,642 egg masses or animals translocated in 314 events to 115 distinct sites and > 5800 visual encounter surveys from 641 sites; 120 of these sites were also surveyed with environmental DNA methods in 2018. We used a hierarchical dynamic occupancy model that accounted for imperfect detection to identify patch- and landscape-level attributes associated with site occupancy, and then used predictions from that model to evaluate factors associated with population persistence at translocation sites. Across all sites, extinction probability for Chiricahua Leopard Frogs was higher in lotic (stream) than lentic (pond) habitats and when Western Tiger Salamanders (Ambystoma mavortium) were present. Restoration of sites specifically for frog conservation reduced extinction probability. Colonization of unoccupied sites increased moderately with increasing numbers of translocation sites within 2 km, indicating a benefit of translocation efforts beyond sites where frogs were stocked. At translocation sites, persistence was greater in lentic than lotic habitats and was negatively correlated with the proportion of years tiger salamanders were present. Increasing numbers of translocation events, especially of late-stage larvae, increased persistence. There was little difference in population persistence based on whether stock was from captive, semi-captive, or wild sources, but translocations during the dry season (January—July) succeeded more than those after the typical arrival of summer rains (August—December). Based on the number of years translocation sites were predicted to be occupied, 2 or more translocations produced, on average, a > 4-yr increase in predicted occupancy compared to sites without translocations. While translocations have increased the number of populations across the landscape, continued management of water availability and threats such as invasive predators and disease remain critical to recovery of the Chiricahua Leopard Frog.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02078","usgsCitation":"Hossack, B., Howell, P., Owens, A., Cobos, C., Goldberg, C.S., Hall, D.L., Hedwall, S., MacVean, S., McCaffery, M., McCall, A.H., Mosley, C., Oja, E.B., Rorabaugh, J.C., Sigafus, B., and Sredl, M.J., 2022, Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations: Global Ecology and Conservation, v. 35, e02078, 22 p., https://doi.org/10.1016/j.gecco.2022.e02078.","productDescription":"e02078, 22 p.","ipdsId":"IP-135486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02078","text":"Publisher Index Page"},{"id":397306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35717773437499,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 31.325486676506983\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":838452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Audrey K","contributorId":288932,"corporation":false,"usgs":false,"family":"Owens","given":"Audrey K","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobos, C","contributorId":288933,"corporation":false,"usgs":false,"family":"Cobos","given":"C","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":838455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":838456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hedwall, Shaula","contributorId":288934,"corporation":false,"usgs":false,"family":"Hedwall","given":"Shaula","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":838457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacVean, Susi","contributorId":288935,"corporation":false,"usgs":false,"family":"MacVean","given":"Susi","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCaffery, Magnus","contributorId":288936,"corporation":false,"usgs":false,"family":"McCaffery","given":"Magnus","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838459,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCall, A. Hunter","contributorId":288937,"corporation":false,"usgs":false,"family":"McCall","given":"A.","email":"","middleInitial":"Hunter","affiliations":[{"id":48661,"text":"Private","active":true,"usgs":false}],"preferred":false,"id":838460,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mosley, C","contributorId":288938,"corporation":false,"usgs":false,"family":"Mosley","given":"C","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838461,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oja, Emily Bea 0000-0002-8621-9665","orcid":"https://orcid.org/0000-0002-8621-9665","contributorId":261164,"corporation":false,"usgs":true,"family":"Oja","given":"Emily","email":"","middleInitial":"Bea","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838462,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, James C.","contributorId":191978,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":838463,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838464,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sredl, Michael J","contributorId":288939,"corporation":false,"usgs":false,"family":"Sredl","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":838465,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229202,"text":"tm6A62 - 2022 - Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","interactions":[],"lastModifiedDate":"2022-03-03T17:29:27.921518","indexId":"tm6A62","displayToPublicDate":"2022-03-03T09:21:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A62","displayTitle":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","title":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","docAbstract":"This report describes the skeletal storage, compaction and subsidence (CSUB) package of MODFLOW 6. The CSUB package simulates the vertical compaction of compressible sediments and land subsidence. The package simulates groundwater storage changes and elastic compaction in coarse-grained aquifer sediments. The CSUB package also simulates groundwater storage changes and elastic and inelastic compaction in fne-grained, compressible interbeds, or in extensive confning units. The package can account for effective stress-dependent changes in storage properties. The CSUB package can also explicitly account for the contribution of water compressibility to groundwater storage changes.
