Surveys of environmental DNA (eDNA) have become an important and multifaceted tool for monitoring and identifying distributions and occupancy of aquatic species. This tool is attractive because it is powerful, easy to apply, and provides an alternative to traditional field survey methods. However, validating eDNA survey methods against traditional field survey methods is warranted prior to their application. We used eDNA and electrofishing to survey 10 sites in 3 tributaries of the Chehalis River, Washington, to infer distribution and occupancy of Entosphenus tridentatus and Lampetra spp. Both methods produced similar detection rates for E. tridentatus, and Lampetra spp. were detected at slightly greater frequency with eDNA in the Black River and Skookumchuck River. Within each of the three tributaries, eDNA concentration was negatively related to sample distance from the Chehalis River mainstem for E. tridentatus but not for Lampetra spp., which indicates E. tridentatus and Lampetra spp. may be distributed differently within tributaries. Application of lamprey eDNA data to a multiscale occupancy model indicated high probability of detecting eDNA in water samples and quantitative PCR (qPCR) assays. Broad distribution and high detection of E. tridentatus and Lampetra spp. suggest robust populations inhabit the Chehalis River basin. Our findings suggest eDNA surveys may be comparable to electrofishing for informing lamprey occupancy and distributions. Such sampling is efficient and cost‐effective and we anticipate that eDNA surveys will become a valuable tool in addressing key research and monitoring needs for conservation and restoration of lampreys in general.
No abstract available
","language":"English","publisher":"International Wold Center","usgsCitation":"Barber-Meyer, S., 2019, Wolf 7271 and the “Wink of the Wild”.: International Wolf, no. Summer.","ipdsId":"IP-102701","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":367166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367165,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wolf.org/wolf-info/wolf-magazine/summer-2019/"}],"country":"United States","state":"Minnesota","issue":"Summer","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barber-Meyer, Shannon 0000-0002-3048-2616 sbarber-meyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":191875,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon","email":"sbarber-meyer@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":767854,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208422,"text":"70208422 - 2019 - Seismic design and hazard maps: Before and after","interactions":[],"lastModifiedDate":"2020-02-10T17:56:45","indexId":"70208422","displayToPublicDate":"2019-06-30T17:54:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5928,"text":"Structure","active":true,"publicationSubtype":{"id":10}},"title":"Seismic design and hazard maps: Before and after","docAbstract":"The 1994 Northridge earthquake generated world-record ground motions. At the time, the horizontal peak ground acceleration of 1.8 g measured by a seismometer in Tarzana was the largest ever. The same is true of the peak ground velocity of 148 cm/s measured in Granada Hills. Both measurements were within approximately 15 km of the source of the earthquake; they were also near most of the damage described in other articles of this series. Consequently, the near-source design forces from the seismic zone maps in the Uniform Building Code (UBC) were increased. From the 1994 to 1997 editions, acceleration- and velocity-related near-source factors were introduced. The factors increased the design forces in Zone 4, already the highest seismic zone, by a multiplier as large as 2.0. More enduringly, generational changes were made to the seismic design maps in the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures. The NEHRP maps were – and continue to be – adopted into the International Building Code (IBC), which supplanted the UBC and other model building codes. As described below, the changes to the NEHRP maps took advantage of another post-Northridge change: the modern generation of U.S. Geological Survey (USGS) National Seismic Hazard Maps.
","language":"English","publisher":"National Council of Structural Engineers Associations","usgsCitation":"Luco, N., 2019, Seismic design and hazard maps: Before and after: Structure, p. 28-30.","productDescription":"3 p.","startPage":"28","endPage":"30","ipdsId":"IP-106546","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":372201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372155,"type":{"id":15,"text":"Index Page"},"url":"https://www.structuremag.org/?p=14562"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":781818,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70204831,"text":"70204831 - 2019 - Hawaiian hoary bat (Lasiurus cinereus semotus) activity, diet and prey availability at the Waihou Mitigation Area, Maui","interactions":[],"lastModifiedDate":"2019-08-19T16:21:46","indexId":"70204831","displayToPublicDate":"2019-06-30T16:12:05","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"HSCU-090","displayTitle":"Hawaiian hoary bat (Lasiurus cinereus semotus) activity, diet and prey availability at the Waihou Mitigation Area, Maui","title":"Hawaiian hoary bat (Lasiurus cinereus semotus) activity, diet and prey availability at the Waihou Mitigation Area, Maui","docAbstract":"Habitat use, diet, prey availability, and foraging ecology of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus, Vespertilionidae), was examined in the east Maui region inclusive of the Waihou Mitigation Area, Pu‘u Makua Restoration Area and the wind energy facility operated by Auwahi Wind Energy, LLC. The study was conducted to inform the mitigation and management requirements of Auwahi Wind Energy. Acoustic monitoring over the three-year period demonstrated that bats are present and actively forage year-round at the Waihou Mitigation Area. Over an 8-month span, 11 bats were uniquely color-banded and released, 3 of which were pregnant or lactating females, and highlights the importance of the area to breeding residents. Our study included the first genetic analysis of Hawaiian hoary bat diet, and confirms the inclusion of Coleoptera, Lepidoptera, Diptera, Hemiptera, and Blattodea among the prey items of this bat identified in previous microscopy-based studies. Hawaiian hoary bats consumed both native and non-native insect species, including several invasive species damaging to crop agriculture. Moths were the primary dietary component, both in prevalence among individual bats and the proportion of gene sequence counts. Through genetic analysis, we identified 18 Lepidoptera families (dominated by Noctuidae, Geometridae, Crambidae, Oecophoridae and Tortricidae) including 24 genus- or species-level taxa. Lepidoptera collected as caterpillars directly from vegetation did not appear in the diet of the 8 bat guano samples at the genus or species level. However, the occurrence of moth larva on native plants suggests that reforestation that includes host plants for these insect families may provide food for locally foraging bats.","language":"English","publisher":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","usgsCitation":"Pinzari, C., Peck, R., Zinn, T., Gross, D., Montoya-Aiona, K., Brinck, K.W., Gorresen, P., and Bonaccorso, F.J., 2019, Hawaiian hoary bat (Lasiurus cinereus semotus) activity, diet and prey availability at the Waihou Mitigation Area, Maui, v, 60 p.","productDescription":"v, 60 p.","ipdsId":"IP-107493","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":366664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366633,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10790/4638"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.38900756835938,\n 20.57301047011032\n ],\n [\n -156.2976837158203,\n 20.57301047011032\n ],\n [\n -156.2976837158203,\n 20.756755953826925\n ],\n [\n -156.38900756835938,\n 20.756755953826925\n ],\n [\n -156.38900756835938,\n 20.57301047011032\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pinzari, Corinna A. 0000-0001-9794-7564","orcid":"https://orcid.org/0000-0001-9794-7564","contributorId":208455,"corporation":false,"usgs":false,"family":"Pinzari","given":"Corinna A.