{"pageNumber":"347","pageRowStart":"8650","pageSize":"25","recordCount":40797,"records":[{"id":70263303,"text":"70263303 - 2019 - The U. S. Geological Survey National Hydrologic Model infrastructure: Rationale, description, and application of a watershed-scale model for the conterminous United States","interactions":[],"lastModifiedDate":"2025-02-05T14:52:07.78121","indexId":"70263303","displayToPublicDate":"2018-10-31T08:48:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"The U. S. Geological Survey National Hydrologic Model infrastructure: Rationale, description, and application of a watershed-scale model for the conterminous United States","docAbstract":"<p><span>The ability to effectively manage water resources to meet present and future human and environmental needs is essential. Such an ability necessitates a comprehensive understanding of hydrologic processes that affect&nbsp;streamflow&nbsp;at a watershed scale. In the United States, water-resources management at scales ranging from local to national can benefit from a nationally consistent, process-based watershed modeling capability to provide the requisite understanding. The National Hydrologic Model (NHM) infrastructure, which was developed by the&nbsp;</span><a class=\"topic-link\" title=\"Learn more about U.S. from ScienceDirect's AI-generated Topic Pages\" href=\"https://www-sciencedirect-com.usgslibrary.idm.oclc.org/topics/earth-and-planetary-sciences/united-states-of-america\" data-mce-href=\"https://www-sciencedirect-com.usgslibrary.idm.oclc.org/topics/earth-and-planetary-sciences/united-states-of-america\">U.S.</a><span>&nbsp;Geological Survey to support coordinated, comprehensive, and consistent&nbsp;hydrologic modeling&nbsp;at multiple scales for the conterminous United States, provides this essential capability. NHM-based applications provide information to enable more effective water-resources planning and management, fill knowledge gaps in ungaged areas, and support basic scientific inquiry. In the future, as process algorithms and data sets improve, the NHM infrastructure will continue to evolve to better support the nation's water-resources research and management needs.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2018.09.023","usgsCitation":"Regan, R.S., Juracek, K.E., Hay, L., Markstrom, S.L., Viger, R.J., Driscoll, J.M., LaFontaine, J.H., and Norton, P.A., 2019, The U. S. Geological Survey National Hydrologic Model infrastructure: Rationale, description, and application of a watershed-scale model for the conterminous United States: Environmental Modelling & Software, v. 111, p. 192-203, https://doi.org/10.1016/j.envsoft.2018.09.023.","productDescription":"12 p.","startPage":"192","endPage":"203","ipdsId":"IP-090180","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":481697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous 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":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":926243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":926244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":926245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":926246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":926247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":926248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926249,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926250,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70200853,"text":"70200853 - 2019 - Stable isotope analysis enhances our understanding of diamondback terrapin Malaclemys terrapin foraging ecology","interactions":[],"lastModifiedDate":"2019-02-11T15:06:16","indexId":"70200853","displayToPublicDate":"2018-10-30T10:10:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Stable isotope analysis enhances our understanding of diamondback terrapin <i>Malaclemys terrapin</i> foraging ecology","title":"Stable isotope analysis enhances our understanding of diamondback terrapin Malaclemys terrapin foraging ecology","docAbstract":"<p><span>Dietary studies on generalist predators may provide valuable information on spatial or temporal changes in the structure of ecological communities. We initiated this study to provide baseline data and determine the utility of stable isotope analysis (SIA) to evaluate the foraging strategies of an opportunistic reptilian predator, the diamondback terrapin (</span><i class=\"EmphasisTypeItalic \">Malaclemys terrapin</i><span>), which specializes in salt marshes and mangrove estuaries along the Atlantic and Gulf coasts. We evaluated stable carbon (δ</span><sup>13</sup><span>C) and nitrogen (δ</span><sup>15</sup><span>N) isotope values of multiple tissues from terrapins inhabiting mainland and island mangrove habitats in south Florida and potential food sources to examine spatial and temporal variations in terrapin resource use. We fit linear regression models to determine the best predictors of isotopic values for both terrapins and their prey, and Stable Isotope Bayesian Ellipses in R (SIBER) analysis to examine terrapin isotopic niche space and overlap between groups. We identified differences in terrapin isotopic δ</span><sup>13</sup><span>C and δ</span><sup>15</sup><span>N values among all sites. Blood and scute tissues revealed different isotopic compositions and niche overlap between sites, suggesting diets or foraging locations may change over time, and amount of variation is site specific. Niche overlap between size classes was larger for blood (short term) versus scute (long term), suggesting greater variability in food habits or resource isotopes over the long term versus short term. These results demonstrate the usefulness of SIA in examining the spatial and temporal variability in diamondback terrapin resource use within estuary systems and further define their niche within these dynamic food webs.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-018-0476-6","usgsCitation":"Denton, M.J., Demopoulos, A.W., Baldwin, J.D., Smith, B., and Hart, K.M., 2019, Stable isotope analysis enhances our understanding of diamondback terrapin Malaclemys terrapin foraging ecology: Estuaries and Coasts, v. 42, no. 2, p. 596-611, https://doi.org/10.1007/s12237-018-0476-6.","productDescription":"16 p.","startPage":"596","endPage":"611","ipdsId":"IP-091296","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468064,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-018-0476-6","text":"Publisher Index Page"},{"id":437621,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z89BK7","text":"USGS data release","linkHelpText":"Stable isotope ratios of carbon and nitrogen from diamondback terrapins and resources within Southern Everglades and Key West National Wildlife Refuge, sampled 2012-2013"},{"id":359277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-30","publicationStatus":"PW","scienceBaseUri":"5be40822e4b0b3fc5cf7cc04","contributors":{"authors":[{"text":"Denton, Mathew J. 0000-0002-1024-3722 mdenton@usgs.gov","orcid":"https://orcid.org/0000-0002-1024-3722","contributorId":4862,"corporation":false,"usgs":true,"family":"Denton","given":"Mathew","email":"mdenton@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":750903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":750904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, John D.","contributorId":210505,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":750888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Brian 0000-0002-0531-0492 bjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":202305,"corporation":false,"usgs":true,"family":"Smith","given":"Brian","email":"bjsmith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":750902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Kristen M. 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":210506,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":750889,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204437,"text":"70204437 - 2019 - Survival and cause-specific mortality of desert bighorn sheep lambs","interactions":[],"lastModifiedDate":"2019-07-25T12:44:25","indexId":"70204437","displayToPublicDate":"2018-10-26T12:42:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Survival and cause-specific mortality of desert bighorn sheep lambs","docAbstract":"Juvenile recruitment in desert bighorn sheep (Ovis canadensis mexicana) is highly variable, yet the mechanisms driving neonate survival are not well understood for the species.  Few studies have equipped desert bighorn sheep lambs with radiocollars.  As a result, definitive data on cause-specific mortality and lamb survival estimates are lacking.  Our objectives were to estimate lamb survival rates and determine cause-specific mortality for desert bighorn sheep lambs during a period of mountain lion (Puma concolor) and coyote (Canis latrans) removal in southwestern New Mexico.  We captured pregnant adult females each fall and fitted them with a telemetry collar and a vaginal implant transmitter to aid with neonate captures.  We captured and radiocollared 12 desert bighorn sheep lambs in 2012 and 14 in 2013 within 48 hrs of parturition in the Peloncillo Mountains, New Mexico.  We used the nest survival model in program MARK to estimate lamb survival to 6 months of age.  Across both years there were 14 mortalities, 12 (86%) of which were due to predation.  Mountain lions killed 5 lambs (2 in 2012 and 3 in 2013), coyotes killed 4 lambs (all in 2013), a gray fox (Urocyon cinereoargenteus) killed 1 lamb in 2012; 2 lambs were killed by unknown predators in 2013.  Staged-based survival estimates indicated the highest mortality rates occurred in the first week post birth; 33% to 36% of all lamb mortalities occurred before 7 days of age.  Lamb survival was substantially lower in 2013 (0.20 ± 0.11 [SE]) than in 2012 (0.69 ± 0.16) with the differences in survival attributed to increased coyote predation in 2013.  We did not detect differences in body mass, chest girth, or neck circumference between lambs that were killed by predators and those that survived.  Coyotes, mountain lions and gray fox killed lambs <8 weeks of age, but only mountain lions killed lambs > 8 weeks old.  Studies that fail to capture desert bighorn lambs near parturition will likely produce negatively biased survival estimates and inaccurate appraisals of primary causes of mortality due to early mortality of lambs.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21597","usgsCitation":"Cain, J.W., KARSCH, R.C., Goldstein, E.J., Rominger, E.M., and Gould, W.R., 2019, Survival and cause-specific mortality of desert bighorn sheep lambs: Journal of Wildlife Management, v. 83, no. 2, p. 251-259, https://doi.org/10.1002/jwmg.21597.","productDescription":"9 p.","startPage":"251","endPage":"259","ipdsId":"IP-083223","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":365949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-105.998003,32.002328],[-106.099756,32.002492],[-106.125534,32.002533],[-106.18184,32.00205],[-106.200699,32.001785],[-106.205915,32.001762],[-106.313307,32.001512],[-106.376861,32.001172],[-106.377165,32.001177],[-106.394298,32.001484],[-106.411075,32.001334],[-106.565142,32.000736],[-106.566056,32.000759],[-106.587972,32.000749],[-106.595333,32.000778],[-106.598639,32.000754],[-106.599096,32.000731],[-106.618486,32.000495],[-106.619448,31.994733],[-106.623568,31.990999],[-106.631182,31.989809],[-106.636492,31.985719],[-106.639529,31.980348],[-106.638186,31.97682],[-106.630114,31.971258],[-106.626466,31.97069],[-106.623216,31.97291],[-106.621873,31.972933],[-106.619569,31.971578],[-106.618745,31.966955],[-106.619371,31.964777],[-106.620454,31.963403],[-106.624299,31.961054],[-106.625535,31.957476],[-106.625123,31.954531],[-106.622819,31.952891],[-106.617708,31.956008],[-106.614702,31.956],[-106.616136,31.948439],[-106.623659,31.94551],[-106.622377,31.940863],[-106.622117,31.936621],[-106.622529,31.934863],[-106.625322,31.930053],[-106.629747,31.92657],[-106.628663,31.923614],[-106.623933,31.925335],[-106.611846,31.920003],[-106.614346,31.918003],[-106.623445,31.914034],[-106.625947,31.912227],[-106.633668,31.90979],[-106.64084,31.904598],[-106.645479,31.89867],[-106.645646,31.895649],[-106.645296,31.894859],[-106.6429,31.892933],[-106.638154,31.891663],[-106.633927,31.889184],[-106.630692,31.886411],[-106.629197,31.883717],[-106.630799,31.879697],[-106.634873,31.874478],[-106.63588,31.871514],[-106.635926,31.866235],[-106.627808,31.860593],[-106.625763,31.856276],[-106.621857,31.852854],[-106.614637,31.84649],[-106.605845,31.846305],[-106.605245,31.845905],[-106.602045,31.844405],[-106.601945,31.839605],[-106.605267,31.827912],[-106.602727,31.825024],[-106.593826,31.824901],[-106.589045,31.822706],[-106.588045,31.822106],[-106.582144,31.815506],[-106.581344,31.813906],[-106.577244,31.810406],[-106.570944,31.810206],[-106.566844,31.813306],[-106.563444,31.812606],[-106.562945,31.811104],[-106.558444,31.810406],[-106.547144,31.807305],[-106.545344,31.805007],[-106.544714,31.804287],[-106.542144,31.802107],[-106.542097,31.802146],[-106.535843,31.798607],[-106.535343,31.797507],[-106.535154,31.797089],[-106.534743,31.796107],[-106.533043,31.791907],[-106.533,31.791829],[-106.53248,31.791914],[-106.530515,31.792103],[-106.527943,31.790507],[-106.527738,31.789761],[-106.527623,31.789119],[-106.527997,31.786945],[-106.528543,31.784407],[-106.528543,31.783907],[-106.750547,31.783706],[-106.750547,31.783898],[-106.993544,31.783689],[-106.998235,31.783671],[-107.00056,31.783679],[-107.00056,31.783513],[-107.296824,31.783762],[-107.422246,31.783599],[-107.422495,31.783599],[-108.208394,31.783599],[-108.208087,31.613489],[-108.208521,31.499798],[-108.208572,31.499742],[-108.208573,31.333395],[-108.707657,31.333191],[-108.788711,31.332365],[-108.851105,31.332301],[-108.861028,31.332315],[-109.050044,31.332502],[-109.050173,31.480004],[-109.049843,31.499515],[-109.049813,31.499528],[-109.049112,31.636598],[-109.049195,31.796551],[-109.048763,31.810776],[-109.049106,31.843715],[-109.048769,31.861383],[-109.04859,31.870791],[-109.048599,32.013651],[-109.048731,32.028174],[-109.048296,32.084093],[-109.048286,32.089114],[-109.047612,32.426377],[-109.047653,32.681379],[-109.047653,32.686327],[-109.047645,32.689988],[-109.047638,32.693439],[-109.047117,32.777569],[-109.047117,32.77757],[-109.04748,33.06842],[-109.047453,33.069427],[-109.046905,33.091931],[-109.047013,33.092917],[-109.047117,33.137559],[-109.047116,33.137995],[-109.047237,33.208965],[-109.04747,33.250063],[-109.046827,33.365272],[-109.046909,33.36557],[-109.047045,33.36928],[-109.04687,33.372654],[-109.046564,33.37506],[-109.047298,33.409783],[-109.046662,33.625055],[-109.047145,33.74001],[-109.046941,33.778233],[-109.046426,33.875052],[-109.047006,34.00005],[-109.046182,34.522393],[-109.046182,34.522553],[-109.046156,34.579291],[-109.046086,34.771016],[-109.045363,34.785406],[-109.046104,34.799981],[-109.045624,34.814226],[-109.046072,34.828566],[-109.045851,34.959718],[-109.046024,35.175499],[-109.046084,35.250025],[-109.046796,35.363606],[-109.046481,35.546326],[-109.046509,35.54644],[-109.046296,35.614251],[-109.046295,35.616517],[-109.046024,35.8798],[-109.046055,35.888721],[-109.046054,35.92586],[-109.046011,35.925896],[-109.045973,36.002338],[-109.045729,36.117028],[-109.046183,36.181751],[-109.045431,36.500001],[-109.045433,36.874589],[-109.045407,36.874998],[-109.045272,36.968871],[-109.045244,36.969489],[-109.045223,36.999084],[-108.958868,36.998913],[-108.954404,36.998906],[-108.620309,36.999287],[-108.619689,36.999249],[-108.379203,36.999459],[-108.320721,36.99951],[-108.320464,36.999499],[-108.2884,36.99952],[-108.288086,36.999555],[-108.250635,36.999561],[-108.249358,36.999015],[-108.000623,37.000001],[-107.481737,37.000005],[-107.420915,37.000005],[-107.420913,37.000005],[-106.877292,37.000139],[-106.869796,36.992426],[-106.750591,36.992461],[-106.675626,36.993123],[-106.661344,36.993243],[-106.628733,36.993161],[-106.628652,36.993175],[-106.617125,36.993004],[-106.617159,36.992967],[-106.500589,36.993768],[-106.47628,36.993839],[-106.343139,36.99423],[-106.293279,36.99389],[-106.248675,36.994288],[-106.247705,36.994266],[-106.201469,36.994122],[-106.006634,36.995343],[-105.997472,36.995417],[-105.996159,36.995418],[-105.71847,36.995846],[-105.716471,36.995849],[-105.66472,36.995874],[-105.62747,36.995679],[-105.533922,36.995875],[-105.512485,36.995777],[-105.508836,36.995895],[-105.465182,36.995991],[-105.447255,36.996017],[-105.442459,36.995994],[-105.41931,36.995856],[-105.251296,36