Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using grey wolves (Canis lupus). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs and trade-offs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk and seasonality. It accomplished this using simple behavioural rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behaviour.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2021.2512","usgsCitation":"Sells, S.N., Mitchell, M.S., Ausband, D.E., Luis, A.D., Emlen, D.J., Podruzny, K.M., and Gude, J., 2022, Economical defence of resources structures territorial space use in a cooperative carnivore: Proceedings of the Royal Society B: Biological Sciences, v. 289, no. 1966, 20212512, 10 p., https://doi.org/10.1098/rspb.2021.2512.","productDescription":"20212512, 10 p.","ipdsId":"IP-134147","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2021.2512","text":"Publisher Index Page"},{"id":429873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-105.038405,45.000345],[-105.848065,45.000396],[-105.913382,45.000941],[-105.914258,44.999986],[-105.928184,44.993647],[-106.263586,44.993788],[-107.050801,44.996424],[-107.074996,44.997004],[-107.084939,44.996599],[-107.105685,44.998734],[-107.125633,44.999388],[-107.13418,45.000109],[-107.351441,45.001407],[-107.49205,45.00148],[-107.608854,45.00086],[-107.750654,45.000778],[-107.997353,45.001565],[-108.000663,45.001223],[-108.14939,45.001062],[-108.218479,45.000541],[-108.238139,45.000206],[-108.249345,44.999458],[-108.271201,45.000251],[-108.500679,44.999691],[-108.565921,45.000578],[-109.08301,44.99961],[-109.103445,45.005904],[-109.375713,45.00461],[-109.386432,45.004887],[-109.574321,45.002631],[-109.663673,45.002536],[-109.75073,45.001605],[-109.875735,45.003275],[-109.99505,45.003174],[-110.026347,45.003665],[-110.110103,45.003905],[-110.199503,44.996188],[-110.28677,44.99685],[-110.324441,44.999156],[-110.342131,44.999053],[-110.362698,45.000593],[-110.402927,44.99381],[-110.48807,44.992361],[-110.552433,44.992237],[-110.705272,44.992324],[-110.750767,44.997948],[-110.761554,44.999934],[-110.785008,45.002952],[-111.055199,45.001321],[-111.056207,44.935901],[-111.055629,44.933578],[-111.056888,44.866658],[-111.056416,44.749928],[-111.055511,44.725343],[-111.055208,44.624927],[-111.048974,44.474072],[-111.062729,44.476073],[-111.122654,44.493659],[-111.131379,44.499925],[-111.139455,44.517112],[-111.143557,44.535732],[-111.15959,44.546376],[-111.166892,44.54722],[-111.175747,44.552219],[-111.182551,44.566874],[-111.189617,44.571062],[-111.201459,44.575696],[-111.225208,44.581006],[-111.23018,44.587025],[-111.231227,44.606915],[-111.224161,44.623402],[-111.25268,44.651092],[-111.262839,44.649658],[-111.276956,44.655626],[-111.26875,44.668279],[-111.29626,44.702271],[-111.323669,44.724474],[-111.341351,44.7293],[-111.348184,44.725459],[-111.355768,44.727602],[-111.366723,44.738361],[-111.36627,44.742234],[-111.37476,44.750295],[-111.385005,44.755128],[-111.393854,44.752549],[-111.397805,44.746738],[-111.394459,44.744578],[-111.398575,44.723343],[-111.414271,44.710741],[-111.424214,44.714024],[-111.429604,44.720149],[-111.438793,44.720546],[-111.486019,44.707654],[-111.489339,44.704946],[-111.490228,44.700221],[-111.484898,44.687578],[-111.47798,44.682393],[-111.468833,44.679335],[-111.473178,44.665479],[-111.50494,44.635746],[-111.521688,44.613371],[-111.525764,44.604883],[-111.524213,44.595585],[-111.519126,44.582916],[-111.492024,44.56081],[-111.469185,44.552044],[-111.467736,44.544521],[-111.471682,44.540824],[-111.500792,44.540062],[-111.518095,44.544177],[-111.524006,44.548385],[-111.546637,44.557099],[-111.556577,44.554495],[-111.562814,44.555209],[-111.585763,44.562843],[-111.591768,44.561502],[-111.601249,44.55421],[-111.614405,44.548991],[-111.681571,44.559864],[-111.704218,44.560205],[-111.709553,44.550206],[-111.715474,44.543543],[-111.737191,44.54306],[-111.746401,44.540766],[-111.758966,44.533766],[-111.761904,44.529841],[-111.806512,44.516264],[-111.807914,44.511716],[-111.821488,44.509286],[-111.842542,44.526069],[-111.849293,44.539837],[-111.870504,44.564033],[-111.887852,44.563413],[-111.903566,44.55723],[-111.947941,44.556776],[-111.951522,44.550062],[-111.980833,44.536682],[-111.995231,44.535444],[-112.01385,44.542348],[-112.032707,44.546642],[-112.035025,44.542691],[-112.034133,44.537716],[-112.036943,44.530323],[-112.053434,44.535089],[-112.069011,44.537104],[-112.093304,44.530002],[-112.096299,44.523212],[-112.101564,44.520847],[-112.106755,44.520829],[-112.125101,44.528527],[-112.129078,44.5363],[-112.136454,44.539911],[-112.164597,44.541666],[-112.179703,44.533021],[-112.183937,44.533067],[-112.221698,44.543519],[-112.229477,44.549494],[-112.226841,44.555239],[-112.230117,44.562759],[-112.242785,44.568091],[-112.258665,44.569516],[-112.286187,44.568472],[-112.307642,44.557651],[-112.312899,44.553536],[-112.315047,44.550049],[-112.315008,44.5419],[-112.319198,44.53911],[-112.348794,44.538691],[-112.35421,44.535638],[-112.358917,44.528847],[-112.3566,44.493127],[-112.358926,44.48628],[-112.368764,44.467153],[-112.387389,44.448058],[-112.435342,44.462216],[-112.460347,44.47571],[-112.473207,44.480027],[-112.50031,44.463051],[-112.511713,44.466445],[-112.512036,44.47042],[-112.518871,44.475784],[-112.541989,44.483971],[-112.550557,44.484928],[-112.573513,44.480983],[-112.584197,44.481368],[-112.601863,44.491015],[-112.660696,44.485756],[-112.664485,44.48645],[-112.671169,44.491265],[-112.707815,44.503023],[-112.71911,44.504344],[-112.735084,44.499159],[-112.749011,44.491233],[-112.781294,44.484888],[-112.797863,44.466112],[-112.828191,44.442472],[-112.836034,44.422653],[-112.821896,44.407436],[-112.812608,44.392275],[-112.81324,44.378103],[-112.820489,44.370946],[-112.844859,44.358221],[-112.855395,44.359975],[-112.881769,44.380315],[-112.886041,44.395874],[-112.915602,44.402699],[-112.951146,44.416699],[-112.981682,44.434279],[-113.003544,44.450814],[-113.020917,44.493827],[-113.018636,44.520064],[-113.019777,44.528505],[-113.032722,44.537137],[-113.04282,44.546757],[-113.042363,44.565237],[-113.061071,44.577329],[-113.083819,44.60222],[-113.07376,44.613928],[-113.065593,44.617391],[-113.05677,44.618657],[-113.053529,44.621187],[-113.049349,44.62938],[-113.051504,44.63695],[-113.065589,44.649371],[-113.068306,44.656374],[-113.07042,44.667844],[-113.067756,44.672807],[-113.06776,44.679474],[-113.081906,44.691392],[-113.098064,44.697477],[-113.101154,44.708578],[-113.102138,44.729027],[-113.116874,44.738104],[-113.134824,44.752763],[-113.137704,44.760109],[-113.131387,44.764738],[-113.131453,44.772837],[-113.140618,44.776698],[-113.158206,44.780847],[-113.163806,44.778921],[-113.179366,44.787142],[-113.183395,44.793565],[-113.19436,44.802151],[-113.209624,44.80907],[-113.238729,44.814144],[-113.247166,44.82295],[-113.278382,44.812706],[-113.29683,44.803358],[-113.301508,44.798985],[-113.341704,44.784853],[-113.354034,44.791745],[-113.354763,44.795468],[-113.346692,44.798898],[-113.3461,44.800611],[-113.356062,44.819798],[-113.377153,44.834858],[-113.383984,44.8374],[-113.422376,44.842595],[-113.455071,44.865424],[-113.474573,44.910846],[-113.491121,44.927548],[-113.498745,44.942314],[-113.494446,44.948597],[-113.480836,44.95031],[-113.474781,44.948795],[-113.467467,44.948061],[-113.448958,44.953544],[-113.443782,44.95989],[-113.444862,44.976141],[-113.447013,44.984637],[-113.446884,44.998545],[-113.437726,45.006967],[-113.449909,45.035167],[-113.44912,45.046098],[-113.45197,45.059247],[-113.460578,45.064879],[-113.465073,45.062755],[-113.47377,45.0617],[-113.485278,45.063519],[-113.520134,45.093033],[-113.510819,45.099902],[-113.506638,45.107288],[-113.513342,45.115225],[-113.538037,45.11503],[-113.546488,45.112285],[-113.554744,45.112901],[-113.57467,45.128411],[-113.594632,45.166034],[-113.589891,45.176986],[-113.599506,45.191114],[-113.636889,45.212983],[-113.647399,45.228282],[-113.650064,45.23471],[-113.657027,45.241436],[-113.665633,45.246265],[-113.674409,45.249411],[-113.678749,45.24927],[-113.684946,45.253706],[-113.692039,45.265191],[-113.691557,45.270912],[-113.688077,45.276407],[-113.689359,45.28355],[-113.735601,45.325265],[-113.738729,45.329741],[-113.7402,45.34559],[-113.73553,45.364738],[-113.73239,45.385058],[-113.733092,45.390173],[-113.734402,45.392353],[-113.750546,45.40272],[-113.760924,45.406501],[-113.765203,45.410601],[-113.768058,45.418147],[-113.763368,45.427732],[-113.764591,45.431403],[-113.783272,45.451839],[-113.78416,45.454946],[-113.759986,45.480735],[-113.766022,45.520621],[-113.778361,45.523415],[-113.796579,45.523462],[-113.802849,45.523159],[-113.809144,45.519908],[-113.834555,45.520729],[-113.819868,45.566326],[-113.804796,45.580358],[-113.803261,45.584193],[-113.802955,45.592631],[-113.806729,45.602146],[-113.823068,45.612486],[-113.861404,45.62366],[-113.886006,45.61702],[-113.904691,45.622007],[-113.902539,45.636945],[-113.898883,45.644167],[-113.900588,45.648259],[-113.903582,45.651165],[-113.919752,45.658536],[-113.930403,45.671878],[-113.93422,45.682232],[-113.971565,45.700636],[-113.986656,45.704564],[-114.015633,45.696127],[-114.019315,45.692937],[-114.020533,45.681223],[-114.02007,45.670332],[-114.013786,45.658238],[-114.014973,45.654008],[-114.018731,45.648616],[-114.033456,45.648629],[-114.067619,45.627706],[-114.08179,45.611329],[-114.083149,45.603996],[-114.0821,45.596958],[-114.086584,45.59118],[-114.100308,45.586354],[-114.122322,45.58426],[-114.131469,45.574444],[-114.132359,45.572531],[-114.128601,45.568996],[-114.129099,45.565491],[-114.135249,45.557465],[-114.154837,45.552916],[-114.180043,45.551432],[-114.18647,45.545539],[-114.192802,45.536596],[-114.203665,45.53557],[-114.227942,45.546423],[-114.248121,45.545877],[-114.251836,45.537812],[-114.248183,45.533226],[-114.247824,45.524283],[-114.261616,45.495816],[-114.270717,45.486116],[-114.279217,45.480616],[-114.333218,45.459316],[-114.345019,45.459916],[-114.360719,45.474116],[-114.36562,45.490416],[-114.36852,45.492716],[-114.388618,45.502903],[-114.415804,45.509753],[-114.438991,45.536076],[-114.450863,45.54253],[-114.456764,45.543983],[-114.460542,45.561283],[-114.473759,45.563278],[-114.498176,45.555473],[-114.506341,45.559216],[-114.517761,45.568129],[-114.526075,45.570771],[-114.549508,45.56059],[-114.559038,45.565706],[-114.558253,45.585104],[-114.553999,45.591279],[-114.538132,45.606834],[-114.544905,45.616673],[-114.553937,45.619299],[-114.563305,45.631612],[-114.563652,45.637412],[-114.561046,45.639906],[-114.53577,45.650613],[-114.529678,45.65232],[-114.522142,45.64934],[-114.507645,45.658949],[-114.499637,45.669035],[-114.495421,45.703321],[-114.497553,45.710677],[-114.504869,45.722176],[-114.535634,45.739095],[-114.566172,45.773864],[-114.562509,45.779927],[-114.555487,45.786249],[-114.544692,45.791447],[-114.512973,45.828825],[-114.51704,45.833148],[-114.517143,45.835993],[-114.514596,45.840785],[-114.509303,45.845531],[-114.498809,45.850676],[-114.470296,45.851343],[-114.455532,45.855012],[-114.44868,45.858891],[-114.422963,45.855381],[-114.409477,45.85164],[-114.388243,45.88234],[-114.387166,45.889164],[-114.395059,45.901458],[-114.404314,45.903497],[-114.413168,45.911479],[-114.431159,45.935737],[-114.431328,45.938023],[-114.427717,45.939625],[-114.423681,45.9441],[-114.415977,45.947891],[-114.411933,45.952358],[-114.404708,45.9559],[-114.402261,45.961489],[-114.403712,45.967049],[-114.409353,45.97141],[-114.411892,45.977883],[-114.419899,45.981106],[-114.425843,45.984984],[-114.470965,45.995742],[-114.47729,46.000802],[-114.477922,46.009025],[-114.473811,46.016614],[-114.480241,46.030325],[-114.485793,46.030022],[-114.490572,46.032427],[-114.493418,46.03717],[-114.494683,46.042546],[-114.492153,46.04729],[-114.468529,46.062484],[-114.461864,46.078571],[-114.460049,46.097104],[-114.474415,46.112515],[-114.488303,46.113106],[-114.5213,46.125287],[-114.527096,46.146218],[-114.514706,46.167726],[-114.489254,46.167684],[-114.478333,46.160876],[-114.472643,46.162202],[-114.457549,46.170231],[-114.445928,46.173933],[-114.443215,46.202943],[-114.445497,46.220227],[-114.449819,46.237119],[-114.451912,46.241253],[-114.468254,46.248796],[-114.470479,46.26732],[-114.465024,46.273127],[-114.453257,46.270939],[-114.441326,46.2738],[-114.43544,46.27661],[-114.427309,46.283624],[-114.425587,46.287899],[-114.433478,46.305502],[-114.431708,46.310744],[-114.413758,46.335945],[-114.410682,46.360673],[-114.411592,46.366688],[-114.422458,46.387097],[-114.408974,46.400438],[-114.384756,46.411784],[-114.376413,46.442983],[-114.379338,46.460166],[-114.383051,46.466402],[-114.394447,46