{"pageNumber":"449","pageRowStart":"11200","pageSize":"25","recordCount":46644,"records":[{"id":70160371,"text":"70160371 - 2015 - Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","interactions":[],"lastModifiedDate":"2015-12-23T11:00:01","indexId":"70160371","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","docAbstract":"<p>Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.</p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2015.10.051","usgsCitation":"Witt, E.C., 2015, Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain: Journal of Hydrology, v. 531, no. 3, p. 759-767, https://doi.org/10.1016/j.jhydrol.2015.10.051.","productDescription":"9 p.","startPage":"759","endPage":"767","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066431","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":312794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","city":"Greenville","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.3298454284668,\n              35.628488848361336\n            ],\n            [\n              -77.32804298400879,\n              35.60330002507124\n            ],\n            [\n              -77.36005783081055,\n              35.604346810028304\n            ],\n            [\n              -77.37645149230957,\n              35.61174370007563\n            ],\n            [\n              -77.37722396850586,\n              35.62583776685229\n            ],\n            [\n              -77.3298454284668,\n              35.628488848361336\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3bbe4b0a04ef491a1f9","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":582830,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70159860,"text":"70159860 - 2015 - Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions","interactions":[],"lastModifiedDate":"2018-10-30T14:24:46","indexId":"70159860","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions","docAbstract":"<p><span>Recent observations suggest that polar bears (</span><i>Ursus maritimus</i><span>) are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their sea ice habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi Sea between two periods (1986&ndash;1995 and 2008&ndash;2013) when substantial summer sea-ice loss occurred. In both time periods, polar bears predominantly occupied sea-ice, although land was used during the summer sea-ice retreat and during the winter for maternal denning. However, the proportion of bears on land for &gt; 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia), highlighting the importance of these northernmost land habitats to Chukchi Sea polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of sea ice retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to sea-ice loss. Implications of increased land use for Chukchi Sea polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to sea ice loss. However, projections of continued sea ice loss suggest that polar bears in the Chukchi Sea and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0142213","usgsCitation":"Rode, K.D., Wilson, R.H., Regehr, E.V., St. Martin, M., Douglas, D., and Olson, J., 2015, Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions: PLoS ONE, v. 10, no. 11, e0142213; 18 p., https://doi.org/10.1371/journal.pone.0142213.","productDescription":"e0142213; 18 p.","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064932","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471592,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0142213","text":"Publisher Index Page"},{"id":438661,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BZ643N","text":"USGS data release","linkHelpText":"Chukchi Sea Polar Bear Locations, 1985-1996"},{"id":311761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chukchi Sea","volume":"10","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"565ec4b0e4b071e7ea544411","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":580722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":580723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"St. Martin, Michelle","contributorId":150114,"corporation":false,"usgs":false,"family":"St. Martin","given":"Michelle","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":580724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olson, Jay","contributorId":150116,"corporation":false,"usgs":false,"family":"Olson","given":"Jay","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":580726,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70159871,"text":"70159871 - 2015 - Alpine biodiversity and assisted migration: The case of the American pika (<i>Ochotona princeps</i>)","interactions":[],"lastModifiedDate":"2016-01-25T12:34:42","indexId":"70159871","displayToPublicDate":"2015-12-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1004,"text":"Biodiversity","active":true,"publicationSubtype":{"id":10}},"title":"Alpine biodiversity and assisted migration: The case of the American pika (<i>Ochotona princeps</i>)","docAbstract":"<p><span>Alpine mammals are predicted to be among the species most threatened by climate change, due to the projected loss and further fragmentation of alpine habitats. As temperature or precipitation regimes change, alpine mammals may also be faced with insurmountable barriers to dispersal. The slow rate or inability to adjust to rapidly shifting environmental conditions may cause isolated alpine species to become locally extirpated, resulting in reduced biodiversity. One proposed method for mitigating the impacts of alpine species loss is assisted migration. This method, which involves translocating a species to an area with more favourable climate and habitat characteristics, has become the subject of debate and controversy in the conservation community. The uncertainty associated with climate change projections, coupled with the thermal sensitivity of many alpine mammals, makes it difficult to a priori assess the efficacy of this technique as a conservation management tool. Here we present the American pika (</span><i>Ochotona princeps</i><span>) as a case study. American pikas inhabit rocky areas throughout the western US, and populations in some mountainous areas have become locally extirpated in recent years. We review known climatic and habitat requirements for this species, and also propose protocols designed to reliably identify favourable relocation areas. We present data related to the physiological constraints of this species and outline specific requirements which must be addressed for translocation of viable populations, including wildlife disease and genetic considerations. Finally, we discuss potential impacts on other alpine species and alpine communities, and overall implications for conserving alpine biodiversity in a changing climate.</span></p>","language":"English","publisher":"Taylor & Francis","publisherLocation":"London","doi":"10.1080/14888386.2015.1112304","usgsCitation":"Wilkening, J.L., Ray, C., Ramsay, N.G., and Klingler, K., 2015, Alpine biodiversity and assisted migration: The case of the American pika (<i>Ochotona princeps</i>): Biodiversity, v. 16, no. 4, p. 1-13, https://doi.org/10.1080/14888386.2015.1112304.","productDescription":"13 p.","startPage":"1","endPage":"13","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067134","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":311784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.04687499999999,\n              49.095452162534826\n            ],\n            [\n              -105.29296874999999,\n              49.095452162534826\n            ],\n            [\n              -104.23828125,\n              44.902577996288876\n            ],\n            [\n              -103.88671875,\n              40.979898069620155\n            ],\n            [\n              -103.798828125,\n              38.548165423046584\n            ],\n            [\n              -103.271484375,\n              36.24427318493909\n            ],\n            [\n              -103.095703125,\n              34.379712580462204\n            ],\n            [\n              -103.0078125,\n              32.10118973232094\n            ],\n            [\n              -104.4140625,\n              31.50362930577303\n            ],\n            [\n              -106.34765625,\n              31.57853542647338\n            ],\n            [\n              -108.19335937499999,\n              31.728167146023935\n            ],\n            [\n              -111.357421875,\n              31.353636941500987\n            ],\n            [\n              -114.78515624999999,\n              32.694865977875075\n            ],\n            [\n              -117.42187500000001,\n              32.694865977875075\n            ],\n            [\n              -118.125,\n              33.211116472416855\n            ],\n            [\n              -119.44335937499999,\n              33.94335994657882\n            ],\n            [\n              -121.025390625,\n              34.161818161230386\n            ],\n            [\n              -121.81640624999999,\n              35.24561909420681\n            ],\n            [\n              -123.22265625000001,\n              37.16031654673677\n            ],\n            [\n              -124.365234375,\n              38.61687046392973\n            ],\n            [\n              -124.45312499999999,\n              39.774769485295465\n            ],\n            [\n              -125.15625000000001,\n              41.244772343082076\n            ],\n            [\n              -124.892578125,\n              41.902277040963696\n            ],\n            [\n              -125.24414062499999,\n              43.51668853502909\n            ],\n            [\n              -124.71679687499999,\n              45.27488643704894\n            ],\n            [\n              -124.71679687499999,\n              47.2195681123155\n            ],\n            [\n              -125.068359375,\n              48.574789910928864\n            ],\n            [\n              -123.31054687499999,\n              48.3416461723746\n            ],\n            [\n              -123.04687499999999,\n              49.095452162534826\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5660243ae4b071e7ea544ca5","contributors":{"authors":[{"text":"Wilkening, Jennifer