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":768650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":768651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zinn, Terry","contributorId":218187,"corporation":false,"usgs":false,"family":"Zinn","given":"Terry","affiliations":[{"id":39774,"text":"USGS-PIERC (intermittent)","active":true,"usgs":false}],"preferred":false,"id":768652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gross, Danielle","contributorId":218186,"corporation":false,"usgs":false,"family":"Gross","given":"Danielle","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":768653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":768649,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":150936,"corporation":false,"usgs":false,"family":"Brinck","given":"Kevin","email":"kbrinck@usgs.gov","middleInitial":"W.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":768654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gorresen, P. Marcos 0000-0002-0707-9212","orcid":"https://orcid.org/0000-0002-0707-9212","contributorId":196628,"corporation":false,"usgs":false,"family":"Gorresen","given":"P. Marcos","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":768655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bonaccorso, Frank J 0000-0002-5490-3083","orcid":"https://orcid.org/0000-0002-5490-3083","contributorId":216486,"corporation":false,"usgs":false,"family":"Bonaccorso","given":"Frank","email":"","middleInitial":"J","affiliations":[{"id":39456,"text":"USGS-PIERC (formerly)","active":true,"usgs":false}],"preferred":false,"id":768656,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204169,"text":"70204169 - 2019 - Flood-inundation mapping of a steep, gravel desert stream in Death Valley National Park, California","interactions":[],"lastModifiedDate":"2022-01-12T15:16:20.416575","indexId":"70204169","displayToPublicDate":"2019-06-30T14:43:02","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Flood-inundation mapping of a steep, gravel desert stream in Death Valley National Park, California","docAbstract":"In desert landscapes, flooding can result in dramatic changes to streams. However, the frequency, magnitude, and geomorphic effects of floods in such environments are less understood compared to wetter environments (Tooth, 2000). In desert landscapes, steep slopes and sparse vegetation result in runoff and flashy flood peaks, often lasting for only a few hours. Many floods are the result of isolated, convective thunderstorms that cannot be predicted easily in advance and frequently occur at night. Therefore, direct observations or measurements of streamflow during floods often are limited, with data collection mostly occurring after the event. In ephemeral streams, limited vegetation within channels and on overbanks result in large stream velocity and higher probability for erosion during flooding. Moreover, flood occurrence in desert streams is often highly variable and some sites may go for years without streamflow, complicating flood frequency analyses. Finally, data sets in desert environments are often short and have few long-term, systematic collection sites.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceeding of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"Jun 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Morris, C.M., and Welborn, T.L., 2019, Flood-inundation mapping of a steep, gravel desert stream in Death Valley National Park, California, in Proceeding of SEDHYD 2019, v. 1, Reno, NV, Jun 24-28, 2019, 4 p.","productDescription":"4 p.","ipdsId":"IP-104925","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":375133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365397,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/#sedhyd-2019-proceedings"}],"country":"United States","state":"California","otherGeospatial":"Death Valley National Park, Grapevine Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.09846496582031,\n 36.86863488530103\n ],\n [\n -117.47337341308594,\n 37.17891977403989\n ],\n [\n -117.6141357421875,\n 37.160863765847395\n ],\n [\n -117.60795593261717,\n 36.8829160128315\n ],\n [\n -117.42050170898436,\n 36.772442463300195\n ],\n [\n -117.26669311523438,\n 36.55101728853513\n ],\n [\n -117.14996337890625,\n 36.50301312197295\n ],\n [\n -116.80870056152342,\n 36.69099683732502\n ],\n [\n -117.09846496582031,\n 36.86863488530103\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Morris, Christopher M. 0000-0002-0477-7605","orcid":"https://orcid.org/0000-0002-0477-7605","contributorId":216851,"corporation":false,"usgs":true,"family":"Morris","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welborn, Toby L. 0000-0003-4839-2405 tlwelbor@usgs.gov","orcid":"https://orcid.org/0000-0003-4839-2405","contributorId":2295,"corporation":false,"usgs":true,"family":"Welborn","given":"Toby","email":"tlwelbor@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789930,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204984,"text":"70204984 - 2019 - Council Monitoring and Assessment Program (CMAP): Inventory of existing water quality and habitat monitoring, and mapping metadata for Gulf of Mexico Programs","interactions":[],"lastModifiedDate":"2025-05-13T16:15:43.690141","indexId":"70204984","displayToPublicDate":"2019-06-30T13:29:31","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5145,"text":"Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"262","title":"Council Monitoring and Assessment Program (CMAP): Inventory of existing water quality and habitat monitoring, and mapping metadata for Gulf of Mexico Programs","docAbstract":"Under the Council-Selected Restoration Component of the RESTORE Act, the Council develops Funded Priority Lists (FPLs) that describe the projects and programs it will fund. Projects and programs funded through this component must be in furtherance of the goals and objectives of the Council’s Comprehensive Plan and address at least one of the restoration criteria identified in the RESTORE Act. The Initial FPL, finalized in December of 2015, had a strong focus on watershed and estuary restoration and foundational cross-Gulf projects. Approved as a Gulf-wide investment in the 2015 Initial FPL, The Council Monitoring and Assessment Program (CMAP) is administered jointly by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS). Funded activities include the development of basic, foundational components for Gulf-wide monitoring to measure beneficial impacts of investments in Gulf restoration by the Council. The program, in coordination with the Gulf of Mexico Alliance (GOMA) and through collaboration with the Gulf States, Federal and local partners, academia, non-governmental organizations, and business and industry, has leveraged existing resources, capacities, and expertise and build on existing monitoring data and programs.
Lake Sturgeon (Acipenser fulvescens, LST) is a state, provincial, and tribal species of special concern that is sensitive to lampricides used in sea lamprey control. As such, there is significant interest in the Great Lakes fisheries community to develop alternative sea lamprey (Petromyzon marinus, SL) control approaches to minimize impacts on LST for applicable LST producing streams. Currently, lampricides are applied continuously to streams for 10 to 14 hours to achieve at least a 9-hour lampricide block at or above the SL minimum lethal concentration (MLC). Once the application of lampricides are initiated it usually takes 1-4 hours for the lampricide concentration to build to the target concentration during treatments depending on the flow dynamics of the stream. An interrupted lampricide block, wherein the treatment consists of two lampricide blocks (cumulative MLC of at least 9 hours) with a break in the middle, has been shown to decrease burrowing mayfly (Hexagenia limbata) mortality and resulted in no change to MLC when interruptions were up to 12 hours in duration. This study compared mortality of LST and SL during continuous and interrupted lampricide blocks with the goal of establishing whether an interrupted lampricide block treatment could be used to protect LST while maintaining treatment efficacy. Results show that there was no difference in toxicity to larval SL or LST between the interrupted block and continuous exposures. No differences were detected among calculated LC25s andLC50s for LST in the interrupted block tests compared to the continuous block tests during laboratory and streamside bioassays. An interrupted block field trial on Eliza Creek resulted in high mortality among caged larval SL (99.5%); however, posttreatment surveys estimated the treatment kill at 83.5% compared to >99% from the two previous continuous block treatments (2007, 2001). This suggests a substantial decrease in treatment effectiveness when using the interrupted block strategy. The lack of separation in toxicity between LST and SL under continuous interrupted block treatment and the reduced efficacy of the interrupted treatment block combine to make this treatment method a less desirable option.