.469549],[-114.400068,46.47718],[-114.403019,46.498675],[-114.400257,46.502143],[-114.395204,46.503148],[-114.385871,46.50437],[-114.375348,46.501855],[-114.35874,46.505306],[-114.351655,46.508119],[-114.342072,46.519679],[-114.349208,46.529514],[-114.348733,46.533792],[-114.34534,46.548444],[-114.339533,46.564039],[-114.33175,46.571914],[-114.331338,46.577781],[-114.333931,46.582732],[-114.334992,46.588154],[-114.333931,46.592162],[-114.322519,46.611066],[-114.322912,46.642938],[-114.320665,46.646963],[-114.32456,46.653579],[-114.332887,46.660756],[-114.360709,46.669059],[-114.394514,46.664846],[-114.403383,46.659633],[-114.410907,46.657466],[-114.424424,46.660648],[-114.453239,46.649266],[-114.45425,46.640974],[-114.466902,46.631695],[-114.486218,46.632829],[-114.498007,46.637655],[-114.547321,46.644485],[-114.561582,46.642043],[-114.583385,46.633227],[-114.593292,46.632848],[-114.615036,46.639733],[-114.616354,46.643646],[-114.611676,46.647704],[-114.614716,46.655256],[-114.621483,46.658143],[-114.635713,46.659375],[-114.642713,46.673145],[-114.641745,46.679286],[-114.631898,46.68397],[-114.623198,46.691511],[-114.620859,46.707415],[-114.626695,46.712889],[-114.632954,46.715495],[-114.649388,46.73289],[-114.696656,46.740572],[-114.699008,46.740223],[-114.710425,46.717704],[-114.713516,46.715138],[-114.727445,46.714604],[-114.740115,46.711771],[-114.747758,46.702649],[-114.749257,46.699688],[-114.751921,46.697207],[-114.76689,46.696901],[-114.787065,46.711255],[-114.788656,46.714033],[-114.779668,46.730411],[-114.773765,46.731805],[-114.76718,46.738828],[-114.765127,46.745383],[-114.765106,46.758153],[-114.79004,46.778729],[-114.808587,46.78235],[-114.818161,46.781139],[-114.829117,46.782503],[-114.835917,46.791111],[-114.844794,46.794305],[-114.856874,46.801633],[-114.860067,46.804988],[-114.861376,46.81196],[-114.864342,46.813858],[-114.880588,46.811791],[-114.888146,46.808573],[-114.897857,46.813184],[-114.904505,46.822851],[-114.920459,46.827697],[-114.927837,46.83599],[-114.92845,46.843242],[-114.92349,46.847594],[-114.928615,46.854815],[-114.940398,46.85605],[-114.947413,46.859324],[-114.943281,46.867971],[-114.938713,46.869021],[-114.931608,46.876799],[-114.931058,46.882108],[-114.936805,46.897378],[-114.935035,46.901749],[-114.927948,46.909948],[-114.927432,46.914185],[-114.929997,46.919625],[-114.960597,46.93001],[-114.986539,46.952099],[-115.00091,46.967703],[-115.001274,46.971901],[-115.028386,46.975659],[-115.028994,46.973159],[-115.031651,46.971548],[-115.047857,46.969533],[-115.049538,46.970774],[-115.057098,46.986758],[-115.066223,46.996375],[-115.071254,47.022083],[-115.087806,47.045519],[-115.098136,47.048897],[-115.102681,47.047239],[-115.107132,47.049041],[-115.120917,47.061237],[-115.136671,47.078276],[-115.139515,47.08456],[-115.140375,47.093013],[-115.170436,47.106265],[-115.172938,47.112881],[-115.189451,47.131032],[-115.200547,47.139154],[-115.223246,47.148974],[-115.243707,47.150347],[-115.255146,47.162876],[-115.255786,47.174725],[-115.261885,47.181742],[-115.286353,47.18327],[-115.300504,47.188139],[-115.300805,47.19393],[-115.295986,47.205658],[-115.29211,47.209861],[-115.294785,47.220914],[-115.298794,47.225245],[-115.307239,47.229892],[-115.311875,47.229673],[-115.317124,47.233305],[-115.324832,47.244841],[-115.326903,47.255912],[-115.339201,47.261623],[-115.3593,47.259461],[-115.36628,47.261485],[-115.371825,47.265213],[-115.410685,47.264228],[-115.421645,47.271736],[-115.423173,47.276222],[-115.428359,47.278722],[-115.443566,47.277309],[-115.457077,47.277794],[-115.470959,47.284873],[-115.487314,47.286518],[-115.51186,47.295219],[-115.526751,47.303219],[-115.531971,47.314121],[-115.548658,47.332213],[-115.551079,47.349856],[-115.556318,47.353076],[-115.564766,47.353476],[-115.570887,47.356375],[-115.578619,47.367007],[-115.609492,47.380799],[-115.617247,47.382521],[-115.639186,47.378605],[-115.644341,47.381826],[-115.648479,47.390293],[-115.657681,47.400651],[-115.69057,47.415059],[-115.71034,47.417784],[-115.718934,47.420967],[-115.72148,47.424469],[-115.728801,47.428925],[-115.731348,47.433381],[-115.728801,47.445159],[-115.718247,47.45316],[-115.69293,47.457237],[-115.671188,47.45439],[-115.663867,47.456936],[-115.654318,47.468077],[-115.653044,47.476035],[-115.655272,47.477944],[-115.686704,47.485596],[-115.694106,47.498634],[-115.708748,47.51264],[-115.71034,47.52951],[-115.717024,47.532693],[-115.741371,47.538645],[-115.747263,47.543197],[-115.748536,47.549245],[-115.746945,47.555293],[-115.734674,47.567401],[-115.721207,47.576323],[-115.706473,47.577299],[-115.689404,47.595402],[-115.694284,47.62346],[-115.708537,47.635356],[-115.715193,47.63634],[-115.72993,47.642442],[-115.73627,47.654762],[-115.726613,47.672093],[-115.72377,47.696671],[-115.730764,47.704426],[-115.752349,47.716743],[-115.758623,47.719041],[-115.763424,47.717313],[-115.77177,47.717412],[-115.776219,47.719818],[-115.783504,47.729305],[-115.780441,47.743447],[-115.797299,47.75752],[-115.803917,47.75848],[-115.824597,47.752154],[-115.831755,47.755785],[-115.835365,47.760957],[-115.835069,47.77006],[-115.837438,47.774846],[-115.84044,47.780172],[-115.847487,47.785227],[-115.848509,47.809331],[-115.845474,47.814967],[-115.852291,47.827991],[-115.870861,47.834939],[-115.875262,47.843272],[-115.881522,47.849672],[-115.900934,47.843064],[-115.906409,47.846261],[-115.919291,47.857406],[-115.939993,47.883153],[-115.959946,47.898142],[-115.965153,47.910131],[-115.969076,47.914256],[-115.982791,47.915994],[-115.993678,47.926183],[-115.995121,47.933827],[-115.998236,47.938779],[-116.007246,47.950087],[-116.030751,47.973349],[-116.03834,47.971318],[-116.04882,47.97716],[-116.049153,47.999923],[-116.048739,48.060093],[-116.04932,48.066644],[-116.049415,48.07722],[-116.048911,48.12493],[-116.049977,48.237604],[-116.049353,48.249936],[-116.049735,48.274668],[-116.048948,48.309847],[-116.050003,48.413492],[-116.049155,48.481247],[-116.049193,49.000912],[-116.00103,49.00127],[-115.990685,49.000909],[-115.501016,49.000694],[-115.207912,48.999228],[-114.375977,49.00139],[-114.250971,49.000905],[-114.224912,48.999687],[-114.201107,48.999249],[-114.180211,48.999703],[-114.059188,48.998856],[-113.907487,48.998858],[-113.864127,48.998276],[-113.692982,48.997632],[-113.576118,48.998478],[-113.375925,48.998562],[-113.356874,48.998224],[-113.19474,48.998909],[-113.116356,48.998462],[-112.143769,48.998917],[-112.003866,48.99857],[-112.000878,48.998921],[-111.761679,48.997614],[-111.500812,48.996963],[-111.003916,48.997537],[-110.592465,48.999012],[-110.531615,48.99839],[-110.438151,48.999188],[-109.500737,49.00044],[-109.454023,49.001132],[-109.437397,49.000631],[-109.384068,49.000374],[-109.285975,49.000479],[-109.250722,49.000011],[-109.000708,48.999234],[-107.704696,48.999872],[-107.441017,48.999363],[-107.363582,49.000019],[-106.050543,48.999207],[-105.612577,48.999703],[-104.875527,48.998991],[-104.048736,48.999877],[-104.0489,48.847387],[-104.047582,48.633984],[-104.048212,48.599055],[-104.047876,48.530798],[-104.047513,48.525913],[-104.048054,48.500025],[-104.047555,48.49414],[-104.046969,48.390675],[-104.046371,48.374154],[-104.046039,48.256761],[-104.045645,48.246179],[-104.044162,47.992836],[-104.041662,47.862282],[-104.043242,47.747106],[-104.043742,47.625016],[-104.044241,47.612288],[-104.043912,47.603229],[-104.044109,47.523595],[-104.045333,47.343452],[-104.045057,47.266868],[-104.045517,47.215666],[-104.044788,47.12743],[-104.045018,47.081202],[-104.045354,47.078574],[-104.045052,47.040863],[-104.045901,46.83079],[-104.045045,46.509788],[-104.046103,46.383916],[-104.045481,46.366871],[-104.045237,46.125002],[-104.045759,46.123946],[-104.046822,46.000199],[-104.04403,45.881975],[-104.042597,45.749998],[-104.041937,45.557915],[-104.041145,45.503367],[-104.041764,45.490789],[-104.040816,45.462708],[-104.040114,45.374214],[-104.039977,45.124988],[-104.039563,45.124039],[-104.040128,44.999987],[-104.039681,44.998041],[-104.057698,44.997431],[-104.250145,44.99822],[-104.665171,44.998618],[-104.72637,44.999518],[-104.759855,44.999066],[-105.038405,45.000345]]]},\"properties\":{\"name\":\"Montana\",\"nation\":\"USA \"}}]}","volume":"289","issue":"1966","noUsgsAuthors":false,"publicationDate":"2022-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sells, Sarah N.","contributorId":171706,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":902988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S.","contributorId":338172,"corporation":false,"usgs":false,"family":"Mitchell","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luis, Angela D.","contributorId":33199,"corporation":false,"usgs":true,"family":"Luis","given":"Angela","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":902989,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Emlen, Douglas J.","contributorId":338162,"corporation":false,"usgs":false,"family":"Emlen","given":"Douglas","email":"","middleInitial":"J.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":902990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Podruzny, Kevin M.","contributorId":85865,"corporation":false,"usgs":true,"family":"Podruzny","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":902992,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230367,"text":"70230367 - 2022 - Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy","interactions":[],"lastModifiedDate":"2022-04-11T14:00:54.827276","indexId":"70230367","displayToPublicDate":"2022-01-12T08:52:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy","docAbstract":"This work investigates bituminite (amorphous sedimentary organic matter) in Upper Jurassic Kimmeridge Clay source rock via confocal laser scanning microscopy (CLSM) and atomic force microscopy (AFM). These petrographic tools were used to provide better understanding of the nature of bituminite, which has been historically difficult to identify and differentiate from similar organic matter types in source rocks. As part of an International Committee for Coal and Organic Petrology (ICCP) working group, an immature (0.42% vitrinite reflectance), organic-rich (44.1 wt% total organic carbon content) sample of Kimmeridge Clay was distributed to multiple laboratories for CLSM characterization. The primary observations from CLSM imaging and spectroscopy include: 1) the interpreted presence of Botryococcus algae as a contributor to bituminite precursors; 2) color red-shift of sulfide reflectance and bituminite auto-fluorescence from below the sample surface; 3) positive alteration of bituminite from laser-induced photo-oxidation of the sample surface, including fluorescence blue-shift; 4) fluorescence blue-shift associated to higher fluorescence intensity regions in bituminite indicative of compositional (fluorophore) differences; 5) the need for fluorescence spectroscopy standardization as applied via CLSM; and 6) the suitability of CLSM fluorescence spectroscopy to predict solid bitumen reflectance from bituminite spectral emission via calibration to an extant dataset. Secondary CLSM observations include detection of reflected laser light from highly reflective inclusions in bituminite, including sulfides and fusinite, and radiolytic alteration of bituminite caused by substitution of U for Fe in sulfides. Findings from AFM include the observation that surface roughening or surface flattening of bituminite are induced by differential broad ion beam (BIB) milling and are dependent on the location and scale of AFM topology measurement. This result highlights our still limited understanding of the effects of BIB milling on sedimentary organic matter and indicates the need for further research before this technique can be advanced as a standard practice in petrographic sample preparation. Collectively, the results of this study illustrate the general applicability and versatility of AFM and CLSM as tools for organic petrology research, specifically for better understanding of the nature and properties of the bituminite maceral.