Prioritizing restoration opportunities effectively across entire riverscape networks (i.e., riverine landscape including floodplain and stream channel networks) can be difficult when relying on in-channel, reach-scale monitoring data, or watershed-level summaries that fail to capture riverscape heterogeneity and the information necessary to implement restoration actions. Leveraging remote sensing and geospatial tools to develop spatially continuous information across nested hierarchical scales may support increased understanding of local riverscape reaches in their broader network context. Using riparian (vegetation) and geomorphic (elevation) indicators to assess status of riverscape health, along with a measure of restoration capacity (valley bottom area), could be adapted to fit specific management goals related to riverscape restoration. Frameworks using remotely sensed vegetation and elevation data to prioritize restoration continuously across riverscapes at restoration-relevant, reach-scales may uphold the ecosystem services provided by riverscapes. By incorporating local knowledge and identifying caveats for using these datasets, continuous inferences can be applied at network scales (watershed to regional extent and reach-scale resolution) to prioritize restoration over a wide variety of ecoregions.
","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1716","usgsCitation":"Glassic, H.C., McGwire, K.C., Macfarlane, W., Rasmussen, C., Bouwes, N., Wheaton, J.M., and Al-Chokhachy, R., 2024, From pixels to riverscapes: How remote sensing and geospatial tools can prioritize riverscape restoration at multiple scales: WIREs Water, v. 11, no. 3, e1716, 22 p., https://doi.org/10.1002/wat2.1716.","productDescription":"e1716, 22 p.","ipdsId":"IP-154971","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":440545,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1716","text":"Publisher Index Page"},{"id":433404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Reese River, Upper Humboldt River, West Walker River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.28783058394662,\n 38.09843600904033\n ],\n [\n -114.17949392211462,\n 40.01850103667016\n ],\n [\n -114.21927949998788,\n 41.75225521374173\n ],\n [\n -117.26200493565987,\n 41.87323893635414\n ],\n [\n -120.03969790583245,\n 38.533308782806046\n ],\n [\n -119.28783058394662,\n 38.09843600904033\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glassic, Hayley Corrine 0000-0001-6839-1026","orcid":"https://orcid.org/0000-0001-6839-1026","contributorId":305858,"corporation":false,"usgs":true,"family":"Glassic","given":"Hayley","email":"","middleInitial":"Corrine","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGwire, Kenneth C.","contributorId":140699,"corporation":false,"usgs":false,"family":"McGwire","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":911985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macfarlane, William W.","contributorId":337429,"corporation":false,"usgs":false,"family":"Macfarlane","given":"William W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasmussen, Cashe","contributorId":305859,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Cashe","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouwes, Nicolaas","contributorId":305860,"corporation":false,"usgs":false,"family":"Bouwes","given":"Nicolaas","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911988,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wheaton, Joseph M.","contributorId":343789,"corporation":false,"usgs":false,"family":"Wheaton","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":911989,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":222450,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":911990,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261103,"text":"70261103 - 2024 - Ohi'a lehua (Metrosideros polymorpha): A most resilient and persistent foundation species in Hawaiian forests","interactions":[],"lastModifiedDate":"2024-11-22T15:24:54.85348","indexId":"70261103","displayToPublicDate":"2024-02-01T08:17:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2990,"text":"Pacific Science","active":true,"publicationSubtype":{"id":10}},"title":"Ohi'a lehua (Metrosideros polymorpha): A most resilient and persistent foundation species in Hawaiian forests","docAbstract":"Metrosideros polymorpha (‘ōhi‘a, ‘ōhi‘a lehua) is an important foundation species in Hawaiian forest habitats. The genus originated in New Zealand and was dispersed to the Hawaiian archipelago approximately 3.9 million years ago. It evolved into five distinct endemic species and one of these, Metrosideros polymorpha, further differentiated into eight varieties across what are now the main Hawaiian Islands. ‘Ōhi‘a is a tree that has great significance in indigenous Hawaiian culture. It is considered a physical manifestation of several principal Hawaiian deities, and serves a broad range of uses in Hawaiian material culture. It occupies a wide diversity of habitats, extending from sea level to over 2,200 m elevation, occupying habitats that range from extremely wet to dry rainfall zones. It is the dominant or co-dominant tree species in wet and mesic forests and is also one of the first woody species to become established on young lava flows. Although ‘ōhi‘a is a dominant forest tree it also exhibits many characteristics of a pioneer species. ‘Ōhi‘a provides the matrix for a wide diversity of endemic plants and animals found in these habitats and functions as the primary vegetation cover on native Hawaiian watersheds, facilitating groundwater recharge and regulating surface runoff. ‘Ōhi‘a has shown remarkable resilience by recolonizing forests that were opened up by disturbance, such as the widespread ‘ōhi‘a canopy dieback that occurred on East Maui in the 1900s and on the east side of the Island of Hawai‘i in the 1970s. Several human-related conditions threaten the continued stability of Hawaii’s native ecosystems, including invasive plants, plant diseases, introduced animals, and changing climate. The research and conservation legacy of Dr. Dieter Mueller-Dombois helped to expand our knowledge of the ecology and importance of ‘ōhi‘a forests, and to increase awareness and appreciation of the remarkable Hawaiian ecosystems that are unique to the world.
","language":"English","publisher":"BioOne","doi":"10.2984/77.2.4","usgsCitation":"Jacobi, J.D., Boehmer, H.J., Fortini, L., Gon III, S., Mertelmeyer, L., and Price, J., 2024, Ohi'a lehua (Metrosideros polymorpha): A most resilient and persistent foundation species in Hawaiian forests: Pacific Science, v. 77, no. 2-3, p. 177-186, https://doi.org/10.2984/77.2.4.","productDescription":"10 p.","startPage":"177","endPage":"186","ipdsId":"IP-154260","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":464438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-155.778234,20.245743],[-155.772734,20.245409],[-155.746893,20.232325],[-155.737004,20.222773],[-155.735822,20.212417],[-155.732704,20.205392],[-155.653966,20.16736],[-155.630382,20.146916],[-155.624565,20.145911],[-155.607797,20.137987],[-155.600909,20.126573],[-155.598033,20.124539],[-155.590923,20.122497],[-155.58168,20.123617],[-155.568368,20.130545],[-155.558933,20.13157],[-155.523661,20.120028],[-155.516795,20.11523],[-155.502561,20.114155],[-155.468211,20.104296],[-155.443957,20.095318],[-155.405459,20.078772],[-155.4024,20.075541],[-155.387578,20.067119],[-155.33021,20.038517],[-155.29548,20.024438],[-155.282629,20.021969],[-155.270316,20.014525],[-155.240933,19.990173],[-155.204486,19.969438],[-155.194593,19.958368],[-155.179939,19.949372],[-155.149215,19.922872],[-155.144394,19.920523],[-155.131235,19.906801],[-155.124618,19.897288],[-155.12175,19.886099],[-155.107541,19.872467],[-155.098716,19.867811],[-155.095032,19.867882],[-155.086341,19.855399],[-155.084357,19.849736],[-155.085674,19.838584],[-155.088979,19.826656],[-155.094414,19.81491],[-155.09207,19.799409],[-155.091216,19.776368],[-155.093517,19.771832],[-155.093387,19.737751],[-155.087118,19.728013],[-155.079426,19.726193],[-155.063972,19.728917],[-155.045382,19.739824],[-155.006423,19.739286],[-154.997278,19.72858],[-154.987168,19.708524],[-154.981102,19.690687],[-154.984718,19.672161],[-154.983778,19.641647],[-154.974342,19.633201],[-154.963933,19.627605],[-154.950359,19.626461],[-154.947874,19.62425],[-154.947718,19.621947],[-154.951014,19.613614],[-154.947106,19.604856],[-154.93394,19.597505],[-154.928205,19.592702],[-154.924422,19.586553],[-154.903542,19.570622],[-154.875,19.556797],[-154.852618,19.549172],[-154.837384,19.538354],[-154.826732,19.537626],[-154.814417,19.53009],[-154.809561,19.522377],[-154.809379,19.519086],[-154.822968,19.48129],[-154.838545,19.463642],[-154.86854,19.438126],[-154.887817,19.426425],[-154.928772,19.397646],[-154.944185,19.381852],[-154.964619,19.365646],[-154.980861,19.349291],[-155.020537,19.331317],[-155.061729,19.316636],[-155.113272,19.290613],[-155.1337,19.276099],[-155.159635,19.268375],[-155.172413,19.26906],[-155.187427,19.266156],[-155.19626,19.261295],[-155.205892,19.260907],[-155.243961,19.271313],[-155.264619,19.274213],[-155.296761,19.266289],[-155.303808,19.261835],[-155.31337,19.250698],[-155.341268,19.234039],[-155.349148,19.217756],[-155.360631,19.20893],[-155.378638,19.202435],[-155.390701,19.201171],[-155.417369,19.187858],[-155.427093,19.179546],[-155.432519,19.170623],[-155.453516,19.151952],[-155.465663,19.146964],[-155.505281,19.137908],[-155.51474,19.132501],[-155.51214,19.128174],[-155.512137,19.124296],[-155.519652,19.117025],[-155.526136,19.115889],[-155.528902,19.11371],[-155.544806,19.091059],[-155.551129,19.08878],[-155.557817,19.08213],[-155.555326,19.069377],[-155.555177,19.053932],[-155.557371,19.046565],[-155.566446,19.032531],[-155.576599,19.027412],[-155.581903,19.02224],[-155.596032,18.998833],[-155.596521,18.980654],[-155.601866,18.971572],[-155.613966,18.970399],[-155.625256,18.961951],[-155.625,18.959934],[-155.638054,18.941723],[-155.658486,18.924835],[-155.672005,18.917466],[-155.681825,18.918694],[-155.687716,18.923358],[-155.690171,18.932195],[-155.693117,18.940542],[-155.726043,18.969437],[-155.763598,18.981837],[-155.806109,19.013967],[-155.853943,19.023762],[-155.88155,19.036644],[-155.884077,19.039266],[-155.886278,19.05576],[-155.903693,19.080777],[-155.908355,19.081138],[-155.921389,19.121183],[-155.917292,19.155963],[-155.903339,19.217792],[-155.90491,19.230147],[-155.902565,19.258427],[-155.895435,19.274639],[-155.890842,19.298905],[-155.887356,19.337101],[-155.888701,19.348031],[-155.898792,19.377984],[-155.913849,19.401107],[-155.909087,19.415455],[-155.921707,19.43055],[-155.924269,19.438794],[-155.925166,19.468081],[-155.922609,19.478611],[-155.924124,19.481406],[-155.930523,19.484921],[-155.935641,19.485628],[-155.936403,19.481905],[-155.939145,19.481577],[-155.95149,19.486649],[-155.952897,19.488805],[-155.953663,19.510003],[-155.960457,19.546612],[-155.962264,19.551779],[-155.965211,19.554745],[-155.96935,19.555963],[-155.970969,19.586328],[-155.978206,19.608159],[-155.997728,19.642816],[-156.028982,19.650098],[-156.032928,19.653905],[-156.034994,19.65936],[-156.033326,19.66923],[-156.027427,19.672154],[-156.029281,19.678908],[-156.036079,19.690252],[-156.04796,19.698938],[-156.051652,19.703649],[-156.052485,19.718667],[-156.064364,19.730766],[-156.05722,19.742536],[-156.052315,19.756836],[-156.049651,19.780452],[-156.021732,19.8022],[-156.006267,19.81758],[-155.982821,19.845651],[-155.976651,19.85053],[-155.964817,19.855183],[-155.949251,19.857034],[-155.945297,19.853443],[-155.940311,19.852305],[-155.925843,19.858928],[-155.926938,19.870221],[-155.92549,19.875],[-155.915662,19.887126],[-155.901987,19.912081],[-155.894099,19.923135],[-155.894474,19.926927],[-155.892533,19.932162],[-155.866919,19.954172],[-155.856588,19.968885],[-155.840708,19.976952],[-155.838692,19.975527],[-155.835312,19.976078],[-155.831948,19.982775],[-155.828965,19.995542],[-155.825473,20.025944],[-155.828182,20.035424],[-155.850385,20.062506],[-155.866931,20.078652],[-155.88419,20.10675],[-155.899149,20.145728],[-155.906035,20.205157],[-155.901452,20.235787],[-155.890663,20.25524],[-155.882631,20.263026],[-155.873921,20.267744],[-155.853293,20.271548],[-155.811459,20.26032],[-155.783242,20.246395],[-155.778234,20.245743]]],[[[-157.789581,21.438396],[-157.789734,21.437679],[-157.789276,21.435833],[-157.790543,21.434313],[-157.791718,21.434881],[-157.793045,21.43391],[-157.793167,21.43574],[-157.791565,21.43651],[-157.791779,21.437752],[-157.793289,21.437658],[-157.791779,21.438435],[-157.791092,21.438442],[-157.790741,21.43874],[-157.789581,21.438396]]],[[[-160.125,21.95909],[-160.122262,21.962881],[-160.112746,21.995245],[-160.09645,22.001489],[-160.072123,22.003334],[-160.058543,21.99638],[-160.051992,21.983681],[-160.052729,21.980321],[-160.056336,21.977939],[-160.060549,21.976729],[-160.063349,21.978354],[-160.065811,21.976562],[-160.078393,21.955153],[-160.085787,21.927295],[-160.080012,21.910808],[-160.079065,21.89608],[-160.098897,21.884711],[-160.124283,21.876789],[-160.147609,21.872814],[-160.16162,21.864746],[-160.174796,21.846923],[-160.189782,21.82245],[-160.205211,21.789053],[-160.200427,21.786479],[-160.205851,21.779518],[-160.218044,21.783755],[-160.23478,21.795418],[-160.24961,21.815145],[-160.244943,21.848943],[-160.231028,21.886263],[-160.228965,21.889117],[-160.21383,21.899193],[-160.205528,21.907507],[-160.202716,21.912422],[-160.190158,21.923592],[-160.167471,21.932863],[-160.13705,21.948632],[-160.127302,21.955508],[-160.125,21.95909]]],[[[-159.431707,22.220015],[-159.40732,22.230555],[-159.388119,22.223252],[-159.385977,22.220009],[-159.367563,22.214906],[-159.359842,22.214831],[-159.357227,22.217744],[-159.353795,22.217669],[-159.339964,22.208519],[-159.315613,22.186817],[-159.308855,22.155555],[-159.297808,22.149748],[-159.295875,22.144547],[-159.295271,22.13039],[-159.297143,22.113815],[-159.317451,22.080944],[-159.321667,22.063411],[-159.324775,22.05867],[-159.333267,22.054639],[-159.337996,22.046575],[-159.341401,22.028978],[-159.333224,21.973005],[-159.333109,21.964176],[-159.334714,21.961099],[-159.350828,21.950817],[-159.356613,21.939546],[-159.382349,21.924479],[-159.408284,21.897781],[-159.425862,21.884527],[-159.446599,21.871647],[-159.471962,21.88292],[-159.490914,21.888898],[-159.517973,21.890996],[-159.555415,21.891355],[-159.574991,21.896585],[-159.577784,21.900486],[-159.584272,