","language":"English","usgsCitation":"Lantz, S.R., Kaye, C., Criger, L.A., Sullivan, T.J., Stephens, B., Boogaard, M.A., and Hubert, T., 2019, Comparison of continuous and interrupted lampricide block toxicity to sea lamprey and lake sturgeon.","ipdsId":"IP-106866","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":367612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367611,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/pdfs/research/reports/2015_LAN_54057.htm"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lantz, Stephen R.","contributorId":191039,"corporation":false,"usgs":false,"family":"Lantz","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":765674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaye, Cheryl","contributorId":167292,"corporation":false,"usgs":false,"family":"Kaye","given":"Cheryl","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":765675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Criger, Lori A.","contributorId":191036,"corporation":false,"usgs":false,"family":"Criger","given":"Lori","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":765676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Timothy J.","contributorId":196720,"corporation":false,"usgs":false,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stephens, Brian","contributorId":208621,"corporation":false,"usgs":false,"family":"Stephens","given":"Brian","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":765678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boogaard, Michael A. 0000-0002-5192-8437 mboogaard@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-8437","contributorId":865,"corporation":false,"usgs":true,"family":"Boogaard","given":"Michael","email":"mboogaard@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":765673,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hubert, Terrance 0000-0001-9712-1738","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":215420,"corporation":false,"usgs":false,"family":"Hubert","given":"Terrance","affiliations":[{"id":39242,"text":"UMESC (retired)","active":true,"usgs":false}],"preferred":false,"id":765679,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209570,"text":"70209570 - 2019 - Climate change adaptation for coastal national wildlife refuges","interactions":[],"lastModifiedDate":"2020-12-14T17:53:28.904407","indexId":"70209570","displayToPublicDate":"2019-06-30T11:52:13","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":7461,"text":"Final Project Memorandum","active":true,"publicationSubtype":{"id":9}},"title":"Climate change adaptation for coastal national wildlife refuges","docAbstract":"National Wildlife Refuges (NWRs) along the East Coast of the United States protect habitat for a host of wildlife species, while also offering storm surge protection, improving water quality, supporting nurseries for commercially important fish and shellfish, and providing recreation opportunities for coastal communities. Yet in the last century, coastal ecosystems in the eastern U.S. have been severely altered by human development activities as well as sea-level rise and more frequent extreme events related to climate change. These influences threaten the ability of NWRs to protect our nation’s natural resources and to sustain their many beneficial services.
Through this project, researchers are collaborating with managers of the North Carolina Coastal Refuges Complex, Cape Romain NWR, South Carolina, and other local interested partners to assist with their long-term planning under uncertain conditions regarding sea-level rise and other global change processes. Researchers are using a variety of state-of-the-art approaches, including formal decision science for systematically analyzing management alternatives and scenario planning methods for engaging with stakeholders to explore possible futures. These approaches are aimed at helping NWR staff develop management objectives, identify and weigh potential management actions for adaptation, and generate decision-support tools and models. Outcomes and products from these efforts will aid managers as they plan for and adapt to the complex challenges facing the NWR system as changing climate and other conditions make their work increasingly more difficult.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Eaton, M.J., Costanza, J.K., Johnson, F.A., Martin, J., and Taylor, L., 2019, Climate change adaptation for coastal national wildlife refuges: Final Project Memorandum, 12 p.","productDescription":"12 p.","ipdsId":"IP-115967","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":381264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381263,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c6557e4b0546c0c397b4c/553fddf0e4b0a658d7938ef5"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":786933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costanza, Jennifer K.","contributorId":176907,"corporation":false,"usgs":false,"family":"Costanza","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":786934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":224058,"corporation":false,"usgs":false,"family":"Johnson","given":"Fred","email":"","middleInitial":"A","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":786935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":786936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Laura","contributorId":224059,"corporation":false,"usgs":false,"family":"Taylor","given":"Laura","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":786937,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227825,"text":"70227825 - 2019 - Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","interactions":[],"lastModifiedDate":"2022-02-02T14:38:48.7666","indexId":"70227825","displayToPublicDate":"2019-06-30T11:51:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10076,"text":"BMC Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","title":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","docAbstract":"Background Microsatellite loci have been used extensively over the past two decades to study the genetic characteristics of non-model species. The relative ease of microsatellite development and ability to adapt markers from related species has led to the proliferation of available markers, particularly for those species that are intensively studied and managed. Because it is often infeasible to genotype individuals across all available loci, researchers generally rely on subsets of markers. Marker choice and genotyping errors can bias inferences made using disparate suites of microsatellite loci. This can limit comparative and collaborative efforts among research groups and has been a primary motivation for panel standardization efforts. Here, we develop a methodology for identifying a suite of markers from previous literature that can be generalizable across the range of commonly studied organisms. We specifically focus on producing a broadly applicable microsatellite panel for white-tailed deer (Odocoileus virginianus). Results We reviewed microsatellite panels from 58 previous or ongoing projects and identified a total of 106 candidate loci. We developed a multiplex protocol and evaluated the efficacy of 17 of the most commonly used loci using 720 DNA samples collected from the Mid-Atlantic region of the United States, an area where few previous studies were conducted. Amplification errors were detected in six of these loci. The properties of the remaining 11 loci suggest that they are applicable for many common research objectives. Specifically, this panel is highly polymorphic (eight to 20 alleles per locus, polymorphic information criterion = 0.492 to 0.917), exhibits low frequencies of genotyping errors (null alleles < 10%), and is relatively easy to interpret with the aid of allele binning software. Conclusions We were able to identify a panel of microsatellite markers that show potential for broad applicability over the geographic range of white-tailed deer, as evidenced by the distribution of previous studies that utilized them. Validation in an additional region confirmed this. These results suggest that marker standardization and evaluation procedures based on literature reviews offers an effective method for identifying consolidated panels for future studies. This simple procedure addresses previous concerns about the infeasibility of standardization efforts.