L. 0000-0001-8748-4578","orcid":"https://orcid.org/0000-0001-8748-4578","contributorId":127685,"corporation":false,"usgs":false,"family":"Wilkening","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7111,"text":"U. Colorado, Boulder, Dept. Ecology & Evol.Biol., PhD Student","active":true,"usgs":false}],"preferred":false,"id":580835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Chris","contributorId":150148,"corporation":false,"usgs":false,"family":"Ray","given":"Chris","email":"","affiliations":[{"id":17921,"text":"Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":580836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsay, Nathan G. nramsay@usgs.gov","contributorId":3191,"corporation":false,"usgs":true,"family":"Ramsay","given":"Nathan","email":"nramsay@usgs.gov","middleInitial":"G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klingler, Kelly","contributorId":150149,"corporation":false,"usgs":false,"family":"Klingler","given":"Kelly","affiliations":[{"id":17922,"text":"Program in Ecology, Evolution, and Conservation Biology, University of Nevada, Reno,","active":true,"usgs":false}],"preferred":false,"id":580837,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70203506,"text":"70203506 - 2015 - A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","interactions":[],"lastModifiedDate":"2019-05-20T10:16:54","indexId":"70203506","displayToPublicDate":"2015-12-01T10:16:27","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","docAbstract":"In the geosciences, isotopic ratios and trace element concentrations are often used along with major element concentrations to help determine sources of and processes affecting geochemical variation. Compositional Data Analysis (CoDA) is a set of tools, generally attuned to major element data, concerned with the proper statistical treatment and removal of spurious correlations from compositional data. Though recent insights have been made on the incorporation of trace elements and stable isotope ratios to CoDA, this study provides a general approach to thinking about how radiogenic isotopes, stable isotopes, and trace elements fit with major elements in the CoDA framework. In the present study, we use multiple data sets of deep formation brines and compare traditional mixing models to their CoDA counterparts to examine fluid movement between reservoirs. Concentrations of individual isotopes are calculated using isotopic ratios and global mean isotopic abundances. One key result is that isotope parts (e.g.   18O, 17O, 16O, 2H, 1H, 87Sr, 86Sr) can simply be modelled by the major element concentration (H2O, Sr) in a clr-biplot as they are perfectly dependent. Another important result is that an ilr transformation of radiogenic isotope parts (e.g. 86Sr and 87Sr in 87Sr/86Sr) and trace elements can, like stable isotopes in delta notation, be treated as a linear function of the isotopic ratio or trace element concentration, scaled only by a constant. This implies that there are multiple situations in which an ilr transformation provides little additional insight for the analysis of trends: (1) any two parts with low log ratio variance (e.g. an isotope ratio), no matter their concentrations in the solution, (2) any low concentration parts (trace elements) or a ratio of a trace to a major element, no matter the variance of the elements, and (3) large positive ratios (major/trace) over a restricted range of variance. Similarly, a multivariate ilr transformation of a large data set with many parts will also be a simple perturbation if the balances are evenly split between parts. CoDA transformations, however, even if they do not provide new insight in some specific cases, will provide consistent interpretations for all types of data.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Workshop on Compositional Data Analysis","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Workshop on Compositional Data Analysis","conferenceDate":"June 1-5, 2015","conferenceLocation":"L'Escala, Spain","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-44811-4_2","usgsCitation":"Blondes, M., Engle, M.A., and Geboy, N., 2015, A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry, <i>in</i> Proceedings of the International Workshop on Compositional Data Analysis, L'Escala, Spain, June 1-5, 2015, p. 13-29, https://doi.org/10.1007/978-3-319-44811-4_2.","productDescription":"17 p.","startPage":"13","endPage":"29","ipdsId":"IP-070706","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geboy, Nicholas 0000-0003-3949-3001 ngeboy@usgs.gov","orcid":"https://orcid.org/0000-0003-3949-3001","contributorId":215664,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70160736,"text":"70160736 - 2015 - Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","interactions":[],"lastModifiedDate":"2018-01-04T13:06:31","indexId":"70160736","displayToPublicDate":"2015-12-01T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","docAbstract":"<p>The western Pacific island of Rota is the fourth largest human-inhabited island in the Mariana archipelago and designated an Endemic Bird Area. Between 1982 and 2012, 12 point-transect distance-sampling surveys were conducted to assess bird population status. Surveys did not consistently sample the entire island; thus, we used a ratio estimator to estimate bird abundances in strata not sampled during every survey. Trends in population size were reliably estimated for 11 of 13 bird species, and 7 species declined over the 30-y time series, including the island collared-dove <i>Streptopelia bitorquata</i>, white-throated ground-dove <i>Gallicolumba xanthonura</i>, Mariana fruit-dove <i>Ptilinopus roseicapilla</i>, collared kingfisher <i>Todiramphus chloris orii</i>, Micronesian myzomela <i>Myzomela rubratra</i>, black drongo <i>Dicrurus macrocercus</i>, and Mariana crow <i>Corvus kubaryi</i>. The endangered Mariana crow (x̄  =  81 birds, 95% CI 30&ndash;202) declined sharply to fewer than 200 individuals in 2012, down from 1,491 birds in 1982 (95% CI  =  815&ndash;3,115). Trends increased for white tern <i>Gygis alba</i>, rufous fantail <i>Rhipidura rufifrons mariae</i>, and Micronesian starling <i>Aplonis opaca</i>. Numbers of the endangered Rota white-eye <i>Zosterops rotensis</i> declined from 1982 to the late 1990s but returned to 1980s levels by 2012, resulting in an overall stable trend. Trends for the yellow bittern<i> Ixobrychus sinensis</i> were inconclusive. Eurasian tree sparrow <i>Passer montanus</i> trends were not assessed; however, their numbers in 1982 and 2012 were similar. Occupancy models of the 2012 survey data revealed general patterns of land cover use and detectability among 12 species that could be reliably modeled. Occupancy was not assessed for the Eurasian tree sparrow because of insufficient detections. Based on the 2012 survey, bird distribution and abundance across Rota revealed three general patterns: 1) range restriction, including Mariana crow, Rota white-eye, and Eurasian tree sparrow; 2) widespread distribution, low abundance, including collared kingfisher, island collared-dove, white-throated ground-dove, Mariana fruit-dove, white tern, yellow bittern, black drongo, and Micronesian myzomela; and 3) widespread distribution, high abundance, including rufous fantail and Micronesian starling. The Mariana crow was dispersed around the periphery of the island in steep forested land-cover types. In contrast, the Rota white-eye was restricted to the high-elevation mesa. Only for the white-throated ground-dove was there a significant difference among cover types, with lower occupancy in open field than in forested areas. Vegetation was included in the best-fit occupancy models for yellow bittern, black drongo, Micronesian myzomela, and Micronesian starling, but vegetation type was not a significant variable nor included in the top models for the remaining five species: white tern, island collared-dove, Mariana fruit-dove, collared kingfisher, and rufous fantail. Given declining population trends, the Rota bird-monitoring program could benefit from establishing threshold and alert limits and identifying alternative research and management actions. Continued monitoring and demographic sampling, in conjunction with ecological studies, are needed to understand why most bird species on Rota are declining, identify the causative agents, and assess effectiveness of conservation actions, especially for the Mariana crow.</p>","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington D.C.","doi":"10.3996/112014-JFWM-085","usgsCitation":"Camp, R., Brinck, K., Gorresen, P.M., Amidon, F.A., Radley, P.M., Berkowitz, S., and Banko, P.C., 2015, Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands: Journal of Fish and Wildlife Management, v. 6, no. 2, p. 511-540, https://doi.org/10.3996/112014-JFWM-085.","productDescription":"30 p.","startPage":"511","endPage":"540","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061310","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research 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,{"id":70175224,"text":"70175224 - 2015 - Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers","interactions":[],"lastModifiedDate":"2016-08-03T08:22:38","indexId":"70175224","displayToPublicDate":"2015-12-01T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1264,"text":"Cold Regions Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers","docAbstract":"<p><span>Deep slab avalanches are particularly challenging to forecast. These avalanches are difficult to trigger, yet when they release they tend to propagate far and can result in large and destructive avalanches. We utilized a 44-year record of avalanche control and meteorological data from Bridger Bowl ski area in southwest Montana to test the usefulness of meteorological variables for predicting seasons and days with deep slab avalanches. We defined deep slab avalanches as those that failed on persistent weak layers deeper than 0.9&nbsp;m, and that occurred after February 1st. Previous studies often used meteorological variables from days prior to avalanches, but we also considered meteorological variables over the early months of the season. We used classification trees and random forests for our analyses. Our results showed seasons with either dry or wet deep slabs on persistent weak layers typically had less precipitation from November through January than seasons without deep slabs on persistent weak layers. Days with deep slab avalanches on persistent weak layers often had warmer minimum 24-hour air temperatures, and more precipitation over the prior seven days, than days without deep slabs on persistent weak layers. Days with deep wet slab avalanches on persistent weak layers were typically preceded by three days of above freezing air temperatures. Seasonal and daily meteorological variables were found useful to aid forecasting dry and wet deep slab avalanches on persistent weak layers, and should be used in combination with continuous observation of the snowpack and avalanche activity.