21.899038],[-159.610241,21.898356],[-159.637849,21.917166],[-159.648132,21.93297],[-159.671872,21.957038],[-159.681493,21.960054],[-159.705255,21.963427],[-159.72014,21.970789],[-159.758218,21.980694],[-159.765735,21.986593],[-159.788139,22.018411],[-159.790932,22.031177],[-159.786543,22.06369],[-159.780096,22.072567],[-159.748159,22.100388],[-159.741223,22.115666],[-159.733457,22.142756],[-159.726043,22.152171],[-159.699978,22.165252],[-159.66984,22.170782],[-159.608794,22.207878],[-159.591596,22.219456],[-159.583965,22.22668],[-159.559643,22.229185],[-159.554166,22.228212],[-159.548594,22.226263],[-159.54115,22.216764],[-159.534594,22.219403],[-159.523769,22.217602],[-159.51941,22.215646],[-159.518348,22.211182],[-159.515574,22.208008],[-159.507811,22.205987],[-159.501055,22.211064],[-159.500821,22.225538],[-159.488558,22.23317],[-159.480158,22.232715],[-159.467007,22.226529],[-159.45619,22.228811],[-159.441809,22.226321],[-159.431707,22.220015]]],[[[-157.014553,21.185503],[-156.999108,21.182221],[-156.991318,21.18551],[-156.987768,21.18935],[-156.982343,21.207798],[-156.984464,21.210063],[-156.984032,21.212198],[-156.974002,21.218503],[-156.969064,21.217018],[-156.962847,21.212131],[-156.951654,21.191662],[-156.950808,21.182636],[-156.946159,21.175963],[-156.918248,21.168279],[-156.903466,21.16421],[-156.898174,21.16594],[-156.89613,21.169561],[-156.896537,21.172208],[-156.867944,21.16452],[-156.841592,21.167926],[-156.821944,21.174693],[-156.771495,21.180053],[-156.742231,21.176214],[-156.738341,21.17202],[-156.736648,21.16188],[-156.719386,21.163911],[-156.712696,21.161547],[-156.714158,21.152238],[-156.726033,21.13236],[-156.748932,21.1086],[-156.775995,21.089751],[-156.790815,21.081686],[-156.794136,21.075796],[-156.835351,21.06336],[-156.865795,21.057801],[-156.877137,21.0493],[-156.891946,21.051831],[-156.89517,21.055771],[-156.953719,21.067761],[-157.00295,21.083282],[-157.02617,21.089015],[-157.032045,21.091094],[-157.037667,21.097864],[-157.079696,21.105835],[-157.095373,21.10636],[-157.125,21.1026],[-157.143483,21.096632],[-157.254061,21.090601],[-157.298054,21.096917],[-157.313343,21.105755],[-157.299187,21.132488],[-157.299471,21.135972],[-157.293774,21.146127],[-157.284346,21.157755],[-157.276474,21.163175],[-157.274504,21.162762],[-157.259911,21.174875],[-157.254709,21.181376],[-157.251007,21.190952],[-157.25026,21.207739],[-157.256935,21.215665],[-157.261457,21.217661],[-157.263163,21.220873],[-157.26069,21.225684],[-157.257085,21.227268],[-157.241534,21.220969],[-157.226445,21.220185],[-157.212082,21.221848],[-157.202125,21.219298],[-157.192439,21.207644],[-157.185553,21.205602],[-157.157103,21.200706],[-157.148125,21.200745],[-157.144627,21.202555],[-157.128207,21.201488],[-157.113438,21.197375],[-157.097971,21.198012],[-157.064264,21.189076],[-157.053053,21.188754],[-157.047757,21.190739],[-157.039987,21.190909],[-157.014553,21.185503]]],[[[-156.544169,20.522802],[-156.550016,20.520273],[-156.559994,20.521892],[-156.586238,20.511711],[-156.603844,20.524372],[-156.631143,20.514943],[-156.642347,20.508285],[-156.647464,20.512017],[-156.668809,20.504738],[-156.682939,20.506775],[-156.703673,20.527237],[-156.702265,20.532451],[-156.696662,20.541646],[-156.6801,20.557021],[-156.651567,20.565574],[-156.614598,20.587109],[-156.610734,20.59377],[-156.576871,20.60657],[-156.56714,20.604895],[-156.553604,20.594729],[-156.543034,20.580115],[-156.542808,20.573674],[-156.548909,20.56859],[-156.556021,20.542657],[-156.553018,20.539382],[-156.540189,20.534741],[-156.539643,20.527644],[-156.544169,20.522802]]],[[[-156.612012,21.02477],[-156.612065,21.027273],[-156.606238,21.034371],[-156.592256,21.03288],[-156.580448,21.020172],[-156.562773,21.016167],[-156.549813,21.004939],[-156.546291,21.005082],[-156.528246,20.967757],[-156.518707,20.954662],[-156.512226,20.95128],[-156.510391,20.940358],[-156.507913,20.937886],[-156.49948,20.934577],[-156.495883,20.928005],[-156.493263,20.916011],[-156.481055,20.898199],[-156.474796,20.894546],[-156.422668,20.911631],[-156.386045,20.919563],[-156.374297,20.927616],[-156.370729,20.932669],[-156.352649,20.941414],[-156.345655,20.941596],[-156.342365,20.938737],[-156.332817,20.94645],[-156.324578,20.950184],[-156.307198,20.942739],[-156.286332,20.947701],[-156.275116,20.937361],[-156.263107,20.940888],[-156.242555,20.937838],[-156.230159,20.931936],[-156.230089,20.917864],[-156.226757,20.916677],[-156.222062,20.918309],[-156.217953,20.916573],[-156.216341,20.907035],[-156.173103,20.876926],[-156.170458,20.874605],[-156.166746,20.865646],[-156.132669,20.861369],[-156.129381,20.847513],[-156.115735,20.827301],[-156.100123,20.828502],[-156.090291,20.831872],[-156.059788,20.81054],[-156.033287,20.808246],[-156.003532,20.795545],[-156.002947,20.789418],[-155.987944,20.776552],[-155.984587,20.767496],[-155.986851,20.758577],[-155.985413,20.744245],[-155.987216,20.722717],[-155.991534,20.713654],[-156.00187,20.698064],[-156.01415,20.685681],[-156.020044,20.686857],[-156.030702,20.682452],[-156.040341,20.672719],[-156.043786,20.664902],[-156.053385,20.65432],[-156.059753,20.652044],[-156.081472,20.654387],[-156.089365,20.648519],[-156.120985,20.633685],[-156.129898,20.627523],[-156.142665,20.623605],[-156.144588,20.624032],[-156.148085,20.629067],[-156.156772,20.629639],[-156.169732,20.627358],[-156.173393,20.6241],[-156.184556,20.629719],[-156.192938,20.631769],[-156.210258,20.628518],[-156.225338,20.62294],[-156.236145,20.61595],[-156.265921,20.601629],[-156.284391,20.596488],[-156.288037,20.59203],[-156.293454,20.588783],[-156.302692,20.586199],[-156.322944,20.588273],[-156.351716,20.58697],[-156.359634,20.581977],[-156.370725,20.57876],[-156.377633,20.578427],[-156.415313,20.586099],[-156.417523,20.589728],[-156.415746,20.594044],[-156.417799,20.598682],[-156.423141,20.602079],[-156.427708,20.598873],[-156.431872,20.598143],[-156.438385,20.601337],[-156.444242,20.607941],[-156.442884,20.613842],[-156.450651,20.642212],[-156.445894,20.64927],[-156.443673,20.656018],[-156.448656,20.704739],[-156.451038,20.725469],[-156.452895,20.731287],[-156.458438,20.736676],[-156.462242,20.753952],[-156.462058,20.772571],[-156.464043,20.781667],[-156.473562,20.790756],[-156.489496,20.798339],[-156.501688,20.799933],[-156.506026,20.799463],[-156.515994,20.794234],[-156.525215,20.780821],[-156.537752,20.778408],[-156.631794,20.82124],[-156.678634,20.870541],[-156.688969,20.888673],[-156.687804,20.89072],[-156.688132,20.906325],[-156.691334,20.91244],[-156.697418,20.916368],[-156.69989,20.920629],[-156.69411,20.952708],[-156.680905,20.980262],[-156.665514,21.007054],[-156.652419,21.008994],[-156.645966,21.014416],[-156.642592,21.019936],[-156.644167,21.022312],[-156.642809,21.027583],[-156.619581,21.027793],[-156.612012,21.02477]]],[[[-157.010001,20.929757],[-156.989813,20.932127],[-156.971604,20.926254],[-156.937529,20.925274],[-156.91845,20.922546],[-156.897169,20.915395],[-156.837047,20.863575],[-156.825237,20.850731],[-156.809576,20.826036],[-156.808469,20.820396],[-156.809463,20.809169],[-156.817427,20.794606],[-156.838321,20.764575],[-156.846413,20.760201],[-156.851481,20.760069],[-156.869753,20.754701],[-156.890295,20.744855],[-156.909081,20.739533],[-156.949009,20.738997],[-156.96789,20.73508],[-156.984747,20.756677],[-156.994001,20.786671],[-156.988933,20.815496],[-156.991834,20.826603],[-157.006243,20.849603],[-157.010911,20.854476],[-157.054552,20.877219],[-157.059663,20.884634],[-157.061128,20.890635],[-157.062511,20.904385],[-157.05913,20.913407],[-157.035789,20.927078],[-157.025626,20.929528],[-157.010001,20.929757]]],[[[-158.044485,21.306011],[-158.0883,21.2988],[-158.1033,21.2979],[-158.1127,21.3019],[-158.1211,21.3169],[-158.1225,21.3224],[-158.111949,21.326622],[-158.114196,21.331123],[-158.119427,21.334594],[-158.125459,21.330264],[-158.13324,21.359207],[-158.1403,21.3738],[-158.149719,21.385208],[-158.161743,21.396282],[-158.1792,21.4043],[-158.181274,21.409626],[-158.181,21.420868],[-158.182648,21.430073],[-158.192352,21.44804],[-158.205383,21.459793],[-158.219446,21.46978],[-158.233,21.4876],[-158.231171,21.523857],[-158.23175,21.533035],[-158.234314,21.540058],[-158.250671,21.557373],[-158.27951,21.575794],[-158.277679,21.578789],[-158.254425,21.582684],[-158.190704,21.585892],[-158.17,21.5823],[-158.12561,21.586739],[-158.10672,21.596577],[-158.106689,21.603024],[-158.1095,21.6057],[-158.108185,21.607487],[-158.079895,21.628101],[-158.0668,21.6437],[-158.066711,21.65234],[-158.0639,21.6584],[-158.0372,21.6843],[-158.018127,21.699955],[-157.9923,21.708],[-157.98703,21.712494],[-157.968628,21.712704],[-157.947174,21.689568],[-157.939,21.669],[-157.9301,21.6552],[-157.924591,21.651183],[-157.9228,21.6361],[-157.9238,21.6293],[-157.910797,21.611183],[-157.900574,21.605885],[-157.87735,21.575277],[-157.878601,21.560181],[-157.872528,21.557568],[-157.8669,21.5637],[-157.85614,21.560661],[-157.85257,21.557514],[-157.836945,21.529945],[-157.837372,21.512085],[-157.849579,21.509598],[-157.852625,21.499971],[-157.84549,21.466747],[-157.84099,21.459483],[-157.82489,21.455379],[-157.8163,21.4502],[-157.8139,21.4403],[-157.8059,21.4301],[-157.786513,21.415633],[-157.779846,21.417309],[-157.774455,21.421352],[-157.772209,21.431236],[-157.774905,21.453698],[-157.772209,21.457741],[-157.764572,21.461335],[-157.754239,21.461335],[-157.737617,21.459089],[-157.731777,21.455944],[-157.731328,21.444713],[-157.73582,21.438424],[-157.740762,21.424048],[-157.741211,21.414614],[-157.7386,21.4043],[-157.730191,21.401871],[-157.728221,21.402104],[-157.726421,21.402845],[-157.724324,21.403311],[-157.723794,21.40329],[-157.723286,21.403227],[-157.722735,21.403121],[-157.722544,21.403036],[-157.721845,21.401596],[-157.721083,21.399541],[-157.7189,21.3961],[-157.7089,21.3833],[-157.7087,21.3793],[-157.7126,21.3689],[-157.7106,21.3585],[-157.7088,21.3534],[-157.6971,21.3364],[-157.6938,21.3329],[-157.6619,21.3131],[-157.6518,21.3139],[-157.652629,21.308709],[-157.6537,21.302],[-157.6946,21.2739],[-157.6944,21.2665],[-157.7001,21.264],[-157.7097,21.2621],[-157.7139,21.2638],[-157.7142,21.2665],[-157.7114,21.272],[-157.7122,21.2814],[-157.7143,21.2845],[-157.7213,21.2869],[-157.7572,21.278],[-157.765,21.2789],[-157.7782,21.2735],[-157.7931,21.2604],[-157.8096,21.2577],[-157.8211,21.2606],[-157.8241,21.2646],[-157.8253,21.2714],[-157.8319,21.2795],[-157.8457,21.29],[-157.89,21.3065],[-157.894518,21.319632],[-157.898969,21.327391],[-157.90482,21.329172],[-157.918939,21.318615],[-157.917921,21.313781],[-157.913469,21.310983],[-157.910925,21.305768],[-157.952263,21.306531],[-157.950736,21.312509],[-157.951881,21.318742],[-157.967971,21.327986],[-157.973334,21.327426],[-157.989424,21.317984],[-158.0245,21.3093],[-158.044485,21.306011]]]]},\"properties\":{\"name\":\"Hawaii\",\"nation\":\"USA \"}}]}","volume":"77","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":919264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boehmer, Hans Juergen","contributorId":207895,"corporation":false,"usgs":false,"family":"Boehmer","given":"Hans","email":"","middleInitial":"Juergen","affiliations":[{"id":37652,"text":"School of Geography, University of the South Pacific, Suva, Fiji","active":true,"usgs":false}],"preferred":false,"id":919265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":919266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gon III, Samuel M. ‘Ohukaniʻōhiʻa","contributorId":346476,"corporation":false,"usgs":false,"family":"Gon III","given":"Samuel M. ‘Ohukaniʻōhiʻa","affiliations":[{"id":82869,"text":"The Nature Conservancy of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":919267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mertelmeyer, Linda","contributorId":214407,"corporation":false,"usgs":false,"family":"Mertelmeyer","given":"Linda","email":"","affiliations":[{"id":39035,"text":"Technical University of Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":919268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Price, Jonathan","contributorId":187456,"corporation":false,"usgs":false,"family":"Price","given":"Jonathan","affiliations":[],"preferred":false,"id":919269,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238327,"text":"70238327 - 2024 - Advanced quantitative precipitation information: Improving monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay area","interactions":[],"lastModifiedDate":"2024-02-07T16:30:16.692431","indexId":"70238327","displayToPublicDate":"2024-02-01T07:02:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12962,"text":"Bulletin of the American Meteorological Society (BAMS)","active":true,"publicationSubtype":{"id":10}},"title":"Advanced quantitative precipitation information: Improving monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay area","docAbstract":"Advanced Quantitative Precipitation Information (AQPI) is a synergistic project that combines observations and models to improve monitoring and forecasts of precipitation, streamflow, and coastal flooding in the San Francisco Bay Area. As an experimental system, AQPI leverages more than a decade of research, innovation, and implementation of a statewide, state-of-the-art network of observations, and development of the next generation of weather and coastal forecast models. AQPI was developed as a prototype in response to requests from the water management community for improved information on precipitation, riverine, and coastal conditions to inform their decision-making processes. Observation of precipitation in the complex Bay Area landscape of California’s coastal mountain ranges is known to be a challenging problem. But, with new advanced radar network techniques, AQPI is helping fill an important observational gap for this highly populated and vulnerable metropolitan area. The prototype AQPI system consists of improved weather radar data for precipitation estimation; additional surface measurements of precipitation, streamflow, and soil moisture; and a suite of integrated forecast modeling systems to improve situational awareness about current and future water conditions from sky to sea. Together these tools will help improve emergency preparedness and public response to prevent loss of life and destruction of property during extreme storms accompanied by heavy precipitation and high coastal water levels—especially high-moisture laden atmospheric rivers. The Bay Area AQPI system could potentially be replicated in other urban regions in California, the United States, and worldwide.
