This report summarizes an updated inventory of glaciers and perennial snowfields of the conterminous United States. The inventory is based on interpretation of mostly aerial imagery provided by the National Agricultural I magery Program, US Department of Agriculture, with some satellite imagery in places where aerial imagery was not suitable. The inventory includes all perennial snow and ice features ≥ 0.01 km2. Due to aerial survey schedules and seasonal snow cover, imageries acquired over a number of years were required. The earliest date is 2013 and the latest is 2020, but more than 73 % of the outlines were acquired from 2015 imagery. The inventory is compiled as shapefiles within a geographic information system that includes feature classification, area, and location. The inventory identified 1331 (366.52 ± 14.34 km2) glaciers, 1176 (31.01 ± 9.30 km2) perennial snowfields, and 35 (3.57 km2 ± no uncertainty) buried-ice features. The data including both the shapefiles and tabulated results are publicly available at https://doi.org/10.15760/geology-data.03 (Fountain and Glenn, 2022).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-15-4077-2023","usgsCitation":"Fountain, A., Glenn, B., and McNeil, C., 2023, Inventory of glaciers and perennial snowfields of the conterminous USA: Earth System Science Data, v. 15, no. 9, p. 4077-4104, https://doi.org/10.5194/essd-15-4077-2023.","productDescription":"28 p.","startPage":"4077","endPage":"4104","ipdsId":"IP-148100","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":442086,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-15-4077-2023","text":"Publisher Index Page"},{"id":421887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fountain, Andrew","contributorId":299755,"corporation":false,"usgs":false,"family":"Fountain","given":"Andrew","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":885973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Bryce","contributorId":330808,"corporation":false,"usgs":false,"family":"Glenn","given":"Bryce","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":885974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":885975,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248504,"text":"70248504 - 2023 - Toward probabilistic post-fire debris-flow hazard decision support","interactions":[],"lastModifiedDate":"2023-09-15T13:27:51.647204","indexId":"70248504","displayToPublicDate":"2023-09-15T08:11:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Toward probabilistic post-fire debris-flow hazard decision support","docAbstract":"Post-wildfire debris flows (PFDF) threaten life and property in western North America. They are triggered by short-duration, high-intensity rainfall. Following a wildfire, rainfall thresholds are developed that, if exceeded, indicate high likelihood of a PFDF. Existing weather forecast products allow forecasters to identify favorable atmospheric conditions for rainfall intensities that may exceed established thresholds at lead times needed for decision-making (e.g., ≥24 h). However, at these lead times, considerable uncertainty exists regarding rainfall intensity and whether the high-intensity rainfall will intersect the burn area. The approach of messaging on potential hazards given favorable conditions is generally effective in avoiding unanticipated PFDF impacts, but may lead to “messaging fatigue” if favorable triggering conditions are forecast numerous times, yet no PFDF occurs (i.e., false alarm). Forecasters and emergency managers need additional tools that increase their confidence regarding occurrence of short-duration, high-intensity rainfall as well as tools that tie rainfall forecasts to potential PFDF outcomes. We present a concept for probabilistic tools that evaluate PFDF hazards by coupling a high-resolution (1-km), large (100-member) ensemble 24-h precipitation forecast at 5-min resolution with PFDF likelihood and volume models. The observed 15-min maximum rainfall intensities are captured within the ensemble spread, though in highest ∼10% of members. We visualize the model output in several ways to demonstrate most likely and most extreme outcomes and to characterize uncertainty. Our experiment highlights the benefits and limitations of this approach, and provides an initial step toward further developing situational awareness and impact-based decision-support tools for forecasting PFDF hazards.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-22-0188.1","usgsCitation":"Oakley, N.S., Liu, T., McGuire, L., Simpson, M., Hatchett, B.J., Tardy, A., Kean, J.W., Castellano, C., Laber, J.L., and Steinhoff, D., 2023, Toward probabilistic post-fire debris-flow hazard decision support: Bulletin of the American Meteorological Society, v. 104, no. 9, p. E1587-E1605, https://doi.org/10.1175/BAMS-D-22-0188.1.","productDescription":"19 p.","startPage":"E1587","endPage":"E1605","ipdsId":"IP-150218","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":442089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/bams-d-22-0188.1","text":"Publisher Index Page"},{"id":420828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Montecito","otherGeospatial":"Santa Ynez Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.66701649030912,\n 34.452095445537736\n ],\n [\n -119.62687608675861,\n 34.446131312701965\n ],\n [\n -119.57877992754959,\n 34.44672774514967\n ],\n [\n -119.57280690010244,\n 34.42077899761334\n ],\n [\n -119.53700599963841,\n 34.42137561101943\n ],\n [\n -119.49795047185961,\n 34.41242596294916\n ],\n [\n -119.46938207654,\n 34.39392698876664\n ],\n [\n -119.46395769768178,\n 34.39004765291959\n ],\n [\n -119.4509391884223,\n 34.40019322839929\n ],\n [\n -119.4455148095641,\n 34.40884583554798\n ],\n [\n -119.45310893996538,\n 34.42077899761334\n ],\n [\n -119.45310893996538,\n 34.43032430123482\n ],\n [\n -119.44587643482133,\n 34.43151738755279\n ],\n [\n -119.44153693173484,\n 34.4449384350318\n ],\n [\n -119.44406830853514,\n 34.49234220079083\n ],\n [\n -119.47010532705447,\n 34.492640252476065\n ],\n [\n -119.50952248009051,\n 34.48667901636392\n ],\n [\n -119.55002450889825,\n 34.48995774895617\n ],\n [\n -119.58510215884777,\n 34.51409717394719\n ],\n [\n -119.59992879439346,\n 34.514395147854586\n ],\n [\n -119.6082461753092,\n 34.508137472032885\n ],\n [\n -119.6223495603404,\n 34.51260728842783\n ],\n [\n -119.64597689596263,\n 34.52452562662715\n ],\n [\n -119.66586628510927,\n 34.526909089649436\n ],\n [\n -119.70636831391701,\n 34.532867448779726\n ],\n [\n -119.72119494946267,\n 34.53882538155821\n ],\n [\n -119.7313204566646,\n 34.53525067305482\n ],\n [\n -119.74578546695305,\n 34.54180418805544\n ],\n [\n -119.76169697827044,\n 34.54120843528388\n ],\n [\n -119.7776084895878,\n 34.547165771113654\n ],\n [\n -119.79279675039072,\n 34.52422768895302\n ],\n [\n -119.79713625347722,\n 34.50664747995778\n ],\n [\n -119.78990374833282,\n 34.45328822100022\n ],\n [\n -119.76097372775595,\n 34.45388460234258\n ],\n [\n -119.7313204566646,\n 34.45060445225566\n ],\n [\n -119.69190330362859,\n 34.44970984350894\n ],\n [\n -119.66701649030912,\n 34.452095445537736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"104","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oakley, Nina S.","contributorId":197885,"corporation":false,"usgs":false,"family":"Oakley","given":"Nina","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":883104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Tao","contributorId":329738,"corporation":false,"usgs":false,"family":"Liu","given":"Tao","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":883151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Luke","contributorId":197027,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","affiliations":[],"preferred":false,"id":883106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Matthew","contributorId":329726,"corporation":false,"usgs":false,"family":"Simpson","given":"Matthew","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":883107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hatchett, Benjamin J. 0000-0003-1066-3601","orcid":"https://orcid.org/0000-0003-1066-3601","contributorId":214405,"corporation":false,"usgs":false,"family":"Hatchett","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":39033,"text":"Division of Atmospheric Sciences, Desert Research Institute, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":883108,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tardy, Alexander","contributorId":329727,"corporation":false,"usgs":false,"family":"Tardy","given":"Alexander","email":"","affiliations":[{"id":12788,"text":"National Weather Service","active":true,"usgs":false}],"preferred":false,"id":883109,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883110,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Castellano, Christopher","contributorId":329728,"corporation":false,"usgs":false,"family":"Castellano","given":"Christopher","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":883111,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laber, Jayme L.","contributorId":192864,"corporation":false,"usgs":false,"family":"Laber","given":"Jayme","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":883112,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Steinhoff, Daniel","contributorId":329730,"corporation":false,"usgs":false,"family":"Steinhoff","given":"Daniel","email":"","affiliations":[{"id":34004,"text":"Scripps Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":883113,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70248520,"text":"70248520 - 2023 - Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability","interactions":[],"lastModifiedDate":"2023-09-15T13:08:12.301905","indexId":"70248520","displayToPublicDate":"2023-09-15T07:46:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability","docAbstract":"Effective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point-transect distance sampling survey on Mauna Kea, Hawai‘i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit-specific density surface maps. We found that visit-specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within-visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.1471","usgsCitation":"Camp, R.J., Asing, C.K., Banko, P.C., Berry, L., Brinck, K., Farmer, C., and Genz, A., 2023, Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability: Wildlife Society Bulletin, v. 47, no. 3, e1471, 12 p., https://doi.org/10.1002/wsb.1471.","productDescription":"e1471, 12 p.","ipdsId":"IP-141510","costCenters":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":442092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1471","text":"Publisher Index Page"},{"id":420826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hawai'i, Mauna Kea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.46881876229043,\n 19.83012427098143\n ],\n [\n -155.54063798804242,\n 19.820472473849165\n ],\n [\n -155.5293521097099,\n 19.793927010622525\n ],\n [\n -155.50626735857531,\n 19.77075644297679\n ],\n [\n -155.4539419226703,\n 19.76448050106208\n ],\n [\n -155.45445491714,\n 19.80068445784383\n ],\n [\n -155.46881876229043,\n 19.83012427098143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":883143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asing, Chauncey K.","contributorId":272645,"corporation":false,"usgs":false,"family":"Asing","given":"Chauncey","email":"","middleInitial":"K.","affiliations":[{"id":40951,"text":"University of Hawai‘i - Mānoa","active":true,"usgs":false}],"preferred":false,"id":883144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":883145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berry, Lainie","contributorId":272646,"corporation":false,"usgs":false,"family":"Berry","given":"Lainie","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":883146,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":883150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farmer, Chris","contributorId":150179,"corporation":false,"usgs":false,"family":"Farmer","given":"Chris","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false}],"preferred":false,"id":883148,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Genz, Ayesha 0000-0002-2916-1436","orcid":"https://orcid.org/0000-0002-2916-1436","contributorId":196671,"corporation":false,"usgs":false,"family":"Genz","given":"Ayesha","email":"","affiliations":[],"preferred":false,"id":883149,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248733,"text":"70248733 - 2023 - Discharge estimation using video recordings from small unoccupied aircraft systems","interactions":[],"lastModifiedDate":"2023-09-19T12:20:05.292856","indexId":"70248733","displayToPublicDate":"2023-09-15T07:17:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2338,"text":"Journal of Hydraulic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Discharge estimation using video recordings from small unoccupied aircraft systems","docAbstract":"Understanding the accuracy and appropriate application scale of satellite-derived maps of vegetation cover is essential for effective management of the vast, remote rangelands of the world. However, the underlying models are updated frequently and may combine with rapidly changing vegetation conditions to cause variations in accuracy and precision over time. We sought to assess how model performance changed between different versions of satellite-derived cover products (Rangeland Analysis Platform, RAP, and Rangeland Condition Monitoring and Assessment Protocol, RCMAP) and how the performance of LandCart compared to RAP and RCMAP. Additionally, we asked how variability in agreement between LandCart and field-based models varied with scale. We utilized an intensive dataset of grid-point intercept functional group cover data collected between 2016 and 2020 across the ∼113 kHA 2015 Soda Wildfire to 1) evaluate r2 agreement between versions of each satellite-derived product and plot-level field data and 2) assess relative standard error of agreement in cover between LandCart and continuous field-based Empirical Bayesian Kriging (EBK) regression models. Agreement between satellite- compared to field-plot values of cover (r2) increased for RCMAP Version 5.0 compared to Version 2.0, but there were negligible changes between versions of RAP. Despite this, r2 values of RCMAP and LandCart were nearly always less than RAP. Variability in agreement between EBK regression model cover and LandCart-derived cover decreased with the scale of consideration. Variability in agreement between satellite-derived cover products and field-based metrics is lowest at larger scale (mega-fire or regional) and varies from year to year and across versions, which could complicate detection of temporal changes in plant cover.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2023.110950","usgsCitation":"Applestein, C., and Germino, M., 2023, Satellite-derived plant cover maps vary in performance depending on version and product: Ecological Indicators, v. 155, 110950, 8 p., https://doi.org/10.1016/j.ecolind.2023.110950.","productDescription":"110950, 8 p.","ipdsId":"IP-152901","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":442098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2023.110950","text":"Publisher Index Page"},{"id":420825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.56338308098071,\n 43.926296989230224\n ],\n [\n -117.56338308098071,\n 42.354755589015696\n ],\n [\n -115.93309004811645,\n 42.354755589015696\n ],\n [\n -115.93309004811645,\n 43.926296989230224\n ],\n [\n -117.56338308098071,\n 43.926296989230224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"155","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":883089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":883090,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250012,"text":"70250012 - 2023 - Stocking fish in inland waters: Opportunities and risks for sustainable food systems","interactions":[],"lastModifiedDate":"2023-11-14T12:43:11.951223","indexId":"70250012","displayToPublicDate":"2023-09-15T06:41:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Stocking fish in inland waters: Opportunities and risks for sustainable food systems","docAbstract":"Stocking is one of the foremost tools in the inland fisheries management toolbox, but it comes with both opportunities and risks. Stocking is often used as compensation for depleted wild populations, particularly where recruitment processes have been disrupted, but it can introduce disease, disrupt community structures, reduce genetic integrity, and cause conflicts between fishery stakeholders. Despite its widespread use, examples of effective stocking for food fisheries in inland waters are sparse in the peer-reviewed literature. Nevertheless, it is well established that stocking is frequently used to maintain fish yield, so there is a need to conduct the practice in a robust manner that minimises the potential risks. This paper serves as the front matter for a special section of Fisheries Management and Ecology focused on fresh waters feeding the world, which resulted from two panel sessions, one focused on aquaculture and one focused on stocking, hosted by the international InFish research network (https://infish.org/). The paper highlights current practices of fish stock enhancement in inland waters for food, examines potential synergies and interactions of stock enhancement programmes with aquaculture, and provides an outline framework for responsible management of fish stock enhancement.