.995605],[-105.220613,36.995169],[-105.155042,36.995339],[-105.1208,36.995428],[-105.029228,36.992729],[-105.000554,36.993264],[-104.73212,36.993484],[-104.732031,36.993447],[-104.645029,36.993378],[-104.625545,36.993599],[-104.624556,36.994377],[-104.519257,36.993766],[-104.338833,36.993535],[-104.250536,36.994644],[-104.007855,36.996239],[-103.734364,36.998041],[-103.733247,36.998016],[-103.155922,37.000232],[-103.086106,37.000174],[-103.002199,37.000104],[-103.002247,36.911587],[-103.001964,36.909573],[-103.002198,36.719427],[-103.002518,36.675186],[-103.002252,36.61718],[-103.002188,36.602716],[-103.002565,36.526588],[-103.002434,36.500397],[-103.041924,36.500439],[-103.041745,36.318267],[-103.041674,36.317534],[-103.040824,36.055231],[-103.041305,35.837694],[-103.042186,35.825217],[-103.041716,35.814072],[-103.041917,35.796441],[-103.041146,35.791583],[-103.041272,35.739274],[-103.041554,35.622487],[-103.042366,35.250056],[-103.042775,35.241237],[-103.042497,35.211862],[-103.042377,35.183156],[-103.042377,35.183149],[-103.042366,35.182786],[-103.042339,35.181922],[-103.042395,35.178573],[-103.042568,35.159318],[-103.042711,35.144735],[-103.0426,35.142766],[-103.04252,35.135596],[-103.043261,35.125058],[-103.042642,35.109913],[-103.042552,34.954101],[-103.042521,34.899546],[-103.042781,34.850243],[-103.04277,34.792224],[-103.042769,34.747361],[-103.042827,34.671188],[-103.043286,34.653099],[-103.043072,34.619782],[-103.043594,34.46266],[-103.043589,34.459774],[-103.043588,34.459662],[-103.043582,34.455657],[-103.043538,34.405463],[-103.043583,34.400678],[-103.043611,34.397105],[-103.043585,34.393716],[-103.043613,34.390442],[-103.043613,34.388679],[-103.043614,34.384969],[-103.04363,34.38469],[-103.043693,34.383578],[-103.043919,34.380916],[-103.043944,34.37966],[-103.043946,34.379555],[-103.043979,34.312764],[-103.043979,34.312749],[-103.043936,34.302585],[-103.043719,34.289441],[-103.043644,34.256903],[-103.043569,34.087947],[-103.043516,34.079382],[-103.043686,34.063078],[-103.043744,34.049986],[-103.043767,34.043545],[-103.043721,34.04232],[-103.043771,34.041538],[-103.043746,34.037294],[-103.043555,34.032714],[-103.043531,34.018014],[-103.043617,34.003633],[-103.04395,33.974629],[-103.044893,33.945617],[-103.045698,33.906299],[-103.045644,33.901537],[-103.046907,33.8503],[-103.047346,33.824675],[-103.049096,33.74627],[-103.049608,33.737766],[-103.050148,33.701971],[-103.050532,33.672408],[-103.051087,33.658186],[-103.051535,33.650487],[-103.051363,33.64195],[-103.051664,33.629489],[-103.05261,33.570599],[-103.056655,33.388438],[-103.056655,33.388416],[-103.057487,33.329477],[-103.057856,33.315234],[-103.059242,33.260371],[-103.05972,33.256262],[-103.060103,33.219225],[-103.063905,33.042055],[-103.06398,33.038693],[-103.064452,33.01029],[-103.064625,32.999899],[-103.064679,32.964373],[-103.064657,32.959097],[-103.064569,32.900014],[-103.064701,32.879355],[-103.064862,32.868346],[-103.064807,32.857696],[-103.064916,32.85726],[-103.064889,32.849359],[-103.064672,32.82847],[-103.064699,32.827531],[-103.064711,32.784593],[-103.064698,32.783602],[-103.064807,32.777303],[-103.064827,32.726628],[-103.064799,32.708694],[-103.064798,32.690761],[-103.064864,32.682647],[-103.064633,32.64642],[-103.064815,32.624537],[-103.064761,32.601863],[-103.064788,32.600397],[-103.064761,32.587983],[-103.064696,32.522193],[-103.064422,32.145006],[-103.064348,32.123041],[-103.064344,32.087051],[-103.064423,32.000518],[-103.085876,32.000465],[-103.088698,32.000453],[-103.215641,32.000513],[-103.267633,32.000475],[-103.267708,32.000324],[-103.270383,32.000326],[-103.278521,32.000419],[-103.326501,32.00037],[-103.722853,32.000208],[-103.748317,32.000198],[-103.875476,32.000554],[-103.980179,32.000125],[-104.024521,32.00001],[-104.531756,32.000117],[-104.531937,32.000311],[-104.640918,32.000396],[-104.643526,32.000443],[-104.847757,32.000482],[-104.918272,32.000496],[-105.077046,32.000579],[-105.078605,32.000533],[-105.11804,32.000485],[-105.131377,32.000524],[-105.132916,32.000518],[-105.14824,32.000485],[-105.15031,32.000497],[-105.153994,32.000497],[-105.390396,32.000607],[-105.427049,32.000638],[-105.428582,32.0006],[-105.429281,32.000577],[-105.731362,32.001564],[-105.750527,32.002206],[-105.854061,32.00235],[-105.886159,32.00197],[-105.9006,32.0021],[-105.998003,32.002328]]]},\"properties\":{\"name\":\"New Mexico\",\"nation\":\"USA  \"}}]}","volume":"83","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":766905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"KARSCH, REBEKAH C.","contributorId":217498,"corporation":false,"usgs":false,"family":"KARSCH","given":"REBEKAH","email":"","middleInitial":"C.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":766906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldstein, Elise J.","contributorId":217499,"corporation":false,"usgs":false,"family":"Goldstein","given":"Elise","email":"","middleInitial":"J.","affiliations":[{"id":39654,"text":"nmdgf","active":true,"usgs":false}],"preferred":false,"id":766907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rominger, Eric M.","contributorId":217500,"corporation":false,"usgs":false,"family":"Rominger","given":"Eric","email":"","middleInitial":"M.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":766908,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gould, William R.","contributorId":217297,"corporation":false,"usgs":false,"family":"Gould","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":766909,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215740,"text":"70215740 - 2019 - Effects of climate-related stream factors on patterns of individual summer growth of Cutthroat Trout","interactions":[],"lastModifiedDate":"2020-10-28T12:32:54.446395","indexId":"70215740","displayToPublicDate":"2018-10-26T07:24:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate-related stream factors on patterns of individual summer growth of Cutthroat Trout","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Coldwater fishes are sensitive to abiotic and biotic stream factors, which can be influenced by climate. Distributions of inland salmonids in North America have declined significantly, with many of the current strongholds located in small headwater systems that may serve as important refugia as climate change progresses. We investigated the effects of discharge, stream temperature, trout biomass, and food availability on summer growth of Yellowstone Cutthroat Trout<span>&nbsp;</span><i>Oncorhynchus clarkii bouvieri</i>, a species of concern with significant ecological value. Individual size, stream discharge, sample section biomass, and temperature were all associated with growth, but had differing effects on energy allocation. Stream discharge had a positive relationship with growth rates in length and mass; greater rates of prey delivery at higher discharges probably enabled trout to accumulate reserve tissues in addition to structural growth. Temperature effects were positive but not significant, and support in growth models was limited, likely due to the cold thermal regimes of the study area. The strength of the discharge effect on growth suggests that climate adaptation strategies for coldwater fishes that focus solely on thermal characteristics may be misleading and highlights the importance of considering multiple factors, including hydrologic regimes, in conservation planning.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10106","usgsCitation":"Uthe, P., Al-Chokhachy, R., Shepard, B., Zale, A.V., and Kershner, J., 2019, Effects of climate-related stream factors on patterns of individual summer growth of Cutthroat Trout: Transactions of the American Fisheries Society, v. 148, no. 1, p. 21-34, https://doi.org/10.1002/tafs.10106.","productDescription":"14 p.","startPage":"21","endPage":"34","ipdsId":"IP-059914","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":460557,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10106","text":"Publisher Index Page"},{"id":379861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","otherGeospatial":"Shields River, Spread Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.32421875,\n              44.99588261816546\n            ],\n            [\n              -111.005859375,\n              44.74673324024678\n            ],\n            [\n              -111.005859375,\n              43.03677585761058\n            ],\n            [\n              -108.45703125,\n              43.03677585761058\n            ],\n            [\n              -110.0390625,\n              45.98169518512228\n            ],\n            [\n              -111.4013671875,\n              46.830133640447386\n            ],\n            [\n              -112.8955078125,\n              46.31658418182218\n            ],\n            [\n              -112.32421875,\n              44.99588261816546\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"148","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Uthe, Patrick","contributorId":189424,"corporation":false,"usgs":false,"family":"Uthe","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":803251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":228929,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shepard, Bradley","contributorId":152364,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","affiliations":[{"id":18917,"text":"4B.B. Shepard and Associates, Livingston, MT, 59047 USA","active":true,"usgs":false}],"preferred":false,"id":803253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":803254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kershner, Jeffrey L.","contributorId":204244,"corporation":false,"usgs":false,"family":"Kershner","given":"Jeffrey L.","affiliations":[],"preferred":false,"id":803255,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70200631,"text":"70200631 - 2019 - Decreased atmospheric nitrogen deposition in eastern North America: Predicted responses of forest ecosystems","interactions":[],"lastModifiedDate":"2018-10-25T12:39:10","indexId":"70200631","displayToPublicDate":"2018-10-25T12:39:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Decreased atmospheric nitrogen deposition in eastern North America: Predicted responses of forest ecosystems","docAbstract":"<p><span>Historical increases in emissions and atmospheric deposition of oxidized and reduced nitrogen (N) provided the impetus for extensive, global-scale research investigating the effects of excess N in terrestrial and aquatic ecosystems, with several regions within the Eastern Deciduous Forest of the United States found to be susceptible to negative effects of excess N. The Clean Air Act and associated rules have led to decreases in emissions and deposition of oxidized N, especially in eastern U.S., representing a research challenge and opportunity for ecosystem ecologists and biogeochemists. The purpose of this paper is to predict changes in the structure and function of North American forest ecosystems in a future of decreased N deposition. Hysteresis is a property of a system wherein output is not a strict function of corresponding input, incorporating lag, delay, or history dependence, particularly when the response to decreasing input is different from the response to increasing input. We suggest a conceptual hysteretic model predicting varying lag times in recovery of soil acidification, plant biodiversity, soil microbial communities, forest carbon (C) and N cycling, and surface water chemistry toward pre-N impact conditions. Nearly all of these can potentially respond strongly to reductions in N deposition. Most responses are expected to show some degree of hysteresis, with the greatest delays in response occurring in processes most tightly linked to “slow pools” of N in wood and soil organic matter. Because experimental studies of declines in N loads in forests of North America are lacking and because of the expected hysteresis, it is difficult to generalize from experimental results to patterns expected from declining N deposition. These will likely be long-term phenomena, difficult to distinguish from other, concurrent environmental changes, including elevated atmospheric CO</span><sub>2</sub><span>, climate change, reductions in acidity, invasions of new species, and long-term vegetation responses to past disturbance.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2018.09.135","usgsCitation":"Gilliam, F.S., Burns, D., Driscoll, C.T., Frey, S.D., Lovett, G.M., and Watmough, S.A., 2019, Decreased atmospheric nitrogen deposition in eastern North America: Predicted responses of forest ecosystems: Environmental Pollution, v. 244, p. 560-574, https://doi.org/10.1016/j.envpol.2018.09.135.","productDescription":"15 p.","startPage":"560","endPage":"574","ipdsId":"IP-098706","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":358821,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"244","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8dce4b034bf6a7e4d85","contributors":{"authors":[{"text":"Gilliam, Frank S.","contributorId":168383,"corporation":false,"usgs":false,"family":"Gilliam","given":"Frank","email":"","middleInitial":"S.","affiliations":[{"id":16679,"text":"Marshall University","active":true,"usgs":false}],"preferred":false,"id":749763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":749762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":749764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frey, Serita D.","contributorId":177401,"corporation":false,"usgs":false,"family":"Frey","given":"Serita","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":749765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovett, Gary M.","contributorId":210078,"corporation":false,"usgs":false,"family":"Lovett","given":"Gary","email":"","middleInitial":"M.","affiliations":[{"id":36424,"text":"Cary Institute of Ecosystems Studies","active":true,"usgs":false}],"preferred":false,"id":749766,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watmough, Shaun A.","contributorId":178413,"corporation":false,"usgs":false,"family":"Watmough","given":"Shaun","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":749767,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70223221,"text":"70223221 - 2019 - Behavior and survival of stocked trout in southern Appalachian Mountain streams","interactions":[],"lastModifiedDate":"2021-08-19T13:50:16.146081","indexId":"70223221","displayToPublicDate":"2018-10-25T07:46:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Behavior and survival of stocked trout in southern Appalachian Mountain streams","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Stocking of trout to support recreational fisheries is a common practice among state and federal agencies to meet angling and harvest demands. Success of stocking efforts relies upon fish behavior and survival to maximize the availability of fish to anglers. We quantitatively described the movement behavior and survival of&nbsp;stocked Brook Trout<span>&nbsp;</span><i>Salvelinus fontinalis</i>, Brown Trout<span>&nbsp;</span><i>Salmo trutta</i>, and Rainbow Trout<span>&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;</span>in three southern Appalachian Mountain streams in western North Carolina, USA, that were managed under delayed harvest regulations. Hatchery trout were tagged with a combination of PIT tags and radio transmitters (radio tags); stocked into “Delayed Harvest Trout Waters” of the North Toe, East Prong Roaring, and Little rivers; and monitored during the catch-and-release season from October to June. Assessed according to river and species, 19–65% of trout emigrated from the delayed harvest study reaches, while 1–29% died within the reaches. The majority of radio-tagged fish (71%; 59–85% by river) remained within 2&nbsp;km of the stocking location, whereas 6% migrated over 10&nbsp;km from the stocking location. Few trout stocked during fall (October and November) were available to anglers the following June due to a combination of migration and mortality. Emigration from delayed harvest study reaches was associated with stocking and high-flow events. Multi-state modeling detailed these observations with weekly estimates of migration and survival rates. River-specific differences in emigration and mortality suggested that emigration was a greater source of trout loss than mortality in all rivers; no pattern related to river size was apparent in emigration, but mortality was greater in small streams. Brook Trout mortality rates were highest among the three species, and large fish of most species showed higher emigration and mortality than catchable-sized trout. Fisheries managers can apply our results to alter stocking regimes so as to enhance the efficiency of stocking and the acclimation of stocked trout to instream environments.