Agriculture consumes the largest share of freshwater globally; therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. In this study, a framework incorporating the Budyko model was used to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high-confidence cropland map (HCCM). The HCCM was generated for calibration and validation of the crop partitioning framework as an alternative to individual cropland masks which exhibit high disagreement. The accuracy of the framework in partitioning the HCCM was evaluated using an independent validation dataset, yielding an overall accuracy rate of 73 %. The findings of this study indicate that out of the total area covered by the HCCM (2.36 million km2), about 461,000 km2 (19 %) is irrigated cropland. The partitioning framework was applied on eight landcover products, and the extent of irrigated areas varied between 19 % and 30 % of the total cropland area. The framework demonstrated high precision and specificity scores, indicating its effectiveness in correctly identifying irrigated areas while minimizing the misclassification of rainfed areas as irrigated. This study provides an enhanced understanding of rainfed and irrigation patterns across Africa, supporting efforts towards achieving sustainable and resilient agricultural systems. Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.
The Mississippi Alluvial Plain (MAP) in the United States (US).
Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km3/year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately.
We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.
There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.
Geographical distributions of waterfowl exhibit annual variation in response to spatiotemporal variation in weather conditions, habitat availability, and other factors. Continuing changes in climate and land use could lead to persistent shifts of waterfowl distributions, potentially causing a mismatch with habitat conservation planning, wetland restoration efforts, and harvest management decisions informed by historical distributions. We used band recoveries and harvest records (i.e., hunter-harvested wings) from the United States Fish and Wildlife Service Waterfowl Parts Collection Survey as indices of duck distribution in autumn and winter, and quantified intra-annual, interannual, and interspecific variation in their geographic distributions across 6 decades (1960–2019) for 15 duck species in the Central and Mississippi flyways in North America. Specifically, we tested for annual and decadal shifts in mean latitude and longitude of recoveries for each month (Oct–Jan) by species and taxonomic guild (i.e., dabbling, diving ducks). Overall, species varied in the extent, timing, and sometimes direction, of distributional change in recoveries. From 1960–2019, mean recovery locations for dabbling ducks shifted south 105–296 km in October and 27 km in November (wings only), whereas mean latitudes shifted north 144–234 km in December and 186–301 km in January. Mean recovery locations for diving ducks shifted north 162 km in October (wings only), 84–173 km in December, and 66–120 km in January, but shifted 99–512 km south in November. Shifts in longitude were less consistent between guilds and data types. Finally, distributional change rarely accelerated during recent decades, except for southward shifts of band recoveries of diving ducks in November and northward shifts of band and wing recoveries of dabbling ducks in January. Although anecdotal accounts of large-scale northward shifts in duck distributions are prolific in the land management and hunting communities, our data demonstrate more subtle shifts that vary considerably by species and month. Observed changes in recovery distributions could necessitate changes in timing of habitat management practices throughout the Central and Mississippi flyways and may result in fewer hunting and recreational opportunities for some species in southern states. Quantifying patterns of historical change is a necessary first step to understanding temporal and interspecific variation in waterfowl distributions, which will help with landscape-scale conservation and management efforts in the future and enable effective communication to core constituencies regarding ongoing changes and their implications for recreational engagement.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22521","usgsCitation":"Verheijen, B., Webb, E.B., Brasher, M., and Hagy, H.M., 2024, Spatiotemporal dynamics of duck harvest distributions in the Central and Mississippi flyways, 1960–2019: The Journal of Wildlife Management, v. 88, no. 2, e22521, 18 p., https://doi.org/10.1002/jwmg.22521.","productDescription":"e22521, 18 p.","ipdsId":"IP-151486","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.31640625,\n 28.92163128242129\n ],\n [\n -85.4296875,\n 28.92163128242129\n ],\n [\n -85.4296875,\n 51.069016659603896\n ],\n [\n -99.31640625,\n 51.069016659603896\n ],\n [\n -99.31640625,\n 28.92163128242129\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Verheijen, Bram H. F.","contributorId":274514,"corporation":false,"usgs":false,"family":"Verheijen","given":"Bram H. F.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":907872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907873,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brasher, Michael G.","contributorId":338627,"corporation":false,"usgs":false,"family":"Brasher","given":"Michael G.","affiliations":[{"id":81180,"text":"Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":907874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":907875,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251195,"text":"sir20235137 - 2024 - Isolation and identification of microcystin-degrading bacteria in Lake Erie source waters and drinking-water plant sand filters","interactions":[],"lastModifiedDate":"2026-01-30T19:40:43.248539","indexId":"sir20235137","displayToPublicDate":"2024-01-31T15:40:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5137","displayTitle":"Isolation and Identification of Microcystin-Degrading Bacteria in Lake Erie Source Waters and Drinking-Water Plant Sand Filters","title":"Isolation and identification of microcystin-degrading bacteria in Lake Erie source waters and drinking-water plant sand filters","docAbstract":"The increasing prevalence of cyanobacterial harmful algal blooms and the toxins they produce is a global water-quality issue. In the Western Basin of Lake Erie, high microcystin concentrations have led to water-quality advisories, process adjustments for treating drinking water, and increased water-quality monitoring. Biodegradation is an environmentally friendly and cost-effective way to reduce concentrations of microcystins in drinking water; however, few studies have been done to determine biodegradation potential of bacteria indigenous to the Lake Erie watershed. As part of a cooperative program between the U.S. Geological Survey and the U.S. Environmental Protection Agency, this study aimed to identify naturally occurring microcystin-degrading bacteria in source waters and in the sand filters of drinking-water treatment plants in the Western Basin of Lake Erie. Biodegradation of microcystin-LR was found to occur in microcosms developed with three different Lake Erie-area sources—Lake Erie water, water from storage reservoirs supplied by inland streams, and water or solid medium from sand/anthracite filters at drinking-water plants. In microplates with microcystin-LR as the sole carbon source, 10 isolates exhibited cellular respiration and were, therefore, identified as promising microcystin biodegraders; 4 of those isolates subsequently were found to have potential to form biofilms. The 10 promising isolates along with 14 additional isolates from the microcosms were identified by 16S ribosomal RNA sequencing: 15 isolates were γ-proteobacteria, 6 isolates were β-proteobacteria, 1 isolate was an α-proteobacterium, 1 isolate was a flavobacterium in the phylum Bacteroidetes, and 1 isolate was in the phylum Actinobacteria. Isolates were screened for possession of the mlrA gene (found to encode for the protein responsible for cleaving the cyclic structure of microcystin), and results indicate that, for Lake Erie source waters and elsewhere, more work would be required to identify microcystin-biodegradation pathways and products and to confirm biodegradation rates in pure culture isolates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235137","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Francy, D.S., Cicale, J.R., Stelzer, E.A., Reano, D.C., and Ecker, C.D., 2024, Isolation and identification of microcystin-degrading bacteria in Lake Erie source waters and drinking-water plant sand filters: U.S. Geological Survey Scientific Investigations Report 2023–5137, 23 p., https://doi.org/10.3133/sir20235137","productDescription":"Report: vii, 23 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095884","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":499399,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115978.htm","linkFileType":{"id":5,"text":"html"}},{"id":425054,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DL080Y","text":"USGS data release","linkHelpText":"Microcosm experiment data of microcystin-degrading bacteria in Lake Erie source waters and drinking-water plants, 2015–18"},{"id":425053,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5137/images/"},{"id":425052,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5137/sir20235137.XML"},{"id":425051,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235137/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5137"},{"id":425050,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5137/sir20235137.pdf","text":"Report","size":"1.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5137"},{"id":425049,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5137/coverthb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.035308272771,\n 41.1710613373711\n ],\n [\n -78.41030827277076,\n 41.1710613373711\n ],\n [\n -78.41030827277076,\n 43.25385984825451\n ],\n [\n -84.035308272771,\n 43.25385984825451\n ],\n [\n -84.035308272771,\n 41.1710613373711\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd.
Indianapolis, IN 46278-1996
The widespread application of pesticides in agricultural and urban areas leads to their presence in surface waters. Presence of these biologically active chemicals in environmental waters potentially has adverse effects on nontarget organisms. To better understand the environmental fate of these contaminants, a robust method to capture chemicals with wide-ranging physicochemical properties has been developed. The method was developed by the U.S. Geological Survey’s Organic Chemistry Research Laboratory to monitor pesticides, pesticide degradates, and other agrochemicals in environmental surface waters throughout the country. The analysis involves a multiresidue method to determine 183 pesticides and pesticide degradates in filtered water samples and 178 pesticides and pesticide degradates in paired suspended sediment samples. After the filtration of whole water, contaminants are individually measured in the filtered water and the collected suspended sediment. Filtered water is extracted via solid-phase extraction, whereas suspended sediment is extracted using an ultrasonication, solid-liquid extraction. Samples are analyzed by liquid chromatography-tandem mass spectrometry using an electrospray ionization source in positive and negative modes and analyzed by gas chromatography-tandem mass spectrometry using an advanced electron ionization source in positive mode. Instrument parameters were optimized for the highest sensitivity, and at least two transitions (quantifier and qualifier) were monitored for each analyte.