</span></p>","language":"English","publisher":"Elsevier Science","publisherLocation":"New York, NY","doi":"10.1016/j.coldregions.2015.08.007","usgsCitation":"Marienthal, A., Hendrikx, J., Birkeland, K.W., and Irvine, K.M., 2015, Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers: Cold Regions Science and Technology, v. 120, p. 227-236, https://doi.org/10.1016/j.coldregions.2015.08.007.","startPage":"227","endPage":"236","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061005","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Bridger Bowl ski area","volume":"120","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a315cae4b006cb45558b0a","contributors":{"authors":[{"text":"Marienthal, Alex","contributorId":173365,"corporation":false,"usgs":false,"family":"Marienthal","given":"Alex","email":"","affiliations":[{"id":27212,"text":"Snow and Avalanche Laboratory, Montana State University, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":644408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrikx, Jordy 0000-0001-6194-3596","orcid":"https://orcid.org/0000-0001-6194-3596","contributorId":140954,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","email":"","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":644409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birkeland, Karl W.","contributorId":173366,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","middleInitial":"W.","affiliations":[{"id":27213,"text":"USDA Forest Service National Avalanche Center, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":644410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70160536,"text":"70160536 - 2015 - Changes in depth occupied by Great Lakes lake whitefish populations and the influence of survey design","interactions":[],"lastModifiedDate":"2017-08-15T12:51:21","indexId":"70160536","displayToPublicDate":"2015-12-01T01:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Changes in depth occupied by Great Lakes lake whitefish populations and the influence of survey design","docAbstract":"<p><span>Understanding fish habitat use is important in determining conditions that ultimately affect fish energetics, growth and reproduction. Great Lakes lake whitefish (</span><i>Coregonus clupeaformis</i><span>) have demonstrated dramatic changes in growth and life history traits since the appearance of dreissenid mussels in the Great Lakes, but the role of habitat occupancy in driving these changes is poorly understood. To better understand temporal changes in lake whitefish depth of capture (</span><i>D<sub>w</sub></i><span>), we compiled a database of fishery-independent surveys representing multiple populations across all five Laurentian Great Lakes. By demonstrating the importance of survey design in estimating&nbsp;</span><i>D<sub>w</sub></i><span>, we describe a novel method for detecting survey-based bias in&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;and removing potentially biased data. Using unbiased&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;estimates, we show clear differences in the pattern and timing of changes in lake whitefish&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;between our reference sites (Lake Superior) and those that have experienced significant benthic food web changes (lakes Michigan, Huron, Erie and Ontario). Lake whitefish&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;in Lake Superior tended to gradually shift to shallower waters, but changed rapidly in other locations coincident with dreissenid establishment and declines in&nbsp;</span><i>Diporeia</i><span>&nbsp;densities. Almost all lake whitefish populations that were exposed to dreissenids demonstrated deeper&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;following benthic food web change, though a subset of these populations subsequently shifted to more shallow depths. In some cases in lakes Huron and Ontario, shifts towards more shallow&nbsp;</span><i>D<sub>w</sub></i><span>&nbsp;are occurring well after documented&nbsp;</span><i>Diporeia</i><span>&nbsp;collapse, suggesting the role of other drivers such as habitat availability or reliance on alternative prey sources.</span></p>","language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor, MI","doi":"10.1016/j.jglr.2015.09.014","collaboration":"Lakehead University, IISD-Experimental Lakes Area, Michigan Department of Natural Resources, Ontario Ministry of Natural Resources and Forestry","usgsCitation":"Rennie, M.D., Weidel, B., Claramunt, R., and Dunlob, E.S., 2015, Changes in depth occupied by Great Lakes lake whitefish populations and the influence of survey design: Journal of Great Lakes Research, v. 41, no. 4, p. 1150-1161, https://doi.org/10.1016/j.jglr.2015.09.014.","productDescription":"12 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D.","contributorId":34007,"corporation":false,"usgs":true,"family":"Rennie","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":583078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claramunt, Randall M.","contributorId":19047,"corporation":false,"usgs":true,"family":"Claramunt","given":"Randall M.","affiliations":[],"preferred":false,"id":583079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunlob, Erin S.","contributorId":150805,"corporation":false,"usgs":false,"family":"Dunlob","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":583080,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70162143,"text":"70162143 - 2015 - Geologic cross sections and preliminary geologic map of the Questa Area, Taos County, New Mexico","interactions":[],"lastModifiedDate":"2017-04-24T14:12:34","indexId":"70162143","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"578","subseriesTitle":"New Mexico Bureau of Geology and Mineral Resources","title":"Geologic cross sections and preliminary geologic map of the Questa Area, Taos County, New Mexico","docAbstract":"<p>In 2011, the senior authors were contacted by Ron Gardiner of Questa, and Village of Questa Mayor Esther Garcia, to discuss the existing and future groundwater supply for the Village of Questa. This meeting led to the development of a plan in 2013 to perform an integrated geologic, geophysical, and hydrogeologic investigation of the Questa area by the New Mexico Bureau of Geology &amp; Mineral Resources (NMBG), the U.S. Geological Survey (USGS), and New Mexico Tech (NMT). </p><p>The NMBG was responsible for the geologic map and geologic cross sections. The USGS was responsible for a detailed geophysical model to be incorporated into the NMBG products. NMT was responsible for providing a graduate student to develop a geochemical and groundwater flow model. This report represents the final products of the geologic and geophysical investigations conducted by the NMBG and USGS. The USGS final products have been incorporated directly into the geologic cross sections. </p><p>The objective of the study was to characterize and interpret the shallow (to a depth of approximately 5,000 ft) three-dimensional geology and preliminary hydrogeology of the Questa area. The focus of this report is to compile existing geologic and geophysical data, integrate new geophysical data, and interpret these data to construct three, detailed geologic cross sections across the Questa area. These cross sections can be used by the Village of Questa to make decisions about municipal water-well development, and can be used in the future to help in the development of a conceptual model of groundwater flow for the Questa area. Attached to this report are a location map, a preliminary geologic map and unit descriptions, tables of water wells and springs used in the study, and three detailed hydrogeologic cross sections shown at two different vertical scales. The locations of the cross sections are shown on the index map of the cross section sheet.</p>","language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Bauer, P.W., Grauch, V.J., Johnson, P.S., Thompson, R.A., Drenth, B.J., and Kelson, K., 2015, Geologic cross sections and preliminary geologic map of the Questa Area, Taos County, New Mexico: Open-File Report 578, 16 p.","productDescription":"16 p.","ipdsId":"IP-069393","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0ea0e4b006455f2d61d2","contributors":{"authors":[{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":588672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":588673,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Peggy S.","contributorId":85689,"corporation":false,"usgs":true,"family":"Johnson","given":"Peggy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":588674,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":588671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":588675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelson, Keith I.","contributorId":75851,"corporation":false,"usgs":true,"family":"Kelson","given":"Keith I.","affiliations":[],"preferred":false,"id":588676,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70176704,"text":"70176704 - 2015 - Seismic hazard in the Intermountain West","interactions":[],"lastModifiedDate":"2016-10-03T16:29:05","indexId":"70176704","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Seismic hazard in the Intermountain West","docAbstract":"The 2014 national seismic-hazard model for the conterminous United States incorporates new scientific results and important model