The U.S. Geological Survey (USGS) assessed undiscovered potash resources in the Elk Point Basin in Canada and the United States as part of a global mineral resource assessment. The Elk Point Basin is a large, Middle Devonian (Givetian) intracratonic evaporite basin covering approximately 1,200,000 square kilometers (km2) and filled mainly with marine evaporite and minor clastic sedimentary rocks that contain stratabound potash-bearing salt. The potash-bearing salt is concentrated in four stratigraphic members (Patience Lake, Belle Plaine, White Bear, and Esterhazy) in the upper 100 meters (m) of the Prairie Evaporite and are separated by beds of halite (NaCl) that contain lesser—presently non-economic—amounts of sylvite (KCl) and carnallite (KMgCl3·6H2O). The principal ore-bearing salt contains mainly sylvite. Four permissive tracts were defined that permit the presence of undiscovered stratabound potash (both sylvite- and carnallite-bearing salt) using geological criteria.
Permissive tracts are defined by the spatial extent of each stratigraphic member that is at least 1 m thick, are less than 3 kilometers (km) from the surface, contain at least 4 percent equivalent potassium oxide (K2O), and contain the currently known resources. The permissive tracts include known potash deposits and potash occurrences as wells or mines not in production and show where undiscovered potash resources may be present. Well data are used to define the extent, thickness, average K2O equivalent grades, and volumes of each member. Data were supplied by the Saskatchewan Geological Survey or were obtained from published National Instrument (NI) 43-101 technical reports and other published reports, such as annual 10-K reports or news releases.
The Elk Point Basin is the world’s largest source of potash, producing 23.0 million metric tons (Mt) of potassium chloride (KCl) (the equivalent of about 14.4 Mt of K2O) in 2018. In terms of global importance, the Elk Point Basin may contain 40 to greater than 50 percent of the world’s potash resources. Since 1962, potash companies have mined more than 1.5 trillion metric tons of ore containing 605 Mt of KCl (the equivalent of about 380 Mt of K2O). The total value of the ore produced through 2018 is on the order of $70 trillion (CAD). Potash is currently produced from eight conventional and three underground solution mines at depths ranging from 900 m to nearly 1,800 m. Estimates of the amount of potash in the Elk Point Basin vary considerably and the data and methods used in those estimations are not well documented. Known potash resources are approximately 99 billion metric tons (Bt) of ore containing 22 Bt of K2O equivalent.
As a result of new mine openings and increased production capacity at existing mines, the total production capacity of mines in the Elk Point Basin has increased significantly (to about 32.8 Mt of KCl or 22.8 Mt of K2O equivalent per year). Additional production capacity of about 31 Mt of KCl (or 17 Mt of K2O equivalent) per year could be realized over the next decade if several current (as of 2019) exploration and development projects reach production status.
Stratabound potash-bearing salt of the Prairie Evaporite presently underlies a total area of about 188,000 km2 and has a total volume of about 2,690 cubic kilometers (km3). Post-depositional solution processes considerably modified the mineralogy and presence of the potash-bearing salt. These changes had a profound effect on the volume and grade of potash resources that remained in the Prairie Evaporite and are a major consideration of exploration and mining operations as well as in this assessment of undiscovered potash resources.
This USGS assessment includes the locations and possible amounts of undiscovered potash resources in the Prairie Evaporite. Volumes for each stratigraphic member were computed using member thicknesses and areal extent modified by actual, estimated geologic loss owing to salt dissolution and extraction ratios, as well as estimated distribution of carnallite and sylvite. Both sylvite- and carnallite-bearing salts were assessed for potash in this study. The assessment uses modern published grade and tonnage data. The amount of undiscovered potash is estimated by using Monte Carlo simulations to combine volume estimates of the potash-bearing members with probability distributions for average grade and bulk density.
Mean potash grades (expressed as percentage of K2O equivalent) calculated using drill core analyses are 17.76 for the Patience Lake Member, 15.98 for the Belle Plaine Member, 10.66 for the White Bear Member, and 15.30 for the Esterhazy Member. Geologic losses reported as extraction ratios during mining may range from 27.5 to 41.6 percent and are dependent on mining method and local geologic conditions. The assessment determined that mean estimated undiscovered K2O equivalent resources for the Patience Lake, Belle Plaine, White Bear, and Esterhazy Members are 340, 220, 34, and 190 Bt, respectively, and estimated a total mean of 790 Bt for the entire Prairie Evaporite above a depth of 3 km. The total mineralized rock tonnage is estimated to be about 5,000 Bt. Most of the assessed potash is located within Saskatchewan with lesser amounts in Alberta and Manitoba as well as Montana and North Dakota within the United States.
Although carnallite is mined for potash in Europe, it has historically been avoided in mining plans for potash-producing companies in Saskatchewan because of mining, processing, and grade considerations. Carnallite-rich salt is locally present in concentrations and volumes that could be a significant resource of magnesium chloride (MgCl2) obtained as a byproduct of processing the carnallite for potash. Previously estimated reserves (not NI 43-101 compliant) of mineralized material from 1955 to 2019 are 695 Mt at 22.1 percent MgCl2. The total amount of K2O equivalent as carnallite was estimated during this USGS assessment to be about 120 Bt (or 180 Bt KCl). With uncertainties in defining the areal extent of carnallite in each of the potash-bearing members, the amount of MgCl2 as carnallite in the Elk Point Basin could be approximately 180 Bt.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090CC","usgsCitation":"Cocker, M.D., Orris, G.J., Dunlap, P., Yang, C., and Bliss, J.D., 2023, Geology and undiscovered resource assessment of the potash-bearing, Middle Devonian (Givetian), Prairie Evaporite, Elk Point Basin, Canada and United States: U.S. Geological Survey Scientific Investigations Report 2010–5090–CC, 145 p. and data files, https://doi.org/10.3133/sir20105090cc.","productDescription":"Report: ix, 145 p.; Spatial Data; Table; Readme","numberOfPages":"145","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053948","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":420793,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2010/5090/cc/sir20105090cc_readme.txt","size":"20 KB","linkFileType":{"id":2,"text":"txt"}},{"id":420792,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/cc/sir20105090cc.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420791,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/cc/covrthb.jpg"},{"id":500441,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115404.htm","linkFileType":{"id":5,"text":"html"}},{"id":420795,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/cc/sir20105090cc_gis.zip","text":"GIS data","size":"5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":420794,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2010/5090/cc/sir20105090cc_tableD1.xlsx","text":"Table D1","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"Canada, United States","otherGeospatial":"Elk Point basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.62003370031768,\n 47.834501224842995\n ],\n [\n -101.94859207917939,\n 46.78881376731823\n ],\n [\n -99.38036924401605,\n 47.064056171229\n ],\n [\n -98.5222551132618,\n 47.90409118922611\n ],\n [\n -98.07428783462548,\n 49.274981575913074\n ],\n [\n -99.04751209813486,\n 51.323577075700086\n ],\n [\n -100.3990594914377,\n 52.712828172299055\n ],\n [\n -101.88661026215635,\n 53.29557322524738\n ],\n [\n -105.10333042439493,\n 55.3188488619183\n ],\n [\n -109.45509609372056,\n 56.74298922060379\n ],\n [\n -112.20142702562293,\n 60.35496296087831\n ],\n [\n -117.3247083017325,\n 60.31647251233596\n ],\n [\n -118.81440244912545,\n 59.02540113843418\n ],\n [\n -120.91916585824947,\n 57.85206145280617\n ],\n [\n -122.23992348667531,\n 57.6515156864875\n ],\n [\n -121.81553356709298,\n 55.96853063691535\n ],\n [\n -114.91051096218939,\n 55.415073221874025\n ],\n [\n -116.12311653915395,\n 53.68014339688571\n ],\n [\n -114.36068663970394,\n 51.40761693922349\n ],\n [\n -114.73749958809637,\n 49.58765797184398\n ],\n [\n -108.67606009110042,\n 49.31809944743287\n ],\n [\n -105.62003370031768,\n 47.834501224842995\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information
Mineral Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
913 National Center
Reston, VA 20192
The position of mangrove forests in the dynamic intertidal zone means that they are expected to be heavily impacted by climate change. Much focus is put on mangroves and their response to sea-level rise, but this ecosystem is exposed to a much broader range of climate change stressors, including increased storminess and waves, more dynamic and unpredictable precipitation patterns, and increases in air and sea surface temperatures, particularly at their latitudinal limits. We show that individual climate change stressors can have (rarely considered) positive, as well as negative impacts on mangroves and associated ecosystem functions such as carbon sequestration. While we generally study climate change stressors individually, they are not expected to act in isolation with other climate change stressors or with anthropogenic stressors. We present a stressor interaction framework previously suggested for coral reefs, and adapt it for use in mangroves, using the recent mangrove dieback in northern Australia as a case study. We show the benefits of moving mangrove and climate change research beyond the study of single stressors and towards identifying key synergistic and antagonistic interactions between climate change stressors.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Climate Change and Estuaries","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","doi":"10.1201/9781003126096-22","usgsCitation":"Friess, D., Chen, L., Cormier, N., Krauss, K., Lovelock, C.E., Raw, J.L., Rogers, K., Saintilan, N., and Sidik, F., 2023, Mangrove forests and climate change: Impacts and interactions, chap. of Climate Change and Estuaries, p. 381-400, https://doi.org/10.1201/9781003126096-22.","productDescription":"20 p.","startPage":"381","endPage":"400","ipdsId":"IP-126290","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":421192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Kennish, Michael J.","contributorId":111903,"corporation":false,"usgs":true,"family":"Kennish","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":884236,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Paerl, Hans W.","contributorId":172724,"corporation":false,"usgs":false,"family":"Paerl","given":"Hans","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":884237,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Crosswell, Joseph","contributorId":217003,"corporation":false,"usgs":false,"family":"Crosswell","given":"Joseph","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":884238,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Friess, Daniel A.","contributorId":35454,"corporation":false,"usgs":false,"family":"Friess","given":"Daniel A.","affiliations":[{"id":25407,"text":"Department of Geography, National University of Singapore","active":true,"usgs":false}],"preferred":false,"id":879414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Luzhen","contributorId":194706,"corporation":false,"usgs":false,"family":"Chen","given":"Luzhen","email":"","affiliations":[],"preferred":false,"id":879415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cormier, Nicole 0000-0003-2453-9900","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":214726,"corporation":false,"usgs":false,"family":"Cormier","given":"Nicole","affiliations":[{"id":16788,"text":"Macquarie University","active":true,"usgs":false}],"preferred":false,"id":879416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":222378,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":879417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovelock, Catherine E.","contributorId":215562,"corporation":false,"usgs":false,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":39280,"text":"School of Biological Sciences, The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":879418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raw, Jacqueline L.","contributorId":317837,"corporation":false,"usgs":false,"family":"Raw","given":"Jacqueline","email":"","middleInitial":"L.","affiliations":[{"id":69167,"text":"Department of Botany and Institute for Coastal and Marine Research, Nelson Mandela University","active":true,"usgs":false}],"preferred":false,"id":879419,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogers, Kerrylee","contributorId":64151,"corporation":false,"usgs":false,"family":"Rogers","given":"Kerrylee","email":"","affiliations":[{"id":16754,"text":"University of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":879420,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saintilan, Neil","contributorId":300648,"corporation":false,"usgs":false,"family":"Saintilan","given":"Neil","affiliations":[{"id":65215,"text":"Macquarie University, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":879421,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sidik, Frida","contributorId":149631,"corporation":false,"usgs":false,"family":"Sidik","given":"Frida","email":"","affiliations":[],"preferred":false,"id":879422,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70248727,"text":"70248727 - 2023 - PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations","interactions":[],"lastModifiedDate":"2023-09-18T14:49:18.727694","indexId":"70248727","displayToPublicDate":"2023-09-14T09:19:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"PopEquus: A predictive modeling tool to support management decisions for free-roaming horse populations","title":"PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations","docAbstract":"Feral horse (Equus caballus) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus, that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4632","usgsCitation":"Folt, B.P., Schoenecker, K., Ekernas, L., Edmunds, D.R., and