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.103927","usgsCitation":"Hackley, P.C., Kus, J., Mendonca Filho, J.G., Czaja, A.D., Borrego, A., Životić, D., Valentine, B.J., and Hatcherian, J.J., 2022, Characterization of bituminite in Kimmeridge Clay by confocal laser scanning and atomic force microscopy: International Journal of Coal Geology, v. 251, 103927, 17 p., https://doi.org/10.1016/j.coal.2022.103927.","productDescription":"103927, 17 p.","ipdsId":"IP-133126","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":449187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2022.103927","text":"Publisher Index Page"},{"id":398465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"England","city":"Kimmeridge","otherGeospatial":"Upper Jurassic Kimmeridge Clay Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -2.1928024291992188,\n 50.58607046502884\n ],\n [\n -2.0602798461914062,\n 50.58607046502884\n ],\n [\n -2.0602798461914062,\n 50.629428887865565\n ],\n [\n -2.1928024291992188,\n 50.629428887865565\n ],\n [\n -2.1928024291992188,\n 50.58607046502884\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"251","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":840090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Jolanta","contributorId":289942,"corporation":false,"usgs":false,"family":"Kus","given":"Jolanta","affiliations":[{"id":62291,"text":"BGR.de","active":true,"usgs":false}],"preferred":false,"id":840091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mendonca Filho, Joao Graciano","contributorId":289943,"corporation":false,"usgs":false,"family":"Mendonca Filho","given":"Joao","email":"","middleInitial":"Graciano","affiliations":[{"id":62294,"text":"UFRJ","active":true,"usgs":false}],"preferred":false,"id":840092,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Czaja, Andrew D.","contributorId":289944,"corporation":false,"usgs":false,"family":"Czaja","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":62295,"text":"Univ. Cincinnati,","active":true,"usgs":false}],"preferred":false,"id":840093,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borrego, Angeles G.","contributorId":289945,"corporation":false,"usgs":false,"family":"Borrego","given":"Angeles G.","affiliations":[{"id":27409,"text":"Incar","active":true,"usgs":false}],"preferred":false,"id":840094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Životić, Dragana","contributorId":289946,"corporation":false,"usgs":false,"family":"Životić","given":"Dragana","affiliations":[{"id":62296,"text":"Univ. Belgrade","active":true,"usgs":false}],"preferred":false,"id":840095,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":840096,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":840097,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252840,"text":"70252840 - 2022 - Assessment of native fish passage through Brandon Road Lock and Dam, Des Plaines River, Illinois, using fin ray microchemistry","interactions":[],"lastModifiedDate":"2024-04-09T12:25:01.204236","indexId":"70252840","displayToPublicDate":"2022-01-12T07:22:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of native fish passage through Brandon Road Lock and Dam, Des Plaines River, Illinois, using fin ray microchemistry","docAbstract":"This study examined evidence of native fish passage through Brandon Road Lock and Dam (BRLD) on the Des Plaines River, Illinois, in light of proposed modifications to prevent the upstream passage of invasive carps. Direct evidence of upstream passage by native fishes at BRLD is lacking and could help to inform assessment of the impacts of barrier technology installation. Fin ray microchemistry was used to assess upstream BRLD passage in the native taxa Centrarchidae, Catostomidae, Ictaluridae, and Lepisosteidae. The fin ray edge strontium : calcium ratio (Sr:Ca) of fish sampled from the Des Plaines River upstream of BRLD and in rivers downstream of BRLD was used to characterize ranges of river-specific fin ray Sr:Ca for each taxon. These were applied to Sr:Ca data along a transect from fin ray core to edge to infer the environmental history of individual fish that were captured upstream from BRLD and to estimate the proportion of fish that had passed upstream through BRLD. Depending on the taxon, 6–37% of individuals sampled upstream from BRLD exhibited fin ray Sr:Ca indicating prior residency in rivers downstream of BRLD and therefore upstream passage through BRLD. Upstream passage was indeterminate for 19–91% of individuals in each taxon due to uncertainty in environmental history inferred from fin ray Sr:Ca. These results provide the first definitive evidence of upstream native fish passage at BRLD and suggest that the installation of barrier technology could have an impact on native fish.
The quality and quantity of geochronologic data used to constrain the history of major earthquakes in a region exerts a first-order control on the accuracy of seismic hazard assessments that affect millions of people. However, evaluations of geochronological data are limited by uncertainties related to inherently complex depositional processes that may vary spatially and temporally. To improve confidence in models of earthquake timing, we use a high-density suite of radiocarbon and optically stimulated luminescence (OSL) ages with a grid of 342 portable OSL samples to explore spatiotemporal trends in geochronological data across an exemplary normal fault colluvial wedge exposure. The data reveal a two-dimensional age map of the paleoseismic exposure and demonstrate how vertical and horizontal trends in age relate to dominant sedimentary facies and soil characteristics at the site. Portable OSL data provide critical context for the interpretation of 14C and OSL ages, show that geochronologic age boundaries between pre- and post-earthquake deposits do not match stratigraphic contacts, and provide the basis for selecting alternate Bayesian models of earthquake timing. Our results demonstrate the potential to use emergent, portable OSL methods to dramatically improve paleoseismic constraints on earthquake timing.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G49472.1","usgsCitation":"DuRoss, C., Gold, R.D., Gray, H., and Nicovich, S.R., 2022, Portable optically stimulated luminescence age map of a paleoseismic exposure: Geology, v. 50, no. 4, p. 470-475, https://doi.org/10.1130/G49472.1.","productDescription":"6 p.","startPage":"470","endPage":"475","ipdsId":"IP-134256","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":449199,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g49472.1","text":"Publisher Index Page"},{"id":399085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Deep Creek site, Wasatch fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8639,\n 39.5056\n ],\n [\n -111.8583,\n 39.5056\n ],\n [\n -111.8583,\n 39.5111\n ],\n [\n -111.8639,\n 39.5111\n ],\n [\n -111.8639,\n 39.5056\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Harrison J. 0000-0002-4555-7473","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":207019,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":840960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicovich, Sylvia R.","contributorId":290414,"corporation":false,"usgs":false,"family":"Nicovich","given":"Sylvia","email":"","middleInitial":"R.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":840961,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229655,"text":"70229655 - 2022 - Leveraging community science data for population assessments during a pandemic","interactions":[],"lastModifiedDate":"2022-04-12T13:42:34.235584","indexId":"70229655","displayToPublicDate":"2022-01-11T06:38:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging community science data for population assessments during a pandemic","docAbstract":"The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in population distribution. We fit our integrated model to 10 years of eBird (2010-2020) and 9 years of aerial survey (2010-2019) mottled duck count data to forecast 2020 population size along the western Gulf Coast of Texas and Louisiana. Estimates of mottled duck abundance were similar in magnitude to estimates calculated using previous methods, but were more precise and showed evidence of a declining population. The spatial distribution for mottled ducks each year was characterized by several concentrations of relatively high abundance, although the location of these abundance ‘hotspots’ varied over time. Expected abundance was higher for areas with a higher proportion of area covered by marsh habitat. By leveraging large-scale community science data, we were able to conduct a population assessment despite the disruption in structured surveys caused by the pandemic. As participation in community science platforms continues to increase, we anticipate modeling frameworks, like the integrated model we developed here, will become increasingly useful for informing conservation and management decision-making.
We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) along the San Luis Rey River, between College Boulevard in Oceanside and Interstate 15 in Fallbrook, California (middle San Luis Rey River), in 2021. Surveys were conducted from April 13 to July 14 (vireo) and from May 18 to July 13 (flycatcher). We found 180 vireo territories, at least 125 of which were occupied by pairs. The vireo population size decreased by 6 percent from 2020 to 2021. In 2021, vireo territories decreased by 14 percent in the portion of the middle San Luis Rey River that burned in 2017 and decreased by 2 percent outside of the burned area.
Vireos used six different habitat types in the survey area: (1) willow-cottonwood, (2) mixed willow riparian, (3) riparian scrub, (4) upland scrub, (5) willow-sycamore, and (6) non-native. Forty percent of the vireos were detected in habitat characterized as willow-cottonwood, and 97 percent of the vireos were detected in habitat with greater than 50-percent native plant cover. Of the 14 banded vireos detected in the survey area, 3 were resighted with a full color-band combination. There were 10 other vireos with single (natal) federal bands that were recaptured, identified, and color-banded in 2021. One vireo with a single dark blue federal band, indicating that it was banded as a nestling at the lower San Luis Rey River, could not be recaptured for identification. The 10 natal vireos that were recaptured on the middle San Luis Rey River dispersed from 2.0 to 11.7 kilometers from their natal territories. Banded vireos with a known age ranged from 1 to 7 years old.
One resident flycatcher, of undetermined breeding status, was observed in the survey area in 2021. The resident flycatcher (male) was detected in a territory of mixed willow habitat with greater than 50-percent native plant cover. He was detected from May 20 to June 4, 2021, and no evidence of pairing or nesting was observed. The male flycatcher was resighted with a unique color-band combination and had occupied the same territory since 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1147","usgsCitation":"Allen, L.D., and Kus, B.E., 2022, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego County, southern California—2021 Data summary: U.S. Geological Survey Data Report 1147, 12 p., https://doi.org/10.3133/dr1147.","productDescription":"iv, 12 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-135051","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436004,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UPGVPG","text":"USGS data release","linkHelpText":"Distribution and Abundance of Least Bell's Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego County, Southern California in 2021"},{"id":394135,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1147/covrthb.jpg"},{"id":394136,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1147/dr1147.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":394137,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1147/dr1147.pdf"},{"id":394138,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1147/images"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Middle San Luis Rey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.22137451171874,\n 32.90265033334125\n ],\n [\n -117.18841552734374,\n 32.63937487360669\n ],\n [\n -116.48254394531249,\n 32.71566625570313\n ],\n [\n -116.5264892578125,\n 32.960281958039836\n ],\n [\n -117.22137451171874,\n 32.90265033334125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Connectivity is vital to the resiliency of populations to environmental change and stochastic events, especially for cold-adapted species as Arctic and alpine tundra habitats retract as the climate warms. We examined the influence of past and current landscapes on genomic connectivity in cold-adapted galliformes as a critical first step to assess the vulnerability of Alaska ptarmigan and grouse to environmental change. We hypothesize that the mosaic of physical features and habitat within Alaska promoted the formation of genetic structure across species.
Alaska, United States of America.
Ptarmigan and Grouse (Galliformes: Tetraoninae).