Compaction of compressible sediments is formulated using Terzaghi’s elastoplastic model and assumes the total compaction is a small fraction of the total initial thickness of compressible sediments. Compaction is controlled by head or pore-pressure changes and overburden stress changes associated with water-table changes, and thus by effective stress changes within coarse-and fne-grained compressible sediments. If the stress in a compressible unit is less than the preconsolidation stress, compaction is elastic (recoverable). If the stress in a compressible sediment is greater than the preconsolidation stress, compaction is inelastic (irrecoverable) and permanent land subsidence occurs.
The propagation of head changes within fne-grained, compressible interbeds is represented numerically using a transient, one-dimensional (vertical) groundwater fow equation. This equation accounts for delayed release of water from storage or uptake of water into storage in the interbeds. Vertical hydraulic conductivity, elastic and inelastic skeletal specifc storage, and interbed thickness control the timing of interbed storage changes. Interbeds that are thin, have a relatively large vertical hydraulic conductivity, or relatively small specifc-storage values equilibrate quickly with heads/pore pressures in surrounding coarse-grained sediments and can be represented as no-delay interbeds that use the simulated groundwater head in a cell to calculate interbed compaction and do not need to be solved numerically using a vertically discretized interbed and the vertical groundwater fow equation.
In addition to the applicability to confned groundwater fow systems, several features of the CSUB package make it applicable to shallow, unconfned groundwater fow systems. Geostatic stress can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress. The porosity, void ratio, and thickness of shallow and deep coarse-grained aquifer sediments, fne-grained interbeds, and extensive confning units can vary in time based on calculated strain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A62","usgsCitation":"Hughes, J.D., Leake, S.A., Galloway, D.L., and White, J.T., 2022, Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6: U.S. Geological Survey Techniques and Methods, book 6, chap. A62, 57 p., https://doi.org/10.3133/tm6A62.","productDescription":"Report: vi, 57 p.; Software Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114536","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396667,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396668,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396669,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a62/coverthb.jpg"},{"id":396642,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"},{"id":396640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a62/tm6a62.pdf","text":"Report","size":"5.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A62"},{"id":396641,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A61","text":"Techniques and Methods 6-A61","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Transport Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
This report documents a new Groundwater Transport (GWT) Model for MODFLOW 6. The GWT Model simulates three-dimensional transport of a single chemical species in fowing groundwater based on a generalized control-volume fnite-difference approach. Although each GWT Model is only able to represent a single chemical species, multiple GWT Models may be invoked within a single MODFLOW 6 simulation to represent solute transport of multiple non-interacting chemical species. The GWT Model is designed to work with the Groundwater Flow (GWF) Model for MODFLOW 6, which simulates transient, three-dimensional groundwater fow. The version of the GWT model documented here must use the same spatial discretization used by the GWF Model; however, that spatial discretization can be represented by regular MODFLOW grids consisting of layers, rows, and columns, or by more general unstructured grids. The GWT Model simulates (1) advective transport, (2) the combined hydrodynamic dispersion processes of velocity-dependent mechanical dispersion and molecular diffusion, (3) adsorption and absorption (collectively referred to as sorption) of solutes by the aquifer matrix, (4) transfer between the mobile domain and one or more immobile domains, (5) frst-or zero-order solute decay or production, (6) mixing from groundwater sources and sinks, and (7) direct addition of solute mass. The GWT Model can also represent advective solute transport through advanced package features, such as streams, lakes, multi-aquifer wells, and the unsaturated zone. If the GWF Model application uses the Water Mover (MVR) Package to connect fow packages, then solute transport between these packages can also be represented. The transport processes described in this report have been implemented in a fully implicit manner and are solved in a system of equations using iterative numerical methods. The present version of the GWT Model for