Hannon, M.T., 2023, PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations: Ecosphere, v. 14, no. 9, e4632, 20 p., https://doi.org/10.1002/ecs2.4632.","productDescription":"e4632, 20 p.","ipdsId":"IP-141050","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442104,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4632","text":"Publisher Index Page"},{"id":435178,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HVUA6D","text":"USGS data release","linkHelpText":"Scenario Analysis of Management Alternatives for Free-roaming Horse Populations (Version 1.0.0)"},{"id":435177,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NMRQDG","text":"USGS data release","linkHelpText":"PopEquus: A Predictive Modeling Tool to Support Management Decisions for Free-roaming Horse Populations, Version 1.0.1"},{"id":420891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Folt, Brian Patrick 0000-0003-2278-2018","orcid":"https://orcid.org/0000-0003-2278-2018","contributorId":328937,"corporation":false,"usgs":true,"family":"Folt","given":"Brian","email":"","middleInitial":"Patrick","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":883322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":883323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekernas, L. Stefan 0000-0002-9205-1985","orcid":"https://orcid.org/0000-0002-9205-1985","contributorId":329791,"corporation":false,"usgs":false,"family":"Ekernas","given":"L. Stefan","affiliations":[{"id":78719,"text":"The Denver Zoo","active":true,"usgs":false}],"preferred":false,"id":883324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":883325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hannon, Mark T. 0000-0003-1050-749X mhannon@usgs.gov","orcid":"https://orcid.org/0000-0003-1050-749X","contributorId":329792,"corporation":false,"usgs":true,"family":"Hannon","given":"Mark","email":"mhannon@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":883326,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248801,"text":"70248801 - 2023 - Blue carbon in a changing climate and a changing context","interactions":[],"lastModifiedDate":"2023-09-21T13:42:13.711053","indexId":"70248801","displayToPublicDate":"2023-09-14T08:39:29","publicationYear":"2023","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Blue carbon in a changing climate and a changing context","docAbstract":"Blue carbon, a convenient term to encompass the climate mitigation value of coastal carbon dynamics, has received global policy attention and growing datasets to support management actions. Carbon stock assessments in mangroves, seagrass, and tidal marshes document significant carbon storage in soils. Models illustrate significant downward fluxes of carbon dioxide and limited methane emissions, making tidal wetland preservation and restoration notably potent for carbon dioxide removal (CDR). Natural variation in different carbon stocks and fluxes has led to prioritization efforts to characterize coastal lands across physical and biological gradients. However, a larger concern beyond upscaling carbon dynamics is the resilience of these stocks and fluxes with global changes. Data-informed models have greatly improved our assessments of the vulnerability of soil and biomass stocks, greenhouse gas (GHG) balance, and spatial extents. Accelerated sea-level rise is increasingly concerning, but its impacts vary by resilience context, as very few coastal lands are without direct human impact. As the landscape context has changed, blue carbon fluxes have also shifted in terms of importance and distribution. New incentives for tidal ecosystem management are expanding boundaries to include algal carbon and tidal transport of alkalinity, which bring additional co-benefits to coastal waters. Using examples from the conterminous USA on blue carbon stocks, radiative balance, and extent, this chapter explores timelines of physical and biogeochemical stressors and their application to past, current, and future climate mitigation functions of coastal ecosystems.
","largerWorkTitle":"Climate change and estuaries","language":"English","publisher":"CRC Press","usgsCitation":"Windham-Myers, L., 2023, Blue carbon in a changing climate and a changing context, chap. of Climate change and estuaries, p. 203-214.","productDescription":"12 p.","startPage":"203","endPage":"214","ipdsId":"IP-144897","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":421025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421024,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/chapters/edit/10.1201/9781003126096-12/blue-carbon-changing-climate-changing-context-lisamarie-windham-myers?context=ubx&refId=09c63ae2-147c-4d3e-a44e-e123f1046fc4","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Kennish, Michael J.","contributorId":111903,"corporation":false,"usgs":true,"family":"Kennish","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":883743,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Paerl, Hans W.","contributorId":172724,"corporation":false,"usgs":false,"family":"Paerl","given":"Hans","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":883744,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Crosswell, Joseph","contributorId":217003,"corporation":false,"usgs":false,"family":"Crosswell","given":"Joseph","email":"","affiliations":[{"id":36909,"text":"CSIRO","active":true,"usgs":false}],"preferred":false,"id":883745,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":883711,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248880,"text":"70248880 - 2023 - Molecular data validate historical and contemporary distributions of Pleurobema riddellii (Bivalvia: Unionidae) and help guide conservation and recovery efforts","interactions":[],"lastModifiedDate":"2023-09-25T12:11:32.614155","indexId":"70248880","displayToPublicDate":"2023-09-14T07:09:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Molecular data validate historical and contemporary distributions of Pleurobema riddellii (Bivalvia: Unionidae) and help guide conservation and recovery efforts","docAbstract":"Accurate taxonomic and distributional information are arguably the most critical components of conservation status assessments but can be greatly affected by misidentifications. The Louisiana pigtoe Pleurobema riddellii is a freshwater mussel proposed as threatened under the US Endangered Species Act. The species belongs to the tribe Pleurobemini, which includes multiple taxa that are inherently challenging to identify without molecular data. We validated historical and recent survey records of P. riddellii using a combination of DNA sequence data and morphological characters to provide a more definitive assessment of range and spatiotemporal trends in distribution. Our comprehensive assessment identified specimens collected from the Pearl drainage as P. riddellii, extending the species’ known range into eastern Gulf of Mexico drainages. Contemporary records were unavailable from the Trinity drainage; however, we designed novel minibarcode PCR primers and used historical DNA from a specimen collected in the late 1800s to confirm the historical presence of P. riddellii at the species’ type locality in the Trinity River near Dallas, Texas, USA. Our range-wide genetic diversity assessment provides strong support for 2 main geographic groups, the Ouachita and all remaining populations, with individuals from the Pearl and Trinity drainages sharing haplotypes with conspecifics from other drainages. Available data suggest P. riddellii has been extirpated from a significant portion of the historical range, including the entire Trinity drainage. Additional surveys in Lake Pontchartrain, Trinity, and other drainages in the eastern periphery of the species’ range may provide additional clarity on the distribution and conservation status of P. riddellii.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01266","usgsCitation":"Johnson, N., Beaver, C., Kiser, A., Duplessis, M.A., Wagner, M.D., Ellwanger, R.J., Robertson, C.R., Kinney, S.D., Gregory, B.B., Wolverton, S., Randklev, C.R., Hartfield, P.D., Williams, J.D., and Smith, C.H., 2023, Molecular data validate historical and contemporary distributions of Pleurobema riddellii (Bivalvia: Unionidae) and help guide conservation and recovery efforts: Endangered Species Research, v. 52, p. 1-15, https://doi.org/10.3354/esr01266.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-151124","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442105,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01266","text":"Publisher Index Page"},{"id":435179,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VGXMGN","text":"USGS data release","linkHelpText":"Molecular and distributional data used to investigate misidentifications, population genetic diversity, and spatiotemporal trends in distribution for Pleurobema riddellii to help guide ESA listing decisions"},{"id":421123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":216879,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":884023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaver, Caitlin 0000-0002-9269-7604","orcid":"https://orcid.org/0000-0002-9269-7604","contributorId":219703,"corporation":false,"usgs":true,"family":"Beaver","given":"Caitlin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":884024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiser, Alexander H.","contributorId":291859,"corporation":false,"usgs":false,"family":"Kiser","given":"Alexander H.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":884025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duplessis, Matthew A.","contributorId":330123,"corporation":false,"usgs":false,"family":"Duplessis","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":884026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Matthew D.","contributorId":330124,"corporation":false,"usgs":false,"family":"Wagner","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":884027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellwanger, Robert J.","contributorId":330125,"corporation":false,"usgs":false,"family":"Ellwanger","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":78821,"text":"Mississippi Department of Wildlife, Fisheries, and Parks","active":true,"usgs":false}],"preferred":false,"id":884028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robertson, Clinton R.","contributorId":290319,"corporation":false,"usgs":false,"family":"Robertson","given":"Clinton","email":"","middleInitial":"R.","affiliations":[{"id":62404,"text":"Texas Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":884029,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kinney, Sean D.","contributorId":330127,"corporation":false,"usgs":false,"family":"Kinney","given":"Sean","email":"","middleInitial":"D.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":884030,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gregory, Beau B.","contributorId":330129,"corporation":false,"usgs":false,"family":"Gregory","given":"Beau","email":"","middleInitial":"B.","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":884031,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wolverton, Steve","contributorId":229617,"corporation":false,"usgs":false,"family":"Wolverton","given":"Steve","email":"","affiliations":[{"id":34637,"text":"University of North Texas","active":true,"usgs":false}],"preferred":false,"id":884032,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Randklev, Charles R.","contributorId":202530,"corporation":false,"usgs":false,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":884033,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hartfield, Paul D.","contributorId":221758,"corporation":false,"usgs":false,"family":"Hartfield","given":"Paul","email":"","middleInitial":"D.","affiliations":[{"id":40418,"text":"U.S. Fish and Wildlife Service, Jackson, MS","active":true,"usgs":false}],"preferred":false,"id":884034,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, James D.","contributorId":17690,"corporation":false,"usgs":false,"family":"Williams","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":884035,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Smith, Chase H. 0000-0002-1499-0311","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":225140,"corporation":false,"usgs":false,"family":"Smith","given":"Chase","email":"","middleInitial":"H.","affiliations":[{"id":13716,"text":"Baylor University","active":true,"usgs":false}],"preferred":false,"id":884036,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70248991,"text":"70248991 - 2023 - An inconvenient trend: Decadal decline in ground height of swamps in Southern Illinois","interactions":[],"lastModifiedDate":"2023-12-21T14:24:44.353814","indexId":"70248991","displayToPublicDate":"2023-09-14T06:55:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"An inconvenient trend: Decadal decline in ground height of swamps in Southern Illinois","docAbstract":"An understanding of the long-term trends of ground height and sedimentation in a landscape context can provide a framework to better understand the impacts of agricultural development on floodplain processes. This study examined long-term changes in ground height using surface elevation tables (SETs) and sediment deposition measurements in the Cache River floodplains of Southern Illinois including Taxodium distichum swamps in Crawford Tract and Eagle Pond from 2019 to 2022 and in Deer Pond and Snake Hole from 2005 to 2022. The mean ground heights of these swamps decreased by a mean of −0.33, −033, −0.28 and −0.19 cm year−1, respectively. Annual sediment deposition on feldspar markers in Crawford Tract was negligible from 2020 to 2022 (range of annual deposition depth: <0.1 to 0.4 cm). However, sediment deposition at Deer Pond and Snake Hole was higher from 2006 to 2021 (range of annual deposition depth: <0.1–2.5 and <1 to 2.0 cm, respectively). In some years, the sites appeared scoured, and the feldspar markers had disappeared. The loss of ground height in these swamps could be related to erosion, increased precipitation and/or downcutting of the channel following the construction of a major diversion to dewater the floodplain via the Post Creek Cutoff in the early 1900s. Despite the limitations of this study toward revealing specific mechanisms linking floodplain erosion to channel downcutting and the engineered features of this landscape, this study clearly showed that Cache floodplains have lost height in past decades with potential consequences for the conservation of natural forests.