Recoveries in test filtered water (n=9; 183 analytes) from the American River, California, and suspended sediment (n=9; 178 analytes) samples fortified at 15 nanograms per liter (ng/L) ranged from 70.1 to 121.0 and 71.1 to 117.0 percent in water and suspended sediment filter samples, respectively. Method detection limits of pesticides and pesticide degradates ranged from 0.5 to 10.6 ng/L in water and 0.7 to 11.8 ng/L in suspended sediment filters. Reporting limits were 1.1–21.1 ng/L and 1.5–23.7 ng/L in water and filter samples, respectively. The developed method is applied to surface-water samples for the analysis of pesticides, pesticide degradates, and other agrochemicals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm5A12","programNote":"Water Resources Mission Area—Water Availability and Use Science Program","usgsCitation":"Gross, M.S., Sanders, C.J., De Parsia, M.D., and Hladik, M.L., 2024, Methods of analysis—Determination of pesticides in filtered water and suspended sediment using liquid chromatography- and gas chromatography-tandem mass spectrometry: U.S. Geological Survey Techniques and Methods, book 5, chap. A12, 33 p., https://doi.org/10.3133/tm5A12.","productDescription":"Report: vi, 33 p.; Data Release","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-139193","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":425118,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8E544","text":"USGS Data Release","description":"Gross, M.S., Sanders, C.J., De Parsia, M.D., and Hladik, M.L., 2023, A multiresidue method for the analysis of pesticides in water using solid-phase extraction with gas and liquid chromatography-tandem mass spectrometry (ver. 2.0, April 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9J8E544.","linkHelpText":"A multiresidue method for the analysis of pesticides in water using solid-phase extraction with gas and liquid chromatography-tandem mass spectrometry (ver. 2.0, April 2023)"},{"id":425662,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm5A12/full"},{"id":425113,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/05/a12/tm5a12.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":425114,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/05/a12/tm5a12.xml"},{"id":425112,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/05/a12/covrthb.jpg"},{"id":425661,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/05/a12/images/"}],"contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Millions of small (< 10 ha) waterbodies embedded in grassland and agroecosystems in midcontinental North America provide breeding habitat to an estimated 50–80% of North America’s migratory ducks. Tens of millions of dollars are invested annually to conserve and enhance upland and wetland habitats for breeding ducks by prioritizing locations predicted to have high densities of breeding pairs under average precipitation conditions. An implicit assumption of this approach is that the distribution of breeding habitat remains relatively static. Climate change is an identified risk to this strategy. To assess this assumption and plan for potential forthcoming conditions, we estimated changes in potential breeding duck pairs under different climate scenarios by combining results of 1) a mechanistic hydrology model that simulates ecosystem processes for a subset of wetlands distributed across the U.S. Prairie Pothole Region (USPPR); 2) four downscaled climate model projections at mid- and late-century time horizons; and 3) U.S. Fish and Wildlife Service multi-decadal datasets and predictive breeding waterfowl pair statistical models. We conducted virtual and in-person informational sessions with partners to inform them on the best practices of using downscaled global circulation models and approaches for climate scenario planning. This close coordination led to a joint presentation at a monthly North Central Climate Adaptation Science Center seminar. We are also co-developing simulated wetland- waterfowl responses under different climate futures for wetlands. Information from these robust predictions of waterfowl habitat and settling patterns in this region provides land-management agencies insights in prioritizing current conservation actions given uncertainty. In addition, understanding how many breeding pairs the USPPR might support in coming decades will likely influence overall breeding population sizes and sustainable harvest objectives across North America.
","language":"English","publisher":"North Central Climate Adaptation Science Center","usgsCitation":"McKenna, O.P., and Rangwala, I., 2024, The impact of future changes in climate on breeding waterfowl pairs in the US Prairie Pothole Region: Final Report, 12 p.","productDescription":"12 p.","ipdsId":"IP-160169","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501396,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/65c3d314d34ef4b119cae715"}],"country":"United States","state":"Iowa, Minnesota, Nebraska, North Dakota, South Dakota","otherGeospatial":"Prairie Pothole region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.05393441199925,\n 48.93957527305318\n ],\n [\n -108.27686560641123,\n 49.13252538326782\n ],\n [\n -108.40976144212098,\n 47.91192273687099\n ],\n [\n -106.07828064784712,\n 47.88578029277039\n ],\n [\n -101.59819304168207,\n 47.10144151067459\n ],\n [\n -100.41457783182686,\n 42.307798494527646\n ],\n [\n -96.89275640038099,\n 41.01374950027804\n ],\n [\n -96.60513562002711,\n 43.75532782507912\n ],\n [\n -94.98321580753591,\n 41.5817220442664\n ],\n [\n -94.20767561860225,\n 41.328376780271384\n ],\n [\n -93.63954575827131,\n 42.51490897209834\n ],\n [\n -93.78977025276507,\n 43.36437770770755\n ],\n [\n -94.24637551611141,\n 47.33263848178828\n ],\n [\n -95.05393441199925,\n 48.93957527305318\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":893736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangwala, Imtiaz 0000-0002-4313-9374","orcid":"https://orcid.org/0000-0002-4313-9374","contributorId":148973,"corporation":false,"usgs":false,"family":"Rangwala","given":"Imtiaz","email":"","affiliations":[{"id":34534,"text":"Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado","active":true,"usgs":false}],"preferred":true,"id":957215,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252677,"text":"70252677 - 2024 - Short-term sediment dispersal on a large retreating coastal river delta via 234Th and 7Be sediment geochronology: The Mississippi River Delta Front","interactions":[],"lastModifiedDate":"2024-04-02T14:44:14.447864","indexId":"70252677","displayToPublicDate":"2024-01-31T09:43:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Short-term sediment dispersal on a large retreating coastal river delta via 234Th and 7Be sediment geochronology: The Mississippi River Delta Front","title":"Short-term sediment dispersal on a large retreating coastal river delta via 234Th and 7Be sediment geochronology: The Mississippi River Delta Front","docAbstract":"Many Mississippi River Delta studies have shown recent declines in fluvial sediment load from the river and associated land loss. In contrast, recent sedimentary processes on the subaqueous delta are less documented. To help address this knowledge gap, multicores were collected offshore from the three main river outlets at water depths of 25–280 m in June 2017 just after the peak river discharge period, with locations selected based on 2017 U.S. Geological Survey seabed mapping. The coring locations included the undisturbed upper foreset, mudflow lobes, gullies, and the undisturbed prodelta. Nine multicores were analyzed for Beryllium-7 activity, and four cores were analyzed for excess Thorium-234 activity via gamma spectrometry, granulometry and X-radiography. Our results indicate a general trend of declining 7Be and 234Th activities and inventories with increasing distance from sources and in deeper water. The core X-radiographs are graded from the predominantly physically stratified nearshore to the more bioturbated offshore, consistent with the sedimentation patterns. Sediment focusing assessed via the 7Be and 234Th sediment inventories shows preferential sedimentation in gully and lobe environments, whereas the upper foreset and prodelta focusing factors are relatively depleted. Overall, short-term sediment deposition from the main fluvial source remains active offshore from all three major river outlets, despite the overall declining river load.
","language":"English","publisher":"MDPI","doi":"10.3390/w16030463","usgsCitation":"Courtois, A., Bentley, S., Maloney, J., Xu, K., Chaytor, J., Georgiou, I.Y., Miner, M., Obelcz, J., Jafari, N., and Damour, M., 2024, Short-term sediment dispersal on a large retreating coastal river delta via 234Th and 7Be sediment geochronology: The Mississippi River Delta Front: Water, v. 16, no. 3, 463, 18 p., https://doi.org/10.3390/w16030463.","productDescription":"463, 18 p.","ipdsId":"IP-161126","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440581,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w16030463","text":"Publisher Index Page"},{"id":427313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta Front","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.14856845740192,\n 30.086965664332396\n ],\n [\n -91.2450587263565,\n 30.086965664332396\n ],\n [\n -91.2450587263565,\n 29.065454996104577\n ],\n [\n -89.14856845740192,\n 29.065454996104577\n ],\n [\n -89.14856845740192,\n 30.086965664332396\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Courtois, Andrew","contributorId":205364,"corporation":false,"usgs":false,"family":"Courtois","given":"Andrew","affiliations":[{"id":37089,"text":"Pontchartrain Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":897884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bentley, Samuel J.","contributorId":150402,"corporation":false,"usgs":false,"family":"Bentley","given":"Samuel J.","affiliations":[],"preferred":false,"id":897885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Jillian","contributorId":304141,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":897886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xu, Kehui","contributorId":223696,"corporation":false,"usgs":false,"family":"Xu","given":"Kehui","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":897887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":897888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Georgiou, Ioannis Y.","contributorId":205361,"corporation":false,"usgs":false,"family":"Georgiou","given":"Ioannis","email":"","middleInitial":"Y.","affiliations":[{"id":37089,"text":"Pontchartrain Institute for Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":897889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miner, Michael","contributorId":223694,"corporation":false,"usgs":false,"family":"Miner","given":"Michael","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":897890,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Obelcz, Jeffery","contributorId":335257,"corporation":false,"usgs":false,"family":"Obelcz","given":"Jeffery","email":"","affiliations":[{"id":80360,"text":"United States Naval Research Lab, Stennis Space Center","active":true,"usgs":false}],"preferred":false,"id":897891,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jafari, Navid H.","contributorId":214730,"corporation":false,"usgs":false,"family":"Jafari","given":"Navid H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":897892,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Damour, Melanie","contributorId":223691,"corporation":false,"usgs":false,"family":"Damour","given":"Melanie","email":"","affiliations":[{"id":25296,"text":"BOEM","active":true,"usgs":false}],"preferred":false,"id":897893,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70251072,"text":"fs20233051 - 2024 - Streamflow permanence in Mount Rainier National Park, Washington","interactions":[],"lastModifiedDate":"2026-01-27T17:47:44.950057","indexId":"fs20233051","displayToPublicDate":"2024-01-31T09:19:50","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3051","displayTitle":"Streamflow Permanence in Mount Rainier National Park, Washington","title":"Streamflow permanence in Mount Rainier National Park, Washington","docAbstract":"Streams that flow throughout summer (“permanent” streams) provide critical habitat for aquatic species and serve as an important water supply. Streams that go dry seasonally or only flow after rainfall or snowmelt are a natural feature of mountain systems, including Mount Rainier National Park. However, in years with substantially less than normal snowfall, like 2015, more streams go dry, resulting in less water for Mount Rainier National Park infrastructure and unknown consequences for stream ecology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233051","collaboration":"Prepared in cooperation with the U.S. National Park Service","usgsCitation":"Jaeger, K.L., 2024, Streamflow permanence in Mount Rainier National Park, Washington: U.S. Geological Survey Fact Sheet 2023–3051, 2 p., https://doi.org/10.3133/fs20233051.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-158621","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":499114,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116004.htm"},{"id":424658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3051/fs20233051.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3051"},{"id":424657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3051/fs20233051.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23285025723396,\n 47.201628005617295\n ],\n [\n -122.23285025723396,\n 46.441316165691745\n ],\n [\n -121.05824525132806,\n 46.441316165691745\n ],\n [\n -121.05824525132806,\n 47.201628005617295\n ],\n [\n -122.23285025723396,\n 47.201628005617295\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
No abstract available.
","language":"English","publisher":"Hudson River Foundation","usgsCitation":"Finkelstein, K.M., 2024, 24 hours on the Arthur Kill: Tidal Exchange News, no. January 2024, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-161537","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":426493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426492,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.hudsonriver.org/tidal-exchange-news"}],"country":"United States","state":"New Jersey","otherGeospatial":"Arthur Kill","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.2645433330953,\n 40.50334734453406\n ],\n [\n -74.24828559031762,\n 40.50293528101173\n ],\n [\n -74.23419554657706,\n 40.521063681284545\n ],\n [\n -74.18217076968922,\n 40.609163731683935\n ],\n [\n -74.17295804878228,\n 40.64618050898363\n ],\n [\n -74.19355118963331,\n 40.650292217652606\n ],\n [\n -74.21468625524412,\n 40.617391455312145\n ],\n [\n -74.2612917845396,\n 40.54659992634237\n ],\n [\n -74.26562718261341,\n 40.51117607050753\n ],\n [\n -74.2645433330953,\n 40.50334734453406\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"January 2024","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Finkelstein, Kaitlyn M. 0000-0003-1588-3312","orcid":"https://orcid.org/0000-0003-1588-3312","contributorId":202727,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":896305,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70251529,"text":"70251529 - 2024 - Chytrid infections exhibit historical spread and contemporary seasonality in a declining stream-breeding frog","interactions":[],"lastModifiedDate":"2024-02-14T13:04:59.013696","indexId":"70251529","displayToPublicDate":"2024-01-31T07:00:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3908,"text":"Royal Society Open Science","active":true,"publicationSubtype":{"id":10}},"title":"Chytrid infections exhibit historical spread and contemporary seasonality in a declining stream-breeding frog","docAbstract":"Species with extensive geographical ranges pose special challenges to assessing drivers of wildlife disease, necessitating collaborative and large-scale analyses. The imperilled foothill yellow-legged frog (Rana boylii) inhabits a wide geographical range and variable conditions in rivers of California and Oregon (USA), and is considered threatened by the pathogen Batrachochytrium dendrobatidis (Bd). To assess drivers of Bd infections over time and space, we compiled over 2000 datapoints from R. boylii museum specimens (collected 1897–2005) and field samples (2005–2021) spanning 9° of latitude. We observed a south-to-north spread of Bd detections beginning in the 1940s and increase in prevalence from the 1940s to 1970s, coinciding with extirpation from southern latitudes. We detected eight high-prevalence geographical clusters through time that span the species' geographical range. Field-sampled male R. boylii exhibited the highest prevalence, and juveniles sampled in autumn exhibited the highest loads. Bd infection risk was highest in lower elevation rain-dominated watersheds, and with cool temperatures and low stream-flow conditions at the end of the dry season. Through a holistic assessment of relationships between infection risk, geographical context and time, we identify the locations and time periods where Bd mitigation and monitoring will be critical for conservation of this imperilled species.