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10113","usgsCitation":"Flowers, H., Kwak, T.J., Fischer, J., Cope, W.G., Rash, J., and Besler, D., 2019, Behavior and survival of stocked trout in southern Appalachian Mountain streams: Transactions of the American Fisheries Society, v. 148, no. 1, p. 3-20, https://doi.org/10.1002/tafs.10113.","productDescription":"18 p.","startPage":"3","endPage":"20","ipdsId":"IP-100752","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10113","text":"Publisher Index Page"},{"id":388091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Appalachian Mountains, East Prong Roaring River, Little River, North Toe River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.50457763671874,\n              35.232159412017154\n            ],\n            [\n              -81.6888427734375,\n              35.93354064249312\n            ],\n            [\n              -81.2164306640625,\n              36.39475669987386\n            ],\n            [\n              -81.27685546875,\n              36.55598153635691\n            ],\n            [\n              -82.10357666015625,\n              36.54494944148322\n            ],\n            [\n              -82.5567626953125,\n              35.980228800645676\n            ],\n            [\n              -83.2159423828125,\n              35.71975793933433\n            ],\n            [\n              -83.7762451171875,\n              35.14012515937234\n            ],\n            [\n              -83.22967529296874,\n              35.0367432201753\n            ],\n            [\n              -82.50457763671874,\n              35.232159412017154\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"148","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Flowers, H.J.","contributorId":264382,"corporation":false,"usgs":false,"family":"Flowers","given":"H.J.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, J.R.","contributorId":243988,"corporation":false,"usgs":false,"family":"Fischer","given":"J.R.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cope, W. G.","contributorId":264384,"corporation":false,"usgs":false,"family":"Cope","given":"W.","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":821433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rash, J.M.","contributorId":264387,"corporation":false,"usgs":false,"family":"Rash","given":"J.M.","email":"","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":821434,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Besler, D.A.","contributorId":264389,"corporation":false,"usgs":false,"family":"Besler","given":"D.A.","email":"","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":821435,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70200563,"text":"70200563 - 2019 - A Bayesian life-cycle model to estimate escapement at maximum sustained yield in salmon based on limited information","interactions":[],"lastModifiedDate":"2019-01-28T08:56:43","indexId":"70200563","displayToPublicDate":"2018-10-24T11:10:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian life-cycle model to estimate escapement at maximum sustained yield in salmon based on limited information","docAbstract":"<p><span>Life-cycle models combine several strengths for estimating population parameters and biological reference points of harvested species and are particularly useful for those exhibiting distinct habitat shifts and experiencing contrasting environments. Unfortunately, time series data are often limited to counts of adult abundance and harvest. By incorporating data from other populations and by dynamically linking the life-history stages, Bayesian life-cycle models can be used to estimate stage-specific productivities and capacities as well as abundance of breeders that produce maximum sustained yield (MSY). Using coho salmon (</span><i>Oncorhynchus kisutch</i><span>) as our case study, we show that incorporating information on marine survival variability from nearby populations can improve model estimates and affect management parameters such as escapement at MSY. We further show that the expected long-term average yield of a fishery managed for a spawner escapement target that produces MSY strongly depends on the average marine survival. Our results illustrate the usefulness of incorporating information from other sources and highlight the importance of accounting for variation in marine survival when making inferences about the management of Pacific salmon.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0382","usgsCitation":"Ohlberger, J., Brinkman, S.J., Crain, P., Pess, G.R., Duda, J.J., Buehrens, T.W., Quinn, T.P., and Hilborn, R., 2019, A Bayesian life-cycle model to estimate escapement at maximum sustained yield in salmon based on limited information: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 2, p. 299-307, https://doi.org/10.1139/cjfas-2017-0382.","productDescription":"9 p.","startPage":"299","endPage":"307","ipdsId":"IP-090701","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":501058,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/90654","text":"External Repository"},{"id":358729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125,\n              47\n            ],\n            [\n              -122.5,\n              47\n            ],\n            [\n              -122.5,\n              48.4\n            ],\n            [\n              -125,\n              48.4\n            ],\n            [\n              -125,\n              47\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"76","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a916e4b034bf6a7e4f7e","contributors":{"authors":[{"text":"Ohlberger, Jan","contributorId":210015,"corporation":false,"usgs":false,"family":"Ohlberger","given":"Jan","email":"","affiliations":[{"id":38048,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195","active":true,"usgs":false}],"preferred":false,"id":749596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinkman, Samuel J.","contributorId":210016,"corporation":false,"usgs":false,"family":"Brinkman","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":38049,"text":"National Park Service, Olympic National Park, 600 East Park Avenue, Port Angeles, WA 98362","active":true,"usgs":false}],"preferred":false,"id":749597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crain, Patrick","contributorId":210017,"corporation":false,"usgs":false,"family":"Crain","given":"Patrick","affiliations":[{"id":38049,"text":"National Park Service, Olympic National Park, 600 East Park Avenue, Port Angeles, WA 98362","active":true,"usgs":false}],"preferred":false,"id":749598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":749599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749595,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buehrens, Thomas W.","contributorId":210018,"corporation":false,"usgs":false,"family":"Buehrens","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":38048,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195","active":true,"usgs":false}],"preferred":false,"id":749600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":749601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hilborn, Ray","contributorId":177767,"corporation":false,"usgs":false,"family":"Hilborn","given":"Ray","email":"","affiliations":[],"preferred":false,"id":749602,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70200459,"text":"70200459 - 2019 - Population dynamics of reintroduced Whooping Cranes","interactions":[],"lastModifiedDate":"2018-10-23T14:19:02","indexId":"70200459","displayToPublicDate":"2018-10-23T14:18:41","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Population dynamics of reintroduced Whooping Cranes","docAbstract":"<p><span>Because of the small size and restricted range of the Aransas-Wood Buffalo Population, reintroduction is a prominent element of the recovery effort to ensure persistence of&nbsp;Whooping Cranes&nbsp;(</span><i>Grus americana</i><span>). A fundamental objective of all Whooping Crane reintroduction efforts is the establishment of a self-sustaining population. Therefore, success of reintroduction efforts will ultimately be determined by demography: births and deaths of Whooping Cranes in the released population. We present a detailed review of the demographic modeling efforts for two reintroduced populations of Whooping Cranes: the Florida Nonmigratory Population and the Eastern Migratory Population. Both of these populations have struggled with poor demographic performance, and the Florida Nonmigratory Population is now nearly extirpated. The focus of our review is on the models used to represent Whooping Crane population dynamics and the major uncertainties that still exist about population dynamics in reintroduced Whooping Cranes. We also discuss the centrality of population models to the management of reintroduced Whooping Cranes, and the use of decision analysis to navigate multiple-objective decisions made under uncertainty. Development of demographic models, and articulation and testing of hypotheses about the causes of poor demographic performance in reintroduced populations, will continue to be research areas of importance in support of Whooping Crane reintroduction.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Whooping Cranes: Biology and conservation","language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-803555-9.00007-4","usgsCitation":"Converse, S.J., Servanty, S., Moore, C.T., and Runge, M.C., 2019, Population dynamics of reintroduced Whooping Cranes, chap. <i>of</i> Whooping Cranes: Biology and conservation, p. 139-160, https://doi.org/10.1016/B978-0-12-803555-9.00007-4.","productDescription":"22 p.","startPage":"139","endPage":"160","ipdsId":"IP-076813","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":358686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10a8dee4b034bf6a7e4d99","contributors":{"authors":[{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":748973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Servanty, Sabrina","contributorId":209864,"corporation":false,"usgs":false,"family":"Servanty","given":"Sabrina","email":"","affiliations":[],"preferred":false,"id":748974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":748975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":748976,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70200477,"text":"70200477 - 2019 - Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells","interactions":[],"lastModifiedDate":"2019-01-28T08:57:31","indexId":"70200477","displayToPublicDate":"2018-10-20T17:25:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2832,"text":"Natural Resources Research","onlineIssn":"1573-8981","printIssn":"1520-7439","active":true,"publicationSubtype":{"id":10}},"title":"Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells","docAbstract":"<p>The application of horizontal and hydraulically fractured wells for producing oil from low permeability formations has changed the face of the North American oil industry. One feature of the production profile of many such wells is a transition from transient linear oil flow to boundary-dominated flow. The identification of the time of this transition is important for the calibration of models that forecast the well’s future production and the expected ultimate recovery. It is preferable that such models generally use data from the boundary-dominated flow regime for parameter calibration. Accurate well production forecasts are needed for operational decisions, long-term planning, commercial transactions, regulatory proceedings, and asset valuation. Petroleum engineers frequently make the call on the transition point based on subjective visual interpretations of log–log plots for individual wells. This is time-consuming and is generally not repeatable by other analysts. This note evaluates statistical approaches that can serve as alternatives to the subjective visual interpretations. Specifically, the predictive performance of production models calibrated with boundary-dominated data based on transition dates calculated with constrained nonlinear least squares and Bayesian regressions was very close to that obtained using the visual method, suggesting that statistical approaches may indeed be constructed to replace less objective visual approaches without loss of accuracy.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11053-018-9389-0","usgsCitation":"Attanasi, E., Coburn, T., and Ran-McDonald, B., 2019, Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells: Natural Resources Research, v. 28, no. 1, p. 259-272, https://doi.org/10.1007/s11053-018-9389-0.","productDescription":"14 p.","startPage":"259","endPage":"272","ipdsId":"IP-091903","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468068,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11053-018-9389-0","text":"Publisher Index Page"},{"id":358589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-26","publicationStatus":"PW","scienceBaseUri":"5c10a91ae4b034bf6a7e4fb3","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coburn, T.C.","contributorId":209912,"corporation":false,"usgs":false,"family":"Coburn","given":"T.C.","email":"","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":749070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ran-McDonald, B.","contributorId":209913,"corporation":false,"usgs":false,"family":"Ran-McDonald","given":"B.","email":"","affiliations":[{"id":38022,"text":"University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":749071,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70203303,"text":"70203303 - 2019 - Tropical cyclone projections: Changing climate threats for Pacific Island defense installations","interactions":[],"lastModifiedDate":"2019-05-02T15:06:24","indexId":"70203303","displayToPublicDate":"2018-10-16T14:11:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5829,"text":"Weather, Climate, and Society","printIssn":"1948-8327","active":true,"publicationSubtype":{"id":10}},"title":"Tropical cyclone projections: Changing climate threats for Pacific Island defense installations","docAbstract":"Potential changing climate threats in the tropical and subtropical North Pacific Ocean were assessed, using coupled ocean-atmosphere and atmosphere-only general circulation models, to explore their response to projected increasing greenhouse gas emissions. Tropical cyclone occurrence, described by their frequency and intensity, near islands housing major U.S. defense installations was the primary focus. Four island regions—Guam and Kwajalein Atoll in the tropical northwestern Pacific, Okinawa in the subtropical northwestern Pacific, and O‘ahu in the tropical northcentral Pacific—were considered, as they provide unique climate and geographical characteristics that either enhance or reduce the tropical cyclone risk. Guam experiences the most frequent and severe tropical cyclones, which often originate as weak systems close to the equator near Kwajalein and sometimes track far enough north to affect Okinawa, whereas intense storms are the least frequent around O‘ahu. From assessments of models that simulate well the tropical Pacific climate, it was determined that, with a projected warming climate, the number of tropical cyclones is likely to decrease for Guam and Kwajalein but remain about the same near Okinawa and O‘ahu; however, the maximum intensity of the strongest storms may increase in most regions. The likelihood of fewer but stronger storms will necessitate new localized assessments of the risk and vulnerabilities to tropical cyclones in the North Pacific.