","language":"English","doi":"10.1186/s12863-019-0750-z","usgsCitation":"Miller, W.L., Edson, J., Pietrandrea, P., Cassandra Miller-Butterworth, and Walter, W., 2019, Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus): BMC Genetics, v. 20, no. 1, 49, 14 p., https://doi.org/10.1186/s12863-019-0750-z.","productDescription":"49, 14 p.","ipdsId":"IP-099036","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12863-019-0750-z","text":"Publisher Index Page"},{"id":395250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.7607421875,\n 38.805470223177466\n ],\n [\n -76.4208984375,\n 38.805470223177466\n ],\n [\n -76.4208984375,\n 41.178653972331674\n ],\n [\n -79.7607421875,\n 41.178653972331674\n ],\n [\n -79.7607421875,\n 38.805470223177466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, William L.","contributorId":272898,"corporation":false,"usgs":false,"family":"Miller","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edson, Jessie","contributorId":272899,"corporation":false,"usgs":false,"family":"Edson","given":"Jessie","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pietrandrea, Peter","contributorId":272902,"corporation":false,"usgs":false,"family":"Pietrandrea","given":"Peter","email":"","affiliations":[{"id":56403,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cassandra Miller-Butterworth","contributorId":272903,"corporation":false,"usgs":false,"family":"Cassandra Miller-Butterworth","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204474,"text":"70204474 - 2019 - Harvest assessment for Taiga bean geese in the Central Management Unit: 2019","interactions":[],"lastModifiedDate":"2019-08-16T15:36:23","indexId":"70204474","displayToPublicDate":"2019-06-30T11:50:11","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Harvest assessment for Taiga bean geese in the Central Management Unit: 2019","docAbstract":"In 2016 the European Goose Management International Working Group (EGM IWG) began development of an Adaptive Harvest Management (AHM) program for Taiga Bean Geese. In 2017, the IWG adopted an Interim Harvest Strategy consisting of a constant harvest rate (on adults) of 3% for the Central Management Unit (MU) of Taiga Bean Geese. The interim strategy is intended to provide limited hunting opportunity while rebuilding the population. Based on a January count of 41,927, the harvest quota for the 2019 hunting season is 1,740 Taiga Bean Geese (compared to 2,335 and 1,610 for the 2017 and 2018 seasons, respectively). We emphasize that these quotas include both, harvest during the regular season and derogation shooting. Going forward, we describe how an Integrated Population Model (IPM) will use counts at multiple times during the year, along with other demographic information, to estimate population size (and its precision). The IPM can be used to develop an adaptive harvest strategy if unambiguous management objectives can be agreed upon. We provide some initial guidance for formulating those objectives.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"AEWA European Goose Management Platform","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"4th Meeting of the AEWA European Goose Management International Working Group","conferenceDate":"18-20 June, 2019","conferenceLocation":"Perth, Scotland, United Kingdom","language":"English","publisher":"Scottish National Heritage","usgsCitation":"Johnson, F., Heldbjerg, H., Alhainen, M., and Madsen, J., 2019, Harvest assessment for Taiga bean geese in the Central Management Unit: 2019, in AEWA European Goose Management Platform, Perth, Scotland, United Kingdom, 18-20 June, 2019.","productDescription":"10 p.","startPage":"1-10","ipdsId":"IP-108160","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365961,"type":{"id":15,"text":"Index Page"},"url":"https://egmp.aewa.info/meetings/iwg/detail/4th-meeting-aewa-european-goose-management-international-working-group-egm-iwg-4"}],"publicComments":"Document AEWA/EGMIWG/4.10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":217602,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":767153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heldbjerg, Henning","contributorId":174479,"corporation":false,"usgs":false,"family":"Heldbjerg","given":"Henning","email":"","affiliations":[],"preferred":false,"id":767154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alhainen, Mikko","contributorId":141140,"corporation":false,"usgs":false,"family":"Alhainen","given":"Mikko","email":"","affiliations":[{"id":13690,"text":"Finnish Wildlife Agency","active":true,"usgs":false}],"preferred":false,"id":767155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":767156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212624,"text":"70212624 - 2019 - Refining the Baseline Sediment Budget for the Klamath River, California","interactions":[],"lastModifiedDate":"2022-01-11T17:32:19.904133","indexId":"70212624","displayToPublicDate":"2019-06-30T10:39:35","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Refining the Baseline Sediment Budget for the Klamath River, California","docAbstract":"Four dams in the Klamath River Hydroelectric Project (KHP) in Oregon and California (Figure 1) are currently scheduled to be removed over a period of a few weeks or months, beginning in January 2021. The Klamath dam removal will be the largest in the world by almost all measures, and is an unprecedented opportunity to advance science of river responses to such events. The KHP contains approximately 10-12 million cubic meters of mostly fine sediment and model estimates suggest approximately 1/3-2/3 of this volume is expected to be eroded from reservoirs. Much of this sediment is expected to be eventually transported by the river to, or through, the Klamath River Estuary, a distance of more than 300 kilometers. To improve the success of restoration activities following dam removal, agencies must understand the baseline conditions for biological, chemical, and physical processes, prior to the removal. We expect large changes in water quality (turbidity, suspended sediment, dissolved oxygen, temperature, and algal toxins) and in fish habitat in the Hydroelectric Reach and the main-stem of the Klamath River to the ocean. For example, modeled sediment concentrations in the Klamath River during dam removal were estimated exceed 10,000 – 15,000 mg/L, depending on streamflows, location, and the dam removal process, and to remain > 100 – 1000 mg/L for months at a time. Final time to achieve background concentrations post dam removal may take over two years (Reclamation, 2011). Plans to assess many of these changes post-dam removal are still being formulated.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"Jun 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Anderson, C.W., Wright, S., Schenk, L.N., Skalak, K., Curtis, J., East, A.E., and Benthem, A.J., 2019, Refining the Baseline Sediment Budget for the Klamath River, California, in Proceedings of SEDHYD 2019, v. 5, Reno, NV, Jun 24-28, 2019, 4 p.","productDescription":"4 p.","ipdsId":"IP-105518","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","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}],"links":[{"id":377828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377827,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_proceedings&action=proceedings.php&a=Accept"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.49069213867188,\n 41.899210607606115\n ],\n [\n -121.83563232421875,\n 41.899210607606115\n ],\n [\n -121.83563232421875,\n 42.157295553651664\n ],\n [\n -122.49069213867188,\n 42.157295553651664\n ],\n [\n -122.49069213867188,\n 41.899210607606115\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Jennifer A. 0000-0001-7766-994X","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":239547,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":797170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797171,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204481,"text":"70204481 - 2019 - Hawai‘i Groundwater Recharge Tool","interactions":[],"lastModifiedDate":"2019-12-03T09:36:08","indexId":"70204481","displayToPublicDate":"2019-06-30T09:32:07","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Hawai‘i Groundwater Recharge Tool","docAbstract":"The Hawai‘i Groundwater Recharge Tool allows users to evaluate the potential effects of land-cover and climate changes on groundwater recharge. This website provides a baseline estimate of recharge representing recent conditions of precipitation (1978–2008 average) and land cover (2010). Users can change land cover and rainfall conditions to evaluate the effects on groundwater recharge. Results will be displayed as on-screen maps, and users will be