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SGA 2023: Mineral resources in a changing world","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SGA 2023: Mineral Resources in a Changing World","conferenceDate":"August 29-September 1, 2023","conferenceLocation":"Zürich, Switzerland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Mauk, J.L., Funk, J.A., and Karl, N., 2023, Can the mining industry meet global demand for critical minerals?, in Proceedings of SGA 2023: Mineral resources in a changing world, v. 5, Zürich, Switzerland, August 29-September 1, 2023, p. 67-70.","productDescription":"4 p.","startPage":"67","endPage":"70","ipdsId":"IP-153004","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":420760,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://sga2023.ch/technical-programme/"},{"id":420776,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mauk, Jeffrey L. 0000-0002-6244-2774 jmauk@usgs.gov","orcid":"https://orcid.org/0000-0002-6244-2774","contributorId":4101,"corporation":false,"usgs":true,"family":"Mauk","given":"Jeffrey","email":"jmauk@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":882943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Jonathan Andrew 0000-0001-7897-687X","orcid":"https://orcid.org/0000-0001-7897-687X","contributorId":297164,"corporation":false,"usgs":true,"family":"Funk","given":"Jonathan","email":"","middleInitial":"Andrew","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":882944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karl, Nick 0000-0003-2858-2498 nkarl@usgs.gov","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":178317,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"nkarl@usgs.gov","affiliations":[],"preferred":true,"id":882945,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70248449,"text":"70248449 - 2023 - Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields","interactions":[],"lastModifiedDate":"2023-09-13T19:15:08.088286","indexId":"70248449","displayToPublicDate":"2023-09-13T13:51:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields","docAbstract":"Understanding land surface change in and sediment export out of proglacial landscapes is critical for understanding geohazard and flood risks over engineering timescales and characterizing landscape evolution over geomorphic timescales. We used automated Structure from Motion software to process historical aerial photographs and, with modern lidar data, generated a high-resolution DEM time series with coverage over 10 glacierized watersheds on Mount Baker, Washington, USA for the time period between 1947 and 2015. We measured basin-wide sediment yields and sediment redistribution on hillslopes and in stream channels. Slopes within most measured erosion sites are above theoretical and observed debris-flow thresholds. We observed significant erosion of hillslopes and limited deposition on hillslopes and in stream channels. Sediment delivery ratios during time periods with net erosion averaged 0.73. We determined, consistent with previous field observations, that debris flows originating from moraines are a primary erosion mechanism in proglacial zones on Mount Baker. Time series measurements indicate that temporal variability in erosion rates is associated with climate oscillations, with higher erosion rates during cooler-wetter periods. Basin-wide sediment yield is positively correlated with lithology (r2 = 0.54), hillslope angle (r2 = 0.52), drainage area (r2 = 0.82), and negatively correlated with stream channel slope (r2 = 0.67). Topographic differences between high and low yielding basins indicate that spatial variability in erosion on Mount Baker is sensitive to Pleistocene and Holocene glacial and volcanic activity. Specific sediment yields in six basins averaged 4600 ton/km2/yr, consistent with global measurements in glacierized catchments. Specific sediment yield decreased with increasing basin area, with total loads in the downstream main stem Nooksack River estimated between 480 and 820 ton/km2/yr. Proglacial sediment yields account for between 18 and 32 % of total sediment load in the main stem Nooksack River and exceed contributions by bluff and terrace erosion, which account for between 8 and 13 % of total load. Our findings indicate that erosion in glacierized basins is sensitive to decadal climate oscillations and that high proglacial sediment yields provide an important contribution to river systems downstream, particularly in catchments where upland topography and lithology is favorable.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.108805","usgsCitation":"Schwat, E., Istanbulluoglu, E., Horner-Devine, A., Anderson, S.W., Knuth, F., and Shean, D., 2023, Multi-decadal erosion rates from glacierized watersheds on Mount Baker, Washington, USA, reveal topographic, climatic, and lithologic controls on sediment yields: Geomorphology, v. 438, 108805, 17 p., https://doi.org/10.1016/j.geomorph.2023.108805.","productDescription":"108805, 17 p.","ipdsId":"IP-152751","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":442107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2023.108805","text":"Publisher Index Page"},{"id":420774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Koma Kulshan, Mount Baker","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.85505311805078,\n 48.71738721735028\n ],\n [\n -121.8138912926704,\n 48.69120451475976\n ],\n [\n -121.72859208826776,\n 48.669266019808475\n ],\n [\n -121.67503212271245,\n 48.72229495768988\n ],\n [\n -121.6804873043895,\n 48.74224816877816\n ],\n [\n -121.66610546178667,\n 48.77461439590772\n ],\n [\n -121.7603313271151,\n 48.82361440118996\n ],\n [\n -121.86298792776248,\n 48.840916292756305\n ],\n [\n -121.92101122378057,\n 48.82034922330564\n ],\n [\n -121.94729528095108,\n 48.77134602689094\n ],\n [\n -121.91357233967562,\n 48.74061295759708\n ],\n [\n -121.85505311805078,\n 48.71738721735028\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"438","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwat, Eli","contributorId":299744,"corporation":false,"usgs":false,"family":"Schwat","given":"Eli","email":"","affiliations":[],"preferred":false,"id":882951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Istanbulluoglu, Erkan 0000-0001-9453-4676","orcid":"https://orcid.org/0000-0001-9453-4676","contributorId":295348,"corporation":false,"usgs":false,"family":"Istanbulluoglu","given":"Erkan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":882952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horner-Devine, Alex 0000-0003-2323-7150","orcid":"https://orcid.org/0000-0003-2323-7150","contributorId":295351,"corporation":false,"usgs":false,"family":"Horner-Devine","given":"Alex","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":882953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knuth, Friedrich","contributorId":299741,"corporation":false,"usgs":false,"family":"Knuth","given":"Friedrich","email":"","affiliations":[],"preferred":false,"id":882955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shean, David","contributorId":299742,"corporation":false,"usgs":false,"family":"Shean","given":"David","affiliations":[],"preferred":false,"id":882956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248439,"text":"70248439 - 2023 - Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","interactions":[],"lastModifiedDate":"2023-09-13T18:44:22.909442","indexId":"70248439","displayToPublicDate":"2023-09-13T13:33:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","title":"Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework","docAbstract":"Introduction: Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined.
Methods: To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region.
Results: A one standard deviation increase in the modeled contributions of elevated AMR from bovine sources or land-applied waste sources [land application of biosolids, sludge, and industrial wastewater (i.e., food processing) and domestic (i.e., municipal and septage)] was associated with 34–80% and 33–77% increases in the relative abundances of the ARGs in riverbed sediment and surface water, respectively. Sources influenced environmental AMR at overland distances of up to 13 km.
Discussion: Our study corroborates previous evidence of offsite migration of microbial pollution from bovine sources and newly suggests offsite migration from land-applied waste. With FIT, we estimated the distance-based influence range overland and downstream around sources to model the impact these sources may have on AMR at unsampled sites. This modeling supports targeted monitoring of AMR from sources for future exposure and risk mitigation efforts.