MODFLOW 6 does not have an option to calculate steady-state transport solutions; if a steady-state solution is required, then transient evolution of the solute must be represented using multiple time steps until no further changes in solute concentrations are detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A61","usgsCitation":"Langevin, C.D., Provost, A.M., Panday, Sorab, and Hughes, J.D., 2022, Documentation for the MODFLOW 6 Groundwater Transport Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A61, 56 p., https://doi.org/10.3133/tm6A61.","productDescription":"Report: vi, 56 p.; Software Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120850","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396637,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A62","text":"Techniques and Methods 6-A62","linkHelpText":"- Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6"},{"id":396666,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396665,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396664,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a61/coverthb2.jpg"},{"id":396636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a61/tm6a61.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A61"},{"id":396638,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
Coastal marshes are globally important, carbon dense ecosystems simultaneously maintained and threatened by sea-level rise. Warming temperatures may increase wetland plant productivity and organic matter accumulation, but temperature-modulated feedbacks between productivity and decomposition make it difficult to assess how wetlands and their thick, organic rich soils will respond to climate warming. Here, we actively increased aboveground plant-surface and below-ground soil temperatures in two marsh plant communities, and found that a moderate amount of warming (1.7°C above ambient temperatures) consistently maximized root growth, marsh elevation gain, and below-ground carbon accumulation. Marsh elevation loss observed at higher temperatures was associated with increased carbon mineralization and increased microtopographic heterogeneity, a potential early warning signal of marsh drowning. Maximized elevation and below-ground carbon accumulation for moderate warming scenarios uniquely suggest linkages between metabolic theory of individuals and landscape-scale ecosystem resilience and function, but our work indicates nonpermanent benefits as global temperatures continue to rise.
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task scaling factor controlled the relative contribution of the auxiliary variable's error to the overall loss during training. Our experiments examined the improvement in prediction accuracy of the multi-task approach using paired streamflow and water temperature data from sites across the conterminous United States. Our results showed that for 56 out of 101 sites, the best performing multi-task models performed better overall than the single-task models in terms of Nash-Sutcliffe efficiency for predicting streamflow with single-site models. For 43 sites, the best multi-task, single-site models made no significant difference in predicting streamflow. The multi-task approach had a smaller effect when applied to a model trained with data from 101 sites together, significantly improving performance for only 17 sites. The multi-task scaling factor was consequential in determining to what extent the multi-task approach was beneficial. A naïve selection of this factor led to significantly worse-performing models for 3 of 101 sites when predicting streamflow as the primary variable, and 47 of 53 sites when predicting stream temperature as the primary variable. We conclude that a multi-task approach can make more accurate predictions by leveraging information from interdependent hydrologic variables, but only for some sites, variables, and model configurations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR030138","usgsCitation":"Sadler, J.M., Appling, A.P., Read, J., Oliver, S.K., Jia, X., Zwart, J.A., and Kumar, V., 2022, Multi-task deep learning of daily streamflow and water temperature: Water Resources Research, v. 58, no. 4, e2021WR030138, 18 p., https://doi.org/10.1029/2021WR030138.","productDescription":"e2021WR030138, 18 p.","ipdsId":"IP-129032","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448611,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030138","text":"Publisher Index Page"},{"id":386338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":817232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229180,"text":"70229180 - 2022 - Assessing mineral supply concentration from different perspectives through a case study of zinc","interactions":[],"lastModifiedDate":"2022-10-31T14:03:16.051554","indexId":"70229180","displayToPublicDate":"2022-03-02T11:25:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Assessing mineral supply concentration from different perspectives through a case study of zinc","docAbstract":"Increasing demand for nonfuel