adjustments. The current model includes updates to the historical catalog, which is spatially smoothed using both fixed-length and adaptive-length smoothing kernels. Fault-source characterization improved by adding faults, revising rates of activity, and incorporating new results from combined inversions of geologic and geodetic data. The update also includes a new suite of published ground motion models. Changes in probabilistic ground motion are generally less than 10% in most of the Intermountain West compared to the prior assessment, and ground-motion hazard in four Intermountain West cities illustrates the range and magnitude of change in the region. Seismic hazard at reference sites in Boise and Reno increased as much as 10%, whereas hazard in Salt Lake City decreased 5–6%. The largest change was in Las Vegas, where hazard increased 32–35%.","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/103114EQS173M","usgsCitation":"Haller, K., Moschetti, M.P., Mueller, C., Rezaeian, S., Petersen, M.D., and Zeng, Y., 2015, Seismic hazard in the Intermountain West: Earthquake Spectra, v. 31, no. S1, p. S149-S176, https://doi.org/10.1193/103114EQS173M.","productDescription":"28 p.","startPage":"S149","endPage":"S176","ipdsId":"IP-069065","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":329245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"57f7ee24e4b0bc0bec09e8ab","contributors":{"authors":[{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":649946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":649947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":649948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":649949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":649950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":649951,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70161741,"text":"70161741 - 2015 - Fire effects on aquatic ecosystems: An assessment of the current state of the science","interactions":[],"lastModifiedDate":"2025-06-25T13:19:04.034953","indexId":"70161741","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fire effects on aquatic ecosystems: An assessment of the current state of the science","docAbstract":"<p><span>Fire is a prevalent feature of many landscapes and has numerous and complex effects on geological, hydrological, ecological, and economic systems. In some regions, the frequency and intensity of wildfire have increased in recent years and are projected to escalate with predicted climatic and landuse changes. In addition, prescribed burns continue to be used in many parts of the world to clear vegetation for development projects, encourage desired vegetation, and reduce fuel loads. Given the prevalence of fire on the landscape, authors of papers in this special series examine the complexities of fire as a disturbance shaping freshwater ecosystems and highlight the state of the science. These papers cover key aspects of fire effects that range from vegetation loss and recovery in watersheds to effects on hydrology and water quality with consequences for communities (from algae to fish), food webs, and ecosystem processes (e.g., organic matter subsidies, nutrient cycling) across a range of scales. The results presented in this special series of articles expand our knowledge of fire effects in different biomes, water bodies, and geographic regions, encompassing aquatic population, community, and ecosystem responses. In this overview, we summarize each paper and emphasize its contributions to knowledge on fire ecology and freshwater ecosystems. This overview concludes with a list of 7 research foci that are needed to further our knowledge of fire effects on aquatic ecosystems, including research on: 1) additional biomes and geographic regions; 2) additional habitats, including wetlands and lacustrine ecosystems; 3) different fire severities, sizes, and spatial configurations; and 4) additional response variables (e.g., ecosystem processes) 5) over long (&gt;5 y) time scales 6) with more rigorous study designs and data analyses, and 7) consideration of the effects of fire management practices and policies on aquatic ecosystems.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/684073","usgsCitation":"Bixby, R.J., Cooper, S., Gresswell, R.E., Brown, L.E., Dahm, C.N., and Dwire, K.A., 2015, Fire effects on aquatic ecosystems: An assessment of the current state of the science: Freshwater Science, v. 34, no. 4, p. 1340-1350, https://doi.org/10.1086/684073.","productDescription":"11 p.","startPage":"1340","endPage":"1350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068454","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471611,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5q9165nf","text":"External Repository"},{"id":381478,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568cf741e4b0e7a44bc0f156","contributors":{"authors":[{"text":"Bixby, Rebecca J.","contributorId":147389,"corporation":false,"usgs":false,"family":"Bixby","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":16834,"text":"Dept. of Biology and Museum of Southwestern Biology, Univ of NM","active":true,"usgs":false}],"preferred":false,"id":807071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooper, Scott D.","contributorId":152035,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott D.","affiliations":[{"id":18860,"text":"Department of Ecology, Evolution, and Marine Biology and Marine Science Institute      University of California","active":true,"usgs":false}],"preferred":false,"id":807072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":587615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Lee E.","contributorId":152036,"corporation":false,"usgs":false,"family":"Brown","given":"Lee","email":"","middleInitial":"E.","affiliations":[{"id":18861,"text":"School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":807073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Clifford N.","contributorId":152037,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford","email":"","middleInitial":"N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":587619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dwire, Kathleen A.","contributorId":225615,"corporation":false,"usgs":false,"family":"Dwire","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":41171,"text":"US Forest Service, Rocky Mountain Research Station, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":807075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70162632,"text":"70162632 - 2015 - High-resolution remote sensing of water quality in the San Francisco Bay-Delta Estuary","interactions":[],"lastModifiedDate":"2017-10-30T09:56:25","indexId":"70162632","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution remote sensing of water quality in the San Francisco Bay-Delta Estuary","docAbstract":"<p><span>The San Francisco Bay&ndash;Delta Estuary watershed is a major source of freshwater for California and a profoundly human-impacted environment. The water quality monitoring that is critical to the management of this important water resource and ecosystem relies primarily on a system of fixed water-quality monitoring stations, but the limited spatial coverage often hinders understanding. Here, we show how the latest technology in visible/near-infrared imaging spectroscopy can facilitate water quality monitoring in this highly dynamic and heterogeneous system by enabling simultaneous depictions of several water quality indicators at very high spatial resolution. The airborne portable remote imaging spectrometer (PRISM) was used to derive high-spatial-resolution (2.6 &times; 2.6 m) distributions of turbidity, and dissolved organic carbon (DOC) and chlorophyll-a concentrations in a wetland-influenced region of this estuary. A filter-passing methylmercury vs DOC relationship was also developed using in situ samples and enabled the high-spatial-resolution depiction of surface methylmercury concentrations in this area. The results illustrate how high-resolution imaging spectroscopy can inform management and policy development in important inland and estuarine water bodies by facilitating the detection of point- and nonpoint-source pollution, and by providing data to help assess the complex impacts of wetland restoration and climate change on water quality and ecosystem productivity.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5b03518","usgsCitation":"Fichot, C.G., Downing, B.D., Bergamaschi, B.A., Windham-Myers, L., Marvin-DiPasquale, M.C., Thompson, D., and Gierach, M.M., 2015, High-resolution remote sensing of water quality in the San Francisco Bay-Delta Estuary: Environmental Science & Technology, v. 50, no. 2, p. 573-583, https://doi.org/10.1021/acs.est.5b03518.","productDescription":"11 p.","startPage":"573","endPage":"583","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067066","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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,{"id":70160353,"text":"70160353 - 2015 - Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network","interactions":[],"lastModifiedDate":"2018-10-24T16:48:39","indexId":"70160353","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network","docAbstract":"<p>We present and describe strong-motion data observations from the 2015 M 7.8 Gorkha, Nepal, earthquake sequence collected using existing and new Quake-Catcher Network (QCN) and U.S. Geological Survey NetQuakes sensors located in the Kathmandu Valley. A comparison of QCN data with waveforms recorded by a conventional strong-motion (NetQuakes) instrument validates the QCN data. We present preliminary analysis of spectral accelerations, and peak ground acceleration and velocity for earthquakes up to M 7.3 from the QCN stations, as well as preliminary analysis of the mainshock recording from the NetQuakes station. We show that mainshock peak accelerations were lower than expected and conclude the Kathmandu Valley experienced a pervasively nonlinear response during the mainshock. Phase picks from the QCN and NetQuakes data are also used to improve aftershock locations. This study confirms the utility of QCN instruments to contribute to ground-motion investigations