","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmicb.2023.1223876","usgsCitation":"Wiesner-Friedman, C., Beattie, R.E., Stewart, J.R., Hristova, K.R., and Serre, M.L., 2023, Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework: Frontiers in Microbiology, v. 14, 1223876, 14 p., https://doi.org/10.3389/fmicb.2023.1223876.","productDescription":"1223876, 14 p.","ipdsId":"IP-149826","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":442109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2023.1223876","text":"Publisher Index Page"},{"id":420771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Kewaunee County","otherGeospatial":"Ahnapee River, East Twin River, Kewaunee River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":3073,\"properties\":{\"name\":\"Kewaunee\",\"state\":\"WI\"},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.3761,44.6754],[-87.3774,44.674],[-87.381,44.6636],[-87.3858,44.6545],[-87.3911,44.6473],[-87.3944,44.6442],[-87.3966,44.6378],[-87.4045,44.6302],[-87.4085,44.6257],[-87.4137,44.6235],[-87.4223,44.6145],[-87.4263,44.61],[-87.4341,44.6056],[-87.442,44.6011],[-87.4428,44.5934],[-87.4468,44.5893],[-87.4502,44.5816],[-87.4544,44.5721],[-87.4604,44.5622],[-87.4664,44.555],[-87.4738,44.5455],[-87.476,44.5369],[-87.4761,44.5305],[-87.4796,44.5223],[-87.4851,44.5106],[-87.488,44.4974],[-87.4959,44.4706],[-87.5046,44.4575],[-87.5041,44.4534],[-87.5062,44.4457],[-87.5064,44.4375],[-87.5074,44.4279],[-87.5121,44.4188],[-87.5163,44.408],[-87.5191,44.3998],[-87.5212,44.3907],[-87.5209,44.3816],[-87.5218,44.3734],[-87.5232,44.3688],[-87.5279,44.3602],[-87.5351,44.3521],[-87.5386,44.3422],[-87.5368,44.338],[-87.5408,44.3331],[-87.5454,44.3277],[-87.6445,44.3273],[-87.7665,44.3271],[-87.7655,44.4146],[-87.7646,44.5017],[-87.7643,44.5888],[-87.7628,44.6477],[-87.7582,44.6522],[-87.7555,44.6558],[-87.7547,44.6608],[-87.7507,44.6667],[-87.7435,44.673],[-87.7389,44.6775],[-87.6413,44.6757],[-87.5193,44.6753],[-87.4384,44.6754],[-87.3973,44.6753],[-87.3761,44.6754]]]}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2023-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wiesner-Friedman, Corinne","contributorId":329682,"corporation":false,"usgs":false,"family":"Wiesner-Friedman","given":"Corinne","email":"","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":882931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beattie, Rachelle Elaine 0000-0002-9648-4948","orcid":"https://orcid.org/0000-0002-9648-4948","contributorId":298312,"corporation":false,"usgs":true,"family":"Beattie","given":"Rachelle","email":"","middleInitial":"Elaine","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":882932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jill R.","contributorId":329683,"corporation":false,"usgs":false,"family":"Stewart","given":"Jill","email":"","middleInitial":"R.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":882933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hristova, Krassimira R.","contributorId":298313,"corporation":false,"usgs":false,"family":"Hristova","given":"Krassimira","email":"","middleInitial":"R.","affiliations":[{"id":64527,"text":"Marquette University","active":true,"usgs":false}],"preferred":false,"id":882934,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serre, Marc L.","contributorId":329684,"corporation":false,"usgs":false,"family":"Serre","given":"Marc","email":"","middleInitial":"L.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":882935,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248448,"text":"70248448 - 2023 - Large-scale variation in lakebed properties interpreted from single-beam sonar in two Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2023-10-11T16:00:09.83459","indexId":"70248448","displayToPublicDate":"2023-09-13T13:10:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale variation in lakebed properties interpreted from single-beam sonar in two Laurentian Great Lakes","docAbstract":"Acoustic seabed classification (ASC) is an important method for understanding landscape-level physical and biological patterns in the aquatic environment. Bottom habitats in the Laurentian Great Lakes are poorly mapped to date, and will require a variety of contributors and data sources to complete. We repurposed a long-term split-beam echosounder dataset gathered for purposes of fisheries assessment to estimate lakebed properties utilizing unsupervised classification of echo return data. We interpreted first echo properties representing lakebed hardness and roughness to define and map three statistically supported lakebed classes revealed through cluster analysis. Our results indicate coherent and logical class boundaries and suggest that the dataset has promise for expanded use in ASC. To improve inferences using repeated measures, future work should focus on collecting ground truth information for areas previously surveyed and on collecting concurrent ground truth information when sampling acoustic data moving forward.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.06.001","usgsCitation":"Pecoraro, S., Esselman, P., O’Brien, T.P., Farha, S., and Warner, D., 2023, Large-scale variation in lakebed properties interpreted from single-beam sonar in two Laurentian Great Lakes: Journal of Great Lakes Research, v. 49, no. 5, p. 1204-1210, https://doi.org/10.1016/j.jglr.2023.06.001.","productDescription":"7 p.","startPage":"1204","endPage":"1210","ipdsId":"IP-132463","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467092,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2023.06.001","text":"Publisher Index Page"},{"id":435185,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z8379Y","text":"USGS data release","linkHelpText":"Lakebed features extracted from single-beam sonar in two Laurentian Great Lakes"},{"id":420766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario, Wisconsin","otherGeospatial":"Lake Huron, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.80074346386446,\n 42.75799542505797\n ],\n [\n -87.86438159430585,\n 42.61249937143569\n ],\n [\n -87.83170223152467,\n 42.43186053364542\n ],\n [\n -87.8480419129156,\n 42.383601984778664\n ],\n [\n -87.86438159430585,\n 42.291002674358424\n ],\n [\n -87.70098478040127,\n 42.04475303613668\n ],\n [\n -87.65196573623047,\n 41.91518968584535\n ],\n [\n -87.65196573623047,\n 41.862479284899365\n ],\n [\n -87.55937420835144,\n 41.73660977275378\n ],\n [\n -87.54303452696054,\n 41.68781972672946\n ],\n [\n -87.4232101967642,\n 41.61049309343707\n ],\n [\n -87.10730968988275,\n 41.59420197617578\n ],\n [\n -86.91287577966004,\n 41.68781972673071\n ],\n [\n -86.56429590999741,\n 41.878702502066346\n ],\n [\n -86.43902501933788,\n 42.10943583914215\n ],\n [\n -86.30286100775061,\n 42.22650535181015\n ],\n [\n -86.21026947987158,\n 42.451957304608186\n ],\n [\n -86.1721435566272,\n 42.6605815114099\n ],\n [\n -86.19937635894382,\n 43.06922804754538\n ],\n [\n -86.36821973331162,\n 43.34315517170518\n ],\n [\n -86.43357845887334,\n 43.49348821920839\n ],\n [\n -86.49893718443504,\n 43.639506441461776\n ],\n [\n -86.4717043821177,\n 43.686787683230534\n ],\n [\n -86.38455941470255,\n 43.812688929828965\n ],\n [\n -86.406345656556,\n 43.94999434033423\n ],\n [\n -86.4741283981799,\n 44.05800957934217\n ],\n [\n -86.33372983416018,\n 44.18230698258038\n ],\n [\n -86.30165647539467,\n 44.2481716802905\n ],\n [\n -86.22026107045023,\n 44.35896937746555\n ],\n [\n -86.20679617029468,\n 44.503600396197626\n ],\n [\n -86.17827747836347,\n 44.57548110372155\n ],\n [\n -86.21848373703246,\n 44.6693937783277\n ],\n [\n -86.04795725014573,\n 44.731499366992324\n ],\n [\n -86.04439241365434,\n 44.889877245502134\n ],\n [\n -85.95546502799279,\n 44.87574954236872\n ],\n [\n -85.9273410165523,\n 44.93042049701882\n ],\n [\n -85.84247372480716,\n 44.90739311334262\n ],\n [\n -85.77280727661727,\n 44.94232004836555\n ],\n [\n -85.69440156881475,\n 45.04055119453666\n ],\n [\n -85.62251935213231,\n 45.146833465186255\n ],\n [\n -85.6138110461084,\n 45.045594890470866\n ],\n [\n -85.66392249773105,\n 44.97997860786631\n ],\n [\n -85.62361949798068,\n 44.95522098882857\n ],\n [\n -85.67971984459497,\n 44.850233757107524\n ],\n [\n -85.64241129234041,\n 44.74786288062532\n ],\n [\n -85.52027236740635,\n 44.71627410416602\n ],\n [\n -85.39929073984148,\n 44.86682366372024\n ],\n [\n -85.3496930469861,\n 45.05315964726615\n ],\n [\n -85.35212700287576,\n 45.22964918361501\n ],\n [\n -85.30432493664912,\n 45.28241140598297\n ],\n [\n -85.15515301287562,\n 45.34299036029927\n ],\n [\n -85.00431520450076,\n 45.3423254429447\n ],\n [\n -84.81451853058019,\n 45.39939711163532\n ],\n [\n -84.98650165632989,\n 45.45816587496684\n ],\n [\n -85.04526041688744,\n 45.475580946739704\n ],\n [\n -85.08553291809326,\n 45.56062283109068\n ],\n [\n -85.03486388267129,\n 45.62141388872956\n ],\n [\n -84.90604471615353,\n 45.735298866569934\n ],\n [\n -84.73270392362537,\n 45.74950145904941\n ],\n [\n -84.56978168087255,\n 45.680358192013216\n ],\n [\n -84.47198087810587,\n 45.62342441296137\n ],\n [\n -84.33048894884351,\n 45.63348711150197\n ],\n [\n -84.24385645026486,\n 45.61236492991323\n ],\n [\n -84.10237399542454,\n 45.46595739347153\n ],\n [\n -84.04249385962876,\n 45.46669064729814\n ],\n [\n -83.9308553847782,\n 45.455572874013455\n ],\n [\n -83.7820982039511,\n 45.382236641451556\n ],\n [\n -83.72312266689082,\n 45.38843424149754\n ],\n [\n -83.61851053497833,\n 45.33990619053945\n ],\n [\n -83.48342629273088,\n 45.27211027852157\n ],\n [\n -83.34507888558228,\n 45.1384378560676\n ],\n [\n -83.38102141326404,\n 45.09694523049143\n ],\n [\n -83.49211216121174,\n 45.03072770939504\n ],\n [\n -83.46807095314482,\n 44.91916761526666\n ],\n [\n -83.36101299995073,\n 44.86423140406805\n ],\n [\n -83.3358266614697,\n 44.80444700405673\n ],\n [\n -83.36170583099641,\n 44.77001267572605\n ],\n [\n -83.32909052681995,\n 44.67577559046022\n ],\n [\n -83.3402398821653,\n 44.549856829249066\n ],\n [\n -83.39573042447435,\n 44.33242048338123\n ],\n [\n -83.57207023465351,\n 44.24066493936199\n ],\n [\n -83.60884934813035,\n 44.097789137726124\n ],\n [\n -83.71508693786456,\n 44.01592500108623\n ],\n [\n -83.87309651269968,\n 43.99362348500213\n ],\n [\n -83.94390179872458,\n 43.891658974771815\n ],\n [\n -83.94934835918845,\n 43.80131383215857\n ],\n [\n -83.98747428243284,\n 43.75805691714217\n ],\n [\n -83.98747428243284,\n 43.691143767329436\n ],\n [\n -83.85131027084556,\n 43.62809841305386\n ],\n [\n -83.68246689647778,\n 43.564986862489974\n ],\n [\n -83.62255473137994,\n 43.58471633254521\n ],\n [\n -83.52451664303703,\n 43.68720537216251\n ],\n [\n -83.4646044779392,\n 43.675388635041145\n ],\n [\n -83.41013887330458,\n 43.754122918494716\n ],\n [\n -83.35022670820605,\n 43.83275374946493\n ],\n [\n -83.31754734542488,\n 43.88380830749986\n ],\n [\n -83.22495581754586,\n 43.95442706176908\n ],\n [\n -83.11602460827658,\n 43.985786270046646\n ],\n [\n -83.06155900364192,\n 43.97794802023543\n ],\n [\n -83.00709339900727,\n 44.02496199606804\n ],\n [\n -82.93628811298171,\n 44.04062504221099\n ],\n [\n -82.81101722232218,\n 44.00929481030613\n ],\n [\n -82.73476537583343,\n 43.92697417255809\n ],\n [\n -82.64762040841761,\n 43.7737903253886\n ],\n [\n -82.62583416656413,\n 43.6004952545145\n ],\n [\n -82.57136856192884,\n 43.42669959891549\n ],\n [\n -82.54958232007539,\n 43.22065956805906\n ],\n [\n -82.52779607822127,\n 43.17301264084011\n ],\n [\n -82.50600983636714,\n 43.109425534877715\n ],\n [\n -82.45699079219635,\n 42.98603734518204\n ],\n [\n -82.2772542969015,\n 43.00993830033809\n ],\n [\n -82.11385748299692,\n 43.07760718328518\n ],\n [\n -81.96135379002006,\n 43.180956378981534\n ],\n [\n -81.87420882260422,\n 43.19684075499282\n ],\n [\n -81.75438449240787,\n 43.28809569080698\n ],\n [\n -81.67268608545592,\n 43.379213925693676\n ],\n [\n -81.67268608545592,\n 43.59655091186892\n ],\n [\n -81.68902576684619,\n 43.84453945058357\n ],\n [\n -81.67813264591912,\n 43.946584672636476\n ],\n [\n -81.72170512962668,\n 44.07976454623466\n ],\n [\n -81.57464799711302,\n 44.20874132571336\n ],\n [\n -81.58009455757688,\n 44.306263395663024\n ],\n [\n -81.4875030296972,\n 44.376379131181295\n ],\n [\n -81.43303742506257,\n 44.38416459224899\n ],\n [\n -81.24276376628094,\n 44.62176709302716\n ],\n [\n -81.24821032674483,\n 44.67988756790854\n ],\n [\n -81.253656887208,\n 44.75729093324023\n ],\n [\n -81.28633624998922,\n 44.85003828983503\n ],\n [\n -81.33535529415998,\n 44.92721384991424\n ],\n [\n -81.33535529415998,\n 45.00813674223582\n ],\n [\n -81.41160714064874,\n 45.01968783588703\n ],\n [\n -81.49875210806455,\n 45.11201270936553\n ],\n [\n -81.54777115223598,\n 45.17347978522503\n ],\n [\n -81.65670236150527,\n 45.2233729870789\n ],\n [\n -81.45517962435696,\n 45.21569995743562\n ],\n [\n -81.32990873369675,\n 45.21953660169129\n ],\n [\n -81.35714153601408,\n 45.14275453122846\n ],\n [\n -81.30267593137944,\n 45.08125431955807\n ],\n [\n -81.30267593137944,\n 45.03893448111839\n ],\n [\n -81.253656887208,\n 44.95420083227316\n ],\n [\n -81.17740504071924,\n 44.91178702187963\n ],\n [\n -81.12838599654847,\n 44.888639013582065\n ],\n [\n -81.03579446866945,\n 44.87320183056545\n ],\n [\n -81.05758071052291,\n 44.84231503860889\n ],\n [\n -81.16106535932897,\n 44.772759180779985\n ],\n [\n -81.1174928756214,\n 44.71473189605126\n ],\n [\n -80.99766854542506,\n 44.7766255954954\n ],\n [\n -80.92141669893631,\n 44.75729093324023\n ],\n [\n -80.93775638032653,\n 44.69924811660516\n ],\n [\n -80.97588230357093,\n 44.586866851818854\n ],\n [\n -80.93775638032653,\n 44.555826813432276\n ],\n [\n -80.87213934933281,\n 44.60835077976765\n ],\n [\n -80.80678062377112,\n 44.66648469087474\n ],\n [\n -80.71963565635528,\n 44.709079208994154\n ],\n [\n -80.6488303703304,\n 44.68584971838496\n ],\n [\n -80.64338380986653,\n 44.62385885086999\n ],\n [\n -80.60525788662214,\n 44.58508090756595\n ],\n [\n -80.5235594796702,\n 44.56956248244481\n ],\n [\n -80.40373514947386,\n 44.51133150284022\n ],\n [\n -80.33292986344827,\n 44.526865458595665\n ],\n [\n -80.24033833556928,\n 44.48802280406534\n ],\n [\n -80.09872776351942,\n 44.43748865747446\n ],\n [\n -79.97345687285926,\n 44.53074830043366\n ],\n [\n -79.97890343332244,\n 44.60447311486121\n ],\n [\n -79.95711719146898,\n 44.654862568061844\n ],\n [\n -79.99524311471336,\n 44.720690459656424\n ],\n [\n -80.08783464259238,\n 44.74777431761734\n ],\n [\n -80.09872776351942,\n 44.79417427761814\n ],\n [\n -80.02247591703069,\n 44.78644353963395\n ],\n [\n -80.00613623563976,\n 44.83281243533543\n ],\n [\n -79.92988438915167,\n 44.840536960424515\n ],\n [\n -79.97345687285926,\n 44.7787117661735\n ],\n [\n -79.89175846590729,\n 44.7787117661735\n ],\n [\n -79.90809814729757,\n 44.74777431761734\n ],\n [\n -79.83729286127266,\n 44.72842999911202\n ],\n [\n -79.72291509153949,\n 44.72456035881632\n ],\n [\n -79.67389604736806,\n 44.77097895723938\n ],\n [\n -79.72836165200272,\n 44.809632647151886\n ],\n [\n -79.76104101478387,\n 44.910011089080285\n ],\n [\n -79.89013755804159,\n 44.977283800856526\n ],\n [\n -80.03719469055525,\n 45.10813027053467\n ],\n [\n -79.95004972313941,\n 45.150398880350224\n ],\n [\n -80.05898093240937,\n 45.20798741364334\n ],\n [\n -80.18425182306893,\n 45.30383886831629\n ],\n [\n -80.00996188823791,\n 45.330648282902104\n ],\n [\n -80.10799997658016,\n 45.41864705386692\n ],\n [\n -80.27139679048474,\n 45.3880543169106\n ],\n [\n -80.36398831836377,\n 45.475963784507854\n ],\n [\n -80.46202640670664,\n 45.60566609652929\n ],\n [\n -80.58729729736616,\n 45.71225511003635\n ],\n [\n -80.61997666014737,\n 45.799658586509736\n ],\n [\n -80.71256818802641,\n 45.87175820659314\n ],\n [\n -80.72346130895347,\n 45.96648381304479\n ],\n [\n -80.81605283683247,\n 45.96269789365007\n ],\n [\n -81.142846464641,\n 45.94755162875887\n ],\n [\n -81.38794168549688,\n 46.00811185054252\n ],\n [\n -81.54044537847439,\n 46.00432877710023\n ],\n [\n -81.53499881801122,\n 46.098828001216845\n ],\n [\n -81.69294907145193,\n 46.11015704291532\n ],\n [\n -81.9543839736987,\n 46.11015704291532\n ],\n [\n -82.14501358991997,\n 46.12903360546147\n ],\n [\n -82.29522574644525,\n 46.16537527120721\n ],\n [\n -82.4422828789596,\n 46.2181603672141\n ],\n [\n -82.61657281379057,\n 46.18046190028028\n ],\n [\n -82.62746593471763,\n 46.2181603672141\n ],\n [\n -83.0359579694781,\n 46.20685354294187\n ],\n [\n -83.30828599265199,\n 46.23323251192761\n ],\n [\n -83.6024002576793,\n 46.29724296152551\n ],\n [\n -83.81481611575532,\n 46.32357848174803\n ],\n [\n -83.87472828085318,\n 46.34990133057653\n ],\n [\n -84.02178541336748,\n 46.34990133057653\n ],\n [\n -84.0708044575383,\n 46.37621150855463\n ],\n [\n -84.07625101800214,\n 46.4100202627414\n ],\n [\n -84.03812509475776,\n 46.52631233719663\n ],\n [\n -84.14160974356385,\n 46.541299669426905\n ],\n [\n -84.21241502958877,\n 46.44380807335605\n ],\n [\n -84.2559875132963,\n 46.52631233719663\n ],\n [\n -84.34313248071213,\n 46.49632526419765\n ],\n [\n -84.29411343654071,\n 46.43254779680592\n ],\n [\n -84.2559875132963,\n 46.32357848174803\n ],\n [\n -84.24509439236992,\n 46.27842411736026\n ],\n [\n -84.228754710979,\n 46.24453390477612\n ],\n [\n -84.33223935978506,\n 46.18800366287303\n ],\n [\n -84.228754710979,\n 46.146511164960856\n ],\n [\n -84.15250286449091,\n 46.157830404704185\n ],\n [\n -84.08169757846534,\n 46.13141522393252\n ],\n [\n -84.12527006217293,\n 46.09743422404375\n ],\n [\n -83.9564266878058,\n 45.99158155409046\n ],\n [\n -84.32679279932186,\n 46.021845870596735\n ],\n [\n -84.46840337137237,\n 46.02562774594537\n ],\n [\n -84.52286897600698,\n 46.04453324206048\n ],\n [\n -84.6838898307518,\n 46.086102567775015\n ],\n [\n -84.76558823770377,\n 45.9764431865685\n ],\n [\n -84.78192791909467,\n 45.87794289137878\n ],\n [\n -84.91809193068129,\n 45.95372787349061\n ],\n [\n -85.00523689809711,\n 46.0218458705952\n ],\n [\n -85.1196146678296,\n 46.06721130017664\n ],\n [\n -85.25033211895301,\n 46.086102567775015\n ],\n [\n -85.3810495700764,\n 46.11253947746462\n ],\n [\n -85.45185485610197,\n 46.11253947746462\n ],\n [\n -85.52810670259075,\n 46.127640591991394\n ],\n [\n -85.58801886768859,\n 46.07854683681495\n ],\n [\n -85.69150351649466,\n 45.9764431865685\n ],\n [\n -85.77320192344663,\n 45.99536549916374\n ],\n [\n -85.86579345132567,\n 45.99158155408895\n ],\n [\n -85.9474918582783,\n 45.96130067943514\n ],\n [\n -86.09999555125518,\n 45.99536549916374\n ],\n [\n -86.2524992442327,\n 45.9764431865685\n ],\n [\n -86.35053733257557,\n 45.91584831962609\n ],\n [\n -86.37919118289861,\n 45.80964791369544\n ],\n [\n -86.51535519448589,\n 45.771670031614406\n ],\n [\n -86.66785888746274,\n 45.67661210724006\n ],\n [\n -86.54258799680319,\n 45.79825726622883\n ],\n [\n -86.50990863402201,\n 45.84380588247262\n ],\n [\n -86.52080175494908,\n 45.896898839869465\n ],\n [\n -86.60250016190106,\n 45.91205894116794\n ],\n [\n -86.68964512931686,\n 45.86656621723964\n ],\n [\n -86.76045041534178,\n 45.88931723672883\n ],\n [\n -86.81491601997706,\n 45.85518721427951\n ],\n [\n -86.80402289905,\n 45.80964791369544\n ],\n [\n -86.86938162461172,\n 45.73366627131384\n ],\n [\n -86.96197315249073,\n 45.703244630147594\n ],\n [\n -86.95108003156366,\n 45.786864289781334\n ],\n [\n -86.97831283388099,\n 45.824831820837176\n ],\n [\n -86.9129541083193,\n 45.87794289137986\n ],\n [\n -86.9129541083193,\n 45.923426300315725\n ],\n [\n -86.9728662734178,\n 45.94615403261639\n ],\n [\n -87.08724404315029,\n 45.82103623220769\n ],\n [\n -87.1035837245412,\n 45.76027162077929\n ],\n [\n -87.11992340593147,\n 45.70704824107773\n ],\n [\n -87.17983557102997,\n 45.67280642590097\n ],\n [\n -87.25608741751807,\n 45.60425990542609\n ],\n [\n -87.38680486864148,\n 45.4172361822946\n ],\n [\n -87.51752231976488,\n 45.248641304557225\n ],\n [\n -87.69181225459653,\n 45.12196018409364\n ],\n [\n -87.65368633135215,\n 45.08736186074313\n ],\n [\n -87.65368633135215,\n 44.99114538498199\n ],\n [\n -87.75172441969438,\n 44.99884865719014\n ],\n [\n -87.86610218942752,\n 44.97188267412989\n ],\n [\n -87.8715487498907,\n 44.88319084625306\n ],\n [\n -87.96958683823361,\n 44.77503335055633\n ],\n [\n -88.02949900333213,\n 44.72474838174219\n ],\n [\n -88.04583868472237,\n 44.612416573491515\n ],\n [\n -88.08396460796673,\n 44.53093695221517\n ],\n [\n -87.96958683823361,\n 44.49209701183014\n ],\n [\n -87.8715487498907,\n 44.52317103485083\n ],\n [\n -87.85520906850047,\n 44.58914832985613\n ],\n [\n -87.79529690340263,\n 44.61629370811653\n ],\n [\n -87.74627785923117,\n 44.61629370811653\n ],\n [\n -87.71359849645,\n 44.670546413106194\n ],\n [\n -87.68636569413269,\n 44.72474838174219\n ],\n [\n -87.58288104532656,\n 44.81754799975607\n ],\n [\n -87.52841544069194,\n 44.805956201866394\n ],\n [\n -87.43582391281292,\n 44.86389189287894\n ],\n [\n -87.38135830817828,\n 44.81754799975607\n ],\n [\n -87.34867894539711,\n 44.86389189287894\n ],\n [\n -87.36501862678801,\n 44.92562576274332\n ],\n [\n -87.25608741751807,\n 45.037349485663526\n ],\n [\n -87.19617525242025,\n 45.13733048596944\n ],\n [\n -87.14715620824879,\n 45.17189852112651\n ],\n [\n -87.03277843851565,\n 45.26397743558533\n ],\n [\n -87.09269060361413,\n 45.17957745912577\n ],\n [\n -87.14715620824879,\n 45.06813150937583\n ],\n [\n -87.18528213149317,\n 45.00655089389372\n ],\n [\n -87.23430117566461,\n 44.92562576274332\n ],\n [\n -87.28876678029926,\n 44.852309414374616\n ],\n [\n -87.38680486864149,\n 44.72474838174219\n ],\n [\n -87.44671703373996,\n 44.63179965808348\n ],\n [\n -87.4957360779114,\n 44.554228492095405\n ],\n [\n -87.52296888022875,\n 44.44934318194029\n ],\n [\n -87.57743448486207,\n 44.305757292128675\n ],\n [\n -87.53930856161766,\n 44.196520763958404\n ],\n [\n -87.58288104532527,\n 44.149643001979655\n ],\n [\n -87.69725881505839,\n 44.10663898672243\n ],\n [\n -87.6918122545952,\n 44.06751725858413\n ],\n [\n -87.76261754062008,\n 43.906847674594275\n ],\n [\n -87.73538473830277,\n 43.71032065425081\n ],\n [\n -87.74627785922985,\n 43.66305795778291\n ],\n [\n -87.84431594757206,\n 43.5447383086684\n ],\n [\n -87.8279762661818,\n 43.4736348259608\n ],\n [\n -87.89878155220737,\n 43.39849028420497\n ],\n [\n -87.94780059637816,\n 43.23205021521784\n ],\n [\n -87.90967467313375,\n 43.17249686629907\n ],\n [\n -87.9369074754511,\n 43.12083694401605\n ],\n [\n -87.89333499174349,\n 43.07311211388972\n ],\n [\n -87.94235403591495,\n 43.0134037728543\n ],\n [\n -87.87699531035325,\n 42.95363732470122\n ],\n [\n -87.88788843128029,\n 42.83792412431018\n ],\n [\n -87.80074346386446,\n 42.75799542505797\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pecoraro, Samuel 0000-0002-3435-649X","orcid":"https://orcid.org/0000-0002-3435-649X","contributorId":221137,"corporation":false,"usgs":true,"family":"Pecoraro","given":"Samuel","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":882946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esselman, Peter C.","contributorId":329685,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":882947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":882948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farha, Steve A. 0000-0001-9953-6996 sfarha@usgs.gov","orcid":"https://orcid.org/0000-0001-9953-6996","contributorId":5170,"corporation":false,"usgs":true,"family":"Farha","given":"Steve A.","email":"sfarha@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":882949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Warner, David 0000-0003-4939-5368","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":216543,"corporation":false,"usgs":true,"family":"Warner","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":882950,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254741,"text":"70254741 - 2023 - Data-limited fishery assessment methods shed light on the exploitation history and population dynamics of Endangered Species Act-listed Yelloweye Rockfish in Puget Sound, Washington","interactions":[],"lastModifiedDate":"2024-06-07T16:51:40.506334","indexId":"70254741","displayToPublicDate":"2023-09-13T11:43:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Data-limited fishery assessment methods shed light on the exploitation history and population dynamics of Endangered Species Act-listed Yelloweye Rockfish in Puget Sound, Washington","docAbstract":"The distinct population segment (DPS) of Yelloweye Rockfish Sebastes ruberrimus inhabiting the Puget Sound/Georgia Basin was listed under the Endangered Species Act (ESA) in 2010, and a formal recovery plan for the DPS was published by National Oceanic and Atmospheric Administration Fisheries in 2017. In this recovery plan, the biological criteria for delisting or downlisting were specified as certain levels of spawning potential ratio (SPR), a commonly used metric of equilibrium stock status for commercially exploited fishes. Although this metric can be estimated from length compositions, the combination of length data with a catch history (which was not previously available for this DPS) improves our understanding of population dynamics over time and allows us to estimate a different measure of stock status, relative (to unfished) spawning stock biomass (SSB), rather than only SPR.