mineral commodities has increased concerns regarding the reliability of their supplies. “Criticality” assessments over the past decade have attempted to capture this concern through a set of indicators, the most common of which quantifies the risk associated with market concentration by applying the Herfindahl-Hirschman Index (HHI) to the world production of a given commodity by country in a given year. Although this approach is useful, it inherently assumes that all of world production is available to the market and is thus potentially at risk. In this analysis, the HHI, as well as HHI weighted by country governance, is calculated for mined and refined zinc using the standard approach of using all world production data and comparing that to the HHI when using the best estimate of what is available to the world market. The results indicate that although the HHI of both mined and refined zinc world production has increased markedly over the past decade, the HHI for what is available to the market for mined and refined zinc has remained relatively constant and low, which is indicative of minimal supply risk. This is mainly owing to the fact that a large and increasing share of the world’s mined and refined zinc production comes from China, but that production supplies domestic consumption as well as small amounts of exports. As a result, the zinc materials that are available to the world market outside of China are produced by a relatively large and diverse set of countries. Although these analyses are specific to zinc, they are likely to be comparable for other commodities of which the largest producers are also the largest consumers and highlight the importance of examining different perspectives in criticality assessments.","language":"English","publisher":"Springer","doi":"10.1007/s13563-021-00291-2","usgsCitation":"Thomas, C.L., Nassar, N.T., and DeYoung, J., 2022, Assessing mineral supply concentration from different perspectives through a case study of zinc: Mineral Economics, v. 35, p. 6067-616, https://doi.org/10.1007/s13563-021-00291-2.","productDescription":"10 p.","startPage":"6067","endPage":"616","ipdsId":"IP-101409","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":448614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13563-021-00291-2","text":"Publisher Index Page"},{"id":396657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2022-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Christine L. 0000-0002-1391-6072","orcid":"https://orcid.org/0000-0002-1391-6072","contributorId":287564,"corporation":false,"usgs":false,"family":"Thomas","given":"Christine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":836874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":836875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeYoung, John H. Jr. jdeyoung@usgs.gov","contributorId":190728,"corporation":false,"usgs":true,"family":"DeYoung","given":"John H.","suffix":"Jr.","email":"jdeyoung@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":836925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228690,"text":"gip213 - 2022 - Visit the U.S. Geological Survey's National Water Dashboard","interactions":[],"lastModifiedDate":"2022-03-03T11:54:44.829334","indexId":"gip213","displayToPublicDate":"2022-03-02T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"213","displayTitle":"Visit the U.S. Geological Survey’s National Water Dashboard","title":"Visit the U.S. Geological Survey's National Water Dashboard","docAbstract":"The U.S. Geological Survey National Water Dashboard supplies critical information to decision makers, emergency managers, and the public during extreme hydrologic events (such as droughts and floods) and during normal hydrologic conditions. It informs decision making that can help protect lives and property before and during extreme hydrologic events. The National Water Dashboard draws upon the extensive site-specific hydrologic data housed in the U.S. Geological Survey National Water Information System database (https://doi.org/10.5066/F7P55KJN) and also links to the U.S. Geological Survey WaterAlert system, which provides users with instant and customized updates about water conditions. Overall, the National Water Dashboard is part of the U.S. Geological Survey's effort to respond to 21st century science needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip213","usgsCitation":"Miller, M.P., Burley, T.E., and McCallum, B.E., 2022, Visit the U.S. Geological Survey's National Water Dashboard: U.S. Geological Survey General Information Product 213, 2 p., https://doi.org/10.3133/gip213.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-127330","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":396097,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/213/coverthb.jpg"},{"id":396098,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/213/gip213.pdf","text":"Report","size":"319 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 213"}],"contact":"Associate Director, Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192