and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal&ndash;Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150146","usgsCitation":"Dixit, A., Ringler, A.T., Sumy, D.F., Cochran, E.S., Hough, S.E., Martin, S., Gibbons, S., Luetgert, J.H., Galetzka, J., Shrestha, S., Rajaure, S., and McNamara, D.E., 2015, Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network: Seismological Research Letters, v. 86, no. 6, p. 1533-1539, https://doi.org/10.1785/0220150146.","productDescription":"7 p.","startPage":"1533","endPage":"1539","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066938","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471599,"rank":0,"type":{"id":41,"text":"Open Access External 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,{"id":70173962,"text":"70173962 - 2015 - Geospatial resources for the geologic community: The USGS National Map","interactions":[],"lastModifiedDate":"2016-06-21T15:13:12","indexId":"70173962","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial resources for the geologic community: The USGS National Map","docAbstract":"<p><span>Geospatial data are a key component of investigating, interpreting, and communicating the geological sciences. Locating geospatial data can be time-consuming, which detracts from time spent on a study because these data are not obviously placed in central locations or are served from many disparate databases. The National Map of the US Geological Survey is a publicly available resource for accessing the geospatial base map data needs of the geological community from a central location. The National Map data are available through a viewer and download platform providing access to eight primary data themes, plus the US Topo and scanned historical topographic maps. The eight themes are elevation, orthoimagery, hydrography, geographic names, boundaries, transportation, structures, and land cover, and they are being offered for download as predefined tiles in formats supported by leading geographic information system software. Data tiles are periodically refreshed to capture the most current content and are an efficient method for disseminating and receiving geospatial information. Elevation data, for example, are offered as a download from the National Map as 1&deg; &times; 1&deg; tiles for the 10- and 30- m products and as 15&prime; &times; 15&prime; tiles for the higher-resolution 3-m product. Vector data sets with smaller file sizes are offered at several tile sizes and formats. Partial tiles are not a download option&mdash;any prestaged data that intersect the requesting bounding box will be, in their entirety, part of the download order. While there are many options for accessing geospatial data via the Web, the National Map represents authoritative sources of data that are documented and can be referenced for citation and inclusion in scientific publications. Therefore, National Map products and services should be part of a geologist&rsquo;s first stop for geospatial information and data.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/682008","usgsCitation":"Witt, E.C., 2015, Geospatial resources for the geologic community: The USGS National Map: Journal of Geology, v. 123, no. 3, p. 283-294, https://doi.org/10.1086/682008.","productDescription":"12 p.","startPage":"283","endPage":"294","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063473","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":324152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a653be4b07657d1a11daa","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":639787,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70160784,"text":"70160784 - 2015 - Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","interactions":[],"lastModifiedDate":"2015-12-31T13:03:13","indexId":"70160784","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends","docAbstract":"<p>Human impacts on wildlife populations are widespread and prolific and understanding wildlife responses to human impacts is a fundamental component of wildlife management. The first step to understanding wildlife responses is the documentation of changes in wildlife population parameters, such as population size. Meaningful assessment of population changes in potentially impacted sites requires the establishment of monitoring at similar, nonimpacted, control sites. However, it is often difficult to identify appropriate control sites in wildlife populations. We demonstrated use of Geographic Information System (GIS) data across large spatial scales to select biologically relevant control sites for population monitoring. Greater sage-grouse (Centrocercus urophasianus; hearafter, sage-grouse) are negatively affected by energy development, and monitoring of sage-grouse population within energy development areas is necessary to detect population-level responses. Weused population data (1995&ndash;2012) from an energy development area in Wyoming, USA, the Atlantic Rim Project Area (ARPA), and GIS data to identify control sites that were not impacted by energy development for population monitoring. Control sites were surrounded by similar habitat and were within similar climate areas to the ARPA. We developed nonlinear trend models for both the ARPA and control sites and compared long-term trends from the 2 areas. We found little difference between the ARPA and control sites trends over time. This research demonstrated an approach for control site selection across large landscapes and can be used as a template for similar impact-monitoring studies. It is important to note that identification of changes in population parameters between control and treatment sites is only the first step in understanding the mechanisms that underlie those changes. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.</p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.601","usgsCitation":"Fedy, B.C., O’Donnell, M.S., and Bowen, Z.H., 2015, Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends: Wildlife Society Bulletin, v. 39, no. 4, p. 700-712, https://doi.org/10.1002/wsb.601.","productDescription":"13 p.","startPage":"700","endPage":"712","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053414","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":499960,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1512b0d458ea4c8ab77bd670ee6a3220","text":"External Repository"},{"id":313148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"South-Central","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.226806640625,\n              42.99259451971113\n            ],\n            [\n              -109.21508789062499,\n              42.97250158602597\n            ],\n            [\n              -109.97863769531249,\n              43.11702412135048\n            ],\n            [\n              -110.841064453125,\n              43.56845179881218\n            ],\n            [\n              -110.841064453125,\n              43.28920196020127\n            ],\n            [\n              -110.9124755859375,\n              42.601619944327965\n            ],\n            [\n              -111.05529785156249,\n              42.589488572714245\n            ],\n            [\n              -111.03881835937499,\n              41.000629848685385\n            ],\n            [\n              -108.2208251953125,\n              41.01721057822846\n            ],\n            [\n              -108.1109619140625,\n              41.27367811566259\n            ],\n            [\n              -107.0562744140625,\n              41.611335399441735\n            ],\n            [\n              -106.3421630859375,\n              41.693424216151314\n            ],\n            [\n              -106.226806640625,\n              42.99259451971113\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-13","publicationStatus":"PW","scienceBaseUri":"56865fc8e4b0e7594ee74ccf","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":64080,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":583891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":583892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70164520,"text":"70164520 - 2015 - Interpretation of <i>S</i> waves generated by near-surface chemical explosions at SAFOD","interactions":[],"lastModifiedDate":"2016-02-09T12:57:30","indexId":"70164520","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Interpretation of <i>S</i> waves generated by near-surface chemical explosions at SAFOD","docAbstract":"<p><span>A series of near-surface chemical explosions conducted at the San Andreas Fault Observatory at Depth (SAFOD) were recorded by high-frequency downhole receiver arrays in separate experiments in November 2003 and May 2005. The 2003 experiment involved &sim;100&thinsp;&thinsp;kg shots detonated along a 46-km-long line (Hole&ndash;Ryberg line) centered on SAFOD and recorded by 32 three-component geophones in the pilot hole between 0.8 and 2.0&nbsp;km depth. The 2005 experiment involved &sim;36&thinsp;&thinsp;kg shots detonated at Parkfield Area Seismic Observatory (PASO) stations (at &sim;1&ndash;8&thinsp;&thinsp;km offset) recorded by 80 three-component geophones in the main hole between the surface and 2.4&nbsp;km depth. These data sample the downgoing seismic wavefield and constrain the shallow velocity and attenuation structure, as well as the first-order characteristics of the source. Using forward modeling on a velocity structure designed for the near field, both observed&nbsp;</span><i>P</i><span>- and&nbsp;</span><i>S</i><span>-wave energy for the PASO shots are identified with the travel times expected for direct and/or reflected phases. Larger-offset recordings from shots along the Hole&ndash;Ryberg line reveal substantial&nbsp;</span><i>SV</i><span>&nbsp;and&nbsp;</span><i>SH</i><span>&nbsp;energy, especially southwest of SAFOD from the source as indicated by&nbsp;</span><i>P</i><span>-to-</span><i>S</i><span>&nbsp;amplitude ratios. The generated&nbsp;</span><i>SV</i><span>&nbsp;energy is interpreted to arise chiefly from&nbsp;</span><i>P</i><span>-to-</span><i>S</i><span>&nbsp;conversions at subhorizontal discontinuities. This provides a simple mechanism for often-observed low&nbsp;</span><i>P</i><span>-to-</span><i>S</i><span>&nbsp;amplitude ratios from nuclear explosions in the far field, as originating from strong near-field wave conversions.