given options to generate interpretive graphics or export results in various formats. Results from this website are based on soil water-balance models. This is a pilot website that is currently limited to the island of O‘ahu, but the website has been designed to be expandable so that other islands and conditions can be added in the future.","language":"English","publisher":"University of Hawaii","usgsCitation":"McLean, J.H., Rotzoll, K., Cleaveland, S.B., and Izuka, S.K., 2019, Hawai‘i Groundwater Recharge Tool, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-104867","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":369857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365986,"rank":1,"type":{"id":18,"text":"Project Site"},"url":"https://recharge.ikewai.org/#/workspace"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.33496093749997,\n 21.210019282760218\n ],\n [\n -157.62359619140625,\n 21.210019282760218\n ],\n [\n -157.62359619140625,\n 21.728885873951494\n ],\n [\n -158.33496093749997,\n 21.728885873951494\n ],\n [\n -158.33496093749997,\n 21.210019282760218\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Jared H.","contributorId":217618,"corporation":false,"usgs":false,"family":"McLean","given":"Jared","email":"","middleInitial":"H.","affiliations":[{"id":37291,"text":"University of Hawaii at Hilo","active":true,"usgs":false}],"preferred":false,"id":767179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":767180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleaveland, Sean B.","contributorId":217619,"corporation":false,"usgs":false,"family":"Cleaveland","given":"Sean","email":"","middleInitial":"B.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":767181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767178,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202422,"text":"70202422 - 2019 - Forecasts of coastal change hazards","interactions":[],"lastModifiedDate":"2019-12-05T08:27:47","indexId":"70202422","displayToPublicDate":"2019-06-30T08:27:37","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Forecasts of coastal change hazards","docAbstract":"Model predictions of severe storm impacts provide coastal residents, emergency managers, and partner organizations valuable predictive information for planning and response to extreme storm events. The foundation of this work is a USGS-developed numerical model to forecast storm-induced coastal water levels and expected coastal change, including dune erosion, overwash, and inundation. The model is operated in three modes: generalized scenarios, real-time storms, and an operational forecast, with each mode requiring slightly different water level inputs. To evaluate and improve the accuracy of the models, we collect data on water levels and coastal change. In particular, observations before, after, and during storm conditions are used to test the different model applications. Forecast validation for Hurricanes Matthew (2016) and Irma (2017) illustrate three cases with demonstrated forecast skill and three cases with poor skill, and reveal elements of the modeling and/or testing approach which require improvement.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019: Proceedings of the 9th international conference ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0122","usgsCitation":"Doran, K.S., Stockdon, H.F., Joseph Long, and Plant, N.G., 2019, Forecasts of coastal change hazards, in Coastal Sediments 2019: Proceedings of the 9th international conference , Tampa/St. Petersburg, FL, May 27-31, 2019, p. 1400-1409, https://doi.org/10.1142/9789811204487_0122.","productDescription":"10 p.","startPage":"1400","endPage":"1409","ipdsId":"IP-105870","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":148059,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":758394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joseph Long","contributorId":213744,"corporation":false,"usgs":false,"family":"Joseph Long","affiliations":[{"id":38846,"text":"UNC Wilmington","active":true,"usgs":false}],"preferred":false,"id":758395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205847,"text":"70205847 - 2019 - Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","interactions":[],"lastModifiedDate":"2019-10-21T14:40:37","indexId":"70205847","displayToPublicDate":"2019-06-29T12:59:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","docAbstract":"Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes. Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change. Twedt (2015) implemented an alternative counting protocol on operational and non-random BBS survey routes in the southeastern United States. Observers on selected routes employed a time-distance protocol in which they recorded birds in 1-minute intervals and in 2 distance categories. We hypothesized that processing and recording observations using this time-distance protocol could cause observers to count fewer birds relative to observers using the standard protocol. We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs time-distance) to assess whether use of the time-distance protocol had a measurable effect on counting birds along BBS routes. We applied this model to BBS data from portions of eight states in which the time-distance protocol was implemented and estimated a protocol effect for 167 bird species. We documented a significant overall effect of the time-distance protocol on observers’ counts of birds. On average, the effect of the time-distance protocol was a 10% decline in count, and 80% of species had lower counts when the time-distance protocol was used on a survey route. However, because the time-distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time-distance protocol data had insignificant effects on analysis of population change. Although the covariate controlled for the effects of the time-distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duz009","usgsCitation":"Sauer, J.R., Link, W.A., Ziolkowski, D., Pardieck, K.L., and Twedt, D.J., 2019, Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts: The Condor, v. 121, no. 2, duz009, 12 p., https://doi.org/10.1093/condor/duz009.","productDescription":"duz009, 12 p.","ipdsId":"IP-081193","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz009","text":"Publisher Index Page"},{"id":368104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204354,"text":"70204354 - 2019 - Differentiating anthropogenic and natural sources of uranium by geochemical fingerprinting of groundwater at the Homestake Uranium Mill, Milan, New Mexico, USA","interactions":[],"lastModifiedDate":"2019-12-22T14:35:26","indexId":"70204354","displayToPublicDate":"2019-06-29T07:37:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Differentiating anthropogenic and natural sources of uranium by geochemical fingerprinting of groundwater at the Homestake Uranium Mill, Milan, New Mexico, USA","docAbstract":"A multiparameter geochemical-isotopic fingerprinting approach was used to differentiate natural and anthropogenic signatures of uranium contamination near the Homestake uranium mill site (Site), near Milan, New Mexico, USA. The Site consists of two tailings piles from milling operations and groundwater contamination from these tailings have been noted. The Site lies within the lower San Mateo Creek Basin with multiple regional sources of U contamination from mining and mill operations and is underlain by a heterogeneous alluvial aquifer, which is underlain by basement rock of the Chinle Group and the lowermost San Andres-Glorieta aquifer. To help decipher signatures, several statistical approaches were used including PCA, NMDS, and cluster analysis.