Arundo donax, commonly called Arundo cane, giant reed, or Carrizo cane, is an invasive bamboo-like perennial grass common in riparian areas throughout the southwestern United States. In Texas, not only does it negatively affect riparian ecosystems, but it has also become a problem for border security because it reduces visibility along the Rio Grande. To address these problems, in 2015 the Texas State Soil and Water Conservation Board was authorized by the Texas State Legislature to develop a program to eradicate Arundo cane along the Rio Grande. In 2020, the Texas State Soil and Water Conservation Board applied imazapyr and glyphosate herbicides along a 19.3-kilometer reach of the Rio Grande, northwest of Laredo, Texas. The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District, used WorldView-3 Standard high-resolution satellite imagery to map Arundo cane extent along the reach before, during, and after the herbicide-treatment period on June 30, 2020, September 26, 2020, and May 7, 2021, respectively. A maximum likelihood supervised classification analysis was computed on the images to map the spatial extent and estimate the area covered by Arundo cane. The estimated area covered by Arundo cane in the before classification was 1,282,000 square meters, in the during classification was 1,064,000 square meters, and in the after classification was 1,108,000 square meters. The qualitative comparison of the three images shows that there was an overall decrease in vegetation classified as Arundo cane throughout the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3512","issn":"2329-132X","collaboration":"Prepared in cooperation with the Texas State Soil and Water Conservation Board and the Webb Soil and Water Conservation District","programNote":"Water Resources Research Act Program","usgsCitation":"Villa, J., 2024, Mapping Arundo donax (Arundo cane) with multispectral imagery before, during, and after herbicide treatment along the Rio Grande in Webb County, Texas, 2020–21: U.S. Geological Survey Scientific Investigations Map 3512, 1 sheet, includes 7-p. pamphlet, https://doi.org/10.3133/sim3512.","productDescription":"Report: viii, 7 p.; 1 Sheet: 32.00 × 34.00 inches; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-144135","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":424979,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B04452","text":"USGS Data Release","linkHelpText":"Arundo donax (Arundo cane) image classification along the Rio Grande in Webb County, Texas, 2020–2021"},{"id":424973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3512/coverthb.jpg"},{"id":424978,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3512/images"},{"id":424976,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3512/full","linkFileType":{"id":5,"text":"html"},"description":"SIM 3512 HTML"},{"id":424974,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3512/sim3512_sheet.pdf","size":"11.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3512 pdf"},{"id":424975,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3512/sim3512_pamphlet.pdf","text":"Pamphlet","size":"1.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Pamphlet to accompany SIM 3512"},{"id":499281,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116006.htm","linkFileType":{"id":5,"text":"html"}},{"id":424977,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3512/sim3512.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3512 XML"}],"country":"United States","state":"Texas","county":"Webb County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-100.2123,28.2002],[-100.1107,28.199],[-100.0008,28.1972],[-99.3901,28.1991],[-99.3882,28.0303],[-98.8025,28.0571],[-98.8,27.3549],[-98.7997,27.2659],[-98.9579,27.2671],[-99.3339,27.2679],[-99.3704,27.3036],[-99.4595,27.2658],[-99.46,27.2658],[-99.4656,27.2668],[-99.4723,27.2659],[-99.4753,27.2636],[-99.4799,27.2599],[-99.4845,27.259],[-99.4858,27.259],[-99.4886,27.2591],[-99.4932,27.2623],[-99.4945,27.2633],[-99.4978,27.266],[-99.4985,27.2675],[-99.4993,27.2693],[-99.4992,27.2739],[-99.4977,27.2794],[-99.4946,27.2863],[-99.4915,27.2923],[-99.492,27.2973],[-99.494,27.3029],[-99.4975,27.3052],[-99.5062,27.3066],[-99.5128,27.3057],[-99.5195,27.3044],[-99.5211,27.3045],[-99.5261,27.3049],[-99.5307,27.3058],[-99.5358,27.3077],[-99.5399,27.3118],[-99.5419,27.316],[-99.5413,27.3206],[-99.5383,27.3252],[-99.5352,27.3266],[-99.5301,27.3275],[-99.525,27.3279],[-99.5204,27.3283],[-99.519,27.329],[-99.5142,27.3311],[-99.5101,27.3357],[-99.508,27.3403],[-99.508,27.3481],[-99.5095,27.3555],[-99.5079,27.361],[-99.5043,27.3688],[-99.5002,27.3739],[-99.4961,27.3785],[-99.4945,27.3831],[-99.4934,27.3914],[-99.4919,27.3997],[-99.4903,27.407],[-99.4908,27.413],[-99.4943,27.4213],[-99.4978,27.4287],[-99.4983,27.4356],[-99.4988,27.4407],[-99.4972,27.4481],[-99.4951,27.4536],[-99.4915,27.4586],[-99.4874,27.4646],[-99.4848,27.4692],[-99.4827,27.4761],[-99.4827,27.4821],[-99.4847,27.4895],[-99.4893,27.4955],[-99.4938,27.4987],[-99.5,27.5006],[-99.5076,27.5006],[-99.5148,27.4988],[-99.5215,27.4965],[-99.5245,27.4961],[-99.5281,27.4984],[-99.5296,27.5007],[-99.5291,27.503],[-99.5291,27.5104],[-99.5285,27.5159],[-99.5275,27.5228],[-99.5259,27.527],[-99.5238,27.5325],[-99.5243,27.538],[-99.5243,27.5445],[-99.5227,27.5491],[-99.5196,27.5532],[-99.516,27.5583],[-99.515,27.5624],[-99.516,27.567],[-99.518,27.5698],[-99.5221,27.5721],[-99.5267,27.5749],[-99.5307,27.5781],[-99.5338,27.5832],[-99.5358,27.5906],[-99.5404,27.5998],[-99.5434,27.6058],[-99.5475,27.6091],[-99.5526,27.6118],[-99.5577,27.6128],[-99.5613,27.611],[-99.5639,27.6082],[-99.5675,27.6055],[-99.5716,27.6032],[-99.5762,27.6027],[-99.5813,27.6023],[-99.5854,27.6028],[-99.588,27.6051],[-99.5874,27.6074],[-99.5859,27.6101],[-99.5828,27.6106],[-99.5792,27.6119],[-99.5782,27.6142],[-99.5797,27.6184],[-99.5828,27.6207],[-99.5889,27.623],[-99.593,27.6244],[-99.5945,27.6267],[-99.596,27.63],[-99.595,27.6341],[-99.5965,27.6383],[-99.5996,27.6406],[-99.6037,27.6415],[-99.6078,27.6411],[-99.6145,27.6383],[-99.617,27.6383],[-99.6206,27.6388],[-99.6237,27.6397],[-99.6262,27.6402],[-99.6293,27.6402],[-99.6303,27.6379],[-99.6298,27.6356],[-99.6293,27.6324],[-99.6299,27.6296],[-99.6329,27.6273],[-99.6365,27.6264],[-99.6401,27.6264],[-99.6447,27.6274],[-99.6545,27.6302],[-99.6606,27.6316],[-99.6647,27.6325],[-99.6667,27.6353],[-99.6678,27.6371],[-99.6662,27.6385],[-99.6631,27.6408],[-99.6611,27.6436],[-99.6611,27.6472],[-99.6626,27.6523],[-99.6651,27.6551],[-99.6692,27.6579],[-99.6759,27.6597],[-99.6825,27.6597],[-99.6861,27.6593],[-99.6902,27.6607],[-99.6917,27.663],[-99.6928,27.6644],[-99.6953,27.6667],[-99.6989,27.6644],[-99.701,27.6607],[-99.7041,27.6557],[-99.7061,27.6552],[-99.7128,27.6548],[-99.7195,27.658],[-99.7251,27.6645],[-99.7264,27.6681],[-99.7281,27.6728],[-99.7347,27.6829],[-99.7421,27.6908],[-99.7424,27.6912],[-99.748,27.6977],[-99.7552,27.706],[-99.7578,27.7107],[-99.7618,27.718],[-99.7622,27.7185],[-99.7659,27.724],[-99.7695,27.7272],[-99.7709,27.7281],[-99.7727,27.7293],[-99.7731,27.7295],[-99.7797,27.7309],[-99.7854,27.73],[-99.7919,27.73],[-99.7926,27.73],[-99.7992,27.7318],[-99.8038,27.7378],[-99.8064,27.7457],[-99.8094,27.7581],[-99.8104,27.7659],[-99.8128,27.7701],[-99.8135,27.7715],[-99.8171,27.7742],[-99.8207,27.7752],[-99.8248,27.7738],[-99.8263,27.771],[-99.8289,27.7669],[-99.832,27.7651],[-99.8371,27.7641],[-99.8407,27.7644],[-99.8419,27.7645],[-99.8428,27.7646],[-99.8434,27.7648],[-99.8464,27.766],[-99.8469,27.7675],[-99.8479,27.7701],[-99.8489,27.7757],[-99.8504,27.7798],[-99.8525,27.7835],[-99.852,27.7881],[-99.8522,27.79],[-99.8525,27.7918],[-99.8545,27.7941],[-99.8597,27.7946],[-99.8674,27.7941],[-99.8722,27.7941],[-99.8745,27.7941],[-99.8781,27.7946],[-99.8812,27.7978],[-99.8817,27.802],[-99.8813,27.805],[-99.8812,27.8056],[-99.8817,27.8116],[-99.8817,27.8181],[-99.8822,27.8222],[-99.8812,27.8282],[-99.8812,27.8356],[-99.8827,27.8406],[-99.8868,27.8484],[-99.893,27.8544],[-99.9027,27.8613],[-99.9073,27.8673],[-99.9094,27.8733],[-99.9078,27.8811],[-99.9042,27.8862],[-99.9025,27.888],[-99.9011,27.8894],[-99.898,27.894],[-99.898,27.9],[-99.8996,27.9051],[-99.9017,27.9088],[-99.9021,27.9097],[-99.9062,27.9124],[-99.9114,27.9152],[-99.9176,27.9179],[-99.9199,27.919],[-99.9237,27.9207],[-99.9294,27.9272],[-99.9314,27.9313],[-99.9319,27.9336],[-99.9345,27.9364],[-99.9371,27.9387],[-99.9407,27.9419],[-99.9422,27.9451],[-99.9422,27.9502],[-99.9412,27.9548],[-99.9381,27.9621],[-99.9365,27.9677],[-99.9355,27.975],[-99.9359,27.9775],[-99.936,27.9787],[-99.9381,27.9819],[-99.9417,27.9838],[-99.9463,27.9838],[-99.954,27.9838],[-99.9638,27.9847],[-99.9705,27.987],[-99.9777,27.9884],[-99.9844,27.9944],[-99.9911,28.0026],[-99.9993,28.0132],[-100.005,28.0197],[-100.0072,28.0239],[-100.0106,28.0302],[-100.0148,28.045],[-100.0158,28.0555],[-100.0168,28.0611],[-100.0176,28.0639],[-100.0184,28.0666],[-100.0214,28.0707],[-100.0271,28.0739],[-100.0333,28.0758],[-100.04,28.0781],[-100.0452,28.0804],[-100.0462,28.0809],[-100.0508,28.0831],[-100.0544,28.0877],[-100.056,28.0923],[-100.057,28.0974],[-100.0565,28.1011],[-100.0565,28.1052],[-100.0575,28.1075],[-100.0622,28.1116],[-100.0694,28.1185],[-100.0751,28.1254],[-100.0807,28.1337],[-100.0838,28.1424],[-100.0856,28.146],[-100.0859,28.1466],[-100.09,28.1498],[-100.0927,28.1505],[-100.0967,28.1516],[-100.106,28.1548],[-100.1138,28.1553],[-100.1178,28.1568],[-100.1185,28.1571],[-100.1205,28.1578],[-100.1236,28.159],[-100.1339,28.1645],[-100.135,28.165],[-100.1396,28.1672],[-100.1437,28.1686],[-100.1478,28.1695],[-100.1535,28.169],[-100.1581,28.1686],[-100.1627,28.1693],[-100.1638,28.1695],[-100.1695,28.1722],[-100.1731,28.1773],[-100.1777,28.1805],[-100.1829,28.1832],[-100.1901,28.1864],[-100.194,28.1879],[-100.1974,28.1892],[-100.2024,28.1908],[-100.203,28.191],[-100.2077,28.1924],[-100.2108,28.1951],[-100.2117,28.1981],[-100.2123,28.2002]]]},\"properties\":{\"name\":\"Webb\",\"state\":\"TX\"}}]}","contact":"For more information about this publication, contact
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
Changes in the quantity of sand stored within river segments can affect aquatic and riparian habitat, archeological resources, and recreation. Since summer to fall of 2002, gaging stations on the Colorado River in Grand Canyon National Park and on its major tributaries and selected lesser tributaries have measured the mass of sand transported past each station, which allows for changes in the mass of sand stored between gaging stations to be calculated. Sand mass balances on six Colorado River segments are currently measured; the upstream two segments measure sand mass balance in Marble Canyon, the middle three segments measure sand mass balance within the majority of Grand Canyon, and the downstream-most segment—western Grand Canyon and the Lake Mead delta—measures the quantity of sand transported past Diamond Creek and ultimately deposited in Lake Mead.