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/WCAS-D-17-0112.1","usgsCitation":"Widlansky, M.J., Annamalai, H., Gingerich, S.B., Storlazzi, C.D., Marra, J.J., Hodges, K.I., Choy, B., and Kitoh, A., 2019, Tropical cyclone projections: Changing climate threats for Pacific Island defense installations: Weather, Climate, and Society, v. 11, no. 1, 13 p., https://doi.org/10.1175/WCAS-D-17-0112.1.","productDescription":"13 p.","ipdsId":"IP-090010","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":460559,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://centaur.reading.ac.uk/80182/1/wcas-d-17-0112.1.pdf","text":"External Repository"},{"id":363492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Widlansky, Matthew J.","contributorId":215334,"corporation":false,"usgs":false,"family":"Widlansky","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39222,"text":"Joint Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":762068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Annamalai, Hariharasubramanian","contributorId":204461,"corporation":false,"usgs":false,"family":"Annamalai","given":"Hariharasubramanian","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":762069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":762070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marra, John J.","contributorId":215335,"corporation":false,"usgs":false,"family":"Marra","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":39223,"text":"NOAA/NESDIS/National Centers for Environmental Information","active":true,"usgs":false}],"preferred":false,"id":762071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hodges, Kevin I.","contributorId":215336,"corporation":false,"usgs":false,"family":"Hodges","given":"Kevin","email":"","middleInitial":"I.","affiliations":[{"id":39224,"text":"University of Reading, U.K.","active":true,"usgs":false}],"preferred":false,"id":762072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Choy, Barry","contributorId":215337,"corporation":false,"usgs":false,"family":"Choy","given":"Barry","email":"","affiliations":[{"id":39225,"text":"NOAA Commissioned Officer Corps/Liaison to U.S. Pacific Command,","active":true,"usgs":false}],"preferred":false,"id":762073,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kitoh, Akio","contributorId":215338,"corporation":false,"usgs":false,"family":"Kitoh","given":"Akio","email":"","affiliations":[{"id":39226,"text":"Japan Meteorological Business Support Center, Tsukuba, Japan","active":true,"usgs":false}],"preferred":false,"id":762074,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70203348,"text":"70203348 - 2019 - Near-surface environmentally forced changes in the Ross Ice Shelf observed with ambient seismic noise","interactions":[],"lastModifiedDate":"2019-05-07T13:16:54","indexId":"70203348","displayToPublicDate":"2018-10-16T13:14:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Near-surface environmentally forced changes in the Ross Ice Shelf observed with ambient seismic noise","docAbstract":"Continuous seismic observations across the Ross Ice Shelf reveal ubiquitous ambient res-\n\tonances at frequencies >5 Hz. These firn-trapped surface wave signals arise through wind\n\tand snow bedform interactions coupled with very low velocity structures. Progressive and long-term spectral changes are associated with surface snow redistribution by wind\n\tand with a January 2016 regional melt event. Modeling demonstrates high spectral sen-\n\tsitivity to near-surface (top several m) elastic parameters. We propose that spectral peak changes arise from surface snow redistribution in wind events, and to velocity drops re-\n\tflecting snow lattice weakening near 0◦C for the melt event. Percolation-related refrozen\n\tlayers and layer thinning may also contribute to long-term spectral changes after the melt\n\tevent. Single-station observations are inverted for elastic structure for multiple stations across the ice shelf. High-frequency ambient noise seismology presents opportunities for\n\tcontinuous assessment of near surface ice shelf or other firn environments.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL079665","usgsCitation":"Chaput, J., Aster, R., McGrath, D., Baker, M., Anthony, R.E., Gerstoft, P., Bromirski, P., Nyblade, A., Stephen, R., and Wiens, D., 2019, Near-surface environmentally forced changes in the Ross Ice Shelf observed with ambient seismic noise: Geophysical Research Letters, v. 45, no. 11, p. 11,187-11,196, https://doi.org/10.1029/2018GL079665.","productDescription":"10 p.","startPage":"11,187","endPage":"11,196","ipdsId":"IP-100650","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468070,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2018gl079665","text":"External Repository"},{"id":363564,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363552,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1029/2018GL079665"}],"otherGeospatial":"Ross Ice Shelf","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -210.9375,\n              -80.70399666821143\n            ],\n            [\n              -38.3203125,\n              -80.70399666821143\n            ],\n            [\n              -38.3203125,\n              -65.21989393613208\n            ],\n            [\n              -210.9375,\n              -65.21989393613208\n            ],\n            [\n              -210.9375,\n              -80.70399666821143\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Chaput, J.","contributorId":215407,"corporation":false,"usgs":false,"family":"Chaput","given":"J.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":762256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aster, R. C.","contributorId":215408,"corporation":false,"usgs":false,"family":"Aster","given":"R. C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":762257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGrath, D.","contributorId":215409,"corporation":false,"usgs":false,"family":"McGrath","given":"D.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":762258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, M.G.W.","contributorId":201473,"corporation":false,"usgs":false,"family":"Baker","given":"M.G.W.","email":"","affiliations":[],"preferred":false,"id":762259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerstoft, P.","contributorId":215410,"corporation":false,"usgs":false,"family":"Gerstoft","given":"P.","email":"","affiliations":[{"id":15303,"text":"University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":762261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bromirski, P.","contributorId":215411,"corporation":false,"usgs":false,"family":"Bromirski","given":"P.","email":"","affiliations":[{"id":15303,"text":"University of California, San Diego","active":true,"usgs":false}],"preferred":false,"id":762262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nyblade, A.","contributorId":215412,"corporation":false,"usgs":false,"family":"Nyblade","given":"A.","email":"","affiliations":[{"id":39240,"text":"Pennsylvania State University, State College","active":true,"usgs":false}],"preferred":false,"id":762263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stephen, R.A.","contributorId":215413,"corporation":false,"usgs":false,"family":"Stephen","given":"R.A.","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":762264,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wiens, D.","contributorId":215414,"corporation":false,"usgs":false,"family":"Wiens","given":"D.","email":"","affiliations":[{"id":35028,"text":"Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":762265,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70200340,"text":"70200340 - 2019 - Potential responses of the Lower Missouri River Shovelnose Sturgeon (Scaphirhynchus platorynchus) population to a commercial fishing ban","interactions":[],"lastModifiedDate":"2019-03-04T11:22:09","indexId":"70200340","displayToPublicDate":"2018-10-12T14:20:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Potential responses of the Lower Missouri River Shovelnose Sturgeon (<i>Scaphirhynchus platorynchus</i>) population to a commercial fishing ban","title":"Potential responses of the Lower Missouri River Shovelnose Sturgeon (Scaphirhynchus platorynchus) population to a commercial fishing ban","docAbstract":"<p><span>We developed an age‐structured population matrix model to perform population viability analysis for Lower Missouri River (LMR) shovelnose sturgeon (</span><i>Scaphirhynchus platorynchus</i><span>). We investigated potential effects of the commercial fishing moratorium put in place to help protect the similar‐appearing pallid sturgeon (</span><i>S. albus</i><span>). The model applies different components of total variance in life history parameters at different levels: sampling variance (parameter uncertainty) between model iterations; temporal variance (temporal environmental fluctuations) between time steps within iterations; and individual variance (individual differences) within each time‐step. The model predicted annual rates of population increase of 1.96% under historic fishing and 2.67% with removal of historic fishing. We identified combinations of fishing and harvest size restrictions that would permit a sustainable harvest of shovelnose sturgeon. Overall, the ban on commercial fishing of shovelnose sturgeon in the LMR due to similarity of appearance to pallid sturgeon should help the LMR shovelnose sturgeon population begin to rebound while decreasing any negative effects it may have had on pallid sturgeon populations.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/jai.13701","usgsCitation":"Green, N., Wildhaber, M.L., and Albers, J.L., 2019, Potential responses of the Lower Missouri River Shovelnose Sturgeon (Scaphirhynchus platorynchus) population to a commercial fishing ban: Journal of Applied Ichthyology, v. 35, no. 1, p. 370-377, https://doi.org/10.1111/jai.13701.","productDescription":"8 p.","startPage":"370","endPage":"377","ipdsId":"IP-072152","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":468073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.13701","text":"Publisher Index Page"},{"id":358350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Missouri River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.103515625,\n              37.020098201368114\n            ],\n            [\n              -90.087890625,\n              37.020098201368114\n            ],\n            [\n              -90.087890625,\n              49.009050809382046\n            ],\n            [\n              -116.103515625,\n              49.009050809382046\n            ],\n            [\n              -116.103515625,\n              37.020098201368114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-20","publicationStatus":"PW","scienceBaseUri":"5c10a91fe4b034bf6a7e5004","contributors":{"authors":[{"text":"Green, Nicholas S. 0000-0002-8538-4191","orcid":"https://orcid.org/0000-0002-8538-4191","contributorId":202040,"corporation":false,"usgs":true,"family":"Green","given":"Nicholas S.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":748390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":748391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albers, Janice L. 0000-0002-6312-8269 jalbers@usgs.gov","orcid":"https://orcid.org/0000-0002-6312-8269","contributorId":3972,"corporation":false,"usgs":true,"family":"Albers","given":"Janice","email":"jalbers@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":748392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207113,"text":"70207113 - 2019 - Testing the potential role of brine reflux in the formation of sedimentary exhalative (Sedex) ore deposits","interactions":[],"lastModifiedDate":"2020-08-06T20:26:40.86865","indexId":"70207113","displayToPublicDate":"2018-10-12T09:36:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Testing the potential role of brine reflux in the formation of sedimentary exhalative (Sedex) ore deposits","docAbstract":"Sedimentary exhalative (sedex) ore deposits are the world’s largest Zn-Pb deposits. While the geologic processes that formed these deposits are generally well understood, the fundamental hydrologic processes that drove these massive hydrothermal systems remain an area of debate. We use numerical modeling to test an emerging hypothesis, supported by recent ore genesis research and sedex basin analysis, that brine reflux flow systems produced and drove the fluids that formed sedex deposits.  A previous numerical model of brine reflux, developed to study dolomitization, is adapted to a sedimentary basin with geologic features essential for sedex formation. We simulate the flow of evaporated brines through the basin and the evolution of salinity, temperature, and flow rates, and find that modeled values for these parameters for brines discharging to the seafloor exceed previously established physiochemical thresholds for ore formation (>170 g/L, >80°C, and total discharge volumes >107 m3 per meter perpendicular to the 2D model section). Sensitivity testing of this modest-sized basin highlights the large effect that aspects of the hydrogeologic framework can have on mineralizing potential of the reflux brines. Finally, modeling alternating periods of active and inactive evaporation produces pulsed brine reflux systems capable of producing multiple deposits of different age as observed in many sedex basins. The modeling thus supports the hypothesis that seawater evaporation on the basin margin significantly inboard of sedex deposits may be responsible for their formation. Sensitivity testing suggests that numerical models with more detailed, basin-specific geologic frameworks might be useful for assessing the mineral potential of sedimentary basins.","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2018.10.003","usgsCitation":"Manning, A.H., and Emsbo, P., 2019, Testing the potential role of brine reflux in the formation of sedimentary exhalative (Sedex) ore deposits: Ore Geology Reviews, v. 102, p. 862-874, https://doi.org/10.1016/j.oregeorev.2018.10.003.","productDescription":"13 p.","startPage":"862","endPage":"874","ipdsId":"IP-097533","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":468075,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2018.10.003","text":"Publisher Index Page"},{"id":370079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":776870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Emsbo, Poul 0000-0001-9421-201X pemsbo@usgs.gov","orcid":"https://orcid.org/0000-0001-9421-201X","contributorId":997,"corporation":false,"usgs":true,"family":"Emsbo","given":"Poul","email":"pemsbo@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":776871,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70199965,"text":"70199965 - 2019 - Grounding simulation models with qualitative case studies: Toward a holistic framework to make climate science usable for US public land management","interactions":[],"lastModifiedDate":"2019-03-15T12:44:12","indexId":"70199965","displayToPublicDate":"2018-10-09T10:43:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5474,"text":"Climate Risk Management","active":true,"publicationSubtype":{"id":10}},"title":"Grounding simulation models with qualitative case studies: Toward a holistic framework to make climate science usable for US public land management","docAbstract":"<p><span>Policies directing agencies and public land managers to incorporate&nbsp;</span>climate change<span>&nbsp;into management face several barriers. These stem, in part, from a disconnect between the information that is produced and the information needs of local resource managers. A disproportionate focus on the natural and physical sciences in climate vulnerability and adaptation assessment obscure understandings of complex social systems and the interactions and feedbacks in social-ecological systems. We use a qualitative case study of bison management on Department of the Interior-managed and tribal lands to explore how a social-science driven Determinants and Analogue Vulnerability Assessment (DAVA) can inform ecological response models, specifically simulation models that account for multiple drivers of change. First, we illustrate how a DAVA approach can help to: 1) identify key processes, entities, and interactions across scales; 2) document local impacts, indicators, and monitoring efforts of drought and climate; and 3) identify major tradeoffs and uncertainties. We then demonstrate how qualitative narratives can inform simulation models by: 1) prioritizing model components included in modeling efforts; 2) framing joint management and climate scenarios; and 3) parameterizing and evaluating model performance. We do this by presenting a conceptual joint agent-based/state-and-transition simulation modeling framework. Simulation models can represent multiple interacting variables and can identify surprising, emergent outcomes that might not be evident from qualitative analysis alone, and we argue that qualitative case studies can ground simulation models in local contexts and help make them more structurally realistic and useful. Together, these can provide a step toward developing actionable&nbsp;climate change adaptation&nbsp;strategies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.crm.2018.09.002","usgsCitation":"Beeton, T.A., McNeeley, S.M., Miller, B.W., and Ojima, D.S., 2019, Grounding simulation models with qualitative case studies: Toward a holistic framework to make climate science usable for US public land management: Climate Risk Management, v. 23, p. 50-66, https://doi.org/10.1016/j.crm.2018.09.002.","productDescription":"17 p.","startPage":"50","endPage":"66","ipdsId":"IP-079241","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":468078,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.crm.2018.09.002","text":"Publisher Index Page"},{"id":358205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f76e4b0fc368eb53835","contributors":{"authors":[{"text":"Beeton, Tyler A.","contributorId":208509,"corporation":false,"usgs":false,"family":"Beeton","given":"Tyler","email":"","middleInitial":"A.