We collected double digest restriction-site-associated DNA sequence data from six ptarmigan and grouse species (N = 13–145/species) sampled across multiple ecosystems up to ~10 degrees of latitude. Spatial genomic structure was analysed using methods that reflect different temporal scales: (1) principal components analysis to identify major trends in the distribution of genomic variation; (2) maximum likelihood clustering analyses to test for the presence of multiple genomic groupings; (3) shared co-ancestry analyses to assess contemporary relationships and (4) effective migration surfaces to identify regions that deviate from a null model of isolation by distance.
Levels of genomic structure varied across species (ΦST =0.009–0.042). Three general patterns of structure emerged: (1) east-west partition located near the Yukon-Tanana uplands; (2) north-south split coinciding with the Alaska Range and (3) northern group near the Brooks Range. Species-specific patterns were observed; not all landscape features were barriers to gene flow for all ptarmigan and grouse and temporal contrasts were detected at the Brooks Range.
Within Alaska galliformes, patterns of genomic structure coincide with physiographic features and highlight the importance of physical and ecological barriers in shaping how genomic diversity is arrayed across the landscape. Lack of concordance in spatial patterns indicates that species behaviour and habitat affinities play key roles in driving the contrasting patterns of genomic structure.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14294","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Talbot, S.L., 2022, Species-specific responses to landscape features shaped genomic structure within Alaska galliformes: Journal of Biogeography, v. 49, no. 2, p. 261-273, https://doi.org/10.1111/jbi.14294.","productDescription":"13 p.","startPage":"261","endPage":"273","ipdsId":"IP-119634","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":449226,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.14294","text":"Publisher Index Page"},{"id":436007,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DDB01R","text":"USGS data release","linkHelpText":"Genomic Data from Ptarmigan and Grouse, Alaska"},{"id":394242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-141.0007667541504,69.64681951728146],[-141.064453125,69.80172356231073],[-141.767578125,69.96043926902489],[-142.734375,70.1478274118401],[-143.26171875,70.25945200030638],[-144.99755859375,70.1925497583889],[-146.14013671875,70.21487465331137],[-147.43652343749997,70.32613725493573],[-148.40332031249997,70.51024068514326],[-149.47998046875,70.63448406630856],[-149.85351562499997,70.63448406630856],[-150.64453125,70.59802116106809],[-151.611328125,70.61261423801925],[-151.8310546875,70.7724429742589],[-152.02880859375,70.90226826757711],[-152.666015625,71.0098110139634],[-153.52294921875,71.05979781529196],[-154.31396484375,70.95969716686398],[-154.70947265625,71.20191973293133],[-155.41259765625,71.3219146980122],[-156.46728515625,71.45515260247822],[-157.10449218749997,71.34301347171373],[-157.58789062499997,71.21607526596131],[-157.91748046875,70.99550574822297],[-158.62060546875,70.9883492241249],[-159.30175781249997,70.98119010476937],[-159.98291015625,70.94535555009823],[-160.51025390625,70.73622993891799],[-160.90576171875,70.58341752317065],[-161.5869140625,70.45150843439349],[-161.78466796875,70.45885925640687],[-162.5537109375,70.34092679475283],[-163.05908203125,70.09552886456429],[-163.388671875,69.81689109911446],[-163.564453125,69.51914693717981],[-164.02587890625,69.15474044269264],[-164.90478515625,69.03714171275197],[-165.69580078124997,68.97416358340674],[-166.26708984375,69.01354605132325],[-166.376953125,68.80004113882613],[-166.66259765624997,68.5443150407769],[-167.1240234375,68.39918004344189],[-166.61865234375,68.17155518732503],[-166.5087890625,67.99110834539984],[-165.87158203125,67.8672645403614],[-164.61914062499997,67.47492238478702],[-164.24560546874997,67.23806155909902],[-164.091796875,67.02458758377148],[-163.10302734375,66.87834504307976],[-163.05908203125,66.73990169639414],[-162.66357421875,66.58321725728175],[-162.333984375,66.48697584176404],[-162.3779296875,66.34632215978135],[-163.2568359375,66.31103501145373],[-163.19091796875,66.55700652350038],[-163.76220703124997,66.73990169639414],[-164.46533203125,66.69647781801481],[-165.30029296875,66.55700652350038],[-166.1572265625,66.41674787052298],[-166.9482421875,66.24916310923315],[-167.3876953125,66.01801815922045],[-168.42041015625,65.56754970214311],[-168.02490234375,65.33017791526855],[-167.45361328125,65.18303007291382],[-166.9921875,64.86760781632728],[-166.7724609375,64.49172504435471],[-165.69580078124997,64.24459476798195],[-164.59716796875,64.29229248039543],[-164.13574218749997,64.26368374017731],[-163.49853515625,64.18724867664994],[-162.5537109375,64.27322328178595],[-161.82861328124997,64.24459476798195],[-161.52099609375,63.93737246791484],[-163.125,63.68524808030715],[-163.93798828125,63.41119772365924],[-164.5751953125,63.32254947641308],[-165.41015625,63.15435519659187],[-165.78369140625,62.75472592723178],[-166.26708984375,62.42090322195164],[-166.5966796875,62.155240711732425],[-166.48681640625,61.616843178481375],[-166.2451171875,61.23853141060282],[-165.849609375,60.8663124746226],[-166.5966796875,60.56537850464181],[-167.34375,60.468050120874615],[-167.80517578125,60.20707506634915],[-167.8271484375,60.09771842541544],[-167.89306640624997,59.93300042374631],[-167.03613281249997,59.712097173322924],[-166.640625,59.61221219518693],[-165.95947265624997,59.60109549032134],[-165.47607421874997,59.74532608213611],[-165.10253906249997,59.95501026206206],[-164.794921875,59.987997631212224],[-164.72900390624997,59.7563950493563],[-164.46533203125,59.54545678424146],[-163.8720703125,59.54545678424146],[-163.14697265625,59.60109549032134],[-162.26806640625,59.62332522313024],[-162.20214843749997,59.17592824927136],[-162.35595703125,58.81374171570782],[-162.57568359375,58.6769376725869],[-162.09228515625,58.39019698411526],[-161.455078125,58.39019698411526],[-160.68603515625,58.44773280389084],[-160.1806640625,58.516651799363785],[-159.71923828125,58.58543569119917],[-159.43359375,58.47072082411973],[-159.08203125,58.33256713195789],[-158.55468749999997,58.286395482881034],[-158.44482421874997,58.619777025081675],[-157.60986328125,58.52812515905843],[-158.00537109375,58.00809779306888],[-158.48876953125,57.468589192089354],[-159.49951171875,56.84897198026975],[-161.0595703125,56.389583525613055],[-164.9267578125,54.97761367069628],[-165.9814453125,54.470037612805754],[-168.55224609375,53.73571574532637],[-173.232421875,52.92215137976296],[-175.62744140624997,52.3755991766591],[-177.86865234375,52.13348804077147],[-178.9453125,50.98609893339354],[-178.00048828125,51.440312757160115],[-176.8359375,51.467696956223364],[-175.36376953125,51.7406361640977],[-171.826171875,52.119998657638156],[-167.62939453124997,52.9883372533954],[-166.728515625,53.186287573913305],[-165.9375,53.553362785528094],[-165.30029296875,53.76170183021049],[-164.3115234375,54.149567212540525],[-163.89404296875,54.29088164657006],[-163.3447265625,54.18815548107151],[-162.26806640625,54.07228265560388],[-162.09228515625,54.3549556895541],[-161.89453125,54.7246201949245],[-161.0595703125,54.80068486732233],[-160.400390625,54.67383096593114],[-159.19189453125,54.61025498157912],[-159.14794921875,55.07836723201515],[-158.79638671875,55.429013452407396],[-157.58789062499997,55.825973254619015],[-155.7421875,55.541064956111036],[-154.62158203125,56.01066647040695],[-153.47900390625,56.43820369358165],[-151.45751953125,57.397624055000456],[-151.4794921875,58.07787626787517],[-151.45751953125,58.75680543225761],[-149.74365234374997,59.38917842312835],[-148.51318359375,59.63443457494949],[-146.689453125,59.355596110016315],[-144.51416015625,59.75086102411168],[-144.3109130859375,59.87239799228177],[-143.8330078125,59.968758992382334],[-143.0694580078125,60.031929699115615],[-141.5533447265625,59.842055288480076],[-140.9051513671875,59.68160832698723],[-140.020751953125,59.478568831926395],[-139.1693115234375,59.234986238722],[-138.82873535156247,59.09138238455909],[-138.3233642578125,58.96983560365735],[-138.1146240234375,58.862064179600374],[-138.076171875,58.722598828043374],[-136.9775390625,58.19387126497797],[-136.56005859375,57.7862326105289],[-135.966796875,57.33838126552897],[-136.03271484375,57.052681978717494],[-135.81298828125,56.92099675839107],[-134.571533203125,55.8845546603819],[-134.2034912109375,55.56592203025787],[-133.8958740234375,55.263468250921285],[-133.7530517578125,55.06264118216743],[-133.6102294921875,54.64523407607479],[-133.2421875,54.635697306063854],[-130.6171417236328,54.70637513489091],[-130.62950134277344,54.72422365048395],[-130.62606811523438,54.73651472417763],[-130.65765380859375,54.762274228176494],[-130.62950134277344,54.78247406031503],[-130.5663299560547,54.79237225560392],[-130.49697875976562,54.82877675365454],[-130.42282104492188,54.87423625974835],[-130.34591674804688,54.91569803760518],[-130.27244567871094,54.97288463122321],[-130.18661499023438,55.062247951730015],[-130.18043518066406,55.091729515360875],[-130.15090942382812,55.12393783348962],[-130.14747619628906,55.14160209881279],[-130.10284423828125,55.19219635238084],[-129.97169494628906,55.28146181651345],[-129.97581481933594,55.30022902025666],[-130.02044677734375,55.33890835596374],[-130.0396728515625,55.45043679812318],[-130.0884246826172,55.496749338303694],[-130.12825012207028,55.58144971869657],[-130.10971069335938,55.68223010941079],[-130.14816284179688,55.71473455012689],[-130.15296936035156,55.7649857705176],[-130.12550354003906,55.80475427021683],[-130.0843048095703,55.82134464477078],[-130.00465393066406,55.90573012454021],[-130.00465393066406,55.9130425993163],[-130.0190734863281,55.912657766599715],[-130.00259399414062,56.00605986001467],[-130.10421752929688,56.12297419573329],[-130.24635314941406,56.09693875609652],[-130.3479766845703,56.12794955397159],[-130.42556762695312,56.14134155069025],[-130.4674530029297,56.24373146827144],[-130.55740356445312,56.249454174583384],[-130.5677032470703,56.25479459547735],[-130.62400817871094,56.2685236855868],[-130.78262329101562,56.36715174252849],[-131.08612060546875,56.40668363558357],[-131.16989135742188,56.44883107459549],[-131.473388671875,56.551913918713375],[-131.58119201660156,56.61204220477141],[-131.8352508544922,56.59843662755775],[-131.85997009277344,56.702620872371355],[-131.89979553222656,56.75347577609789],[-131.87232971191406,56.805765643008264],[-132.12432861328122,56.87374615531272],[-132.0467376708984,57.04521234171931],[-132.3687744140625,57.09149987857074],[-132.2472381591797,57.211056900559335],[-132.3680877685547,57.347273783306676],[-132.55210876464844,57.49516565182901],[-132.65853881835938,57.61562391374733],[-132.75466918945312,57.69680911844304],[-132.8693389892578,57.83853792318956],[-133.06983947753906,58.00082136594698],[-133.17283630371094,58.15404059343076],[-133.34518432617188,58.27628739957773],[-133.45985412597656,58.38731772556939],[-133.37608337402344,58.430481925680034],[-133.70567321777344,58.611194853078764],[-133.83956909179685,58.730440812979516],[-134.25979614257812,58.861354043320055],[-134.3360137939453,58.92414471817596],[-134.3140411376953,58.962755708753306],[-134.4060516357422,58.978683427688686],[-134.38133239746094,59.03878841190553],[-134.44656372070312,59.08820785301446],[-134.48501586914062,59.13121539881386],[-134.56329345703125,59.130510792073984],[-134.67933654785156,59.191757369765085],[-134.70130920410156,59.24973478117606],[-134.95742797851562,59.279914277804906],[-135.02883911132812,59.34649517787861],[-134.9897003173828,59.3877798237848],[-135.10093688964844,59.42622028594434],[-135.07827758789062,59.45275367774563],[-135.0274658203125,59.47473269180728],[-135.03021240234375,59.564245132658975],[-135.11810302734372,59.62367244601488],[-135.15586853027344,59.625061301654334],[-135.2190399169922,59.6632323288228],[-135.23345947265625,59.69650975428769],[-135.252685546875,59.69789559656873],[-135.36048889160156,59.73598378851403],[-135.4779052734375,59.79821644465919],[-135.94894409179688,59.6632323288228],[-136.1927032470703,59.63998787256213],[-136.34788513183594,59.60109549032134],[-136.25038146972656,59.56633207991906],[-136.24076843261716,59.55972296971678],[-136.24076843261716,59.52387204745182],[-136.3066864013672,59.46461714320982],[-136.36642456054688,59.4496126517294],[-136.47628784179688,59.46566371970234],[-136.46804809570312,59.28552611855346],[-136.49620056152344,59.27465233689575],[-136.4900207519531,59.26096748461385],[-136.5840911865234,59.166075318301345],[-136.8285369873047,59.16009179641602],[-136.8793487548828,59.13544273484683],[-137.28240966796875,59.0009698708429],[-137.449951171875,