\nTrilinear piper diagrams indicate two end member water types at the Site, sulfate-Na-K and sulfate-Ca. Natural alluvial aquifer groundwater in this area, relatively unaffected by mining or milling, appears to be more dominated by bicarbonate than sulfate and the deeper San Andres-Glorieta aquifer that has a mixture of sulfate and bicarbonate. Uranium concentrations from the Site fall into three broad categories, less than the drinking water standard of 30 µg/L (n=3), from 30 to 100 µg/L (n=9) and greater than 100 µg/L (n=8). Component loadings in a principal component analysis are highest for uranium isotopes, 228Ra, gross alpha-beta, molybdenum, chloride, uranium, and sodium, which affect the similarities or differences among wells sampled. Results suggest that several alluvial wells upgradient from the Site have anthropogenic fingerprints from regional sources related to upgradient mining. Wells with higher uranium concentrations have uranium activity ratios close to 1, which is indicative of mining or milling signatures. These same wells have elevated radon activities. This information can be used to inform Site managers on the source of water related to uranium at the Site and provide an approach for geochemical fingerprinting.","language":"English","publisher":"Springer","doi":"10.1007/s12665-019-8385-y","usgsCitation":"Blake, J., Harte, P., and Becher, K., 2019, Differentiating anthropogenic and natural sources of uranium by geochemical fingerprinting of groundwater at the Homestake Uranium Mill, Milan, New Mexico, USA: Environmental Earth Sciences, v. 78, no. 384, https://doi.org/10.1007/s12665-019-8385-y.","ipdsId":"IP-085089","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":365731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Milan","otherGeospatial":"San Mateo Creek Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.19061279296875,\n 35.007502842952896\n ],\n [\n -107.47650146484374,\n 35.007502842952896\n ],\n [\n -107.47650146484374,\n 35.39800594715108\n ],\n [\n -108.19061279296875,\n 35.39800594715108\n ],\n [\n -108.19061279296875,\n 35.007502842952896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"384","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harte, Philip 0000-0002-7718-1204","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":217273,"corporation":false,"usgs":true,"family":"Harte","given":"Philip","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becher, Kent 0000-0002-3947-0793","orcid":"https://orcid.org/0000-0002-3947-0793","contributorId":217274,"corporation":false,"usgs":true,"family":"Becher","given":"Kent","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203473,"text":"ofr20191056 - 2019 - Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making","interactions":[],"lastModifiedDate":"2024-03-04T18:44:10.106398","indexId":"ofr20191056","displayToPublicDate":"2019-06-28T13:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1056","displayTitle":"Optimization of Salt Marsh Management at the Chincoteague National Wildlife Refuge, Virginia, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making","docAbstract":"Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing salt marsh management decisions at the Chincoteague National Wildlife Refuge in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 12 salt marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that would be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per salt marsh management unit, that would maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to approximately $2.5 million, but that further expenditures may yield diminishing return on investment. For multiple salt marsh management units, a scenario incorporating managing grazing practices within the marsh was selected to maximize benefits while constraining total costs for the refuge at less than $2.5 million. Thin-layer deposition was predicted to increase the total management benefit substantially, but at considerable total costs ($2.5 million to $83 million). The prototype presented here provides a framework for decision making at the Chincoteague National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Holcomb, K.S., 2019, Optimization of salt marsh management at the Chincoteague National Wildlife Refuge, Virginia, through use of structured decision making: U.S. Geological Survey Open-File Report 2019–1056, 29 p., https://doi.org/10.3133/ofr20191056.","productDescription":"vi, 29 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101219","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":364633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1056/coverthb.jpg"},{"id":364634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1056/ofr20191056.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1056"}],"country":"United States","state":"Virginia","otherGeospatial":"Chincoteague Island, Chincoteague National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.38440704345703,\n 37.91278405007035\n ],\n [\n -75.3830337524414,\n 37.916169765380076\n ],\n [\n -75.37445068359375,\n 37.917117737741826\n ],\n [\n -75.37273406982422,\n 37.916576040745376\n ],\n [\n -75.36895751953125,\n 37.91468006984207\n ],\n [\n -75.36449432373047,\n 37.91562806140234\n ],\n [\n -75.35608291625977,\n 37.91562806140234\n ],\n [\n -75.35076141357422,\n 37.91684688974227\n ],\n [\n -75.34818649291992,\n 37.920367835943516\n ],\n [\n -75.34629821777344,\n 37.924565666890146\n ],\n [\n -75.34406661987303,\n 37.9276800317787\n ],\n [\n -75.34046173095703,\n 37.936074619194514\n ],\n [\n -75.33823013305664,\n 37.93945926228315\n ],\n [\n -75.34475326538086,\n 37.94094845586459\n ],\n [\n -75.34612655639648,\n 37.947040297194114\n ],\n [\n -75.34114837646484,\n 37.953673061162604\n ],\n [\n -75.33102035522461,\n 37.958681077955525\n ],\n [\n -75.32638549804688,\n 37.958004338883114\n ],\n [\n -75.32655715942383,\n 37.96720745598712\n ],\n [\n -75.31213760375975,\n 37.98141588591056\n ],\n [\n -75.31848907470703,\n 37.983310135428795\n ],\n [\n -75.3219223022461,\n 37.98019812825676\n ],\n [\n -75.32432556152342,\n 37.98182180063798\n ],\n [\n -75.32827377319335,\n 37.982904228934125\n ],\n [\n -75.33102035522461,\n 37.98141588591056\n ],\n [\n -75.33187866210936,\n 37.97153793552019\n ],\n [\n -75.33308029174805,\n 37.968966744104264\n ],\n [\n -75.33565521240234,\n 37.96829009981737\n ],\n [\n -75.34097671508789,\n 37.9630120603577\n ],\n [\n -75.34664154052734,\n 37.959493156611366\n ],\n [\n -75.35642623901367,\n 37.953266990781884\n ],\n [\n -75.36518096923828,\n 37.94568659832042\n ],\n [\n -75.36792755126953,\n 37.942166864531906\n ],\n [\n -75.36672592163085,\n 37.94798787156644\n ],\n [\n -75.3691291809082,\n 37.94988298364895\n ],\n [\n -75.37359237670898,\n 37.94825860485678\n ],\n [\n -75.37445068359375,\n 37.944874367025136\n ],\n [\n -75.37273406982422,\n 37.94162535206254\n ],\n [\n -75.37256240844727,\n 37.93851157792925\n ],\n [\n -75.377197265625,\n 37.935262281661146\n ],\n [\n -75.38389205932617,\n 37.932554425046405\n ],\n [\n -75.39127349853516,\n 37.92402402474885\n ],\n [\n -75.39505004882812,\n 37.916305190751174\n ],\n [\n -75.40895462036133,\n 37.90492859043573\n ],\n [\n -75.40672302246094,\n 37.89937508713545\n ],\n [\n -75.40157318115234,\n 37.898020510564386\n ],\n [\n -75.39573669433594,\n 37.89896871678171\n ],\n [\n -75.39281845092773,\n 37.899781455245545\n ],\n [\n -75.38818359375,\n 37.89910417381559\n ],\n [\n -75.38320541381836,\n 37.90072963877702\n ],\n [\n -75.38114547729492,\n 37.90398046100267\n ],\n [\n -75.3823471069336,\n 37.90858554667319\n ],\n [\n -75.38440704345703,\n 37.91115885137137\n ],\n [\n -75.38440704345703,\n 37.91278405007035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
Dissolved selenium is a contaminant of concern in the lower Gunnison River Basin, Colorado. Selenium is naturally present in the Cretaceous Mancos Shale and is leached to groundwater and surface water by irrigation. The groundwater on the east side of the Uncompahgre River in Delta and Montrose Counties is one of the primary sources of selenium concentration and load to surface water in the lower Gunnison River Basin. Although little information about the contribution of groundwater to surface water has been historically available, groundwater has often been implicated as an appreciable source of selenium to surface water. From 2012 to 2016, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program, established a 30-well groundwater-monitoring network on irrigated land to characterize the hydrology and groundwater quality of the shallow groundwater system on the east side of the Uncompahgre River in the lower Gunnison River Basin. The installation of the 30-well network and the data collected allowed for the development of a conceptual model of selenium mobilization and transport in the shallow groundwater system. Monitoring wells were completed in surficial deposits and in weathered Mancos Shale, which generally exhibited unconfined and confined conditions, respectively. Groundwater-quality monitoring provides information on the distribution of selenium and the geochemical processes controlling selenium concentrations in shallow groundwater. Monitoring wells were sampled between August 2013 and March 2015 to understand groundwater quality, seasonality, sources of recharge, and groundwater age. Concentrations of dissolved selenium ranged from below the limit of detection to 4,100 micrograms per liter (µg/L), with a median concentration of 14 µg/L. Concentrations showed a high degree of spatial variability and no seasonal difference. Similarly, no seasonal pattern was observed in specific conductance values of groundwater despite the considerably lower specific conductance value of irrigation water.