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":747504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNeeley, Shannon M.","contributorId":208510,"corporation":false,"usgs":false,"family":"McNeeley","given":"Shannon","email":"","middleInitial":"M.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":747505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Brian W. 0000-0003-1716-1161 bwmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":191731,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"bwmiller@usgs.gov","middleInitial":"W.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":747503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ojima, Dennis S.","contributorId":208511,"corporation":false,"usgs":false,"family":"Ojima","given":"Dennis","email":"","middleInitial":"S.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":747506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199802,"text":"70199802 - 2019 - Mineralization at oceanic transform faults and fracture zones","interactions":[],"lastModifiedDate":"2018-10-09T15:14:28","indexId":"70199802","displayToPublicDate":"2018-10-09T10:38:24","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Mineralization at oceanic transform faults and fracture zones","docAbstract":"<p id=\"sp0020\"><span>Mineral formation in the modern oceans can take place over millions of years as a result precipitation from ambient ocean water, or orders of magnitude more rapidly from&nbsp;hydrothermal activity&nbsp;related to magmatic and tectonic processes. Here, we review associations between&nbsp;transform faults&nbsp;and related&nbsp;fracture zones&nbsp;and marine minerals. We define&nbsp;</span><i>marine transform faults</i><span>&nbsp;as&nbsp;strike-slip or oblique faults&nbsp;that accommodate lateral offsets along&nbsp;plate boundaries&nbsp;or shifting crustal blocks, and&nbsp;</span><i>fracture zones</i><span>&nbsp;as relicts of transform faulting extending beyond&nbsp;mid-ocean ridge&nbsp;offsets. We consider specifically the modern ocean and exclude regions where the transform or fracture has clearly not generated the&nbsp;mineral deposit, such as the Clarion-Clipperton fracture zone&nbsp;manganese nodule&nbsp;field. As a result, the summarized deposits are mainly hydrothermal in origin.</span></p><p id=\"sp0025\"><span>Oceanic transform faulting has rarely been considered of interest for the mineralization and formation of&nbsp;ore deposits; however, there are locations in the modern oceans where transform faults and fracture zones are spatially related to mineral deposits. These occurrences suggest that transform faulting and fracture zones may be linked to mineralization at (A) intersections with other&nbsp;tectonic features, (B) where transform faults begin to resemble rifts through intra-transform&nbsp;crustal thinning, spreading, and the formation of&nbsp;pull-apart basins, and (C) as a result of&nbsp;</span>serpentinization<span>&nbsp;</span>reactions due to exposure of deep-seated rocks by fracturing and faulting.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Transform plate boundaries and fracture zones","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-812064-4.00005-0","isbn":"978-0128120644","usgsCitation":"Gartman, A., and Hein, J.R., 2019, Mineralization at oceanic transform faults and fracture zones, chap. <i>of</i> Transform plate boundaries and fracture zones, p. 105-118, https://doi.org/10.1016/B978-0-12-812064-4.00005-0.","productDescription":"14 p.","startPage":"105","endPage":"118","ipdsId":"IP-091486","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":358216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f68e4b0fc368eb53807","contributors":{"editors":[{"text":"Duarte, Joao C.","contributorId":208518,"corporation":false,"usgs":false,"family":"Duarte","given":"Joao","email":"","middleInitial":"C.","affiliations":[{"id":34002,"text":"University of Lisbon, Portugal","active":true,"usgs":false}],"preferred":false,"id":747531,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746684,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70222369,"text":"70222369 - 2019 - Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay","interactions":[],"lastModifiedDate":"2021-07-23T21:01:11.543757","indexId":"70222369","displayToPublicDate":"2018-10-06T15:53:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay","docAbstract":"<p><span>Orthophosphate&nbsp;(PO</span><sub>4</sub><span>) is the most bioavailable form of phosphorus (P). Excess PO</span><sub>4</sub><span>&nbsp;may cause&nbsp;harmful algal blooms&nbsp;in&nbsp;aquatic ecosystems. A major restoration effort is underway for Chesapeake Bay (CB) to reduce P, nitrogen, and sediment loading to CB. Although PO</span><sub>4</sub><span>&nbsp;cycling and delivery to streams has been characterized in small-scale studies, regional drivers of PO</span><sub>4</sub><span>&nbsp;patterns remain poorly understood because most water quality trend assessment focus on total P. Moreover, these trend assessments are usually at an annual timestep. To address this research gap, we analyzed PO</span><sub>4</sub><span>&nbsp;patterns over a 9-year period at 53 monitoring stations across the CB watershed to: 1) characterize the role of PO</span><sub>4</sub><span>&nbsp;in total P fluxes and trends; 2) describe spatial and temporal patterns of PO</span><sub>4</sub><span>&nbsp;concentrations across seasons and&nbsp;<a class=\"topic-link\" title=\"Learn more about Streamflow from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/streamflow\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/streamflow\">streamflow</a>; and 3) explore factors explaining these patterns. Agricultural watersheds exported the most total P compared with watersheds under different land uses (e.g., urban or forest), with PO</span><sub>4</sub><span>&nbsp;comprising up to 50% of those exports. Although PO</span><sub>4</sub><span>&nbsp;exports are declining at many sites, some agricultural regions are experiencing increasing trends at a rate sufficient to drive total P trends. Regression modeling results suggest that point source load reductions are likely responsible for decreasing PO</span><sub>4</sub><span>&nbsp;concentrations observed at many sites. Watersheds with more Conservation Reserve Program enrollment had lower summer PO</span><sub>4</sub><span>&nbsp;concentrations, highlighting the effectiveness of this practice. Manure inputs strongly predicted PO</span><sub>4</sub><span>&nbsp;concentrations at high flows across all seasons. Both manure applications and&nbsp;conservation tillage&nbsp;were correlated with changes in PO</span><sub>4</sub><span>&nbsp;concentrations at high flow, suggesting these activities could contribute to increasing PO</span><sub>4</sub><span>&nbsp;concentrations. This study highlights the effectiveness of point source control for reducing PO</span><sub>4</sub><span>&nbsp;exports and underscores the need for management strategies to target sources, practices, and landscape factors determining PO</span><sub>4</sub><span>&nbsp;loss from soils where manure inputs remain high.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.10.062","usgsCitation":"Fanelli, R., Blomquist, J.D., and Hirsch, R.M., 2019, Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay: Science of the Total Environment, v. 652, p. 422-433, https://doi.org/10.1016/j.scitotenv.2018.10.062.","productDescription":"12 p.","startPage":"422","endPage":"433","ipdsId":"IP-096738","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":468080,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.10.062","text":"Publisher Index Page"},{"id":387402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.1904296875,\n              38.41916639395372\n            ],\n            [\n              -75.223388671875,\n              38.64261790634527\n            ],\n            [\n              -75.35522460937499,\n              38.79690830348427\n            ],\n            [\n              -75.498046875,\n              38.87392853923629\n            ],\n            [\n              -75.5419921875,\n              39.0533181067413\n            ],\n            [\n              -75.662841796875,\n              39.30029918615029\n            ],\n            [\n              -75.750732421875,\n              39.70718665682654\n            ],\n            [\n              -75.6298828125,\n              40.052847601823984\n            ],\n            [\n              -75.69580078125,\n              40.07807142745009\n            ],\n            [\n              -75.95947265625,\n              40.052847601823984\n            ],\n            [\n              -76.0693359375,\n              40.069664523297774\n            ],\n            [\n              -76.058349609375,\n              40.18726672309203\n            ],\n            [\n              -75.9375,\n              40.29628651711716\n            ],\n            [\n              -75.91552734375,\n              40.3549167507906\n            ],\n            [\n              -75.89355468749999,\n              40.47202439692057\n            ],\n            [\n              -76.09130859375,\n              40.56389453066509\n            ],\n            [\n              -76.190185546875,\n              40.64730356252251\n            ],\n            [\n              -76.0693359375,\n              40.75557964275589\n            ],\n            [\n              -75.83862304687499,\n              40.871987756697415\n            ],\n            [\n              -75.76171875,\n              40.91351257612758\n            ],\n            [\n              -75.706787109375,\n              40.95501133048621\n            ],\n            [\n              -75.7177734375,\n              41.071069130806414\n            ],\n            [\n              -75.662841796875,\n              41.1455697310095\n            ],\n            [\n              -75.5419921875,\n              41.13729606112276\n            ],\n            [\n              -75.322265625,\n              41.104190944576466\n            ],\n            [\n              -75.377197265625,\n              41.22824901518529\n            ],\n            [\n              -75.377197265625,\n              41.28606238749825\n            ],\n            [\n              -75.377197265625,\n              41.43449030894922\n            ],\n            [\n              -75.399169921875,\n              41.6154423246811\n            ],\n            [\n              -75.34423828125,\n              41.68111756290652\n            ],\n            [\n              -75.2783203125,\n              41.91045347666418\n            ],\n            [\n              -75.38818359375,\n              42.00848901572399\n            ],\n            [\n              -75.377197265625,\n              42.09007006868398\n            ],\n            [\n              -75.223388671875,\n              42.17968819665961\n            ],\n            [\n              -74.970703125,\n              42.26917949243506\n            ],\n            [\n              -74.8388671875,\n              42.32606244456202\n            ],\n            [\n              -74.520263671875,\n              42.415346114253616\n            ],\n            [\n              -74.278564453125,\n              42.54498667313236\n            ],\n            [\n              -74.322509765625,\n              42.64204079304426\n            ],\n            [\n              -74.410400390625,\n              42.80346172417078\n            ],\n            [\n              -74.68505859374999,\n              42.924251753870685\n            ],\n            [\n              -75.069580078125,\n              42.98053954751642\n            ],\n            [\n              -75.38818359375,\n              42.96446257387128\n            ],\n            [\n              -75.684814453125,\n              42.93229601903058\n            ],\n            [\n              -75.9375,\n              42.87596410238256\n            ],\n            [\n              -76.201171875,\n              42.827638636242284\n            ],\n            [\n              -76.26708984375,\n              42.72280375732727\n            ],\n            [\n              -76.2890625,\n              42.601619944327965\n            ],\n            [\n              -76.2890625,\n              42.52069952914966\n            ],\n            [\n              -76.343994140625,\n              42.415346114253616\n            ],\n            [\n              -76.46484375,\n              42.382894009614034\n            ],\n            [\n              -76.640625,\n              42.431565872579185\n            ],\n            [\n              -76.7724609375,\n              42.39912215986002\n            ],\n            [\n              -76.80541992187499,\n              42.24478535602799\n            ],\n            [\n              -76.88232421875,\n              42.285437007491545\n            ],\n            [\n              -76.9482421875,\n              42.415346114253616\n            ],\n            [\n              -77.04711914062499,\n              42.44778143462245\n            ],\n            [\n              -77.14599609375,\n              42.415346114253616\n            ],\n            [\n              -77.2998046875,\n              42.382894009614034\n            ],\n            [\n              -77.222900390625,\n              42.54498667313236\n            ],\n            [\n              -77.442626953125,\n              42.69858589169842\n            ],\n            [\n              -77.574462890625,\n              42.60970621339408\n            ],\n            [\n              -77.640380859375,\n              42.48830197960227\n            ],\n            [\n              -77.728271484375,\n              42.439674178149424\n            ],\n            [\n              -77.6513671875,\n              42.31793945446847\n            ],\n            [\n              -77.596435546875,\n              42.22851735620852\n            ],\n            [\n              -77.5634765625,\n              42.09007006868398\n            ],\n            [\n              -77.6953125,\n              41.92680320648791\n            ],\n            [\n              -77.9150390625,\n              41.83682786072714\n            ],\n            [\n              -78.0908203125,\n              41.795888098191426\n            ],\n            [\n              -78.453369140625,\n              41.599013054830216\n            ],\n            [\n              -78.453369140625,\n              41.50857729743935\n            ],\n            [\n              -78.42041015625,\n              41.376808565702355\n            ],\n            [\n              -78.3984375,\n              41.21172151054787\n            ],\n            [\n              -78.519287109375,\n              41.054501963290505\n            ],\n            [\n              -78.541259765625,\n              40.9218144123785\n            ],\n            [\n              -78.409423828125,\n              40.713955826286046\n            ],\n            [\n              -78.299560546875,\n              40.55554790286311\n            ],\n            [\n              -78.343505859375,\n              40.48873742102282\n            ],\n            [\n              -78.475341796875,\n              40.30466538259176\n            ],\n            [\n              -78.64013671875,\n              40.06125658140474\n            ],\n            [\n              -78.826904296875,\n              39.9434364619742\n            ],\n            [\n              -78.848876953125,\n              39.80853604144591\n            ],\n            [\n              -78.85986328125,\n              39.715638134796336\n            ],\n            [\n              -78.99169921875,\n              39.69873414348139\n            ],\n            [\n              -79.046630859375,\n              39.64799732373418\n            ],\n            [\n              -79.266357421875,\n              39.436192999314095\n            ],\n            [\n              -79.420166015625,\n              39.2832938689385\n            ],\n            [\n              -79.354248046875,\n              39.26628442213066\n            ],\n            [\n              -79.266357421875,\n              39.232253141714885\n            ],\n            [\n              -79.2333984375,\n              39.155622393423215\n            ],\n            [\n              -79.244384765625,\n              39.01918369029134\n            ],\n            [\n              -79.27734374999999,\n              38.89103282648846\n            ],\n            [\n              -79.398193359375,\n              38.74551518488265\n            ],\n            [\n              -79.661865234375,\n              38.54816542304656\n            ],\n            [\n              -79.683837890625,\n              38.47079371120379\n            ],\n            [\n              -79.727783203125,\n              38.34165619279595\n            ],\n            [\n              -79.815673828125,\n              38.20365531807149\n            ],\n            [\n              -80.04638671875,\n              38.013476231041935\n            ],\n            [\n              -80.17822265625,\n              37.779398571318765\n            ],\n            [\n              -80.2880859375,\n              37.59682400108367\n            ],\n            [\n              -80.4638671875,\n              37.47485808497102\n            ],\n            [\n              -80.694580078125,\n              37.38761749978395\n            ],\n            [\n              -80.771484375,\n              37.23032838760387\n            ],\n            [\n              -80.57373046875,\n              37.26530995561875\n            ],\n            [\n              -80.44189453125,\n              37.309014074275915\n            ],\n            [\n              -80.255126953125,\n              37.31775185163688\n            ],\n            [\n              -80.013427734375,\n              37.3002752813443\n            ],\n            [\n              -79.8486328125,\n              37.23907530202184\n            ],\n            [\n              -79.771728515625,\n              37.18657859524883\n            ],\n            [\n              -79.6728515625,\n              37.07271048132943\n            ],\n            [\n              -79.541015625,\n              37.09900294387622\n            ],\n            [\n              -79.354248046875,\n              37.142803443716836\n            ],\n            [\n              -79.1455078125,\n              37.10776507118514\n            ],\n            [\n              -79.112548828125,\n              37.055177106660814\n            ],\n            [\n              -78.936767578125,\n              36.932330061503144\n            ],\n            [\n              -78.837890625,\n              36.94111143010769\n            ],\n            [\n              -78.662109375,\n              37.055177106660814\n            ],\n            [\n              -78.486328125,\n              37.03763967977139\n            ],\n            [\n              -78.42041015625,\n              36.94111143010769\n            ],\n            [\n              -78.20068359374999,\n              36.96744946416934\n            ],\n            [\n              -77.904052734375,\n              37.03763967977139\n            ],\n            [\n              -77.750244140625,\n              37.081475648860525\n            ],\n            [\n              -77.53051757812499,\n              37.081475648860525\n            ],\n            [\n              -77.354736328125,\n              37.07271048132943\n            ],\n            [\n              -77.069091796875,\n              37.081475648860525\n            ],\n            [\n              -76.959228515625,\n              37.01132594307015\n            ],\n            [\n              -76.893310546875,\n              36.932330061503144\n            ],\n            [\n              -76.871337890625,\n              36.83566824724438\n            ],\n            [\n              -76.849365234375,\n              36.677230602346214\n            ],\n            [\n              -76.7724609375,\n              36.527294814546245\n            ],\n            [\n              -76.629638671875,\n              36.55377524336089\n            ],\n            [\n              -76.46484375,\n              36.589068371399115\n            ],\n            [\n              -76.35498046875,\n              36.48314061639213\n            ],\n            [\n              -76.256103515625,\n              36.57142382346277\n            ],\n            [\n              -76.190185546875,\n              36.66841891894786\n            ],\n            [\n              -76.0693359375,\n              36.65079252503471\n            ],\n            [\n              -75.9375,\n              36.66841891894786\n            ],\n            [\n              -75.948486328125,\n              36.76529191711624\n            ],\n            [\n              -75.904541015625,\n              37.01132594307015\n            ],\n            [\n              -75.926513671875,\n              37.17782559332976\n            ],\n            [\n              -75.882568359375,\n              37.42252593456307\n            ],\n            [\n              -75.618896484375,\n              37.640334898059486\n            ],\n            [\n              -75.509033203125,\n              37.82280243352756\n            ],\n            [\n              -75.38818359375,\n              38.013476231041935\n            ],\n            [\n              -75.16845703124999,\n              38.272688535980976\n            ],\n            [\n              -75.1904296875,\n              38.41916639395372\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"652","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":206608,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":819777,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70204366,"text":"70204366 - 2019 - Microhabitat use of native fishes in the Kootenai River: A fine‐scale evaluation of large‐scale habitat rehabilitation efforts","interactions":[],"lastModifiedDate":"2019-12-22T14:47:40","indexId":"70204366","displayToPublicDate":"2018-10-05T12:22:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Microhabitat use of native fishes in the Kootenai River: A fine‐scale evaluation of large‐scale habitat rehabilitation efforts","docAbstract":"<p><span>Fish and microhabitat data were collected at 542 prepositioned electrofishing sites (surface area of each site&nbsp;=&nbsp;4&nbsp;m</span><sup>2</sup><span>) in the Kootenai River, Idaho, during 2014 and 2015 to evaluate small‐scale habitat use by fishes, as it relates to large‐scale habitat rehabilitation efforts. Samples were collected from a 12‐km braided segment of river that had received localized habitat rehabilitation treatments since 2011. Fish and microhabitat data were collected to investigate habitat drivers related to the occurrence and relative abundance of fishes. Each sampling location was selected at random and characterized as “treated” (i.e., rehabilitated) or “untreated” based on proximity to habitat treatments. Fishes sampled from backwaters composed 71% of the overall catch and 84% of the catch from locally untreated areas of the river. Species‐specific regression models suggested that water depth and current velocity influenced the occurrence and abundance of fishes. In particular, shallow habitats with low current velocities were important for small‐bodied native fishes and likely serve as important rearing areas for juvenile fish. These habitat conditions typically characterize backwater and channel‐margin habitats that are vulnerable to anthropogenic perturbation. Prioritizing process‐based rehabilitation of these areas in large, regulated rivers would allow natural channel‐forming processes for the benefit of native fishes.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3366","usgsCitation":"Branigan, P.R., Quist, M.C., Bradley B. Shepard, and Ireland, S.C., 2019, Microhabitat use of native fishes in the Kootenai River: A fine‐scale evaluation of large‐scale habitat rehabilitation efforts: River Research and Applications, v. 34, no. 10, p. 1267-1277, https://doi.org/10.1002/rra.3366.","productDescription":"11 p.","startPage":"1267","endPage":"1277","ipdsId":"IP-082011","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":365797,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.76269531249999,\n              48.44377831058802\n            ],\n            [\n              -116.03759765625,\n              48.44377831058802\n            ],\n            [\n              -116.03759765625,\n              48.980216985374994\n            ],\n            [\n              -116.76269531249999,\n              48.980216985374994\n            ],\n            [\n              -116.76269531249999,\n              48.44377831058802\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Branigan, Philip R.","contributorId":217303,"corporation":false,"usgs":false,"family":"Branigan","given":"Philip","email":"","middleInitial":"R.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":766548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":766547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley B. Shepard","contributorId":217304,"corporation":false,"usgs":false,"family":"Bradley B. Shepard","affiliations":[{"id":39600,"text":"consulting company","active":true,"usgs":false}],"preferred":false,"id":766549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ireland, Susan C.","contributorId":217305,"corporation":false,"usgs":false,"family":"Ireland","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":39601,"text":"kooteni tribe","active":true,"usgs":false}],"preferred":false,"id":766550,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199939,"text":"70199939 - 2019 - Towards globally customizable ecosystem service models","interactions":[],"lastModifiedDate":"2018-10-04T13:52:16","indexId":"70199939","displayToPublicDate":"2018-10-04T13:52:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Towards globally customizable ecosystem service models","docAbstract":"<p><span>Scientists, stakeholders and decision makers face trade-offs between adopting simple or complex approaches when modeling ecosystem services (ES). Complex approaches may be time- and data-intensive, making them more challenging to implement and difficult to scale, but can produce more accurate and locally specific results. In contrast, simple approaches allow for faster assessments but may sacrifice accuracy and credibility. The&nbsp;</span>ARtificial Intelligence<span>&nbsp;for&nbsp;Ecosystem Services&nbsp;(ARIES) modeling platform has endeavored to provide a spectrum of simple to complex ES models that are readily accessible to a broad range of users. In this paper, we describe a series of five “Tier 1” ES models that users can run anywhere in the world with no user input, while offering the option to easily customize models with context-specific data and parameters. This approach enables rapid ES quantification, as models are automatically adapted to the application context. We provide examples of customized ES assessments at three locations on different continents and demonstrate the use of ARIES' spatial multi-criteria analysis module, which enables spatial prioritization of ES for different beneficiary groups. The models described here use publicly available global- and continental-scale data as defaults. Advanced users can modify data input requirements, model parameters or entire model structures to capitalize on high-resolution data and context-specific&nbsp;model formulations. Data and methods contributed by the research community become part of a growing knowledge base, enabling faster and better ES assessment for users worldwide. By engaging with the ES modeling community to further develop and customize these models based on user needs, spatiotemporal contexts, and scale(s) of analysis, we aim to cover the full arc from simple to complex assessments, minimizing the additional cost to the user when increased complexity and accuracy are needed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.09.371","usgsCitation":"Martinez-Lopez, J., Bagstad, K.J., Balbi, S., Magrach, A., Voigt, B., Athanasiadis, I., Pascual, M., Willcock, S., and Villa, F., 2019, Towards globally customizable ecosystem service models: Science of the Total Environment, v. 650, no. 2, p. 2325-2336, https://doi.org/10.1016/j.scitotenv.2018.09.371.","productDescription":"12 p.","startPage":"2325","endPage":"2336","ipdsId":"IP-098617","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.09.371","text":"Publisher Index Page"},{"id":358142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"650","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f6be4b0fc368eb53809","contributors":{"authors":[{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":747384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Magrach, Ainhoa 0000-0003-2155-7556","orcid":"https://orcid.org/0000-0003-2155-7556","contributorId":208482,"corporation":false,"usgs":false,"family":"Magrach","given":"Ainhoa","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Voigt, Brian","contributorId":208483,"corporation":false,"usgs":false,"family":"Voigt","given":"Brian","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":747388,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Athanasiadis, Ioannis 0000-0003-2764-0078","orcid":"https://orcid.org/0000-0003-2764-0078","contributorId":208484,"corporation":false,"usgs":false,"family":"Athanasiadis","given":"Ioannis","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":747389,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pascual, Marta 0000-0002-2204-7745","orcid":"https://orcid.org/0000-0002-2204-7745","contributorId":208485,"corporation":false,"usgs":false,"family":"Pascual","given":"Marta","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Willcock, Simon 0000-0001-9534-9114","orcid":"https://orcid.org/0000-0001-9534-9114","contributorId":201576,"corporation":false,"usgs":false,"family":"Willcock","given":"Simon","email":"","affiliations":[{"id":36207,"text":"Bangor University","active":true,"usgs":false}],"preferred":false,"id":747391,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747392,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70227761,"text":"70227761 - 2019 - Relationships between landscape constraints and a crayfish assemblage with consideration of competitor presence","interactions":[],"lastModifiedDate":"2022-01-28T13:22:22.29389","indexId":"70227761","displayToPublicDate":"2018-10-04T07:18:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Relationships between landscape constraints and a crayfish assemblage with consideration of competitor presence","docAbstract":"<h3 id=\"ddi12840-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Crayfish are globally diverse and one of the most important taxa in North American streams. Despite their importance, many species are of conservation concern and efforts to improve conditions are limited. Here, we address two major impediments to improving conditions: (a) our lack of knowledge of the interplay among natural landscape and human-induced changes; and (b) a very limited understanding of how species interactions affect overall crayfish distributions.</p><h3 id=\"ddi12840-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Ozark Highlands ecoregion, USA.</p><h3 id=\"ddi12840-sec-0003-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used both existing data and field-collected data to examine the relationships between 12<span>&nbsp;</span><i>Faxonius</i><span>&nbsp;</span>species and physicochemical variables at multiple spatial scales. Data were analysed using a generalized linear mixed model. After fitting our environmental variables, we also considered possible relationships between species considered strong competitors and species occurrence.