58.908900972391415],[-137.52548217773438,58.906418795609426],[-137.5000762939453,58.985760051467075],[-137.54127502441406,59.10478272378236],[-137.60787963867188,59.24376590151355],[-138.62617492675778,59.76746035005358],[-138.66600036621094,59.80961318716828],[-138.6797332763672,59.84481485969105],[-138.70582580566406,59.90650046741583],[-139.05258178710938,59.994179105518434],[-139.19952392578125,60.08950200748712],[-139.0711212158203,60.3187885497516],[-139.07386779785156,60.35243208301854],[-139.69253540039062,60.33544473468298],[-139.97955322265625,60.181818669034776],[-140.4595184326172,60.30858669066228],[-140.5199432373047,60.22003701633967],[-141.00128173828125,60.3058656567224],[-141.0007667541504,69.64681951728146]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-173.07586669921875,60.72157115165579],[-173.155517578125,60.69469537287745],[-173.15277099609375,60.64356945377967],[-173.08135986328125,60.61123754937553],[-173.04016113281247,60.58157148491742],[-173.08135986328125,60.53972302275651],[-173.089599609375,60.511343283202464],[-173.05938720703125,60.4788788301667],[-172.98248291015625,60.468050120874615],[-172.94677734374997,60.43689744859958],[-172.8424072265625,60.403001945865476],[-172.78472900390625,60.373144671593685],[-172.7105712890625,60.329667021005825],[-172.6611328125,60.3187885497516],[-172.5897216796875,60.309266913738156],[-172.49908447265625,60.31606836555203],[-172.4139404296875,60.3187885497516],[-172.35076904296875,60.3187885497516],[-172.30682373046872,60.29021531318375],[-172.2381591796875,60.29021531318375],[-172.17498779296875,60.30518536282736],[-172.2381591796875,60.333745513303114],[-172.34527587890625,60.378575303227215],[-172.364501953125,60.40164539086417],[-172.43041992187497,60.40571488624096],[-172.4798583984375,60.39757538658664],[-172.57598876953125,60.41249624776229],[-172.6556396484375,60.43689744859958],[-172.77374267578122,60.4788788301667],[-172.83416748046875,60.50052541051131],[-172.89459228515625,60.550527811064846],[-172.8863525390625,60.588316165776824],[-172.91656494140625,60.62606036274505],[-172.98797607421875,60.658377412327326],[-173.01544189453125,60.69469537287745],[-173.07586669921875,60.72157115165579]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-171.650390625,63.809167882566385],[-171.793212890625,63.82128765261384],[-171.80419921875,63.73147780336167],[-171.8426513671875,63.65601144183318],[-171.8865966796875,63.54365806976644],[-171.859130859375,63.42594585479083],[-171.7877197265625,63.34966546248425],[-171.62841796875,63.32501562217765],[-171.474609375,63.28306240110864],[-171.353759765625,63.29540792564745],[-171.2548828125,63.33980806067484],[-171.1395263671875,63.38413977217118],[-171.002197265625,63.389061297647125],[-170.760498046875,63.34966546248425],[-170.57373046875,63.32501562217765],[-170.41992187499997,63.27812271092345],[-170.343017578125,63.1989725264735],[-170.3594970703125,63.156835740093236],[-170.2496337890625,63.156835740093236],[-170.145263671875,63.156835740093236],[-170.0408935546875,63.14194929585152],[-169.9090576171875,63.087300267152735],[-169.8321533203125,63.03753005973634],[-169.7991943359375,62.990169510232555],[-169.8101806640625,62.95522304515911],[-169.74975585937497,62.922735326966595],[-169.617919921875,62.91523303947614],[-169.54650878906247,62.9502272814474],[-169.4915771484375,62.97270150065472],[-169.508056640625,62.99765260346662],[-169.4970703125,63.04251090966805],[-169.43664550781247,63.08978654472616],[-169.34326171874997,63.11712157280328],[-169.178466796875,63.13946747896222],[-169.1070556640625,63.14443090047572],[-168.958740234375,63.104699747121074],[-168.760986328125,63.112153479825004],[-168.67309570312497,63.203925767041305],[-168.662109375,63.26576978358972],[-168.7115478515625,63.3348780927218],[-168.92578125,63.366907787681754],[-169.07958984374997,63.366907787681754],[-169.25537109375,63.37183226679281],[-169.420166015625,63.376755901872734],[-169.5245361328125,63.389061297647125],[-169.6124267578125,63.43331707559086],[-169.705810546875,63.46278300222105],[-169.8211669921875,63.46523712749102],[-169.947509765625,63.48976680530999],[-170.0079345703125,63.59011870211632],[-170.0958251953125,63.658448979940175],[-170.2386474609375,63.704722429433225],[-170.4638671875,63.73390885572919],[-170.5902099609375,63.721751503619956],[-170.7659912109375,63.6779417467744],[-171.2164306640625,63.648697570849286],[-171.474609375,63.6779417467744],[-171.54052734375,63.75334975181205],[-171.650390625,63.809167882566385]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-170.40618896484375,57.022794415389725],[-170.3155517578125,57.043718234032625],[-170.22216796875,57.119841130872615],[-170.1947021484375,57.14518072479997],[-170.11505126953125,57.18985535714817],[-170.08209228515625,57.227042992549855],[-170.07110595703125,57.271618718194446],[-170.189208984375,57.23893512461504],[-170.2386474609375,57.22852971878346],[-170.32928466796875,57.22852971878346],[-170.3704833984375,57.22406936030381],[-170.49407958984375,57.20473490715757],[-170.41992187499997,57.12878649751151],[-170.364990234375,57.11387635258491],[-170.42266845703125,57.06910989239133],[-170.46112060546875,57.033257797376066],[-170.40618896484375,57.022794415389725]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-169.8321533203125,56.62904228542147],[-169.8211669921875,56.60486209416893],[-169.7991943359375,56.586716786451156],[-169.71405029296875,56.565536245992064],[-169.71405029296875,56.551913918713375],[-169.63165283203125,56.51707901932375],[-169.56024169921875,56.515563731608296],[-169.5025634765625,56.553427752820355],[-169.43115234375,56.58369172128337],[-169.43664550781247,56.626020608371924],[-169.56024169921875,56.63055303322322],[-169.6783447265625,56.62450967912138],[-169.8321533203125,56.62904228542147]]]}}]}","volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":830649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":830650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":830651,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227296,"text":"ofr20211030E - 2022 - System characterization report on Planet SkySat","interactions":[{"subject":{"id":70227296,"text":"ofr20211030E - 2022 - System characterization report on Planet SkySat","indexId":"ofr20211030E","publicationYear":"2022","noYear":false,"chapter":"E","displayTitle":"System Characterization Report on Planet SkySat","title":"System characterization report on Planet SkySat"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2022-01-07T16:46:40.809608","indexId":"ofr20211030E","displayToPublicDate":"2022-01-07T11:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"E","displayTitle":"System Characterization Report on Planet SkySat","title":"System characterization report on Planet SkySat","docAbstract":"This report addresses system characterization of Planet’s SkySat and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
SkySat is a constellation of submeter resolution Earth observation satellites providing analytics services, high-definition video, and imagery. The goal for the constellation is to capture multiple daily repeats of high-resolution imagery over any spot on the Earth. As of September 2020, 21 SkySat satellites have been launched, and the first launch occurred in November 2013. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.com/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that SkySat has an interior geometric performance in the range of a 0.38- (0.47 pixel) to 0.75-meter (m; 0.93 pixel) root mean square error in easting and a 0.27- (0.33 pixel) to 0.55-m (0.68 pixel) root mean square error in northing, in band-to-band registration; an exterior geometric performance in the range of 0.26 (0.32 pixel) to 1.04 m (1.28 pixels) offset in comparison to ground control points; a radiometric performance in the range of 0.033 to 0.797 (linear regression); and a spatial performance in the range of 3.7 to 4.3 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.004 to 0.009.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030E","usgsCitation":"Kim, M., Park, S., Sampath, A., Anderson, C., and Stensaas, G.L., 2022, System characterization report on Planet SkySat, chap. E of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030E.","productDescription":"iv, 17 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126680","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":394021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/e/coverthb.jpg"},{"id":394022,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/e/ofr20211030e.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-E"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Beginning in February of 2020, researchers and staff of the United States Geological Survey (USGS), Bat Conservation International (BCI), Virginia Polytechnic Institute and State University, and Montana State University associated with the North American Bat Monitoring Program (NABat) collaborated with the United States Fish and Wildlife Service (USFWS) to provide technical assistance in support of the USFWS Three Bat Species Status Assessments (SSA) including the little brown bat (MYLU, Myotis lucifugus), northern long-eared bat (MYSE, Myotis septentrionalis), and tricolored bat (PESU, Perimyotis subflavus). Analytical support for the SSA was not intended to provide interpretive results, which should therefore be considered beyond the scope of this report. Technical assistance for the SSA included facilitating the USFWS data call by educating and working directly with data contributors to manage, submit, and archive a variety of bat monitoring data in the online NABat database1 using standardized data submission templates accessible through the upload features on the NABat website. Most data collected through the USFWS data call for the SSA were submitted and stored in the NABat database. These represent the efforts of hundreds of partnering organizations across more than 200 individual NABat Partner Portal Projects. A few organizations contributed data for use in these analyses that were not submitted to the NABat database. Records submitted in response to the USFWS data call included bat capture, stationary and mobile acoustic, and internal roost count data (winter and summer). Data collated in the NABat database and used for the analyses described herein are documented (NABat 2020a, NABat 2020b, NABat 2021) and available through the NABat third party request feature.
gTOOLS is an open-source software for the processing of relative gravity data. gTOOLS is available in MATLAB and as a compiled executable to be run under the free MATLAB Runtime Compiler. The software has been designed for time-lapse (temporal) gravity monitoring. Although programmed to read the Scintrex CG-5 and CG-6 gravimeters output data files, it can be easily modified to read data files from other gravimeters. The software binds together single-task processing modules within a very simple user interface that is based on one text file. Gravity processing involves three modules: (a) gravimeter calibration; (b) automatic processing of gravity data to find adjusted gravity differences; and (c) post processing of results. Each module is optional and runs independently from the others. Data processing includes (a) averaging out the measurements noise, and correction for solid Earth tides, and ocean loading, and residual instrumental drift, and (b) calculate the residual instrumental drift and gravity differences between the base station and monitoring sites, and their uncertainties, by a weighted least square analysis of the gravity data. The software allows the automatic processing of a gravity campaign spanning multiple days in a single run. The software is tested on gravity data from 2015 eruption at Cotopaxi volcano, Ecuador.
California’s Central Valley provides critical habitat for migratory waterbirds, yet only 10% of naturally occurring wetlands remain. Competition for limited water supplies and climate change will impact the long-term viability of these intensively managed habitats.
Forecast the distribution, abundance, and connectivity of surface water and managed wetland habitats, using 5 spatially explicit (270 m2) climate/land use/water prioritization scenarios. Mapping potential future dynamic flooded habitat used by waterbirds and other wetland-dependent wildlife to inform management decisions.
We integrated a climate-driven hydrologic water use model with a spatially explicit land change model, to examine stakeholder-driven scenarios of future land change, climate, and water use and their impacts on future habitat availability.
Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101—an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion and loss of potential habitat. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability.
Climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when habitat restoration goals are met. Stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01398-1","usgsCitation":"Wilson, T., Matchett, E., Byrd, K.B., Conlisk, E., Reiter, M.E., Wallace, C., Flint, L.E., Flint, A.L., and Moritsch, M.M., 2022, Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley: Landscape Ecology, v. 37, p. 861-881, https://doi.org/10.1007/s10980-021-01398-1.","productDescription":"21 p.","startPage":"861","endPage":"881","ipdsId":"IP-127595","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":394093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 40.111688665595956\n ],\n [\n -122.78320312499999,\n 39.9434364619742\n ],\n [\n -122.607421875,\n 39.13006024213511\n ],\n [\n -122.34374999999999,\n 38.20365531807149\n ],\n [\n -121.59667968749999,\n 37.125286284966805\n ],\n [\n -120.41015624999999,\n 35.92464453144099\n ],\n [\n -118.95996093749999,\n 34.92197103616377\n ],\n [\n -117.90527343750001,\n 34.379712580462204\n ],\n [\n -117.2900390625,\n 34.45221847282654\n ],\n [\n -118.037109375,\n 35.28150065789119\n ],\n [\n -119.3115234375,\n 36.80928470205937\n ],\n [\n -120.7177734375,\n 38.54816542304656\n ],\n [\n -121.4208984375,\n 39.13006024213511\n ],\n [\n -122.29980468749999,\n 40.111688665595956\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2022-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":830456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conlisk, Erin","contributorId":270185,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":830458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reiter, Matthew E. 0000-0002-0587-786X","orcid":"https://orcid.org/0000-0002-0587-786X","contributorId":271031,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":56258,"text":"Point Blue","active":true,"usgs":false}],"preferred":false,"id":830459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallace, Cynthia 0000-0003-0001-8828 cwallace@usgs.gov","orcid":"https://orcid.org/0000-0003-0001-8828","contributorId":149179,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia","email":"cwallace@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830460,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830461,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830462,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830463,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70228524,"text":"70228524 - 2022 - Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2022-07-07T16:38:12.50761","indexId":"70228524","displayToPublicDate":"2022-01-07T06:37:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","docAbstract":"RestoreNet is an ecological restoration experiment that is networked across multiple sites, spanning dryland ecosystems in the southwestern United States. The experiment is organized and led by the U.S. Geological Survey’s Restoration Assessment and Monitoring Program for the Southwest (RAMPS). This protocol functions to provide guidance to additional partners on how to set up a RestoreNet site and expand the network to new locations. This protocol contains information for site selection, materials acquisition, experiment installation, data collection and monitoring, and data curation. Information includes protocols for the RestoreNet seeded experiment and an additional optional experiment using installed container seedlings initially propagated in a greenhouse. Participation in RestoreNet contributes to a growing body of knowledge on cutting edge ecological restoration methods for use in the southwestern United States to benefit land managers, landowners, and restoration practitioners.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2A18","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Laushman, K.M., McCormick, M.L., Munson, S.M., Balazs, K.R., and Butterfield, B.J., 2021, Protocol for installing and monitoring a RestoreNet restoration field trial network site: U.S. Geological Survey Techniques and Methods, book 2, chap. A18, 34 p., https://doi.org/10.3133/tm2A18.","productDescription":"vii, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-124290","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":393961,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/a18/covrthb.jpg"},{"id":393962,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/a18/tm2a18.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Texas, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.83984375,\n 32.84267363195431\n ],\n [\n -115.927734375,\n 32.65787573695528\n ],\n [\n -114.78515624999999,\n 32.731840896865684\n ],\n [\n -114.873046875,\n 32.509761735919426\n ],\n [\n -111.26953125,\n 31.42866311735861\n ],\n [\n -108.2373046875,\n 31.316101383495624\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.4794921875,\n 31.80289258670676\n ],\n [\n -106.0400390625,\n 31.615965936476076\n ],\n [\n -105.2490234375,\n 30.751277776257812\n ],\n [\n -104.853515625,\n 30.29701788337205\n ],\n [\n -104.5458984375,\n 29.6880527498568\n ],\n [\n -103.71093749999999,\n 29.19053283229458\n ],\n [\n -103.095703125,\n 28.92163128242129\n ],\n [\n -102.39257812499999,\n 29.76437737516313\n ],\n [\n -101.689453125,\n 29.878755346037977\n ],\n [\n -100.6787109375,\n 29.11377539511439\n ],\n [\n -100.986328125,\n 30.06909396443887\n ],\n [\n -102.3486328125,\n 31.50362930577303\n ],\n [\n -103.095703125,\n 32.13840869677249\n ],\n [\n -104.5458984375,\n 32.879587173066305\n ],\n [\n -105.380859375,\n 33.61461929233378\n ],\n [\n -105.732421875,\n 34.34343606848294\n ],\n [\n -105.29296874999999,\n 35.60371874069731\n ],\n [\n -104.8974609375,\n 37.09023980307208\n ],\n [\n -105.0732421875,\n 37.89219554724437\n ],\n [\n -106.171875,\n 37.3002752813443\n ],\n [\n -106.34765625,\n 36.38591277287651\n ],\n [\n -107.09472656249999,\n 35.71083783530009\n ],\n [\n -107.57812499999999,\n 35.460669951495305\n ],\n [\n -107.4462890625,\n 36.35052700542763\n ],\n [\n -107.4462890625,\n 37.19533058280065\n ],\n [\n -107.314453125,\n 38.13455657705411\n ],\n [\n -107.05078125,\n 38.993572058209466\n ],\n [\n -107.9296875,\n 40.68063802521456\n ],\n [\n -108.6328125,\n 40.88029480552824\n ],\n [\n -109.2041015625,\n 40.84706035607122\n ],\n [\n -109.951171875,\n 40.713955826286046\n ],\n [\n -111.6650390625,\n 40.44694705960048\n ],\n [\n -112.587890625,\n 40.212440718286466\n ],\n [\n -112.32421875,\n 39.50404070558415\n ],\n [\n -113.818359375,\n 38.788345355085625\n ],\n [\n -115.13671875,\n 38.685509760012\n ],\n [\n -116.45507812500001,\n 38.54816542304656\n ],\n [\n -118.91601562499999,\n 38.8225909761771\n ],\n [\n -120.10253906249999,\n 38.8225909761771\n ],\n [\n -120.14648437499999,\n 37.71859032558816\n ],\n [\n -119.66308593749999,\n 36.914764288955936\n ],\n [\n -119.88281249999999,\n 35.496456056584165\n ],\n [\n -119.267578125,\n 34.95799531086792\n ],\n [\n -117.94921874999999,\n 34.488447837809304\n ],\n [\n -116.6748046875,\n 33.76088200086917\n ],\n [\n -115.83984375,\n 32.84267363195431\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Although the Greater Caucasus Mountains have played a central role in absorbing late Cenozoic convergence between the Arabian and Eurasian plates, the orogenic architecture and the ways in which it accommodates modern shortening remain debated. Here, we addressed this problem using geologic mapping along two transects across the southern half of the western Greater Caucasus to reveal a suite of regionally coherent stratigraphic packages that are juxtaposed across a series of thrust faults, which we call the North Georgia fault system. From south to north within this system, stratigraphically repeated ~5–10-km-thick thrust sheets show systematically increasing bedding dip angles (<30° in the south to subvertical in the core of the range). Likewise, exhumation depth increases toward the core of the range, based on low-temperature thermochronologic data and metamorphic grade of exposed rocks. In contrast, active shortening in the modern system is accommodated, at least in part, by thrust faults along the southern margin of the orogen. Facilitated by the North Georgia fault system, the western Greater Caucasus Mountains broadly behave as an in-sequence, southward-propagating imbricate thrust fan, with older faults within the range progressively abandoned and new structures forming to accommodate shortening as the thrust propagates southward. We suggest that the single-fault-centric “Main Caucasus thrust” paradigm is no longer appropriate, as it is a system of faults, the North Georgia fault system, that dominates the architecture of the western Greater Caucasus Mountains.
Predictive modeling of submerged archaeological sites requires accurate sea-level predictions in order to reconstruct coastal paleogeography and associated geographic features that may have influenced the locations of occupation sites such as rivers and embayments. Earlier reconstructions of the paleogeography of parts of the western U.S. coast used an assumption of eustatic sea level, but this neglects the large spatial variations in relative sea level (RSL) associated with glacial isostatic adjustment (GIA) and tectonics. Subsequent work using a one-dimensional (1-D) solid Earth model showed that reconstructions that accounted for GIA result in significant differences from those based on eustatic sea level. However, these analyses neglected the complex three-dimensional (3-D) solid Earth structure associated with the Cascadia subduction zone that has also strongly influenced RSL along the Oregon-Washington (OR-WA) coast, requiring that the paleogeographic reconstructions must also account for this effect. Here we use RSL predictions from a 3-D solid Earth model that have been validated by RSL data to update previous paleogeographic reconstructions of the OR-WA coast for the last 12 kyr based on a 1-D solid Earth model. The large differences in the spatial variations in RSL on the OR-WA continental shelves predicted by the 3-D model relative to eustatic and 1-D models demonstrate that accurate reconstructions of coastal paleogeography for predictive modeling of submerged archaeological sites need to account for 3-D viscoelastic Earth structure in areas of complex tectonics.
The U.S. Geological Survey, in cooperation with DeKalb County Department of Watershed Management, established a long-term water-quantity and water-quality monitoring program in 2012 to monitor and analyze the hydrologic and water-quality conditions of 15 watersheds in DeKalb County, Georgia—an urban and suburban area located in north-central Georgia that includes the easternmost part of the City of Atlanta. This report synthesizes the watershed characteristics and monitoring data collected for the first 5 years of the program, 2012 through 2016. The study area was predominantly medium-density residential (43.9 percent), commercial/industrial/institutional (21.4 percent), forest/park/agriculture (13.6 percent), and high-density residential (11.5 percent) land uses. Land-surface slope averaged 8.7 percent, imperviousness averaged 25.3 percent, and population density averaged 2,936 people per square mile. Watershed imperviousness ranged from 8.7 to 36.6 percent.
In the study area for 2014 to 2016 (when streamflow data were available for all watersheds), runoff represented 40.9 percent of precipitation. Hydrograph separations indicated that 43 percent of runoff occurred as base flow, whereas the remainder occurred as stormflow. Higher watershed imperviousness was significantly related to higher amounts of runoff (Pearson product-moment correlation coefficient [r] = 0.517), higher runoff ratios (r = 0.646), and lower amounts (r = −0.637) and proportions (r = −0.898) of base-flow runoff. Stormwater best management practices have been implemented in the study watersheds; however, these practices do not appear to fully mitigate the effects of urban development and land use on stream hydrology.
Total copper, lead, and zinc concentrations in base-flow and stormflow samples exceeded the national recommended aquatic life criteria for chronic and acute conditions, respectively, to varying degrees. Escherichia coli density predictive regression models indicated that the U.S. Environmental Protection Agency’s Beach Action Value was exceeded at individual watersheds between 44.6 and 100 percent of the time. Exceedance of the Beach Action Value indicates possible unsafe conditions for primary contact recreation and could be used for timely notification of the potential health risks. Annual loads and yields were estimated for 15 constituents. Loads were typically higher for years with higher runoff while variations among watershed yields appear associated with watershed and land use characteristics. The lowest yields for almost all constituents occurred in the Stone Mountain Creek watershed—likely the result of the retention of sediment and reduction of nutrients in Stone Mountain Lake and two smaller downstream reservoirs within the watershed. The Little Stone Mountain Creek watershed also had some of the lowest yields for most constituents, likely due to the lack of many pollutant sources associated with its predominantly medium-density residential land use (95.5 percent), but had the highest total nitrate plus nitrite yields. The Intrenchment Creek watershed consistently had some of the highest yields across all constituents except for total nitrate plus nitrite. The high yields may be related to its high percentage of impervious area (36.0 percent) and high amount of heavily developed land use (high-density residential, 29.9 percent and commercial/industrial/institutional, 26.0 percent). Mean watershed constituent yields in this study were significantly higher than those from a similar analysis of 13 suburban to urban watersheds in adjacent Gwinnett County for 6 of the 10 constituents compared.