Reduction-oxidation processes are important controls on selenium mobility. Nitrate derived from geologic material was a primary control on reduction-oxidation conditions in groundwater and inhibited selenium reduction to less mobile forms. Nitrate was reduced by denitrification in groundwater, but it was not reduced to the extent necessary to allow for selenium reduction. Groundwater ages were determined for groundwater samples from eight wells and ranged from 6 to 20 years old. Isotopic data indicate groundwater was recharged by irrigation water; no information collected supported an older, deeper source of recharge to the shallow groundwater system. Data on water level in all wells showed response to irrigation practices, but the response was delayed in some wells, which may be an indication of distance from recharge source.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195029","collaboration":"Prepared in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program","usgsCitation":"Thomas, J.C., McMahon, P.B., and Arnold, L.R., 2019, Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the lower Gunnison River Basin, Colorado, 2012–16: U.S. Geological Survey Scientific Investigations Report 2019–5029, 69 p., https://doi.org/10.3133/sir20195029.","productDescription":"viii, 69 p.","onlineOnly":"Y","ipdsId":"IP-084069","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5029/coverthb.jpg"},{"id":365133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5029/sir20195029.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5029"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.80584716796875,\n 39.01064750994083\n ],\n [\n -109.11895751953125,\n 38.8782049970615\n ],\n [\n -108.6328125,\n 38.10214399750345\n ],\n [\n -108.69598388671875,\n 37.77288579232439\n ],\n [\n -107.87750244140625,\n 37.309014074275915\n ],\n [\n -107.4462890625,\n 37.31338308990806\n ],\n [\n -107.1441650390625,\n 37.727280276860036\n ],\n [\n -107.18536376953125,\n 38.07620357665235\n ],\n [\n -107.26776123046875,\n 38.50304202775689\n ],\n [\n -107.50671386718749,\n 38.9380483825641\n ],\n [\n -107.6495361328125,\n 39.115144700901475\n ],\n [\n -108.80584716796875,\n 39.01064750994083\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
Infections from antibiotic resistant microorganisms are considered to be one of the greatest global public health challenges that result in huge annual economic losses. While genes that impart resistance to antibiotics (AbR) existed long before the discovery and use of antibiotics, anthropogenic uses of antibiotics in agriculture, domesticated animals, and humans are known to influence the prevalence of these genes in pathogenic microorganisms. It is critical to understand the role that natural and anthropogenic processes have on the occurrence and distribution of antibiotic resistance in microbial populations to minimize health risks associated with exposures. As part of this research, 15 antibiotic resistance genes were analyzed in coastal sediments and soils along the eastern seaboard of the USA using presence/absence quantitative and digital polymerase chain reaction assays. Samples (53 soil and 192 sediment samples including 54 replicates) were collected from a variety of coastal settings where human and wildlife exposure is likely. At least one of the antibiotic resistance genes was detected in 76.4% of the samples. Samples that contained at least five or more antibiotic resistance genes (5.7%) where typically hydrologically down gradient of watersheds influenced by combined sewer outfalls (CSO). The most frequently detected antibiotic resistance target genes were found in 33.2%, 34.4%, and 42.2% of samples (target genes blaSHV, tetO, and aadA2, respectively). These data provide unique insight into potential exposure of AbR genes over a large geographical region of the eastern seaboard of the USA.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10661-019-7426-z","usgsCitation":"Griffin, D.W., Benzel, W., Fisher, S.C., Focazio, M.J., Iwanowicz, L.R., Loftin, K., Reilly, T.J., and Jones, D.K., 2019, The presence of antibiotic resistance genes in coastal soil and sediment samples from the eastern seaboard of the USA: Environmental Monitoring and Assessment, v. 19, no. Suppl 2, 300, 17 p., https://doi.org/10.1007/s10661-019-7426-z.","productDescription":"300, 17 p.","ipdsId":"IP-086519","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"links":[{"id":367003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.379150390625,\n 45.042478050891546\n ],\n [\n -69.8291015625,\n 44.41024041296011\n ],\n [\n -70.784912109375,\n 43.59630591596548\n ],\n [\n -71.641845703125,\n 42.25291778330197\n ],\n [\n -71.9384765625,\n 41.582579601430346\n ],\n [\n -73.004150390625,\n 41.50857729743935\n ],\n [\n -74.15771484375,\n 40.896905775860006\n ],\n [\n -74.90478515625,\n 40.32141999593439\n ],\n [\n -76.83837890625,\n 39.317300373271024\n ],\n [\n -77.222900390625,\n 38.93377552819722\n ],\n [\n -77.464599609375,\n 38.460041065720446\n ],\n [\n -77.03887939453125,\n 36.855449936136495\n ],\n [\n -76.7669677734375,\n 36.59127365634205\n ],\n [\n -75.86883544921875,\n 36.558187766360675\n ],\n [\n -73.575439453125,\n 39.90973623453719\n ],\n [\n -69.840087890625,\n 41.236511201246216\n ],\n [\n -70.015869140625,\n 42.61779143282346\n ],\n [\n -69.818115234375,\n 43.51668853502906\n ],\n [\n -66.873779296875,\n 44.68427737181225\n ],\n [\n -67.1044921875,\n 45.042478050891546\n ],\n [\n -67.379150390625,\n 45.042478050891546\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"Suppl 2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benzel, William 0000-0002-4085-1876 wbenzel@usgs.gov","orcid":"https://orcid.org/0000-0002-4085-1876","contributorId":3594,"corporation":false,"usgs":true,"family":"Benzel","given":"William","email":"wbenzel@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":769594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Shawn C. 0000-0001-6324-1061 scfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-6324-1061","contributorId":4843,"corporation":false,"usgs":true,"family":"Fisher","given":"Shawn","email":"scfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":769596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":769597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":205662,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":769598,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"preferred":true,"id":769599,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769600,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203961,"text":"ofr20191074 - 2019 - Effects of experimental removal of Barred Owls on population Demography of Northern Spotted Owls in Washington and Oregon—2018 Progress Report","interactions":[],"lastModifiedDate":"2019-07-01T09:36:40","indexId":"ofr20191074","displayToPublicDate":"2019-06-28T10:34:46","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1074","displayTitle":"Effects of Barred Owl (Strix varia) Removal on Population Demography of Northern Spotted Owls (Strix occidentalis caurina) in Washington and Oregon, 2015–18","title":"Effects of experimental removal of Barred Owls on population Demography of Northern Spotted Owls in Washington and Oregon—2018 Progress Report","docAbstract":"Populations of Northern Spotted Owls (Strix occidentalis caurina; herineafter referred to as Spotted Owl) have declined throughout the subspecies’ geographic range. Evidence indicates that competition with invading Barred Owls (S. varia) has contributed significantly to those declines. A pilot study in California showed that removal of Barred Owls coupled with conservation of suitable habitat conditions can slow or even reverse population declines of Spotted Owls. It is unknown, however, whether similar results can be obtained in areas with different forest conditions, greater densities of Barred Owls, and fewer remaining Spotted Owls. We initiated a before-after-control-impact (BACI) experiment at three study areas in Oregon and Washington to determine if removal of Barred Owls can improve population trends of Spotted Owls. This report describes research accomplishments and initial results from the first 3.5 years of the study (March 2015–August 2018).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191074","usgsCitation":"Wiens, J.D., Dugger, K.M., Lesmeister, D.B., Dilione, K.E., and Simon, D.C., 2019, Effects of Barred Owl (Strix varia) removal on population demography of Northern Spotted Owls (Strix occidentalis caurina) in Washington and Oregon, 2015–18: U.S. Geological Survey Open-File Report 2019-1074, 17 p., https://doi.org/10.3133/ofr20191074.","productDescription":"vi, 17 p.","onlineOnly":"Y","ipdsId":"IP-108218","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":365174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1074/coverthb.jpg"},{"id":365175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1074/ofr20191074.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1074"}],"country":"United States","state":"Oregon, Washington","city":"Cle Elum","otherGeospatial":"Oregon Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.9093017578125,\n 43.79885402720353\n ],\n [\n -122.3382568359375,\n 43.79885402720353\n ],\n [\n -122.3382568359375,\n 45.41773242370463\n ],\n [\n -123.9093017578125,\n 45.41773242370463\n ],\n [\n -123.9093017578125,\n 43.79885402720353\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.991943359375,\n 42.532844281713125\n ],\n [\n -120.86608886718749,\n 42.532844281713125\n ],\n [\n -120.86608886718749,\n 43.55252937447483\n ],\n [\n -122.991943359375,\n 43.55252937447483\n ],\n [\n -122.991943359375,\n 42.532844281713125\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.37695312499999,\n 46.619261036171515\n ],\n [\n -120.14648437499999,\n 46.619261036171515\n ],\n [\n -120.14648437499999,\n 47.73932336136857\n ],\n [\n -121.37695312499999,\n 47.73932336136857\n ],\n [\n -121.37695312499999,\n 46.619261036171515\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
The carbon dioxide (CO2) storage capacity of saline formations may be constrained by reservoir pressure limitations. Brine extraction could be necessary to increase the CO2 storage capacity of a given formation, manage the extent of the underground CO2 plume and induced pressure front, and control the migration direction. To estimate the additional CO2 storage capacity of a saline formation that can be made accessible by extraction of in-situ brines, a three-dimensional (3D) generic cubic cell containing one CO2 injector in the middle surrounded by four brine extractors at each corner of the cell was assumed. A series of Tough2-ECO2N reservoir simulations were constructed with varying reservoir properties and run. Based on a series of scenarios, a mechanism was developed and demonstrated that resulted in derivation of a function to provide estimates of the ratio of total CO2 injection over the brine extraction rate for a given scenario. We selected multiple saline formations in U.S. basins and evaluated the potential to increase the combined dynamic CO2 storage capacity of the selected saline formations to over 1000 million metric tonnes per year (Mt/yr) of CO2 for 100 years by means of brine extraction. Such storage capacities may be adequate to accommodate the CO2 injection rates suggested for the United States under a “beyond two-degree Celsius scenario” (B2DS) that has been proposed to maintain global temperature rise to less than 2°C above pre-industrial reported levels. The results suggest that B2DS goals could be achieved with a volume ratio of brine extraction to CO2injection as low as 1:4, which is far lower than the ratios that have been commonly assumed in the literature.
","language":"English","publisherLocation":"Elsevier","doi":"10.1016/j.ijggc.2019.06.009","usgsCitation":"Jahediesfanjani, H., Anderson, S.T., and Warwick, P., 2019, Improving pressure-limited CO2 storage capacity in saline formations by means of brine extraction: International Journal of Greenhouse Gas Control, v. 88, p. 299-310, https://doi.org/10.1016/j.ijggc.2019.06.009.","productDescription":"12 p.","startPage":"299","endPage":"310","ipdsId":"IP-104245","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":467496,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijggc.2019.06.009","text":"Publisher Index Page"},{"id":365243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jahediesfanjani, Hossein 0000-0001-6281-5166","orcid":"https://orcid.org/0000-0001-6281-5166","contributorId":201000,"corporation":false,"usgs":false,"family":"Jahediesfanjani","given":"Hossein","affiliations":[],"preferred":false,"id":765279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Steven T. 0000-0003-3481-3424 sanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-3481-3424","contributorId":2532,"corporation":false,"usgs":true,"family":"Anderson","given":"Steven","email":"sanderson@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warwick, Peter D. 0000-0002-3152-7783","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":205928,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765278,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}