</p><h3 id=\"ddi12840-sec-0004-title\" class=\"article-section__sub-title section1\">Results</h3><p>Our results indicated that elevation, lithology, an interaction between drainage area and anthropogenic disturbance, and the presence of strong competitors were associated with<span>&nbsp;</span><i>Faxonius</i><span>&nbsp;</span>occurrences.<span>&nbsp;</span><i>Faxonius</i><span>&nbsp;</span>occurrences were associated with assemblage-structuring variables: lithology and elevation. More interestingly, we found several patterns of interactions between drainage area and disturbance. The most common pattern among several species was a decline in occurrence in larger drainages when disturbance was high; however, longpincered crayfish (<i>Faxonius longidigitus</i>) was more likely to occupy large drainages as disturbance increased. Additionally, the presence of species considered strong competitors resulted in lower occurrence probability for many species, including two of the species classified as competitors.</p><h3 id=\"ddi12840-sec-0005-title\" class=\"article-section__sub-title section1\">Main conclusions</h3><p>In addition to identifying the relationships between native species and assemblage-structuring variables, we show how the probability of species occurrences relate to interactions between disturbance and natural landscape features. Further, our results suggest competitor presence also plays a role in structuring distributions at the stream segment scale. Our findings emphasize the value of considering both competitor presence and interactions among landscape variables and disturbances in structuring crayfish assemblages.</p>","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12840","usgsCitation":"Mouser, J., Mollenhauer, R., and Brewer, S.K., 2019, Relationships between landscape constraints and a crayfish assemblage with consideration of competitor presence: Diversity and Distributions, v. 25, no. 1, p. 61-73, https://doi.org/10.1111/ddi.12840.","productDescription":"13 p.","startPage":"61","endPage":"73","ipdsId":"IP-091645","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12840","text":"Publisher Index Page"},{"id":395040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Ozark Highlands ecoregion","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.603271484375,\n              34.134541681937364\n            ],\n            [\n              -89.23095703125,\n              34.134541681937364\n            ],\n            [\n              -89.23095703125,\n              38.35888785866677\n            ],\n            [\n              -94.603271484375,\n              38.35888785866677\n            ],\n            [\n              -94.603271484375,\n              34.134541681937364\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Mouser, J.B.","contributorId":244447,"corporation":false,"usgs":false,"family":"Mouser","given":"J.B.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mollenhauer, Robert","contributorId":242899,"corporation":false,"usgs":false,"family":"Mollenhauer","given":"Robert","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":832065,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832066,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70200424,"text":"70200424 - 2019 - Overview of the oxygen isotope systematics of land snails from North America","interactions":[],"lastModifiedDate":"2019-02-21T14:54:00","indexId":"70200424","displayToPublicDate":"2018-10-03T10:46:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Overview of the oxygen isotope systematics of land snails from North America","docAbstract":"<p><span>Continental paleoclimate proxies with near-global coverage are rare. Land snail δ</span><span class=\"sup\">18</span><span>O is one of the few proxies abundant in Quaternary sediments ranging from the tropics to the high Arctic tundra. However, its application in paleoclimatology remains difficult, attributable in part to limitations in published calibration studies. Here we present shell δ</span><span class=\"sup\">18</span><span>O of modern small (&lt;10 mm) snails across North America, from Florida (30°N) to Manitoba (58°N), to examine the main climatic controls on shell δ</span><span class=\"sup\">18</span><span>O at a coarse scale. This transect is augmented by published δ</span><span class=\"sup\">18</span><span>O values, which expand our coverage from Jamaica (18°N) to Alaska (64°N). Results indicate that shell δ</span><span class=\"sup\">18</span><span>O primarily tracks the average annual precipitation δ</span><span class=\"sup\">18</span><span>O. Shell δ</span><span class=\"sup\">18</span><span>O increases 0.5–0.7‰ for every 1‰ increase in precipitation δ</span><span class=\"sup\">18</span><span>O, and 0.3–0.7‰ for every 1°C increase in temperature. These relationships hold true when all taxa are included regardless of body size (ranging from ~1.6 to ~58 mm), ecology (herbivores, omnivores, and carnivores), or behavior (variable seasonal active periods and mobility habits). Future isotopic investigations should include calibration studies in tropical and high-latitude settings, arid environments, and along altitudinal gradients to test if the near linear relationship between shell and meteoric precipitation δ</span><span class=\"sup\">18</span><span>O observed on a continental scale remains significant.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.79","usgsCitation":"Yanes, Y., Al-Qattan, N.M., Rech, J.A., Pigati, J.S., Dodd, J.P., and Nekola, J.C., 2019, Overview of the oxygen isotope systematics of land snails from North America: Quaternary Research, v. 91, no. 1, p. 329-344, https://doi.org/10.1017/qua.2018.79.","productDescription":"16 p.","startPage":"329","endPage":"344","ipdsId":"IP-094692","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":358472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5c10a92fe4b034bf6a7e505e","contributors":{"authors":[{"text":"Yanes, Yurena","contributorId":197219,"corporation":false,"usgs":false,"family":"Yanes","given":"Yurena","email":"","affiliations":[],"preferred":false,"id":748772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Qattan, Nasser M.","contributorId":209766,"corporation":false,"usgs":false,"family":"Al-Qattan","given":"Nasser","email":"","middleInitial":"M.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":748773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rech, Jason A.","contributorId":117323,"corporation":false,"usgs":false,"family":"Rech","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":748774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":748771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dodd, Justin P.","contributorId":209767,"corporation":false,"usgs":false,"family":"Dodd","given":"Justin","email":"","middleInitial":"P.","affiliations":[{"id":13666,"text":"Northern Illinois University","active":true,"usgs":false}],"preferred":false,"id":748775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":748776,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204107,"text":"70204107 - 2019 - Population vulnerability to tsunami hazards informed by previous and projected disasters: A case study of American Samoa","interactions":[],"lastModifiedDate":"2019-07-05T16:35:02","indexId":"70204107","displayToPublicDate":"2018-10-01T16:32:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Population vulnerability to tsunami hazards informed by previous and projected disasters: A case study of American Samoa","docAbstract":"<p><span>Population vulnerability from tsunamis is a function of the number and location of individuals in hazard zones and their ability to reach safety before wave arrival. Previous tsunami disasters can provide insight on likely evacuation behavior, but post-disaster assessments have not been used extensively in evacuation modeling. We demonstrate the utility of post-disaster assessments in pedestrian evacuation modeling for tsunami hazards and use the US territory of American Samoa as our case study. We model pedestrian travel times out of tsunami inundation zones recreated for the 2009&nbsp;</span><i class=\"EmphasisTypeItalic \">M</i><sub>w</sub><span>&nbsp;8.1 Samoa earthquake, as well as for a probable maximum tsunami zone for future threats. Modeling assumptions are guided by fatality trends and observations of 2009 evacuation behavior, including insights on departure delays, environmental cues, transportation mode, and demographic characteristics. Differences in actual fatalities from the 2009 disaster and modeled population vulnerability suggest that a single set of estimated travel times to safety does not fully characterize evacuation potential of a dispersed, at-risk population. Efforts to prepare coastal communities in American Samoa for future tsunamis may be challenging given substantial differences in wave characteristics and evacuation potential of the probable maximum hazard compared to the 2009 event.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-018-3493-7","usgsCitation":"Wood, N.J., Jones, J.M., Yamazaki, Y., Cheung, K., Brown, J., Jones, J., and Abdollahian, N., 2019, Population vulnerability to tsunami hazards informed by previous and projected disasters: A case study of American Samoa: Natural Hazards, v. 95, no. 3, p. 505-528, https://doi.org/10.1007/s11069-018-3493-7.","productDescription":"24 p.","startPage":"505","endPage":"528","ipdsId":"IP-094726","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":460567,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11069-018-3493-7","text":"Publisher Index Page"},{"id":437629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9USLV20","text":"USGS data release","linkHelpText":"Pedestrian tsunami evacuation results for two tsunami-inundation zones (2009 and probable maximum tsunami (PMT)) and four travel speeds (slow walk, fast walk, slow run, and fast run) for American Samoa"},{"id":365315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"American Samoa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -170.5675506591797,\n              -14.246414530379399\n            ],\n            [\n              -170.5792236328125,\n              -14.2477455837054\n            ],\n            [\n              -170.58815002441406,\n              -14.255731738748931\n            ],\n            [\n              -170.60256958007812,\n              -14.253069718484149\n            ],\n            [\n              -170.61355590820312,\n              -14.253069718484149\n            ],\n            [\n              -170.62660217285156,\n              -14.249742148971979\n            ],\n            [\n              -170.6396484375,\n              -14.246414530379399\n            ],\n            [\n              -170.67054748535156,\n              -14.239093596764377\n            ],\n            [\n              -170.70075988769528,\n              -14.248411107424003\n            ],\n            [\n              -170.71998596191406,\n              -14.26571403483186\n            ],\n            [\n              -170.73165893554685,\n              -14.28235021221402\n            ],\n            [\n              -170.77491760253906,\n              -14.287008121596337\n            ],\n            [\n              -170.79757690429688,\n              -14.288338935138412\n            ],\n            [\n              -170.82229614257812,\n              -14.297654409469711\n            ],\n            [\n              -170.84976196289062,\n              -14.32426792282882\n            ],\n            [\n              -170.84701538085938,\n              -14.331586085911042\n            ],\n            [\n              -170.81886291503906,\n              -14.33358190713021\n            ],\n            [\n              -170.79689025878906,\n              -14.335577710585268\n            ],\n            [\n              -170.7886505126953,\n              -14.342230260443346\n            ],\n            [\n              -170.7872772216797,\n              -14.357530375512127\n            ],\n            [\n              -170.77011108398438,\n              -14.366177804130347\n            ],\n            [\n              -170.75775146484375,\n              -14.37549004573761\n            ],\n            [\n              -170.738525390625,\n              -14.366177804130347\n            ],\n            [\n              -170.69869995117188,\n              -14.328259677742766\n            ],\n            [\n              -170.6781005859375,\n              -14.300315902681023\n            ],\n            [\n              -170.66505432128906,\n              -14.291000538604875\n            ],\n            [\n              -170.60531616210938,\n              -14.283681053304013\n            ],\n            [\n              -170.54763793945312,\n              -14.291000538604875\n            ],\n            [\n              -170.5455780029297,\n              -14.285011886524028\n            ],\n            [\n              -170.55999755859372,\n              -14.243752400174483\n            ],\n            [\n              -170.5675506591797,\n              -14.246414530379399\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"95","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yamazaki, Yoshiki","contributorId":216792,"corporation":false,"usgs":false,"family":"Yamazaki","given":"Yoshiki","email":"","affiliations":[{"id":39517,"text":"University of Hawaii at Mano","active":true,"usgs":false}],"preferred":false,"id":765546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheung, Kwok-Fai","contributorId":216793,"corporation":false,"usgs":false,"family":"Cheung","given":"Kwok-Fai","email":"","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":765547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jacinta","contributorId":216794,"corporation":false,"usgs":false,"family":"Brown","given":"Jacinta","email":"","affiliations":[{"id":39518,"text":"American Samoa Department of Homeland Security","active":true,"usgs":false}],"preferred":false,"id":765548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Jamie 0000-0002-9967-3314 jamiejones@usgs.gov","orcid":"https://orcid.org/0000-0002-9967-3314","contributorId":204514,"corporation":false,"usgs":true,"family":"Jones","given":"Jamie","email":"jamiejones@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abdollahian, Nina 0000-0002-8607-2202","orcid":"https://orcid.org/0000-0002-8607-2202","contributorId":216795,"corporation":false,"usgs":false,"family":"Abdollahian","given":"Nina","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":765550,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70205192,"text":"70205192 - 2019 - In vivo effects of 17α-ethinylestradiol, 17B-estradiol and 4-nonylphenol on insulin-like growth-factor binding proteins (igfbps) in Atlantic salmon","interactions":[],"lastModifiedDate":"2019-09-06T08:29:13","indexId":"70205192","displayToPublicDate":"2018-10-01T15:33:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":874,"text":"Aquatic Toxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"<i>In vivo</i> effects of 17α-ethinylestradiol, 17β-estradiol and 4-nonylphenol on <i>insulin-like growth-factor binding proteins (igfbps)</i> in Atlantic salmon","title":"In vivo effects of 17α-ethinylestradiol, 17B-estradiol and 4-nonylphenol on insulin-like growth-factor binding proteins (igfbps) in Atlantic salmon","docAbstract":"<p><span>Feminizing endocrine disrupting compounds (EDCs) affect the growth and development of teleost fishes. The major regulator of growth performance, the growth hormone (Gh)/insulin-like growth-factor (Igf) system, is sensitive to estrogenic compounds and mediates certain physiological and potentially behavioral consequences of EDC exposure. Igf binding proteins (Igfbps) are key modulators of Igf activity, but their alteration by EDCs has not been examined. We investigated two life-stages (fry and smolts) of Atlantic salmon (</span><i>Salmo salar</i><span>), and characterized how the Gh/Igf/Igfbp system responded to waterborne 17α-ethinylestradiol (EE</span><sub>2</sub><span>), 17β-estradiol (E</span><sub>2</sub><span>) and 4-nonylphenol (NP). Fry exposed to EE</span><sub>2</sub><span>&nbsp;and NP for 21 days had increased hepatic&nbsp;</span><i>vitellogenin</i><span>&nbsp;(</span><i>vtg</i><span>) mRNA levels while hepatic&nbsp;</span><i>estrogen receptor α</i><span>&nbsp;(</span><i>erα</i><span>),&nbsp;</span><i>gh receptor (ghr)</i><span>,&nbsp;</span><i>igf1</i><span>&nbsp;and&nbsp;</span><i>igf2</i><span>&nbsp;mRNA levels were decreased. NP-exposed fry had reduced body mass and total length compared to controls. EE</span><sub>2</sub><span>&nbsp;and NP reduced hepatic&nbsp;</span><i>igfbp1b1</i><span>,&nbsp;</span><i>-2a</i><span>,&nbsp;</span><i>-2b1</i><span>,&nbsp;</span><i>-4</i><span>,&nbsp;</span><i>-5b2</i><span>&nbsp;and&nbsp;</span><i>-6b1</i><span>, and stimulated&nbsp;</span><i>igfbp5a</i><span>. In smolts, hepatic&nbsp;</span><i>vtg</i><span>&nbsp;mRNA levels were induced following 4-day exposures to all three EDCs, while&nbsp;</span><i>erα</i><span>&nbsp;only responded to EE</span><sub>2</sub><span>&nbsp;and E</span><sub>2</sub><span>. EDC exposures did not affect body mass or fork length; however, EE</span><sub>2</sub><span>&nbsp;diminished plasma Gh and Igf1 levels in parallel with reductions in hepatic&nbsp;</span><i>ghr</i><span>&nbsp;and&nbsp;</span><i>igf1</i><span>. In smolts, EE</span><sub>2</sub><span>&nbsp;and E</span><sub>2</sub><span>&nbsp;diminished hepatic&nbsp;</span><i>igfbp1b1</i><span>,&nbsp;</span><i>-4</i><span>&nbsp;and&nbsp;</span><i>-6b1</i><span>, and stimulated&nbsp;</span><i>igfbp5a</i><span>. There were no signs of compromised ionoregulation in smolts, as indicated by unchanged branchial ion pump/transporter mRNA levels. We conclude that hepatic&nbsp;</span><i>igfbps</i><span>&nbsp;respond (directly and/or indirectly) to environmental estrogens during two key life-stages of Atlantic salmon, and thus may modulate the growth and development of exposed individuals.