</span></p>","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140242","usgsCitation":"Pollitz, F., Ellsworth, W.L., and Rubinstein, J.L., 2015, Interpretation of <i>S</i> waves generated by near-surface chemical explosions at SAFOD: Bulletin of the Seismological Society of America, v. 105, no. 6, p. 2835-2851, https://doi.org/10.1785/0120140242.","productDescription":"17 p.","startPage":"2835","endPage":"2851","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057606","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":316740,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-30","publicationStatus":"PW","scienceBaseUri":"56bb1bc5e4b08d617f654e1f","contributors":{"authors":[{"text":"Pollitz, Fred F. fpollitz@usgs.gov","contributorId":2408,"corporation":false,"usgs":true,"family":"Pollitz","given":"Fred F.","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":597718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, William L. ellsworth@usgs.gov","contributorId":787,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":597719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":597720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70168393,"text":"70168393 - 2015 - Quantifying the adaptive cycle","interactions":[],"lastModifiedDate":"2016-02-11T09:40:31","indexId":"70168393","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the adaptive cycle","docAbstract":"<p><span>The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994&ndash;2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0146053","usgsCitation":"Angeler, D., Allen, C.R., Garmestani, A.S., Gunderson, L.H., Hjerne, O., and Winder, M., 2015, Quantifying the adaptive cycle: PLoS ONE, v. 10, no. 12, e0146053: 17 p., https://doi.org/10.1371/journal.pone.0146053.","productDescription":"e0146053: 17 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071543","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471602,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0146053","text":"Publisher Index Page"},{"id":317931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Baltic Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              9.31640625,\n              53.69670647530323\n            ],\n            [\n              9.31640625,\n              66.17826596326798\n            ],\n            [\n              30.0146484375,\n              66.17826596326798\n            ],\n            [\n              30.0146484375,\n              53.69670647530323\n            ],\n            [\n              9.31640625,\n              53.69670647530323\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-30","publicationStatus":"PW","scienceBaseUri":"56bdbecae4b06458514aeede","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":619869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":619859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunderson, Lance H.","contributorId":12182,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":619871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hjerne, Olle","contributorId":166719,"corporation":false,"usgs":false,"family":"Hjerne","given":"Olle","email":"","affiliations":[],"preferred":false,"id":619872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Winder, Monika","contributorId":68178,"corporation":false,"usgs":true,"family":"Winder","given":"Monika","affiliations":[],"preferred":false,"id":619873,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70184227,"text":"70184227 - 2015 - Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2017-03-06T11:05:53","indexId":"70184227","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model","docAbstract":"<p><span>We present the updated seismic source characterization (SSC) for the 2014 update of the National Seismic Hazard Model (NSHM) for the conterminous United States. Construction of the seismic source models employs the methodology that was developed for the 1996 NSHM but includes new and updated data, data types, source models, and source parameters that reflect the current state of knowledge of earthquake occurrence and state of practice for seismic hazard analyses. We review the SSC parameterization and describe the methods used to estimate earthquake rates, magnitudes, locations, and geometries for all seismic source models, with an emphasis on new source model components. We highlight the effects that two new model components—incorporation of slip rates from combined geodetic-geologic inversions and the incorporation of adaptively smoothed seismicity models—have on probabilistic ground motions, because these sources span multiple regions of the conterminous United States and provide important additional epistemic uncertainty for the 2014 NSHM.</span></p>","language":"English","publisher":"EERI","doi":"10.1193/110514EQS183M","usgsCitation":"Moschetti, M.P., Powers, P.M., Petersen, M.D., Boyd, O.S., Chen, R., Field, E.H., Frankel, A.D., Haller, K., Harmsen, S., Mueller, C.S., Wheeler, R., and Zeng, Y., 2015, Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model: Earthquake Spectra, v. 31, no. S1, p. S31-S57, https://doi.org/10.1193/110514EQS183M.","productDescription":"27 p.","startPage":"S31","endPage":"S57","ipdsId":"IP-066842","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1193/110514eqs183m","text":"Publisher Index Page"},{"id":336861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833de4b014cc3a3a99f9","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Rui","contributorId":187504,"corporation":false,"usgs":false,"family":"Chen","given":"Rui","email":"","affiliations":[],"preferred":false,"id":680639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680642,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harmsen, Stephen harmsen@usgs.gov","contributorId":152128,"corporation":false,"usgs":true,"family":"Harmsen","given":"Stephen","email":"harmsen@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680643,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mueller, Charles S. 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":955,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":680780,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wheeler, Russell wheeler@usgs.gov","contributorId":175474,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680644,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zeng, Yuehua 0000-0003-1161-1264 zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680645,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70187255,"text":"70187255 - 2015 - Annual survival rate estimate of satellite transmitter–marked eastern population greater sandhill cranes","interactions":[],"lastModifiedDate":"2017-04-28T11:42:48","indexId":"70187255","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Annual survival rate estimate of satellite transmitter–marked eastern population greater sandhill cranes","docAbstract":"<p><span>Several surveys have documented the increasing population size and geographic distribution of Eastern Population greater sandhill cranes </span><i>Grus canadensis tabida</i><span> since the 1960s. Sport hunting of this population of sandhill cranes started in 2012 following the provisions of the Eastern Population Sandhill Crane Management Plan. However, there are currently no published estimates of Eastern Population sandhill crane survival rate that can be used to inform harvest management. As part of two studies of Eastern Population sandhill crane migration, we deployed solar-powered global positioning system platform transmitting terminals on Eastern Population sandhill cranes (</span><i>n</i><span>  =  42) at key concentration areas from 2009 to 2012. We estimated an annual survival rate for Eastern Population sandhill cranes from data resulting from monitoring these cranes by using the known-fates model in the MARK program. Estimated annual survival rate for adult Eastern Population sandhill cranes was 0.950 (95% confidence interval  =  0.885–0.979) during December 2009–August 2014. All fatalities (</span><i>n</i><span>  =  5) occurred after spring migration in late spring and early summer. We were unable to determine cause of death for crane fatalities in our study. Our survival rate estimate will be useful when combined with other population parameters such as the population index derived from the U.S. Fish and Wildlife Service fall survey, harvest, and recruitment rates to assess the effects of harvest on population size and trend and evaluate the effectiveness of management strategies.</span></p>","language":"English","publisher":"Scientific Journals","doi":"10.3996/042015-JFWM-035","usgsCitation":"Fronczak, D.L., Andersen, D., Hanna, E.E., and Cooper, T.R., 2015, Annual survival rate estimate of satellite transmitter–marked eastern population greater sandhill cranes: Journal of Fish and Wildlife Management, v. 6, no. 2, p. 464-471, https://doi.org/10.3996/042015-JFWM-035.","productDescription":"8 p.","startPage":"464","endPage":"471","ipdsId":"IP-064500","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/042015-jfwm-035","text":"Publisher Index Page"},{"id":340606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-01","publicationStatus":"PW","scienceBaseUri":"590454a6e4b022cee40dc248","contributors":{"authors":[{"text":"Fronczak, David L.","contributorId":191560,"corporation":false,"usgs":false,"family":"Fronczak","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanna, Everett E.","contributorId":191561,"corporation":false,"usgs":false,"family":"Hanna","given":"Everett","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Thomas R.","contributorId":191468,"corporation":false,"usgs":false,"family":"Cooper","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":693472,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70191099,"text":"70191099 - 2015 - Combining NLCD and MODIS to create a land cover-albedo database for the continental United States","interactions":[],"lastModifiedDate":"2017-09-26T14:06:20","indexId":"70191099","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Combining NLCD and MODIS to create a land cover-albedo database for the continental United States","docAbstract":"<p><span>Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14&nbsp;years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500&nbsp;m&nbsp;×&nbsp;500&nbsp;m) from the NLCD product (30&nbsp;m&nbsp;×&nbsp;30&nbsp;m), and provides an albedo data record per 500&nbsp;m&nbsp;×&nbsp;500&nbsp;m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥&nbsp;50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2015.09.012","usgsCitation":"Wickham, J., Barnes, C., Nash, M., and Wade, T., 2015, Combining NLCD and MODIS to create a land cover-albedo database for the continental United States: Remote Sensing of Environment, v. 170, p. 143-152, https://doi.org/10.1016/j.rse.2015.09.012.","productDescription":"10 p.","startPage":"143","endPage":"152","ipdsId":"IP-069951","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":346099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6734e4b017cf3141c6a7","contributors":{"authors":[{"text":"Wickham, J.","contributorId":102230,"corporation":false,"usgs":true,"family":"Wickham","given":"J.","email":"","affiliations":[],"preferred":false,"id":711200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Christopher A. 