Between July 1, 2017, and June 30, 2020, the amount of sand stored in the Colorado River in Marble Canyon decreased, whereas the sand mass balance in Grand Canyon was indeterminate. Of the 3 years of study presented herein, sand was eroded from Marble Canyon during sediment year 2018 (July 1, 2017–June 30, 2018), a year with less than 40 percent of the 2003–2020 mean Paria River sand input, and sediment year 2020 (July 1, 2019–June 30, 2020), a year with negligible Paria River sand input. During sediment year 2018, when the Little Colorado River supplied negligible sand, sand was also eroded from Grand Canyon. The sand mass balance was indeterminate for Grand Canyon during sediment year 2020. During sediment year 2019 (July 1, 2018–June 30, 2019) sand accumulated in both Marble Canyon and Grand Canyon. This sediment year had sand inputs from both the Paria River and the Little Colorado River of more than 170 percent the 2003–2020 mean, coupled with below post-1964 mean discharge from Glen Canyon Dam.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231093","usgsCitation":"Griffiths, R.E., Topping, D.J., and Unema, J.A., 2024, Changes in sand storage in the Colorado River in Grand Canyon National Park from July 2017 through June 2020: U.S. Geological Survey Open-File Report 2023–1093, 9 p., https://doi.org/10.3133/ofr20231093.","productDescription":"v, 9 p.","numberOfPages":"9","onlineOnly":"Y","ipdsId":"IP-147171","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":425105,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1093/images"},{"id":425103,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1093/ofr20231093.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":425102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1093/covrthb.jpg"},{"id":425104,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1093/ofr20231093.xml","linkFileType":{"id":8,"text":"xml"}},{"id":499200,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116003.htm","linkFileType":{"id":5,"text":"html"}},{"id":425106,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231093/full"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.67941991219553,\n 37.29250555492341\n ],\n [\n -114.67941991219553,\n 35.64936002497116\n ],\n [\n -111.03195897469551,\n 35.64936002497116\n ],\n [\n -111.03195897469551,\n 37.29250555492341\n ],\n [\n -114.67941991219553,\n 37.29250555492341\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
In 2012, the Secretary of the U.S. Department of the Interior placed a 20-year limit on mineral extraction on Federal lands in the Grand Canyon watershed to permit further study of the environmental effects of uranium mining. Tribal concerns were also noted by the U.S. Department of the Interior and included in the rationale for the decision stating Tribal resource impacts could not be mitigated and cultural degradation may result should mining occur within sacred and traditional places of Tribal peoples. The U.S. Geological Survey previously developed a conceptual framework for a uranium mine in the region that defined contaminant sources and physical, chemical, and biological processes that affect contaminant transport to ecological receptors. However, published risk models have largely ignored exposure pathways relevant to Tribal communities in terms of traditional uses and existential values of the resources included. This report presents an updated conceptual risk framework for uranium mining that includes indigenous knowledge components informed by the Havasupai Tribe perspective.
The expansion of the framework relied on connecting to the foundations of the Havasupai ceremonial wheel—food, environment, belief system, and ceremony. The framework is applied to uranium development near Red Butte, an important gathering place for multiple federally recognized Tribes including the Havasupai, Hopi, Navajo, and Zuni. Plants and animals important to the Havasupai for subsistence, ceremonial, and medicinal practices and how mining affects these practices are described. The final framework is presented in English and Havasupai to aid Tribal members in understanding how the framework relates to their community and to help preserve the language and historical cultural practices for future generations. New or expanded exposure pathways include inhalation, ingestion, and absorption from traditional food and medicines as well as ceremonial practices. The updated framework has allowed the U.S. Geological Survey to take first steps in understanding resources important to the Havasupai and to build relationships to improve co-production in our research. Ideally, the framework and other research can be used, along with indigenous knowledge, in Federal research and decision making for mining in the Grand Canyon region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231092","usgsCitation":"Tilousi, C., and Hinck, J.E., 2024, Expanded conceptual risk framework for uranium mining in Grand Canyon watershed—Inclusion of the Havasupai Tribe perspective (ver. 1.1, February 2024): U.S. Geological Survey Open-File Report 2023–1092, 25 p., https://doi.org/10.3133/ofr20231092.","productDescription":"vi, 25 p.","numberOfPages":"36","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-157227","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":499197,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116005.htm","linkFileType":{"id":5,"text":"html"}},{"id":425864,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip241","text":"General Information Product 241"},{"id":425233,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1092/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":424862,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231092/full"},{"id":424859,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1092/images/"},{"id":424858,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1092/ofr20231092.XML"},{"id":424857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1092/ofr20231092.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1092"},{"id":424856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1092/coverthb2.jpg"},{"id":425791,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip240","text":"General Information Product 240"},{"id":425790,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip239","text":"General Information Product 239"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.19147841939832,\n 38.32491175913418\n ],\n [\n -117.19147841939832,\n 32.88011313999995\n ],\n [\n -110.33600966939846,\n 32.88011313999995\n ],\n [\n -110.33600966939846,\n 38.32491175913418\n ],\n [\n -117.19147841939832,\n 38.32491175913418\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: January 30, 2024; Version 1.1: February 1, 2024","contact":"Associate Director, Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
This study characterizes hydroclimatic variability and change in peak streamflow and daily streamflow in Wisconsin from water years 1921 through 2020. Nonstationarity in peak streamflow in Wisconsin can include monotonic trends, change points, and autocorrelation. Spatial patterns of nonstationarity in peak streamflow, daily streamflow, and monthly precipitation, temperature, and snowfall were examined using four temporal periods. Upward trends in peak streamflow and daily streamflow were detected across the State, from around 1990 to 2020 and were likely predominantly driven by concurrent increases in precipitation and temperatures during this time. Earlier decreases in peak streamflow between the 1920s to the 1980s in the southern parts of the State were likely affected by nonclimate-related factors such as urbanization, water use, and land-use changes associated with agriculture.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064J","collaboration":"Prepared in cooperation with the Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Levin, S.B., 2024, Peak streamflow trends in Wisconsin and their relation to changes in climate, water years 1921–2020, chap. J of Ryberg, K.R., comp., Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, 49 p., https://doi.org/10.3133/sir20235064J.","productDescription":"Report: ix, 49 p.; Data Release; Dataset","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144130","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":424964,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R71WWZ","text":"USGS data release","linkHelpText":"Peak streamflow data, climate data, and results from investigating hydroclimatic trends and climate change effects on peak streamflow in the Central United States, 1921–2020"},{"id":424963,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5064/j/images/"},{"id":424966,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235064J/full"},{"id":424965,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":424962,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5064/j/sir20235064j.XML"},{"id":424961,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/j/sir20235064j.pdf","text":"Report","size":"16.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5064–J"},{"id":424960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/j/coverthb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-90.403306,47.026693],[-90.411972,47.014958],[-90.425351,47.007526],[-90.464079,46.994636],[-90.465465,47.002593],[-90.457688,47.012484],[-90.4553,47.02375],[-90.455502,47.051331],[-90.449572,47.064965],[-90.438734,47.072557],[-90.417272,47.07757],[-90.395367,47.077175],[-90.393342,47.066204],[-90.403306,47.026693]]],[[[-90.730883,46.873096],[-90.677989,46.897527],[-90.667776,46.890037],[-90.675239,46.881029],[-90.718547,46.864531],[-90.745356,46.83566],[-90.756052,46.830595],[-90.760991,46.838277],[-90.749816,46.861806],[-90.730883,46.873096]]],[[[-90.764857,46.946524],[-90.741417,46.9636],[-90.71511,46.957332],[-90.694487,46.93671],[-90.689302,46.918563],[-90.737107,46.914712],[-90.764857,46.946524]]],[[[-90.568938,46.847391],[-90.58505,46.839789],[-90.613569,46.837958],[-90.673838,46.819684],[-90.683356,46.813275],[-90.685753,46.805003],[-90.652916,46.797755],[-90.65892,46.7885],[-90.696465,46.78204],[-90.716456,46.785418],[-90.7625,46.755547],[-90.787751,46.753301],[-90.783086,46.772939],[-90.790965,46.781373],[-90.790231,46.786103],[-90.733231,46.800183],[-90.720932,46.815897],[-90.656946,46.843476],[-90.622048,46.872872],[-90.602619,46.872715],[-90.568938,46.847391]]],[[[-90.572383,46.958835],[-90.528182,46.968396],[-90.508157,46.956836],[-90.524018,46.935714],[-90.539947,46.92785],[-90.543852,46.918289],[-90.549104,46.915461],[-90.569169,46.920309],[-90.637124,46.906724],[-90.64412,46.908373],[-90.654796,46.919249],[-90.634507,46.942944],[-90.572383,46.958835]]],[[[-87.335299,45.211327],[-87.331962,45.199251],[-87.33622,45.173174],[-87.327284,45.157363],[-87.376777,45.177298],[-87.375403,45.199296],[-87.335299,45.211327]]],[[[-90.962901,46.962028],[-90.980316,46.971578],[-90.98222,46.985417],[-90.949383,46.991208],[-90.939866,47.001321],[-90.928563,47.000726],[-90.923764,46.987928],[-90.932132,46.962655],[-90.962901,46.962028]]],[[[-90.757147,47.03372],[-90.688544,47.043347],[-90.643623,47.041177],[-90.608824,47.007558],[-90.560936,47.037013],[-90.544875,47.017383],[-90.552867,46.999686],[-90.609715,46.991208],[-90.634105,46.970983],[-90.671581,46.948973],[-90.712032,46.98526],[-90.767985,47.002327],[-90.776921,47.024324],[-90.757147,47.03372]]],[[[-87.405658,44.860098],[-87.384821,44.865532],[-87.385396,44.889964],[-87.406199,44.90449],[-87.393752,44.933751],[-87.374805,44.956631],[-87.360288,44.987643],[-87.322117,45.034201],[-87.264877,45.081361],[-87.257449,45.121644],[-87.240813,45.137559],[-87.242924,45.149377],[-87.238426,45.166492],[-87.224065,45.174551],[-87.21437,45.165735],[-87.195876,45.163201],[-87.17517,45.173],[-87.163169,45.185331],[-87.13303,45.192843],[-87.119972,45.191103],[-87.122708,45.221786],[-87.109541,45.255397],[-87.078316,45.265723],[-87.071035,45.280355],[-87.057627,45.292838],[-87.0517,45.285888],[-87.043895,45.284767],[-87.017036,45.299254],[-86.994112,45.298061],[-86.97778,45.290684],[-86.970355,45.278455],[-86.984938,45.259036],[-86.983066,45.250764],[-86.973287,45.246381],[-86.985973,45.215872],[-87.002806,45.211773],[-87.00754,45.222127],[-87.032521,45.222274],[-87.040909,45.211535],[-87.045242,45.158798],[-87.030225,45.147382],[-87.03292,45.141963],[-87.045748,45.134987],[-87.054282,45.120074],[-87.049346,45.110122],[-87.048213,45.089124],[-87.057415,45.087472],[-87.064864,45.078427],[-87.079552,45.070783],[-87.081866,45.059103],[-87.090849,45.055465],[-87.121156,45.058311],[-87.139384,45.012565],[-87.163477,45.004913],[-87.189134,44.969078],[-87.188399,44.94856],[-87.17524,44.939753],[-87.1717,44.931476],[-87.204238,44.916819],[-87.215808,44.906744],[-87.217171,44.898013],[-87.206285,44.885928],[-87.204815,44.877199],[-87.267061,44.847025],[-87.282561,44.814729],[-87.304824,44.804603],[-87.313363,44.794237],[-87.320397,44.784963],[-87.319903,44.769672],[-87.353789,44.701915],[-87.401629,44.631191],[-87.437751,44.604559],[-87.467089,44.553557],[-87.483696,44.511354],[-87.490024,44.477224],[-87.498662,44.460686],[-87.506362,44.423804],[-87.517965,44.394356],[-87.517597,44.375696],[-87.533583,44.351111],[-87.545382,44.321385],[-87.541382,44.294018],[-87.508457,44.229755],[-87.507419,44.210803],[-87.512903,44.192808],[-87.51966,44.17987],[-87.53994,44.15969],[-87.563181,44.144195],[-87.603572,44.13039],[-87.6458,44.105222],[-87.654935,44.082552],[-87.656062,44.051919],[-87.683361,44.020139],[-87.695053,43.990715],[-87.69892,43.965936],[-87.71817,43.939498],[-87.735436,43.882219],[-87.728698,43.852524],[-87.726408,43.810454],[-87.700251,43.76735],[-87.702985,43.749695],[-87.709885,43.735795],[-87.702685,43.687596],[-87.789105,43.564844],[-87.797608,43.52731],[-87.793239,43.492783],[-87.807799,43.461136],[-87.855608,43.405441],[-87.872504,43.380178],[-87.882392,43.352099],[-87.889207,43.307652],[-87.901847,43.284117],[-87.911787,43.250406],[-87.896286,43.197108],[-87.881085,43.170609],[-87.900285,43.13731],[-87.900496,43.126],[-87.893185,43.114011],[-87.876084,43.099011],[-87.866487,43.074419],[-87.870184,43.064412],[-87.894813,43.042497],[-87.898184,43.030689],[-87.896157,43.017486],[-87.887789,43.000715],[-87.857182,42.978015],[-87.845181,42.962015],[-87.842786,42.944865],[