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquatox.2018.07.018","usgsCitation":"Breves, J.P., Duffy, T.A., Einarsdottir, I.E., Bjornsson, B.T., and McCormick, S.D., 2019, In vivo effects of 17α-ethinylestradiol, 17B-estradiol and 4-nonylphenol on insulin-like growth-factor binding proteins (igfbps) in Atlantic salmon: Aquatic Toxicology, v. 203, p. 28-39, https://doi.org/10.1016/j.aquatox.2018.07.018.","productDescription":"12 p.","startPage":"28","endPage":"39","ipdsId":"IP-094300","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468084,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquatox.2018.07.018","text":"Publisher Index Page"},{"id":367233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"203","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Breves, Jason P.","contributorId":6349,"corporation":false,"usgs":false,"family":"Breves","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":770300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Tara A.","contributorId":139213,"corporation":false,"usgs":false,"family":"Duffy","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":770301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Einarsdottir, Ingibjorg E.","contributorId":173274,"corporation":false,"usgs":false,"family":"Einarsdottir","given":"Ingibjorg","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":770302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bjornsson, Bjorn Thrandur","contributorId":173275,"corporation":false,"usgs":false,"family":"Bjornsson","given":"Bjorn","email":"","middleInitial":"Thrandur","affiliations":[],"preferred":false,"id":770303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":770299,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70204439,"text":"70204439 - 2019 - Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data","interactions":[],"lastModifiedDate":"2019-07-23T14:41:00","indexId":"70204439","displayToPublicDate":"2018-10-01T14:38:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Increasing tree&nbsp;canopy&nbsp;cover has led to increasing&nbsp;wildfire&nbsp;activity in conifer dominated areas of the southwestern United States. Estimating historical changes in the spatial distribution of tree canopy cover can provide further insights into the dynamics of forest and fuel conditions in these landscapes and help prioritize areas for restoration to mitigate wildfire risks and restore biological functioning. In this study, we explored the relationship between LiDAR derived canopy cover data and&nbsp;Landsat&nbsp;reflectance&nbsp;values, and derived a model to estimate percent canopy cover (PCC) on historical Landsat data from 1987 to 2015 for the Valles&nbsp;Caldera&nbsp;National Preserve (VCNP), located in the southwest Jemez Mountains of New Mexico. We developed a&nbsp;regression model&nbsp;between LiDAR generated canopy cover collected in June 2010 and Landsat Thematic Mapper (TM) reflectance values (bands 1–7 except band 6) and&nbsp;vegetation indices&nbsp;collected for the same date. About 5% (17,000) of the total LiDAR points (329,102) were used as training points and a separate, non-overlapping set of 17,000 points as test points to validate the regression model. A simple linear model with the red band (band 3;&nbsp;</span><i>R</i><sup><i>2</i></sup><span> = 0.70) was selected as the best model to predict PCC in the rest of the images for 1987–2015. In general, we found a strong consistency between the spatial dynamics of modelled tree canopy cover based on historical Landsat data, wildfire events and forest&nbsp;management practicesthat occurred during the same period. Results showed that about 11% of the&nbsp;study area&nbsp;experienced an increase in PCC for the period of 1987–2015 while 41% of the study area experienced a reduction in PCC during the same time period, mostly in the areas which were affected by stand replacing wildfires in 2011 and 2013. The results indicate an overall increase in medium and high canopy cover classes in specific&nbsp;regions&nbsp;of the study area, which could lead to hazardous wildfires such as those in 2011 and 2013. In the context of ongoing&nbsp;ecological restoration&nbsp;of these&nbsp;montane forests, predicted PCC of contemporary forests could help local managers to identify the areas in the need of immediate restoration efforts by focusing management practices on the areas with closed canopy.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2018.07.024","usgsCitation":"Cain, J.W., Humagain1, K., Portillo-Quintero1, C., and Cox1, R.D., 2019, Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data: Applied Geography, v. 99, p. 120-132, https://doi.org/10.1016/j.apgeog.2018.07.024.","productDescription":"13 p.","startPage":"120","endPage":"132","ipdsId":"IP-083749","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":365870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Valles Caldera National Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.0562744140625,\n              35.51881428123057\n            ],\n            [\n              -105.9466552734375,\n              35.51881428123057\n            ],\n            [\n              -105.9466552734375,\n              36.328402729422656\n            ],\n            [\n              -107.0562744140625,\n              36.328402729422656\n            ],\n            [\n              -107.0562744140625,\n              35.51881428123057\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"99","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":766911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Humagain1, Kamal","contributorId":217501,"corporation":false,"usgs":false,"family":"Humagain1","given":"Kamal","email":"","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":766912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Portillo-Quintero1, Carlos","contributorId":217502,"corporation":false,"usgs":false,"family":"Portillo-Quintero1","given":"Carlos","email":"","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":766913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox1, Robert D.","contributorId":217503,"corporation":false,"usgs":false,"family":"Cox1","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":37463,"text":"TTU","active":true,"usgs":false}],"preferred":false,"id":766914,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199743,"text":"70199743 - 2019 - Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA","interactions":[],"lastModifiedDate":"2019-03-26T16:18:40","indexId":"70199743","displayToPublicDate":"2018-09-26T15:15:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA","docAbstract":"<p><span>A method is presented for deriving a volume model of groundwater total dissolved solids (TDS) from borehole geophysical and aqueous geochemical measurements. While previous TDS mapping techniques have proved useful in the hydrogeologic setting in which they were developed, they may yield poor results in settings with lithological heterogeneity, complex water chemistry, or limited data. Problems arise because of assumed values for empirical constants in Archie’s Equation, unrealistic porosity and temperature gradients, or bicarbonate-rich groundwater. These issues become critical in complex geologic settings such as the San Joaquin Valley of California, USA. To address this, a method to map TDS in three dimensions is applied to the Fruitvale and Rosedale Ranch oil fields near Bakersfield, California. Borehole resistivity, porosity, and temperature data are used to derive TDS using Archie’s Equation, and are then kriged to interpolate TDS. Archie’s&nbsp;</span><i class=\"EmphasisTypeItalic \">a</i><span>&nbsp;and&nbsp;</span><i class=\"EmphasisTypeItalic \">m</i><span>&nbsp;(tortuosity factor and cementation exponent, respectively) are found by comparing model predictions, after kriging, to TDS measurements, and minimizing the differences via mathematical optimization. Contributions of abundant bicarbonate ions to TDS were corrected using an empirical model. This work was motivated by federal and state law requirements to monitor and protect underground sources of drinking water. Modeling shows the legally significant boundary of 10,000&nbsp;ppm TDS is at ~1,067&nbsp;m below sea level in Rosedale Ranch, and deepens into Fruitvale to ~1,341&nbsp;m. Mapping groundwater TDS at this resolution reveals that TDS is primarily controlled by depth, recharge, stratigraphy, and in some places, by faulting and facies changes.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10040-018-1872-5","usgsCitation":"Stephens, M.J., Shimabukuro, D.H., Gillespie, J., and Chang, W., 2019, Groundwater salinity mapping using geophysical log analysis within the Fruitvale and Rosedale Ranch oil fields, Kern County, California, USA: Hydrogeology Journal, v. 27, no. 2, p. 731-746, https://doi.org/10.1007/s10040-018-1872-5.","productDescription":"16 p.","startPage":"731","endPage":"746","ipdsId":"IP-088343","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468086,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-018-1872-5","text":"Publisher Index Page"},{"id":437630,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S181PH","text":"USGS data release","linkHelpText":"Geochemical and geophysical data for wells in the Fruitvale and Rosedale Ranch oil and gas fields, Kern County, California, USA"},{"id":357806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.17,\n              35.34\n            ],\n            [\n              -119.02,\n              35.34\n            ],\n            [\n              -119.02,\n              35.458\n            ],\n            [\n              -119.17,\n              35.458\n            ],\n            [\n              -119.17,\n              35.34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-26","publicationStatus":"PW","scienceBaseUri":"5bc02f8ae4b0fc368eb538a5","contributors":{"authors":[{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":746427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":746428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chang, Will 0000-0002-0796-0763","orcid":"https://orcid.org/0000-0002-0796-0763","contributorId":208210,"corporation":false,"usgs":false,"family":"Chang","given":"Will","email":"","affiliations":[{"id":37763,"text":"Hypergradient LLC","active":true,"usgs":false}],"preferred":false,"id":746429,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199700,"text":"70199700 - 2019 - Drivers of chaparral type conversion to herbaceous vegetation in coastal Southern California","interactions":[],"lastModifiedDate":"2019-01-28T09:18:55","indexId":"70199700","displayToPublicDate":"2018-09-26T12:09:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of chaparral type conversion to herbaceous vegetation in coastal Southern California","docAbstract":"<div id=\"ddi12827-sec-0001\" class=\"article-section__content\"><p class=\"article-section__sub-title section1\"><strong>Aim</strong></p><p>In Southern California, native woody shrublands known as chaparral support exceptional biodiversity. However, large‐scale conversion of chaparral into largely exotic herbaceous cover is a major ecological threat and serious conservation concern. Due to substantial uncertainty regarding the causes and extent of this vegetation change, we aimed to quantify the primary drivers of and map potentially vulnerable locations for vegetation type conversion from woody into herbaceous cover.</p></div><p class=\"article-section__sub-title section1\"><strong>Location</strong></p><p>Santa Monica Mountains National Recreational Area, Southern California, USA.</p><p class=\"article-section__sub-title section1\"><strong>Methods</strong></p><p>We used air photograph image interpretation to quantify the extent to which chaparral shrublands transitioned to herbaceous cover from 1943 to 2014 across nearly 800 randomly located plots. Comparing plots that remained chaparral to those that converted to herbaceous cover, we performed hierarchical partitioning to quantify the independent contribution of a range of explanatory variables, and then used classification trees to explore variable interactions. We also developed a spatial model to create a seamless map delineating relative probability of type conversion.</p><p class=\"article-section__sub-title section1\"><strong>Results</strong></p><p>Of the original plots that were chaparral in 1943, 284 (36%) changed cover by 2014, with 79 completely converting, and 142 mostly converting to herbaceous cover. The primary mechanism behind shrubland decline and replacement was short intervals between fires (&lt;=10&nbsp;years), and type conversion was most likely to occur in arid parts of the landscape with low topographic heterogeneity and close proximity to trails and roads. Predictive maps delineated several hotspots with environmental conditions similar to those of type‐converted plots.</p><div id=\"ddi12827-sec-0005\" class=\"article-section__content\"><p class=\"article-section__sub-title section1\"><strong>Main conclusions</strong></p><p>Chaparral type conversion is a widespread conservation concern, and results here suggest that short‐interval fire and landscape disturbance are the most likely factors to exacerbate it, particularly in water‐limited portions of the landscape where chaparral is subject to greater physiological stress and slower recovery. Reducing fire ignitions and mapping vulnerable areas may be important strategies for prevention.</p></div>","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12827","usgsCitation":"Syphard, A.D., Brennan, T.J., and Keeley, J.E., 2019, Drivers of chaparral type conversion to herbaceous vegetation in coastal Southern California: Diversity and Distributions, v. 25, no. 1, p. 90-101, https://doi.org/10.1111/ddi.12827.","productDescription":"12 p.","startPage":"90","endPage":"101","ipdsId":"IP-097153","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12827","text":"Publisher Index Page"},{"id":357763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.16870117187501,\n              33.980947501499635\n            ],\n            [\n              -118.46557617187499,\n              33.980947501499635\n            ],\n            [\n              -118.46557617187499,\n              34.228835385227214\n            ],\n            [\n              -119.16870117187501,\n              34.228835385227214\n            ],\n            [\n              -119.16870117187501,\n              33.980947501499635\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"25","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-31","publicationStatus":"PW","scienceBaseUri":"5bc02f8be4b0fc368eb538ad","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":746256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brennan, Teresa J. 0000-0002-0646-3298 tjbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-0646-3298","contributorId":4323,"corporation":false,"usgs":true,"family":"Brennan","given":"Teresa","email":"tjbrennan@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":746257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":746255,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}