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":178108,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher A.","email":"christopher.barnes.ctr@usgs.gov","affiliations":[],"preferred":false,"id":711201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nash, M.S.","contributorId":43946,"corporation":false,"usgs":true,"family":"Nash","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":711202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wade, T.G.","contributorId":74113,"corporation":false,"usgs":true,"family":"Wade","given":"T.G.","email":"","affiliations":[],"preferred":false,"id":711203,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70187762,"text":"70187762 - 2015 - Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products","interactions":[],"lastModifiedDate":"2017-05-17T11:19:03","indexId":"70187762","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products","docAbstract":"<p><span>There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-14-0230.1","usgsCitation":"Ji, L., Senay, G.B., and Verdin, J.P., 2015, Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products: Journal of Hydrometeorology, v. 16, p. 2463-2480, https://doi.org/10.1175/JHM-D-14-0230.1.","productDescription":"18 p.","startPage":"2463","endPage":"2480","ipdsId":"IP-060871","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0230.1","text":"Publisher Index Page"},{"id":341434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"publicationDate":"2015-11-17","publicationStatus":"PW","scienceBaseUri":"593e26a5e4b0764e6c61b754","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":695524,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184232,"text":"70184232 - 2015 - Hydrologic implications of GRACE satellite data in the Colorado River Basin","interactions":[],"lastModifiedDate":"2018-01-30T18:44:55","indexId":"70184232","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic implications of GRACE satellite data in the Colorado River Basin","docAbstract":"<p><span>Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km</span><sup>3</sup><span> during 1986–1990 and by 102 km</span><sup>3</sup><span> during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km</span><sup>3</sup><span>) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018090","usgsCitation":"Scanlon, B., Zhang, Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., and Winester, D., 2015, Hydrologic implications of GRACE satellite data in the Colorado River Basin: Water Resources Research, v. 51, no. 12, p. 9891-9903, https://doi.org/10.1002/2015WR018090.","productDescription":"13 p.","startPage":"9891","endPage":"9903","ipdsId":"IP-070650","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018090","text":"Publisher Index Page"},{"id":336855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Colorado River Basin","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-24","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f3","contributors":{"authors":[{"text":"Scanlon, Bridget R.","contributorId":74093,"corporation":false,"usgs":true,"family":"Scanlon","given":"Bridget R.","affiliations":[],"preferred":false,"id":680670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zizhan","contributorId":187508,"corporation":false,"usgs":false,"family":"Zhang","given":"Zizhan","email":"","affiliations":[],"preferred":false,"id":680671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reedy, Robert C.","contributorId":187509,"corporation":false,"usgs":false,"family":"Reedy","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":680672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":680673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":680674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Jianli","contributorId":187512,"corporation":false,"usgs":false,"family":"Chen","given":"Jianli","email":"","affiliations":[],"preferred":false,"id":680675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":680676,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conway, Brian D.","contributorId":187513,"corporation":false,"usgs":false,"family":"Conway","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680677,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Winester, Daniel","contributorId":187514,"corporation":false,"usgs":false,"family":"Winester","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":680678,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70182765,"text":"70182765 - 2015 - Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD","interactions":[],"lastModifiedDate":"2017-02-28T12:59:39","indexId":"70182765","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD","docAbstract":"The San Andreas Fault Observatory at Depth (SAFOD) scientific drillhole near Parkfield, California crosses the San Andreas Fault at a depth of 2.7 km.  Downhole measurements and analysis of core retrieved from Phase 3 drilling reveal two narrow, actively deforming zones of smectite-clay gouge within a roughly 200 m-wide fault damage zone of sandstones, siltstones and mudstones.  Here we report electrical resistivity and permeability measurements on core samples from all of these structural units at effective confining pressures up to 120 MPa.  Electrical resistivity (~10 ohm-m) and permeability (10-21 to 10-22 m2) in the actively deforming zones were one to two orders of magnitude lower than the surrounding damage zone material, consistent with broader-scale observations from the downhole resistivity and seismic velocity logs.  The higher porosity of the clay gouge, 2 to 8 times greater than that in the damage zone rocks, along with surface conduction were the principal factors contributing to the observed low resistivities.  The high percentage of fine-grained clay in the deforming zones also greatly reduced permeability to values low enough to create a barrier to fluid flow across the fault.  Together, resistivity and permeability data can be used to assess the hydrogeologic characteristics of the fault, key to understanding fault structure and strength. The low resistivities and strength measurements of the SAFOD core are consistent with observations of low resistivity clays that are often found in the principal slip zones of other active faults making resistivity logs a valuable tool for identifying these zones.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012214","usgsCitation":"Morrow, C.A., Lockner, D.A., and Hickman, S.H., 2015, Low resistivity and permeability in actively deforming shear zones on the San Andreas Fault at SAFOD: Journal of Geophysical Research, v. 120, no. 12, p. 8240-8258, https://doi.org/10.1002/2015JB012214.","productDescription":"18 p. ","startPage":"8240","endPage":"8258","ipdsId":"IP-063635","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012214","text":"Publisher Index Page"},{"id":336346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"58b69a42e4b01ccd54ff3faa","contributors":{"authors":[{"text":"Morrow, Carolyn A. 0000-0003-3500-6181 cmorrow@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-6181","contributorId":3206,"corporation":false,"usgs":true,"family":"Morrow","given":"Carolyn","email":"cmorrow@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":673675,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184229,"text":"70184229 - 2015 - The 2014 United States National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2017-03-06T10:59:13","indexId":"70184229","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2014 United States National Seismic Hazard Model","docAbstract":"<p><span>New seismic hazard maps have been developed for the conterminous United States using the latest data, models, and methods available for assessing earthquake hazard. The hazard models incorporate new information on earthquake rupture behavior observed in recent earthquakes; fault studies that use both geologic and geodetic strain rate data; earthquake catalogs through 2012 that include new assessments of locations and magnitudes; earthquake adaptive smoothing models that more fully account for the spatial clustering of earthquakes; and 22 ground motion models, some of which consider more than double the shaking data applied previously. Alternative input models account for larger earthquakes, more complicated ruptures, and more varied ground shaking estimates than assumed in earlier models. The ground motions, for levels applied in building codes, differ from the previous version by less than ±10% over 60% of the country, but can differ by ±50% in localized areas. The models are incorporated in insurance rates, risk assessments, and as input into the U.S. building code provisions for earthquake ground shaking.