To estimate relative SSB and reconstruct the historical dynamics of this DPS, we reconstructed the catch history from fisheries records, collated length data from historical and contemporary hook-and-line surveys, and fitted a data-limited version of a statistical catch-at-age model.
Despite a high level of uncertainty, we estimated that Yelloweye Rockfish in Puget Sound are above 25% of unfished biomass (a reference point detailed in the recovery criteria) under the assumption of deterministic recruitment, presenting the first direct estimates of Yelloweye Rockfish population status in Puget Sound.
However, as informed by recent genetic studies, the DPS boundaries of ESA-listed Yelloweye Rockfish extend from South Puget Sound to Queen Charlotte Strait in British Columbia. The Canadian portion of this population is managed separately and is currently estimated to be at 32% of unfished biomass (95% quantiles = 15%–68%). Thus, the disjunction between the biological boundaries of the population and the jurisdictional boundaries between Canada and the United States presents an additional source of uncertainty in assessing recovery that must be addressed to achieve DPS-wide recovery goals.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10251","usgsCitation":"Min, M., Cope, J., Lowry, D., Selleck, J., Tonnes, D., Andrews, K., Pacunski, R., Hennings, A., and Scheuerell, M.D., 2023, Data-limited fishery assessment methods shed light on the exploitation history and population dynamics of Endangered Species Act-listed Yelloweye Rockfish in Puget Sound, Washington: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 15, no. 5, e1051, 16 p., https://doi.org/10.1002/mcf2.10251.","productDescription":"e1051, 16 p.","ipdsId":"IP-146495","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442111,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10251","text":"Publisher Index Page"},{"id":429657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.09326531847128,\n 49.00502906664644\n ],\n [\n -124.94030563468002,\n 49.00502906664644\n ],\n [\n -124.94030563468002,\n 46.793491720907355\n ],\n [\n -122.09326531847128,\n 46.793491720907355\n ],\n [\n -122.09326531847128,\n 49.00502906664644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Min, Markus","contributorId":337385,"corporation":false,"usgs":false,"family":"Min","given":"Markus","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":902398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cope, Jason","contributorId":337386,"corporation":false,"usgs":false,"family":"Cope","given":"Jason","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowry, Dayv","contributorId":337387,"corporation":false,"usgs":false,"family":"Lowry","given":"Dayv","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selleck, James","contributorId":337388,"corporation":false,"usgs":false,"family":"Selleck","given":"James","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tonnes, Daniel","contributorId":337390,"corporation":false,"usgs":false,"family":"Tonnes","given":"Daniel","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902402,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andrews, Kelly","contributorId":337392,"corporation":false,"usgs":false,"family":"Andrews","given":"Kelly","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902403,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pacunski, Robert","contributorId":337393,"corporation":false,"usgs":false,"family":"Pacunski","given":"Robert","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902404,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hennings, Andrea","contributorId":337396,"corporation":false,"usgs":false,"family":"Hennings","given":"Andrea","email":"","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":902405,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902406,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256516,"text":"70256516 - 2023 - Multi-resolution habitat models of the Puerto Rican Nightjar Antrostromus noctitherus","interactions":[],"lastModifiedDate":"2024-08-20T16:40:42.78689","indexId":"70256516","displayToPublicDate":"2023-09-13T11:35:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-resolution habitat models of the Puerto Rican Nightjar Antrostromus noctitherus","title":"Multi-resolution habitat models of the Puerto Rican Nightjar Antrostromus noctitherus","docAbstract":"The Puerto Rican Nightjar Antrostomus noctitherus is an endemic Caprimulgid found in dry coastal and lower montane forests of south-western Puerto Rico. Information on the species (e.g. abundance, nesting biology) has been mostly restricted to forest reserves (i.e. Guánica Forest and Susúa Forest) with limited information available from private lands. We collected stand-level vegetation structure and geographical information from forest reserves and private lands to model habitat suitability and distribution for the Nightjar. Results of the stand-level model indicated forest type and midstorey vegetation density best predicted Nightjar habitat. Our spatial model predicted considerably more Nightjar habitat (17,819.64 ha) located outside protected areas than previously reported. Further, the model highlighted several localities of importance for the species across southern Puerto Rico, all located within private lands. We used a patch occupancy approach to assess regions identified by the landscape-level model as suitable for the Nightjar and documented the presence of the species in 32 of 55 sites, located in 12 of 18 municipalities across southern Puerto Rico. The protection and restoration of forest across the southern coast of Puerto Rico would help to ensure the long-term persistence of the Nightjar across a considerable portion of its range. Addressing habitat needs may be the single most effective mechanism to achieve recovery of the species.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0959270923000278","usgsCitation":"Vilella, F., and Gonzalez, R., 2023, Multi-resolution habitat models of the Puerto Rican Nightjar Antrostromus noctitherus: Bird Conservation International, v. 33, e74, 10 p., https://doi.org/10.1017/S0959270923000278.","productDescription":"e74, 10 p.","ipdsId":"IP-152543","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1017/s0959270923000278","text":"Publisher Index Page"},{"id":432949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.30291952675373,\n 18.570803919744066\n ],\n [\n -67.30291952675373,\n 17.90303830780671\n ],\n [\n -65.57254725538235,\n 17.90303830780671\n ],\n [\n -65.57254725538235,\n 18.570803919744066\n ],\n [\n -67.30291952675373,\n 18.570803919744066\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez, Rafael","contributorId":340993,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Rafael","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907775,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248075,"text":"70248075 - 2023 - Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs","interactions":[],"lastModifiedDate":"2023-10-11T16:01:26.81846","indexId":"70248075","displayToPublicDate":"2023-09-13T09:30:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7485,"text":"Environmental Science and Technology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs","docAbstract":"The transfer of aquatic contaminants, including mercury (Hg), to terrestrial food webs is an often-overlooked exposure pathway to terrestrial animals. While research has implemented the use of shoreline spiders to assess aquatic to terrestrial Hg transfer, it is unclear whether Hg sources, estimated from isotope ratios, can be successfully resolved to inform site assessments and remedy effectiveness. To examine aquatic to terrestrial Hg transfer, we collected shoreline spiders (Tetragnatha spp.) and aquatic insect larvae (suborder Anisoptera) across a mosaic of aquatic and shoreline habitats in the St. Louis River and Bad River, tributaries to Lake Superior. The fraction of industrial Hg in sediments was reflected in the δ202Hg values of aquatic dragonfly larvae and predatory fish, connecting benthic Hg sources to the aquatic food web. Shoreline spiders mirrored these aquatic Hg source signatures with highly positive correlations in δ202Hg between tetragnathids and dragonfly larvae (r2 = 0.90). Further assessment of different spider taxa (i.e., araneids and pisaurids) revealed that differences in prey consumption and foraging strategies resulted in isotope differences, highlighting the importance of spider taxa selection for Hg monitoring efforts.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.estlett.3c00450","usgsCitation":"Janssen, S., Kotalik, C.J., Eagles-Smith, C., Beaubien, G.B., Hoffman, J.C., Peterson, G., Mills, M.A., and Walters, D., 2023, Mercury isotope values in shoreline spiders reveal transfer of aquatic mercury sources to terrestrial food webs: Environmental Science and Technology Letters, v. 10, no. 10, p. 891-896, https://doi.org/10.1021/acs.estlett.3c00450.","productDescription":"6 p.","startPage":"891","endPage":"896","ipdsId":"IP-153126","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":442116,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10569030","text":"Publisher Index Page"},{"id":435186,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HIBA4","text":"USGS data release","linkHelpText":"Assessment of Mercury and Mercury Stable Isotopes in Sediments and Biota from Reservoirs and Remedial Zones within the Saint Louis River, Minnesota"},{"id":420951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Bad River, Lake Superior, St. Louis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.97319972002215,\n 46.85080995328977\n ],\n [\n -92.3808806574504,\n 46.85080995328977\n ],\n [\n -92.3808806574504,\n 46.607590925287866\n ],\n [\n -91.97319972002215,\n 46.607590925287866\n ],\n [\n -91.97319972002215,\n 46.85080995328977\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.76604011941525,\n 46.66037391866578\n ],\n [\n -90.76604011941525,\n 46.56740333938299\n ],\n [\n -90.61257263374692,\n 46.56740333938299\n ],\n [\n -90.61257263374692,\n 46.66037391866578\n ],\n [\n -90.76604011941525,\n 46.66037391866578\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kotalik, Christopher James 0000-0001-6739-6036","orcid":"https://orcid.org/0000-0001-6739-6036","contributorId":301847,"corporation":false,"usgs":true,"family":"Kotalik","given":"Christopher","email":"","middleInitial":"James","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":881782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":881783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beaubien, Gale B.","contributorId":244596,"corporation":false,"usgs":false,"family":"Beaubien","given":"Gale","email":"","middleInitial":"B.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":881784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":881785,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Greg","contributorId":256978,"corporation":false,"usgs":false,"family":"Peterson","given":"Greg","email":"","affiliations":[{"id":40396,"text":"US Environmental Protection Agency, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":881786,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":881787,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":203410,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881788,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248906,"text":"70248906 - 2023 - Converting CRP grasslands to cropland, grazing land, or hayland: Effects on breeding bird abundances in the northern Great Plains of the United States","interactions":[],"lastModifiedDate":"2023-09-26T12:22:34.336494","indexId":"70248906","displayToPublicDate":"2023-09-13T07:19:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Converting CRP grasslands to cropland, grazing land, or hayland: Effects on breeding bird abundances in the northern Great Plains of the United States","docAbstract":"Recent declines of grassland bird populations in North America are linked to habitat loss and fragmentation associated with agricultural practices. One tool used to conserve soil, water and wildlife habitat on agricultural fields is the U.S. Department of Agriculture’s Conservation Reserve Program (CRP), the largest agricultural conservation program in the United States. Managers and conservationists recognize CRP as an important component of conserving grassland birds in the central portion of the United States. However, recent widespread expiration of CRP contracts could negatively influence grassland bird populations. Few studies have evaluated how former CRP-enrolled fields may function as grassland bird habitat. In this paper, we analyzed data from a long-term (1990–2017) study aimed at comparing grassland bird abundance (24 species) between idled CRP grasslands and fields where the CRP contracts expired. Some of these fields where contracts expired were maintained as pasture or hayland, and others were converted back to cropland. Estimated abundances of most species were considerably higher in idled CRP than in fields with expired CRP contracts. Post-CRP land use also appeared to affect most bird abundances, with lower abundance in grazed grasslands and haylands relative to idled CRP, but higher abundance than cropland. The responses of obligate and facultative grassland specialists to post-CRP management varied among species, with some being negative and some being positive depending on post-CRP land use, which is unsurprising given the variable habitat requirements of grassland birds. Our results have implications for wildlife managers who must design conservation strategies around the land use decisions of private landowners. Our results support the idea of maintaining a mosaic of undisturbed CRP grasslands and post-CRP grasslands that are hayed or grazed, which should guarantee some undisturbed nesting cover in the landscape for some bird species and some disturbed grasslands that may have long-term benefits for other species.