This study provides a thorough assessment of watershed characteristics, hydrology, and water-quality conditions of the 15 study watersheds and can be used to identify possible factors that affect runoff and water quality. Watershed managers can use these data and analyses to inform management decisions regarding the designated uses of streams, minimization of flooding, protection of aquatic habitats, and optimization of the effectiveness of best management practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215126","collaboration":"Prepared in cooperation with DeKalb County Department of Watershed Management","usgsCitation":"Aulenbach, B.T., Kolb, K., Joiner, J.K., and Knaak, A.E., 2022, Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16: U.S. Geological Survey Scientific Investigations Report 2021–5126, 105 p., https://doi.org/10.3133/sir20215126.","productDescription":"Report: xii, 105 p.; Data Release; Database","numberOfPages":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117184","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":393756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M6WCRH","text":"USGS data release","linkHelpText":"Streamwater constituent load data, models, and estimates for 15 watersheds in DeKalb County, Georgia, 2012–2016"},{"id":393757,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":393755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5126/sir20215126.pdf","text":"Report","size":"7.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5126"},{"id":393754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5126/coverthb.jpg"},{"id":502127,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112069.htm","linkFileType":{"id":5,"text":"html"}},{"id":393759,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5126/sir20215126.XML"},{"id":393758,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5126/images/"}],"country":"United States","state":"Georgia","county":"DeKalb County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-84.2707,33.955],[-84.2656,33.9482],[-84.2672,33.9473],[-84.2711,33.9459],[-84.2727,33.945],[-84.2716,33.9423],[-84.2699,33.9396],[-84.2676,33.936],[-84.2653,33.931],[-84.2601,33.9192],[-84.2596,33.9192],[-84.2562,33.9143],[-84.2523,33.9116],[-84.2511,33.9111],[-84.25,33.9107],[-84.2495,33.9107],[-84.2484,33.9103],[-84.2478,33.9103],[-84.2467,33.9098],[-84.2444,33.9085],[-84.2439,33.9076],[-84.2428,33.9076],[-84.2417,33.9071],[-84.2406,33.9072],[-84.2394,33.9063],[-84.2378,33.9049],[-84.2366,33.9045],[-84.2339,33.9031],[-84.2333,33.9031],[-84.2327,33.9027],[-84.2316,33.9018],[-84.2311,33.9013],[-84.2299,33.9005],[-84.2288,33.8986],[-84.2282,33.8977],[-84.2271,33.8959],[-84.2265,33.8955],[-84.226,33.8946],[-84.2254,33.8937],[-84.2248,33.8932],[-84.2243,33.8928],[-84.2226,33.8923],[-84.2215,33.891],[-84.2198,33.8892],[-84.2192,33.8883],[-84.217,33.886],[-84.2164,33.8851],[-84.2164,33.8842],[-84.2153,33.8842],[-84.2147,33.8838],[-84.2142,33.8833],[-84.2069,33.8761],[-84.2057,33.8748],[-84.2046,33.8734],[-84.2035,33.8725],[-84.2029,33.8721],[-84.2024,33.8721],[-84.2018,33.8721],[-84.2013,33.8721],[-84.2002,33.8717],[-84.1996,33.8717],[-84.1991,33.8717],[-84.1979,33.8712],[-84.1968,33.8708],[-84.1963,33.8703],[-84.1957,33.8699],[-84.1946,33.8694],[-84.1907,33.8672],[-84.1901,33.8668],[-84.1802,33.8646],[-84.1785,33.8633],[-84.1762,33.861],[-84.1751,33.8601],[-84.1745,33.8592],[-84.174,33.8583],[-84.1734,33.8578],[-84.1729,33.8578],[-84.1717,33.8574],[-84.1712,33.8574],[-84.1706,33.857],[-84.169,33.857],[-84.1684,33.857],[-84.1673,33.8565],[-84.1667,33.8565],[-84.1656,33.8557],[-84.164,33.8552],[-84.1612,33.8539],[-84.1606,33.8539],[-84.1595,33.8534],[-84.1584,33.8534],[-84.1573,33.853],[-84.1567,33.8526],[-84.1539,33.8485],[-84.1534,33.8485],[-84.1522,33.8476],[-84.1517,33.8467],[-84.1511,33.8462],[-84.15,33.8453],[-84.1466,33.8417],[-84.1461,33.8413],[-84.1416,33.8391],[-84.1383,33.8373],[-84.1371,33.8364],[-84.1366,33.8364],[-84.136,33.8359],[-84.1355,33.8355],[-84.1349,33.835],[-84.1343,33.8346],[-84.1338,33.8332],[-84.1338,33.8319],[-84.1338,33.831],[-84.1332,33.8305],[-84.1326,33.8296],[-84.1315,33.8287],[-84.1304,33.8274],[-84.1287,33.8256],[-84.1281,33.8256],[-84.127,33.8237],[-84.1264,33.8224],[-84.1259,33.8215],[-84.1248,33.8206],[-84.1231,33.8188],[-84.1225,33.8188],[-84.1214,33.8174],[-84.1208,33.8165],[-84.1208,33.8156],[-84.1202,33.8152],[-84.1197,33.8143],[-84.1191,33.8138],[-84.1186,33.8129],[-84.118,33.8125],[-84.1169,33.8111],[-84.1158,33.8098],[-84.1146,33.8084],[-84.1141,33.8075],[-84.1135,33.8075],[-84.113,33.8075],[-84.1124,33.8071],[-84.1118,33.8066],[-84.1113,33.8057],[-84.1107,33.8057],[-84.1102,33.8057],[-84.1096,33.8053],[-84.1091,33.8053],[-84.1085,33.8053],[-84.1079,33.8048],[-84.1068,33.8039],[-84.1057,33.8035],[-84.1052,33.8026],[-84.104,33.8017],[-84.1035,33.8012],[-84.1029,33.8013],[-84.1024,33.8013],[-84.1013,33.8008],[-84.1007,33.8008],[-84.099,33.7999],[-84.0985,33.7995],[-84.0979,33.799],[-84.0968,33.7972],[-84.0957,33.7963],[-84.094,33.7959],[-84.0934,33.795],[-84.0929,33.7941],[-84.0923,33.7941],[-84.0918,33.7927],[-84.0912,33.7923],[-84.0906,33.7914],[-84.0895,33.7909],[-84.0884,33.79],[-84.0873,33.7896],[-84.0867,33.7896],[-84.0862,33.7882],[-84.0845,33.7869],[-84.0822,33.7842],[-84.0806,33.7824],[-84.08,33.7815],[-84.0772,33.7788],[-84.075,33.777],[-84.0738,33.7761],[-84.0722,33.7756],[-84.0716,33.7752],[-84.0711,33.7752],[-84.0683,33.7747],[-84.0655,33.7743],[-84.0644,33.7739],[-84.0633,33.7734],[-84.0617,33.773],[-84.06,33.773],[-84.0583,33.7726],[-84.0578,33.7721],[-84.0572,33.7721],[-84.0567,33.7717],[-84.0561,33.7708],[-84.0555,33.7703],[-84.055,33.7699],[-84.0538,33.7685],[-84.0533,33.7681],[-84.0527,33.7672],[-84.0522,33.7667],[-84.0516,33.7667],[-84.0511,33.7667],[-84.0505,33.7663],[-84.0499,33.7654],[-84.0494,33.7654],[-84.0488,33.7658],[-84.0483,33.7658],[-84.0472,33.7654],[-84.0466,33.7645],[-84.0455,33.7636],[-84.0444,33.7627],[-84.0438,33.7627],[-84.0433,33.7622],[-84.0438,33.7618],[-84.0433,33.7609],[-84.0427,33.7604],[-84.0421,33.7595],[-84.0416,33.7586],[-84.041,33.7582],[-84.0399,33.7564],[-84.0393,33.7532],[-84.0393,33.7523],[-84.0382,33.7518],[-84.0365,33.7514],[-84.0365,33.75],[-84.0359,33.75],[-84.0359,33.7491],[-84.0359,33.7482],[-84.0353,33.7482],[-84.0326,33.7473],[-84.0318,33.7471],[-84.0386,33.7414],[-84.0572,33.7266],[-84.0641,33.7129],[-84.0711,33.6997],[-84.0744,33.6933],[-84.0867,33.6695],[-84.098,33.648],[-84.1023,33.6398],[-84.1157,33.6147],[-84.1169,33.6178],[-84.1186,33.6215],[-84.1192,33.6224],[-84.1197,33.6224],[-84.1208,33.6228],[-84.1214,33.6228],[-84.1225,33.6232],[-84.1236,33.6237],[-84.1236,33.6255],[-84.1242,33.626],[-84.1253,33.6264],[-84.1275,33.6268],[-84.128,33.6268],[-84.1286,33.6277],[-84.1286,33.6291],[-84.1286,33.6305],[-84.1292,33.6314],[-84.1298,33.6314],[-84.1303,33.6314],[-84.1309,33.6314],[-84.1314,33.6314],[-84.1342,33.6313],[-84.1347,33.6309],[-84.1353,33.6309],[-84.1358,33.6309],[-84.1364,33.6308],[-84.1369,33.6304],[-84.1375,33.6304],[-84.138,33.6304],[-84.1386,33.6304],[-84.1391,33.6308],[-84.1397,33.6308],[-84.1402,33.6313],[-84.1408,33.6313],[-84.1408,33.6322],[-84.1414,33.6326],[-84.1408,33.6331],[-84.1408,33.634],[-84.1408,33.6349],[-84.1425,33.6367],[-84.1442,33.6367],[-84.1447,33.6371],[-84.1453,33.6371],[-84.1469,33.638],[-84.1481,33.6385],[-84.1514,33.6398],[-84.1519,33.6407],[-84.1542,33.6452],[-84.1548,33.6461],[-84.1559,33.6457],[-84.1586,33.642],[-84.1613,33.6383],[-84.1618,33.6379],[-84.1635,33.6383],[-84.1646,33.6388],[-84.1651,33.6383],[-84.1657,33.6383],[-84.1668,33.6387],[-84.1685,33.6387],[-84.169,33.6392],[-84.1696,33.6396],[-84.1701,33.6396],[-84.1707,33.64],[-84.1713,33.6405],[-84.1724,33.6405],[-84.1729,33.6409],[-84.1729,33.6418],[-84.1702,33.646],[-84.1758,33.6464],[-84.1873,33.6463],[-84.1995,33.6466],[-84.2254,33.6468],[-84.2252,33.6308],[-84.2456,33.6306],[-84.2453,33.647],[-84.2497,33.6469],[-84.253,33.6469],[-84.2541,33.6469],[-84.2673,33.6472],[-84.2817,33.6475],[-84.3004,33.6478],[-84.3126,33.6481],[-84.3501,33.6481],[-84.3495,33.6799],[-84.3497,33.6886],[-84.3493,33.7],[-84.3494,33.7377],[-84.3491,33.75],[-84.349,33.7754],[-84.3488,33.8009],[-84.3488,33.8291],[-84.3482,33.8609],[-84.3483,33.8964],[-84.3484,33.9019],[-84.3478,33.9314],[-84.3476,33.951],[-84.3479,33.9682],[-84.3379,33.9706],[-84.3374,33.9711],[-84.3368,33.9706],[-84.3251,33.9671],[-84.324,33.9672],[-84.3235,33.9676],[-84.3224,33.9676],[-84.3213,33.9676],[-84.3202,33.9677],[-84.3196,33.9672],[-84.3179,33.9663],[-84.3168,33.9663],[-84.3085,33.9632],[-84.3068,33.9623],[-84.3057,33.9614],[-84.3046,33.961],[-84.3029,33.9606],[-84.3007,33.9597],[-84.3001,33.9592],[-84.2996,33.9597],[-84.2984,33.9597],[-84.2973,33.9602],[-84.2962,33.9602],[-84.2951,33.9598],[-84.294,33.9598],[-84.2907,33.9584],[-84.289,33.958],[-84.2873,33.9576],[-84.2857,33.9571],[-84.2845,33.9567],[-84.2806,33.9563],[-84.279,33.9576],[-84.2768,33.9581],[-84.2762,33.9545],[-84.2707,33.955]]]},\"properties\":{\"name\":\"DeKalb\",\"state\":\"GA\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093
The Des Moines River alluvial aquifer is an important source of water for Des Moines Water Works, the municipal water utility that provides residential and commercial water resources to the residents of Des Moines, Iowa, and surrounding municipalities. As an initial step in developing a better understanding of the groundwater resources of the Des Moines River alluvial aquifer, the U.S. Geological Survey constructed a steady-state numerical groundwater flow model in cooperation with Des Moines Water Works to simulate water-table elevations in the Des Moines River alluvial aquifer near Prospect Park in Des Moines under winter low-flow conditions.
A simple conceptual model consisting of a hydrogeologic framework, water budget, and inferred water-table elevation map was developed for the model area. The inferred water-table elevation map was constructed based on general knowledge of hydrogeology within the model area and was used to set calibration targets for numerical model calibration. A steady-state numerical model was constructed based on the conceptual model using MODFLOW-NWT to simulate an area of about 15 square kilometers near Prospect Park in Des Moines. Parameter ESTimation software was used for model calibration to assess and optimize performance of the horizontal hydraulic conductivity and recharge parameters. The numerical groundwater flow model and supporting data are available in the USGS data release associated with this report, which contains the model archive.