-87.847745,42.889595],[-87.824,42.836649],[-87.766675,42.784896],[-87.781949,42.74857],[-87.778824,42.728432],[-87.783489,42.705164],[-87.802377,42.676651],[-87.814674,42.64402],[-87.819407,42.617327],[-87.819374,42.60662],[-87.810873,42.58732],[-87.812273,42.52982],[-87.800477,42.49192],[-88.115285,42.496219],[-88.786681,42.491983],[-89.690088,42.505191],[-90.640927,42.508302],[-90.636727,42.518702],[-90.645627,42.5441],[-90.654127,42.5499],[-90.661527,42.567999],[-90.685487,42.589614],[-90.693999,42.614509],[-90.709204,42.636078],[-90.769495,42.651443],[-90.88743,42.67247],[-90.921155,42.685406],[-90.949213,42.685573],[-90.977735,42.696816],[-91.000128,42.716189],[-91.026786,42.724228],[-91.035418,42.73734],[-91.053733,42.738238],[-91.056297,42.747341],[-91.065783,42.753387],[-91.060261,42.761847],[-91.069549,42.769628],[-91.078097,42.806526],[-91.078665,42.827678],[-91.09406,42.830813],[-91.091402,42.84986],[-91.097656,42.859871],[-91.100565,42.883078],[-91.115512,42.894672],[-91.14556,42.90798],[-91.144315,42.926592],[-91.149784,42.940244],[-91.14655,42.963345],[-91.156562,42.978226],[-91.15749,42.991475],[-91.174692,43.038713],[-91.179457,43.067427],[-91.175193,43.103771],[-91.177932,43.128875],[-91.175253,43.134665],[-91.1562,43.142945],[-91.1462,43.152405],[-91.12217,43.197255],[-91.066398,43.239293],[-91.059684,43.248566],[-91.058644,43.257679],[-91.072649,43.262129],[-91.07371,43.274746],[-91.107237,43.313645],[-91.137343,43.329757],[-91.181115,43.345926],[-91.201847,43.349103],[-91.21477,43.365874],[-91.19767,43.395334],[-91.203144,43.419805],[-91.22875,43.445537],[-91.233367,43.455168],[-91.216035,43.481142],[-91.217353,43.512474],[-91.232941,43.523967],[-91.243183,43.540309],[-91.24382,43.54913],[-91.232812,43.564842],[-91.231865,43.581822],[-91.268748,43.615348],[-91.268457,43.627352],[-91.262397,43.64176],[-91.270767,43.65308],[-91.273252,43.666623],[-91.268455,43.709824],[-91.255932,43.729849],[-91.255431,43.744876],[-91.243955,43.773046],[-91.262436,43.792166],[-91.277695,43.837741],[-91.284138,43.847065],[-91.310991,43.867381],[-91.320605,43.888491],[-91.338141,43.897664],[-91.346271,43.910074],[-91.356741,43.916564],[-91.366642,43.937463],[-91.385785,43.954239],[-91.406011,43.963929],[-91.43738,43.999962],[-91.463515,44.009041],[-91.478498,44.00803],[-91.507121,44.01898],[-91.580019,44.026925],[-91.59207,44.031372],[-91.610487,44.04931],[-91.638115,44.063285],[-91.647873,44.064109],[-91.667006,44.086964],[-91.68153,44.0974],[-91.707491,44.103906],[-91.710597,44.12048],[-91.721552,44.130342],[-91.751747,44.134786],[-91.774486,44.147539],[-91.808064,44.159262],[-91.817302,44.164235],[-91.829167,44.17835],[-91.875158,44.200575],[-91.877429,44.212921],[-91.892698,44.231105],[-91.88704,44.251772],[-91.896008,44.262871],[-91.895652,44.273008],[-91.924613,44.291815],[-91.913534,44.311392],[-91.918625,44.322671],[-91.92559,44.333548],[-91.941311,44.340978],[-91.9636,44.362112],[-92.038147,44.388731],[-92.056486,44.402729],[-92.078605,44.404869],[-92.111085,44.413948],[-92.124513,44.422115],[-92.195378,44.433792],[-92.232472,44.445434],[-92.291005,44.485464],[-92.302215,44.500298],[-92.302466,44.516487],[-92.314071,44.538014],[-92.336114,44.554004],[-92.361518,44.558935],[-92.399281,44.558292],[-92.431101,44.565786],[-92.455105,44.561886],[-92.481001,44.568276],[-92.493808,44.566063],[-92.518358,44.575183],[-92.54806,44.567792],[-92.55151,44.571607],[-92.549777,44.58113],[-92.569434,44.603539],[-92.577148,44.605054],[-92.584711,44.599861],[-92.601516,44.612052],[-92.621456,44.615017],[-92.619779,44.634195],[-92.632105,44.649027],[-92.660988,44.660884],[-92.700948,44.693751],[-92.737259,44.717155],[-92.787906,44.737432],[-92.807317,44.750364],[-92.805287,44.768361],[-92.785206,44.792303],[-92.78043,44.812589],[-92.766102,44.834966],[-92.76909,44.861997],[-92.764133,44.875905],[-92.773946,44.889997],[-92.774571,44.898084],[-92.758701,44.908979],[-92.750645,44.937299],[-92.754603,44.955767],[-92.769445,44.97215],[-92.771231,45.001378],[-92.76206,45.02432],[-92.770362,45.033803],[-92.793282,45.047178],[-92.803079,45.060978],[-92.800851,45.069477],[-92.791528,45.079647],[-92.746749,45.107051],[-92.739528,45.116515],[-92.745694,45.123112],[-92.757707,45.155466],[-92.752542,45.171772],[-92.764872,45.182812],[-92.767408,45.190166],[-92.763908,45.204866],[-92.751708,45.218666],[-92.760249,45.2496],[-92.751659,45.26591],[-92.760615,45.278827],[-92.761013,45.289028],[-92.737122,45.300459],[-92.709968,45.321302],[-92.698967,45.336374],[-92.703705,45.35633],[-92.679193,45.37271],[-92.669505,45.389111],[-92.650422,45.398507],[-92.646602,45.441635],[-92.652698,45.454527],[-92.680234,45.464344],[-92.702224,45.493046],[-92.726677,45.514462],[-92.726082,45.541112],[-92.770223,45.566939],[-92.785741,45.567888],[-92.823309,45.560934],[-92.871082,45.567581],[-92.883749,45.575483],[-92.886442,45.598679],[-92.882529,45.610216],[-92.888035,45.624959],[-92.887929,45.639006],[-92.875488,45.689014],[-92.870145,45.696757],[-92.869193,45.717568],[-92.809837,45.744172],[-92.784621,45.764196],[-92.776496,45.790014],[-92.757815,45.806574],[-92.765146,45.830183],[-92.739991,45.846283],[-92.734039,45.868108],[-92.712503,45.891705],[-92.676607,45.90637],[-92.676807,45.91093],[-92.659549,45.922937],[-92.639116,45.924555],[-92.640115,45.932478],[-92.636316,45.934634],[-92.614314,45.934529],[-92.60246,45.940815],[-92.551933,45.951651],[-92.549806,45.967986],[-92.527052,45.983245],[-92.469354,45.973811],[-92.46126,45.979427],[-92.464512,45.985038],[-92.453373,45.992913],[-92.442259,46.016177],[-92.428555,46.024241],[-92.410649,46.027259],[-92.372717,46.014198],[-92.35176,46.015685],[-92.344244,46.02743],[-92.343604,46.040917],[-92.332912,46.062697],[-92.294033,46.074377],[-92.292192,46.666042],[-92.287392,46.667342],[-92.286192,46.660342],[-92.274392,46.657441],[-92.270592,46.650741],[-92.256592,46.658741],[-92.242493,46.649241],[-92.228492,46.652941],[-92.216392,46.649841],[-92.207092,46.651941],[-92.202292,46.655041],[-92.204092,46.666941],[-92.176091,46.686341],[-92.183091,46.695241],[-92.198491,46.696141],[-92.205192,46.698341],[-92.205692,46.702541],[-92.189091,46.717541],[-92.167291,46.719941],[-92.146291,46.71594],[-92.141291,46.72524],[-92.14329,46.73464],[-92.13789,46.73954],[-92.108777,46.749105],[-92.08949,46.74924],[-92.03399,46.708939],[-92.020289,46.704039],[-92.007989,46.705039],[-91.961889,46.682539],[-91.942988,46.679939],[-91.886963,46.690211],[-91.820027,46.690176],[-91.790473,46.694624],[-91.74965,46.709129],[-91.646146,46.734575],[-91.590684,46.754331],[-91.511077,46.757453],[-91.489125,46.766997],[-91.44957,46.773252],[-91.411799,46.78964],[-91.369387,46.793745],[-91.33825,46.817704],[-91.315061,46.826729],[-91.256873,46.836833],[-91.226796,46.86361],[-91.207524,46.865835],[-91.200107,46.854017],[-91.178292,46.844259],[-91.168297,46.844727],[-91.140301,46.873105],[-91.133337,46.870341],[-91.134977,46.859023],[-91.107323,46.857469],[-91.096565,46.86153],[-91.090916,46.88267],[-91.080951,46.883609],[-91.069331,46.878772],[-91.052991,46.881325],[-91.03989,46.88923],[-91.034518,46.903053],[-91.019141,46.911502],[-90.995149,46.917577],[-90.968419,46.94391],[-90.92204,46.931372],[-90.914044,46.933346],[-90.908654,46.941221],[-90.880358,46.957661],[-90.855874,46.962232],[-90.838814,46.957728],[-90.786595,46.927019],[-90.75563,46.899247],[-90.751151,46.887863],[-90.77017,46.876296],[-90.798545,46.823922],[-90.825696,46.803858],[-90.835008,46.790366],[-90.854916,46.788952],[-90.863542,46.780565],[-90.859724,46.774433],[-90.862333,46.768135],[-90.885021,46.756341],[-90.870396,46.723293],[-90.853225,46.70028],[-90.853644,46.694464],[-90.870079,46.679449],[-90.914619,46.659054],[-90.924487,46.625417],[-90.93831,46.608768],[-90.951418,46.600774],[-90.942101,46.588573],[-90.906058,46.58343],[-90.873154,46.601223],[-90.794775,46.624941],[-90.770192,46.636127],[-90.755381,46.646225],[-90.756495,46.664591],[-90.74809,46.669817],[-90.73726,46.692267],[-90.627885,46.623839],[-90.558141,46.586384],[-90.538346,46.581182],[-90.505909,46.589614],[-90.437596,46.561492],[-90.418136,46.566094],[-90.39332,46.532615],[-90.369964,46.540549],[-90.350121,46.537337],[-90.344338,46.552087],[-90.331887,46.553278],[-90.326686,46.54615],[-90.320428,46.546287],[-90.310859,46.539365],[-90.316983,46.517319],[-90.285707,46.518846],[-90.277131,46.524487],[-90.272599,46.521127],[-90.274721,46.515416],[-90.270684,46.508237],[-90.263018,46.502777],[-90.231587,46.509842],[-90.230324,46.501732],[-90.216594,46.501759],[-90.204009,46.478175],[-90.188996,46.469015],[-90.193294,46.463143],[-90.180336,46.456746],[-90.17786,46.440548],[-90.166919,46.439851],[-90.158603,46.422656],[-90.157851,46.409291],[-90.144359,46.390255],[-90.13225,46.381249],[-90.133871,46.371828],[-90.116844,46.355153],[-90.12138,46.338131],[-89.09163,46.138505],[-88.85027,46.040274],[-88.837991,46.030176],[-88.811948,46.021609],[-88.79646,46.023605],[-88.80067,46.030036],[-88.796182,46.033712],[-88.779221,46.031869],[-88.783891,46.020934],[-88.779915,46.015436],[-88.765208,46.022086],[-88.756295,46.020173],[-88.746422,46.025798],[-88.730675,46.026535],[-88.721125,46.022013],[-88.718397,46.013284],[-88.704687,46.018154],[-88.679132,46.013538],[-88.661312,45.988819],[-88.6375,45.98496],[-88.616405,45.9877],[-88.611466,46.003332],[-88.60144,46.017599],[-88.59386,46.015132],[-88.589755,46.005602],[-88.565485,46.015708],[-88.550756,46.012896],[-88.541078,46.013763],[-88.533825,46.020915],[-88.514601,46.019926],[-88.507188,46.0183],[-88.498108,45.99636],[-88.492495,45.992157],[-88.476002,45.992826],[-88.470855,46.001004],[-88.458658,45.999391],[-88.450325,45.990181],[-88.439733,45.990456],[-88.416914,45.975323],[-88.388847,45.982675],[-88.380183,45.991654],[-88.330137,45.965951],[-88.330296,45.956625],[-88.326953,45.955071],[-88.316894,45.960969],[-88.292381,45.951115],[-88.250133,45.963147],[-88.246307,45.962983],[-88.242518,45.950363],[-88.23314,45.947405],[-88.201852,45.945173],[-88.202116,45.949836],[-88.191991,45.95274],[-88.170096,45.93947],[-88.146352,45.935314],[-88.121864,45.92075],[-88.104686,45.922121],[-88.096496,45.917273],[-88.095354,45.913895],[-88.105677,45.904387],[-88.101814,45.883504],[-88.095841,45.880042],[-88.083965,45.881186],[-88.073944,45.875593],[-88.075146,45.864832],[-88.081641,45.865087],[-88.13611,45.819029],[-88.129461,45.809288],[-88.105355,45.800104],[-88.103247,45.791361],[-88.072091,45.780261],[-88.050634,45.780972],[-88.040221,45.789236],[-87.991447,45.795393],[-87.98087,45.776977],[-87.989829,45.772945],[-87.96697,45.764021],[-87.963452,45.75822],[-87.905873,45.759364],[-87.896032,45.752285],[-87.875813,45.753888],[-87.864141,45.745697],[-87.86432,45.737139],[-87.85548,45.726943],[-87.805867,45.706841],[-87.809181,45.700337],[-87.782226,45.683053],[-87.780737,45.675458],[-87.823164,45.662732],[-87.824102,45.647138],[-87.810194,45.638732],[-87.79588,45.618846],[-87.780845,45.614599],[-87.777199,45.588499],[-87.787534,45.581376],[-87.790874,45.564096],[-87.806104,45.562863],[-87.829346,45.568776],[-87.833591,45.562529],[-87.80339,45.538272],[-87.802267,45.514233],[-87.792769,45.499967],[-87.812971,45.4661],[-87.861697,45.434473],[-87.860432,45.423504],[-87.849322,45.403872],[-87.859131,45.398967],[-87.859418,45.388227],[-87.875424,45.379373],[-87.871789,45.373557],[-87.884855,45.362792],[-87.888052,45.354697],[-87.881114,45.351278],[-87.86856,45.360537],[-87.860871,45.351192],[-87.850418,45.347492],[-87.848368,45.340676],[-87.832612,45.352249],[-87.790324,45.353444],[-87.783076,45.349725],[-87.754104,45.349442],[-87.751626,45.354169],[-87.738352,45.358243],[-87.718891,45.377462],[-87.693956,45.389893],[-87.675017,45.382454],[-87.674403,45.378065],[-87.657349,45.368752],[-87.656632,45.358617],[-87.648476,45.352243],[-87.648126,45.339396],[-87.662029,45.326434],[-87.663666,45.318257],[-87.687498,45.298055],[-87.698248,45.281512],[-87.69878,45.26942],[-87.709137,45.260341],[-87.711339,45.239965],[-87.724156,45.233236],[-87.721935,45.228444],[-87.726952,45.218949],[-87.726198,45.209391],[-87.741732,45.198201],[-87.736509,45.173389],[-87.683902,45.144135],[-87.675816,45.135059],[-87.678511,45.131204],[-87.672447,45.121294],[-87.661296,45.112566],[-87.661211,45.108279],[-87.631535,45.106224],[-87.59188,45.094689],[-87.587147,45.089495],[-87.587992,45.085271],[-87.601849,45.082297],[-87.610395,45.075617],[-87.625748,45.045157],[-87.624693,45.014176],[-87.630298,44.976865],[-87.661964,44.973035],[-87.696492,44.974233],[-87.766115,44.965351],[-87.817551,44.951986],[-87.837647,44.933091],[-87.844299,44.918524],[-87.827751,44.891229],[-87.832764,44.880939],[-87.852789,44.86486],[-87.865898,44.840988],[-87.878218,44.839016],[-87.899787,44.828051],[-87.941453,44.75608],[-87.964714,44.74357],[-87.983065,44.72073],[-87.990081,44.669791],[-88.002085,44.664035],[-88.009766,44.637081],[-87.998836,44.609523],[-88.001943,44.603909],[-88.012395,44.602438],[-88.027103,44.578992],[-88.039092,44.574324],[-88.042261,44.567344],[-88.005518,44.539216],[-87.970702,44.530292],[-87.943801,44.529693],[-87.929001,44.535993],[-87.901206,44.568887],[-87.899368,44.573043],[-87.903689,44.581317],[-87.901179,44.584545],[-87.867941,44.607606],[-87.809076,44.636189],[-87.77516,44.639281],[-87.756048,44.649117],[-87.748409,44.667122],[-87.71978,44.693246],[-87.720312,44.725073],[-87.610063,44.838384],[-87.581635,44.851638],[-87.550288,44.85129],[-87.530999,44.857437],[-87.515142,44.869596],[-87.502431,44.864619],[-87.478489,44.863572],[-87.437084,44.892718],[-87.421007,44.887869],[-87.419951,44.87594],[-87.405658,44.860098]]],[[[-86.880572,45.331467],[-86.895055,45.329035],[-86.899488,45.322588],[-86.896667,45.307275],[-86.899891,45.295185],[-86.925681,45.3242],[-86.95499,45.34128],[-86.956192,45.351179],[-86.946297,45.35869],[-86.95497,45.383194],[-86.943041,45.41525],[-86.934724,45.421123],[-86.928045,45.411273],[-86.917686,45.40789],[-86.892893,45.40898],[-86.877502,45.413981],[-86.862174,45.412151],[-86.853145,45.405547],[-86.830353,45.410852],[-86.828731,45.428461],[-86.810055,45.422619],[-86.805415,45.407324],[-86.824383,45.406135],[-86.841432,45.389601],[-86.853103,45.370861],[-86.863367,45.365],[-86.869031,45.333244],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Wisconsin\",\"nation\":\"USA \"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. This work is part of that reexamination.