Biodiversity is generally reduced when non-native species invade an ecosystem. Invasive crayfish, Procambarus clarkii, populate California freshwater streams, and in the Santa Monica Mountains (Los Angeles, USA), their introduction has led to trophic cascades due to omnivorous feeding behavior and a rapid rate of population growth. The native California newt, Taricha torosa, possesses a neurotoxin, tetrodotoxin (TTX), that affects freshwater animal behavior. Given P. clarkii has a limited evolutionary history with TTX, we hypothesized that TTX may affect crayfish feeding behaviors. To determine if TTX affects P. clarkii behavior, we measured cumulative movement and various feeding behaviors of P. clarkii exposed to (i) waterborne, ecologically realistic concentrations of TTX (~ 3.0 × 10− 8 moles/L), (ii) an anuran chemical cue to account for intraguild cues, or (iii) a T. torosa chemical cue with quantitated TTX in it (~ 6.2 × 10− 8 moles/L).
We found that the presence of TTX in any form significantly reduced crayfish movement and decreased the amount of food consumed over time. Crayfish responses to the anuran treatment did not significantly differ from controls.
Our laboratory results show that naturally occurring neurotoxin from native California newts limits invasive crayfish foraging and feeding rates, which may play a role in preserving local stream ecosystems by limiting invasive crayfish behaviors that are detrimental to biodiversity.
","language":"English","publisher":"Springer","doi":"10.1186/s12862-023-02162-6","usgsCitation":"Bucciarelli, G.M., Smith, S.J., Choe, J.J., Shin, P.D., Fisher, R., and Kats, L.B., 2023, Native amphibian toxin reduces invasive crayfish feeding with potential benefits to stream biodiversity: BMC Ecological Evolution, v. 23, 51, 10 p., https://doi.org/10.1186/s12862-023-02162-6.","productDescription":"51, 10 p.","ipdsId":"IP-153361","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12862-023-02162-6","text":"Publisher Index Page"},{"id":420942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.10835949859933,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 33.95419558307488\n ],\n [\n -118.36160958124017,\n 34.24972494086572\n ],\n [\n -119.10835949859933,\n 34.24972494086572\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Bucciarelli, Gary M.","contributorId":209642,"corporation":false,"usgs":false,"family":"Bucciarelli","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":883402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Sierra J.","contributorId":329828,"corporation":false,"usgs":false,"family":"Smith","given":"Sierra","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choe, Justin J.","contributorId":329829,"corporation":false,"usgs":false,"family":"Choe","given":"Justin","email":"","middleInitial":"J.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shin, Phoebe D.","contributorId":329831,"corporation":false,"usgs":false,"family":"Shin","given":"Phoebe","email":"","middleInitial":"D.","affiliations":[{"id":37949,"text":"Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":883406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kats, Lee B.","contributorId":208330,"corporation":false,"usgs":false,"family":"Kats","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":37783,"text":"Seaver College, Pepperdine University","active":true,"usgs":false}],"preferred":false,"id":883407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248277,"text":"sir20235087 - 2023 - Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","interactions":[],"lastModifiedDate":"2026-03-12T21:08:34.632448","indexId":"sir20235087","displayToPublicDate":"2023-09-12T19:46:00","publicationYear":"2023","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":"2023-5087","displayTitle":"Approaches for Assessing Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England With the Stochastic Empirical Loading and Dilution Model (SELDM)","title":"Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)","docAbstract":"The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation.
The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices.
Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235087","collaboration":"Prepared in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation","usgsCitation":"Granato, G.E., Spaetzel, A.B., and Jeznach, L.C., 2023, Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM): U.S. Geological Survey Scientific Investigations Report 2023–5087, 152 p., https://doi.org/10.3133/sir20235087.","productDescription":"Report: xii, 152 p.; Software Release; 4 Data Releases","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133112","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501050,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115402.htm","linkFileType":{"id":5,"text":"html"}},{"id":420555,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K0Y7XR","text":"USGS data release","linkHelpText":"Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420556,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZNIH5","text":"USGS data release","linkHelpText":"Model archive for analysis of flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)"},{"id":420554,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B02EUZ","text":"USGS data release","linkHelpText":"Model archive for analysis of long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading Dilution Model (SELDM)"},{"id":420557,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VK1MCG","text":"USGS data release","linkHelpText":"Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model"},{"id":420548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5087/coverthb.jpg"},{"id":420549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.pdf","text":"Report","size":"8.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5087"},{"id":420552,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5087/images/"},{"id":420887,"rank":11,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9PYG7T5","text":"USGS software release","linkHelpText":"- Stochastic Empirical Loading and Dilution Model (SELDM) software archive"},{"id":420551,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5087/sir20235087.XML"},{"id":420553,"rank":10,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9XBPIOB","text":"USGS software release","linkHelpText":"- Best management practices statistical estimator (BMPSE) version 1.2.0"},{"id":420550,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5087"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, Rhode Island, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.28249194123347,\n 42.97558594616143\n ],\n [\n -73.81823969745555,\n 41.00628384122689\n ],\n [\n -69.72117184187273,\n 40.9949482400483\n ],\n [\n -69.72117184187273,\n 42.97558594616143\n ],\n [\n -73.28249194123347,\n 42.97558594616143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Director, Integrated Information Dissemination Division
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Using manufactured baits to attract fish to passive gear is common practice in fisheries management. The most common method is using hoop nets baited with soybean cakes or waste cheese to increase captures of multiple catfish species; however, these techniques are limited to how often bait is added, the type of bait, gear compatibility, and oversaturation of bait during soak time. The U.S. Geological Survey developed a technique to deliver various types of manufactured, pelleted baits over multiple scenarios and traditional passive gears. A floating platform designed with a dispenser can be constructed easily and allows for the automatic application of varying quantities and sizes of bait. Bait platforms can be modified for use in lakes and rivers where water fluctuations are common. Unlike traditional baiting techniques, these platforms can be positioned over or near any type of gear and release bait as many as nine times daily. Programmed release of bait multiple time a day can be useful to target fish activity during specific hours and can allow for sustained application without bait oversaturation or deterioration from long soak times. This report describes the design of a bait delivery platform developed for deployment in the Sandusky River in Ohio for the removal of Ctenopharyngodon idella (Valenciennes, 1844; grass carp) during 2021 and 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm8D2","usgsCitation":"Wamboldt, J.J., 2023, Design and utility of automatous, floating bait delivery platform for applying fish management baits: U.S. Geological Survey Techniques and Methods, book 8, chap. D2, 8 p., https://doi.org/10.3133/tm8D2.","productDescription":"vi, 8 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153329","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":420736,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm8D2/full","linkFileType":{"id":5,"text":"html"}},{"id":420715,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/08/d02/images/"},{"id":420714,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.XML","linkFileType":{"id":8,"text":"xml"}},{"id":420713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/08/d02/tm8d2.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 8–D2"},{"id":420712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/08/d02/coverthb.jpg"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Our nation’s fish and wildlife species face increasingly complex threats and challenges. Ensuring a healthy future for these species benefits all Americans, contributing to the abundance of our food supply, the well-being of diverse cultures and communities, and the future of biodiverse ecosystems. The U.S. Geological Survey Species Management Research Program (SMRP) plays a critical role in achieving that future by delivering targeted research and foundational scientific services needed to conserve fish and wildlife in a changing world.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip226","programNote":"Species Management Research Program","usgsCitation":"Steinkamp, M.J., Khalil, M., House, S., Wimer, M., Hu, D.H., Adams, M.J., 2023, Species management research program [postcard]: U.S. Geological Survey General Information Product 226, 2 p., https://doi.org/10.3133/gip226.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-156895","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":420718,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/226/coverthb3.jpg"},{"id":420719,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/226/gip226.pdf","text":"Report","size":"1.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 226"}],"contact":"Species Management Research Program
U.S. Geological Survey
12201 Sunrise Valley Dr.
Reston, VA 20192