Performance of the calibrated steady-state model was assessed by comparing observed and simulated water-table elevations, as well as estimated and simulated contributions to streamflow within the model area. The difference between observed water-table elevations and simulated water-table elevations was −0.1 meter at the majority of calibration targets, with the negative value indicating an overestimation of the simulated water-table elevation value compared to the observed water-table elevation value, and the root mean square error was 0.13 meter, which represents about 20 percent of the difference in observed water-table elevations. The simulated value of contributions to streamflow within the model area was considered similar to the estimated value, increasing confidence in the ability of the model to accurately represent the groundwater flow system in the Des Moines River alluvial aquifer in the model area during winter low-flow conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211110","collaboration":"Prepared in cooperation with Des Moines Water Works","usgsCitation":"FitzGerald, K.M., Ha, W.S., Haj, A.E., Gruhn, L.R., Bristow, E.L., and Weber, J.R., 2022, A steady-state groundwater flow model for the Des Moines River alluvial aquifer near Prospect Park, Des Moines, Iowa: U.S. Geological Survey Open-File Report 2021–1110, 20 p., https://doi.org/10.3133/ofr20211110.","productDescription":"Report: vii, 20 p.; Data Release; Dataset","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130288","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501532,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112070.htm","linkFileType":{"id":5,"text":"html"}},{"id":393916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1110/ofr20211110.pdf","text":"Report","size":"2.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1110"},{"id":393915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1110/coverthb.jpg"},{"id":393917,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":393918,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Prospect Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.65175247192383,\n 41.611463744813506\n ],\n [\n -93.61836433410645,\n 41.611463744813506\n ],\n [\n -93.61836433410645,\n 41.63019942878951\n ],\n [\n -93.65175247192383,\n 41.63019942878951\n ],\n [\n -93.65175247192383,\n 41.611463744813506\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The Des Plaines River in southern Wisconsin and northern Illinois is the principal conduit for the discharge of wastewater effluent and stormwater runoff from the greater Chicago metropolitan area. In November 2017, the U.S. Geological Survey, in cooperation with the Metropolitan Water Reclamation District of Greater Chicago, installed a continuous monitoring station to measure water quality and streamflow in the Des Plaines River at Joliet, Illinois. Surrogate models encompassing continuous data and discrete water-quality samples were used to estimate loads of nitrate, total phosphorus, and suspended sediment. Comparisons to other major rivers in Illinois show that the Des Plaines River is a substantial contributor to statewide loading estimates for nitrate and total phosphorus but only a minor contributor to suspended sediment. Future loading estimates of total phosphorus could include more research into the effects of combined sewage overflows because these effects likely increased model uncertainty. The results in this report document current loadings and provide a baseline from which to assess future water-quality management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215125","collaboration":"Prepared in cooperation with Metropolitan Water Reclamation District of Greater Chicago","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., and Hodson, T.O., 2022, Continuous monitoring of nutrient and sediment loads from the Des Plaines River at Route 53 at Joliet, Illinois, water years 2018–20 (ver. 1.1, February 2022): U.S. Geological Survey Scientific Investigations Report 2021–5125, 15 p., https://doi.org/10.3133/sir20215125.","productDescription":"Report: vii, 15 p.; Data Release; Database","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-129874","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":393780,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M4BH1C","text":"USGS data release","linkHelpText":"Modeled nutrient and sediment concentrations from the Des Plaines River at Route 53 at Joliet, Illinois, based on continuous monitoring from October 1, 2017, through September 30, 2020"},{"id":396575,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5125/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":393783,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5125/images/"},{"id":393782,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5125/sir20215125.XML"},{"id":393781,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":393779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5125/sir20215125.pdf","text":"Report","size":"2.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5125"},{"id":393778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5125/coverthb2.jpg"},{"id":502126,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112067.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","city":"Joliet","otherGeospatial":"Des Plaines River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.25,\n 41.5\n ],\n [\n -87.5,\n 41.5\n ],\n [\n -87.5,\n 42.25\n ],\n [\n -88.25,\n 42.25\n ],\n [\n -88.25,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: January 5, 2022; Version 1.1: February 28, 2022","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Secondary sexual traits (e.g., horns and antlers) have ecological and evolutionary importance and are of management interest for game species. Yet, how these traits respond to emerging threats like infectious disease remains underexplored. Infectious pneumonia threatens bighorn sheep (Ovis canadensis) populations across North America and we hypothesized it may also reduce horn growth in male sheep. We assess the effect of pneumonia on horn size in male bighorn sheep using 12 herd datasets from across the western United States that had horn growth and disease data. Disease resulted in 12–35% reduction in increment (yearly) length and 3–13% reduction in total horn length in exposed individuals. The disease effect was prolonged when pathogens continued to circulate in sheep populations. Further, disease likely delays the age at which horns reach ¾-curl and prevents achievement of full-curl. This is further evidenced with 6 of the 12 herds experiencing an increase in average age at harvest following die-off events.
Widespread amphibian declines were well documented at the end of the 20th century, raising concerns about the need to identify individual and interactive contributors to this global trend. At the same time, there was growing interest in the use of amphibians as ecological indicators. In the United States, wetland and amphibian monitoring programs were launched in some national parks as a necessary first step to evaluating the status and trends of amphibian populations within some of North America’s most protected areas. In Grand Teton and Yellowstone national parks, a multi-species amphibian monitoring program was launched by many of the authors in 2006 and continues to this day. This Viewpoint Article serves as a self-evaluation of our journey from conception through implementation of an ongoing, long-term monitoring program. This self-evaluation should provide a framework and guidance for other monitoring programs. We address whether we are fulfilling the program’s main objective of describing status and trends of the four amphibian species, discuss how a one-size-fits-all monitoring approach does not serve all species equally, and describe opportunities to bolster our core work using emerging statistical approaches and thoughtful integration of remote sensing and molecular tools. We also describe how the data generated over the program’s first 15 years have been useful beyond our initial goal of characterizing status and trend. Notably, our integration of climate datasets has allowed us to describe wetland and species-specific amphibian responses to variations in climate drivers. Documenting climate links to amphibian occurrence and their primary habitats has allowed us to identify which species, habitat types, and subregions within this large, protected landscape are most vulnerable to anticipated climate change. Recognizing that tools and threats change over time, it will be important to adapt our original monitoring design to maximize opportunities and use of resulting information. Maintaining engagement by multiple stakeholders and expanding our funding portfolio will also be necessary to sustain our program into the future. Finally, collaboration has become standard for long-term, cross-jurisdictional, landscape-scale monitoring. We argue that collaborative monitoring facilitates resource sharing, leveraging of limited funds, completion of work, and mutual learning. Such collaboration also increases the efficacy of conservation.
In recent years, deep learning has achieved tremendous success in image segmentation for computer vision applications. The performance of these models heavily relies on the availability of large-scale high-quality training labels (e.g., PASCAL VOC 2012). Unfortunately, such large-scale high-quality training data are often unavailable in many real-world spatial or spatiotemporal problems in earth science and remote sensing (e.g., mapping the nationwide river streams for water resource management). Although extensive efforts have been made to reduce the reliance on labeled data (e.g., semi-supervised or unsupervised learning, few-shot learning), the complex nature of geographic data such as spatial heterogeneity still requires sufficient training labels when transferring a pre-trained model from one region to another. On the other hand, it is often much easier to collect lower-quality training labels with imperfect alignment with earth imagery pixels (e.g., through interpreting coarse imagery by non-expert volunteers). However, directly training a deep neural network on imperfect labels with geometric annotation errors could significantly impact model performance. Existing research that overcomes imperfect training labels either focuses on errors in label class semantics or characterizes label location errors at the pixel level. These methods do not fully incorporate the geometric properties of label location errors in the vector representation. To fill the gap, this article proposes a weakly supervised learning framework to simultaneously update deep learning model parameters and infer hidden true vector label locations. Specifically, we model label location errors in the vector representation to partially reserve geometric properties (e.g., spatial contiguity within line segments). Evaluations on real-world datasets in the National Hydrography Dataset (NHD) refinement application illustrate that the proposed framework outperforms baseline methods in classification accuracy.
Throughout their range, Brook Trout (Salvelinus fontinalis) occupy thousands of disjunct drainages with varying levels of disturbance, which presents substantial challenges for conservation. Within the southern Appalachian Mountains, fragmentation and genetic drift have been identified as key threats to the genetic diversity of the Brook Trout populations. In addition, extensive historic stocking of domestic lineages of Brook Trout to augment fisheries may have eroded endemic diversity and impacted locally adapted populations. We used 12 microsatellite loci to describe patterns of genetic diversity within 108 populations of wild Brook Trout from Tennessee and used linear models to explore the impacts of land use, drainage area, and hatchery stockings on metrics of genetic diversity, effective population size, and hatchery introgression. We found levels of within-population diversity varied widely, although many populations showed very limited diversity. The extent of hatchery introgression also varied across the landscape, with some populations showing high affinity to hatchery lineages and others appearing to retain their endemic character. However, we found relatively weak relationships between genetic metrics and landscape characteristics, suggesting that contemporary landscape variables are not strongly related to observed patterns of genetic diversity. We consider this result to reflect both the complex history of these populations and the challenges associated with accurately defining drainages for each population. Our study highlights the importance of genetic data to guide management decisions, as complex processes interact to shape the genetic structure of populations and make it difficult to infer the status of unsampled populations.
The seismic potential of the Lesser Antilles megathrust remains poorly known, despite the potential hazard it poses to numerous island populations and its proximity to the Americas. As it has not produced any large earthquakes in the instrumental era, the megathrust is often assumed to be aseismic. However, historical records of great earthquakes in the 19th century and earlier, which were most likely megathrust ruptures, demonstrate that the subduction is not entirely aseismic. Recent occurrences of giant earthquakes in areas where such events were previously thought to be improbable have illustrated the importance of critically evaluating the seismic potential of other “low-hazard” subduction zones, such as the Lesser Antilles.
Using the method of coral microatoll paleogeodesy developed in Sumatra, we examine 20th-century vertical deformation on the forearc islands of the Lesser Antilles and model the underlying strain accumulation on the megathrust. Our data indicate that the eastern coasts of the forearc islands have been subsiding by up to ∼8 mm/yr relative to sites closer to the arc, suggesting that on the time scale of the 20th century, a portion of the megathrust just east of the forearc islands has been locked. Our findings are in contrast to recent models based on satellite geodesy that suggest little or no strain accumulation anywhere along the Lesser Antilles megathrust. This discrepancy is potentially explained by the different time scales of measurement, as recent studies elsewhere have indicated that interseismic coupling patterns may vary on decadal time scales and that century-scale or longer records are required to fully assess seismic potential. The accumulated strain we have detected will likely be released in future megathrust earthquakes, uplifting previously subsiding areas and potentially causing widespread damage from strong ground motion and tsunami waves.
Benthic diatom assemblages are known to be indicative of water quality but have yet to be widely adopted in biological assessments in the United States due to several limitations. Our goal was to address some of these limitations by developing regional multi-metric indices (MMIs) that are robust to inter-laboratory taxonomic inconsistency, adjusted for natural covariates, and sensitive to a wide range of anthropogenic stressors. We aggregated bioassessment data from two national-scale federal programs and used a data-driven analysis in which all-possible combinations of 2–7 metrics were compared for three measures of performance. After ranking the best-performing MMIs, we selected the final MMIs by evaluating stress-response relations in independent regional datasets of diatom samples paired with measures of several water-quality stressors, including herbicides and streamflow flashiness. Each regional MMI performed well at calibration sites and represented diverse aspects of the structure and function of diatom communities. Most metrics included in the best MMIs were modeled to account for natural variation including climate, topography, soil characteristics, lithology, and groundwater influence on streamflow. MMI performance improved with higher numbers of component metrics, but this effect diminished beyond six metrics. Component metrics of MMIs were associated with a broad suite of measured stressors in every region, including salinity, nutrients, herbicides, and streamflow flashiness. We provide a web-based software application that allows users in the conterminous United States to apply our MMIs to their own datasets and compare MMI scores from their sites to a broader regional context.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108513","usgsCitation":"Carlisle, D.M., Spaulding, S., Tyree, M., Schulte, N.O., Lee, S.S., Mitchell, R., and Pollard, A.A., 2022, A web-based tool for assessing the condition of benthic diatom assemblages in streams and rivers of the conterminous United States: Ecological Indicators, v. 135, 108512, 13 p., https://doi.org/10.1016/j.ecolind.2021.108513.","productDescription":"108512, 13 p.","ipdsId":"IP-123713","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":449280,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108513","text":"Publisher Index Page"},{"id":436017,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XD9398","text":"USGS data release","linkHelpText":"Data Release for: A Web-Based Tool for Assessing the Condition of Benthic Diatom Assemblages in Streams and Rivers of the Conterminous United States"},{"id":408213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"135","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":854301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":223186,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":854302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyree, Meredith","contributorId":207506,"corporation":false,"usgs":false,"family":"Tyree","given":"Meredith","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":854303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulte, Nicholas O. 0000-0001-6284-4987","orcid":"https://orcid.org/0000-0001-6284-4987","contributorId":290510,"corporation":false,"usgs":false,"family":"Schulte","given":"Nicholas","email":"","middleInitial":"O.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":854304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, Sylvia S","contributorId":245621,"corporation":false,"usgs":false,"family":"Lee","given":"Sylvia","email":"","middleInitial":"S","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":854305,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitchell, Richard M.","contributorId":215406,"corporation":false,"usgs":false,"family":"Mitchell","given":"Richard M.","affiliations":[{"id":39239,"text":"USEPA, Washington D.C.","active":true,"usgs":false}],"preferred":false,"id":854306,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pollard, Amina A.","contributorId":297613,"corporation":false,"usgs":false,"family":"Pollard","given":"Amina","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":854307,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}