The stationarity assumption is a concern because flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done to assess potential nonstationarity in peak flows in the north-central United States.
This report summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., comp., 2024, Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, [variously paged], https://doi.org/10.3133/sir20235064.","productDescription":"1 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":424953,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/sir20235064.pdf","text":"Abstract","size":"522 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5064"},{"id":424911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/coverthb.jpg"}],"contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States.
This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States.
Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Peak Streamflow Trends and Their Relation to Changes in Climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235064A","collaboration":"Prepared in cooperation with Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation","usgsCitation":"Ryberg, K.R., Over, T.M., Levin, S.B., Heimann, D.C., Barth, N.A., Marti, M.K., O’Shea, P.S., Sanocki, C.A., Williams-Sether, T.J., Wavra, H.N., Sando, T.R., Sando, S.K., and Liu, M.S., 2024, Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin, chap. A of Ryberg, K.R., comp., Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin: U.S. Geological Survey Scientific Investigations Report 2023–5064, 27 p., https://doi.org/10.3133/sir20235064A.","productDescription":"Report: vi, 27 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-145865","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":424913,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5064/a/coverthb.jpg"},{"id":424914,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5064/a/sir20235064a.pdf","text":"Report","size":"44.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5064–A"},{"id":424915,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5064/a/sir20235064a.XML"},{"id":424916,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5064/a/images/"},{"id":424917,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R71WWZ","text":"USGS data release","linkHelpText":"Peak streamflow data, climate data, and results from investigating hydroclimatic trends and climate change effects on peak streamflow in the Central United States, 1920–2020"},{"id":424918,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":499376,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115980.htm","linkFileType":{"id":5,"text":"html"}},{"id":424919,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235064A/full"}],"country":"United States","state":"Iowa, Illinois, Michigan, Missouri, Minnesota, Montana, North Dakota, South Dakota, Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-87.800477,42.49192],[-87.812461,42.232278],[-87.524844,41.691635],[-87.531646,39.347888],[-87.640435,39.166727],[-87.496537,38.778571],[-87.975511,38.232742],[-88.158207,37.664542],[-88.078046,37.532029],[-88.450127,37.411717],[-88.490068,37.067874],[-89.058036,37.188767],[-89.171881,37.068184],[-89.202607,36.601576],[-89.343753,36.630991],[-89.429311,36.481875],[-89.55264,36.577178],[-89.527029,36.341679],[-89.703511,36.243412],[-89.615128,36.113816],[-89.733095,36.000608],[-90.368718,35.995812],[-90.075934,36.281485],[-90.157136,36.484317],[-94.617919,36.499414],[-94.605734,39.122204],[-95.082714,39.516712],[-94.876344,39.806894],[-95.382957,40.027112],[-95.870481,40.71248],[-95.844088,41.180598],[-96.096186,41.547192],[-96.077543,41.777824],[-96.342395,42.160491],[-96.380107,42.451494],[-96.625958,42.513576],[-96.687669,42.653126],[-97.308853,42.867307],[-98.035034,42.764205],[-98.568936,42.998537],[-104.053127,43.000585],[-104.057698,44.997431],[-111.044275,45.001345],[-111.048974,44.474072],[-111.323669,44.724474],[-111.50494,44.635746],[-111.469185,44.552044],[-112.258665,44.569516],[-112.387389,44.448058],[-112.749011,44.491233],[-112.844859,44.358221],[-113.134824,44.752763],[-113.455071,44.865424],[-113.802955,45.592631],[-114.015633,45.696127],[-114.345019,45.459916],[-114.559038,45.565706],[-114.422963,45.855381],[-114.527096,46.146218],[-114.322912,46.642938],[-114.76689,46.696901],[-115.294785,47.220914],[-115.731348,47.433381],[-115.72377,47.696671],[-116.049153,47.999923],[-116.049193,49.000912],[-95.153711,48.998903],[-95.153314,49.384358],[-94.878454,49.333193],[-94.640803,48.741171],[-93.818375,48.534442],[-92.984963,48.623731],[-92.634931,48.542873],[-92.698824,48.494892],[-92.341207,48.23248],[-92.066269,48.359602],[-91.542512,48.053268],[-90.88548,48.245784],[-90.703702,48.096009],[-89.489226,48.014528],[-90.86827,47.5569],[-92.058888,46.809938],[-91.942988,46.679939],[-90.880358,46.957661],[-90.78804,46.844886],[-90.920813,46.637432],[-90.398478,46.575832],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-88.027103,44.578992],[-87.943801,44.529693],[-87.428144,44.890738],[-87.021088,45.296541],[-87.73063,43.893862],[-87.910172,43.236634],[-87.800477,42.49192]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-83.880387,41.720089],[-86.824828,41.76024],[-86.24971,42.480212],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.110884,45.526285],[-84.94565,45.708621],[-85.011433,45.757962],[-84.204218,45.627116],[-84.095905,45.497298],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.617955,43.768596],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.431103,41.757457],[-83.880387,41.720089]]],[[[-86.880572,45.331467],[-86.956192,45.351179],[-86.82177,45.427602],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Iowa\",\"nation\":\"USA \"}}]}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Ocean acidification (OA) driven by eutrophication, riverine discharge, and other threats from local population growth that affect the inorganic carbonate system is already affecting the eastern Gulf of Mexico. Long-term declines in pH of ~ -0.001 pH units yr-1 have been observed in many southwest Florida estuaries over the past few decades. Coastal and estuarine waters of southwest Florida experience high biomass harmful algal blooms (HABs) of the dinoflagellate Karenia brevis nearly every year; and these blooms have the potential to impact and be impacted by seasonal to interannual patterns of carbonate chemistry. Sampling was conducted seasonally along three estuarine transects (Tampa Bay, Charlotte Harbor, Caloosahatchee River) between May 2020 and May 2023 to obtain baseline measurements of carbonate chemistry prior to, during, and following K. brevis blooms. Conductivity, temperature and depth data and discrete water samples for K. brevis cell abundance, nutrients, and carbonate chemistry (total alkalinity, dissolved inorganic carbonate (DIC), pCO2, and pHT were evaluated to identify seasonal patterns and linkages among carbonate system variables, nutrients, and K. brevis blooms. Karenia brevis blooms were observed during six samplings, and highest pCO2 and lowest pHT was observed either during or after blooms in all three estuaries. Highest average pH and lowest pCO2 were observed in Tampa Bay. In all three estuaries, average DIC and pHT were higher and pCO2 was lower during dry seasons than wet seasons. There was strong influence of net community calcification (NCC) and net community production (NCP) on the carbonate system; and NCC : NCP ratios in Tampa Bay, Charlotte Harbor, and the Caloosahatchee River were 0.83, 0.93, and 1.02, respectively. Linear relationships between salinity and dissolved ammonium, phosphate, and nitrate indicate strong influence of freshwater inflow from river input and discharge events on nutrient concentrations. This study is a first step towards connecting observations of high biomass blooms like those caused by K. brevis and alterations of carbonate chemistry in Southwest Florida. Our study demonstrates the need for integrated monitoring to improve understanding of interactions among the carbonate system, HABs, water quality, and acidification over local to regional spatial scales and event to decadal time scales.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2024.1331285","usgsCitation":"Hall, E.R., Yates, K., Hubbard, K.A., Garrett, M., and Frankle, J., 2024, Nutrient and carbonate chemistry patterns associated with Karenia brevis blooms in three West Florida Shelf estuaries 2020-2023: Frontiers in Marine Science, v. 11, 1331285, 16 p., https://doi.org/10.3389/fmars.2024.1331285.","productDescription":"1331285, 16 p.","ipdsId":"IP-159102","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2024.1331285","text":"Publisher Index Page"},{"id":426239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River, Charlotte Harbor, Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.34832763337916,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 28.08844843847784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.0334613261019,\n 26.994691244568983\n ],\n [\n -82.29301422823401,\n 26.99594814875003\n ],\n [\n -82.2944248418327,\n 26.644724858711314\n ],\n [\n -82.0334613261019,\n 26.643464039045767\n ],\n [\n -82.0334613261019,\n 26.994691244568983\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.835022542123,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.624097850120123\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Emily R.","contributorId":229381,"corporation":false,"usgs":false,"family":"Hall","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":41628,"text":"Mote Marine","active":true,"usgs":false}],"preferred":false,"id":895784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":202055,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":895785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, Katherine A.","contributorId":334472,"corporation":false,"usgs":false,"family":"Hubbard","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrett, Matt","contributorId":334473,"corporation":false,"usgs":false,"family":"Garrett","given":"Matt","email":"","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frankle, Jessica","contributorId":334474,"corporation":false,"usgs":false,"family":"Frankle","given":"Jessica","email":"","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":895788,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70251275,"text":"70251275 - 2024 - The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters","interactions":[],"lastModifiedDate":"2024-02-05T15:24:29.754603","indexId":"70251275","displayToPublicDate":"2024-01-25T06:55:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters","docAbstract":"Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 (m/z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r2 = 0.93), praseodymium (Pr) (r2 = 0.94) and samarium (Sm) (r2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.
Invasive sea lamprey (Petromyzon marinus) are controlled in the Great Lakes with 4-nitro-3-(trifluoromethyl)phenol (commonly 3-trifluoromethyl-4-nitrophenol or TFM). The proper amount of TFM must be applied during treatments to effectively kill larval sea lamprey while minimizing impacts to non-target species. In this study, bioassay tests were conducted in May, July, and September in a portable test trailer at six larval sea lamprey infested rivers in Michigan to determine potential seasonal changes in sensitivity of larval sea lamprey to TFM. Larvae greater than 60 mm were collected from each stream and exposed for 12 h in TFM-treated stream water using two independent continuous-flow diluter systems. A suite of water chemistries and larval physiological parameters were collected during the tests and modeled as potential predictors of seasonal changes in the sensitivity of larval sea lamprey to TFM. The observed minimum lethal concentrations to larval sea lamprey were 0–40% lower (May), 8% lower–59% higher (July), and 49–117% higher (September) than sea lamprey control personnel treatment prediction charts. Water temperature, liver glycogen content, and time of year were strongly associated with seasonal differences in TFM sensitivity, offering sea lamprey control personnel more exact predictions to limit potential residual lamprey surviving future treatments.