</span></p>","language":"English","publisher":"EERI","doi":"10.1193/120814EQS210M","usgsCitation":"Petersen, M.D., Moschetti, M.P., Powers, P.M., Mueller, C., Haller, K., Frankel, A.D., Zeng, Y., Rezaeian, S., Harmsen, S., Boyd, O.S., Field, E., Chen, R., Rukstales, K.S., Luco, N., Wheeler, R., Williams, R., and Olsen, A.H., 2015, The 2014 United States National Seismic Hazard Model: Earthquake Spectra, v. 31, no. S!, p. S1-S30, https://doi.org/10.1193/120814EQS210M.","productDescription":"30 p.","startPage":"S1","endPage":"S30","ipdsId":"IP-066439","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":336857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S!","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f7","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science 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Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680659,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":680660,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chen, Rui","contributorId":187504,"corporation":false,"usgs":false,"family":"Chen","given":"Rui","email":"","affiliations":[],"preferred":false,"id":680661,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680662,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"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":680663,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wheeler, Russell wheeler@usgs.gov","contributorId":175474,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680664,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Williams, Robert 0000-0002-2973-8493 rawilliams@usgs.gov","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":140741,"corporation":false,"usgs":true,"family":"Williams","given":"Robert","email":"rawilliams@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680665,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Olsen, Anna H. aolsen@usgs.gov","contributorId":4703,"corporation":false,"usgs":true,"family":"Olsen","given":"Anna","email":"aolsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science 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,{"id":70160354,"text":"70160354 - 2015 - Tidal marsh susceptibility to sea-level rise: importance of local-scale models","interactions":[],"lastModifiedDate":"2017-07-19T15:43:12","indexId":"70160354","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Tidal marsh susceptibility to sea-level rise: importance of local-scale models","docAbstract":"<p>Increasing concern over sea-level rise impacts to coastal tidal marsh ecosystems has led to modeling efforts to anticipate outcomes for resource management decision making. Few studies on the Pacific coast of North America have modeled sea-level rise marsh susceptibility at a scale relevant to local wildlife populations and plant communities. Here, we use a novel approach in developing an empirical sea-level rise ecological response model that can be applied to key management questions. Calculated elevation change over 13 y for a 324-ha portion of San Pablo Bay National Wildlife Refuge, California, USA, was used to represent local accretion and subsidence processes. Next, we coupled detailed plant community and elevation surveys with measured rates of inundation frequency to model marsh state changes to 2100. By grouping plant communities into low, mid, and high marsh habitats, we were able to assess wildlife species vulnerability and to better understand outcomes for habitat resiliency. Starting study-site conditions were comprised of 78% (253-ha) high marsh, 7% (30-ha) mid marsh, and 4% (18-ha) low marsh habitats, dominated by pickleweed <i>Sarcocornia pacifica</i> and cordgrass <i>Spartina</i> spp. Only under the low sea-level rise scenario (44 cm by 2100) did our models show persistence of some marsh habitats to 2100, with the area dominated by low marsh habitats. Under mid (93 cm by 2100) and high sea-level rise scenarios (166 cm by 2100), most mid and high marsh habitat was lost by 2070, with only 15% (65 ha) remaining, and a complete loss of these habitats by 2080. Low marsh habitat increased temporarily under all three sea-level rise scenarios, with the peak (286 ha) in 2070, adding habitat for the endemic endangered California Ridgway&rsquo;s rail <i>Rallus obsoletus obsoletus</i>. Under mid and high sea-level rise scenarios, an almost complete conversion to mudflat occurred, with most of the area below mean sea level. Our modeling assumed no marsh migration upslope due to human levee and infrastructure preventing these types of processes. Other modeling efforts done for this area have projected marsh persistence to 2100, but our modeling effort with site-specific datasets allowed us to model at a finer resolution with much higher local confidence, resulting in different results for management. Our results suggest that projected sea-level rise will have significant impacts on marsh plant communities and obligate wildlife, including those already under federal and state protection. Comprehensive modeling as done here improves the potential to implement adaptive management strategies and prevent marsh habitat and wildlife loss in the future.</p>","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington D.C.","doi":"10.3996/062014-JFWM-048","usgsCitation":"Thorne, K.M., Buffington, K., Elliott-Fisk, D., and Takekawa, J.Y., 2015, Tidal marsh susceptibility to sea-level rise: importance of local-scale models: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 290-304, https://doi.org/10.3996/062014-JFWM-048.","productDescription":"15 p.","startPage":"290","endPage":"304","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063637","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/062014-jfwm-048","text":"Publisher Index 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kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":582732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott-Fisk, Deborah L.","contributorId":46859,"corporation":false,"usgs":true,"family":"Elliott-Fisk","given":"Deborah L.","affiliations":[],"preferred":false,"id":582733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research 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,{"id":70159597,"text":"70159597 - 2015 - Estimating the risks for adverse effects of total phosphorus in receiving streams with the Stochastic Empirical Loading and Dilution Model (SELDM)","interactions":[],"lastModifiedDate":"2019-02-21T15:33:24","indexId":"70159597","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating the risks for adverse effects of total phosphorus in receiving streams with the Stochastic Empirical Loading and Dilution Model (SELDM)","docAbstract":"<p>Studies from North Carolina (NC) indicate that increasing concentrations of total phosphorus (TP) and other constituents are correlated to adverse effects on stream ecosystems as evidenced by differences in benthic macroinvertebrate populations in streams across the state. As a result, stringent in-stream criteria based on the Water Quality Assessed by Benthic macroinvertebrate health ratings (WQABI) have been proposed for regulating TP concentrations in stormwater discharges and for selecting stormwater best management practices (BMPs). The WQABI criteria concentrations may not be suitable for evaluating stormwater discharges because they are based on baseflow concentration statistics, the criteria do not include a clearly defined allowable exceedance frequency, and there are substantial uncertainties in estimating the quality of runoff, BMP discharge, and receiving waters for sites without monitoring data.</p>\n<p>The Stochastic Empirical Loading and Dilution Model (SELDM), which was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration, was used to simulate the quality of runoff, BMP discharge, and receiving waters to evaluate risks for water-quality exceedances with different criteria concentrations, allowable exceedance frequencies, and selected water-quality statistics. Water-quality data from two neighboring basins in the Piedmont ecoregion in NC were used to simulate in-stream stormwater quality. Data collected at 15 sites in NC were used to simulate runoff quality. Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by BMPs, were used to simulate potential effect of these treatments on discharge quality and downstream stormwater quality. Results of these long-term 30-year simulations were used to evaluate criteria concentrations, the potential frequency of water-quality exceedances, and the effect of data selection on risks for water-quality exceedances.</p>\n<p>The simulations indicate that the potential frequency for exceeding instream and stormwater discharge criteria depend on the detailed definition of the criteria and the data that are selected for simulating water quality. Data and simulation results indicate that the baseflow concentrations do not represent stormwater concentrations, even in predominantly forested basins. There is substantial uncertainty in applying stormwater statistics to unmonitored sites, even if these statistics are applied to neighboring basins such as in this example. Over a period of several years (or more) it would be impossible to meet many of the proposed instream and stormwater discharge quality criteria unless these criteria include an allowable exceedance frequency because stormwater concentrations commonly vary by orders of magnitude. Selection of BMPs by using concentration reduction as the sole criteria may underestimate potential benefits of BMPs that also provide volume reduction, which reduces discharge loads, and hydrograph extension, which increases the dilution of runoff into a larger proportion of the upstream stormflow.</p>\n<p>Results of this study indicate the potential benefits of the multi-decade simulations that SELDM provides because these simulations quantify risks and uncertainties that affect decisions made with available data and statistics. Results of the SELDM simulations indicate that the WQABI criteria concentrations may be too stringent for evaluating the stormwater quality in receiving streams, highway runoff, and BMP discharges; especially with the substantial uncertainties inherent in selecting representative data.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2015 International Conference on Ecology and Transportation (ICOET 2015)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2015 International conference on ecology and transportation","conferenceDate":"September 20, 2015","conferenceLocation":"Raleigh, NC","language":"English","publisher":"Center for Transportation and the Environment","usgsCitation":"Granato, G.E., and Jones, S.C., 2015, Estimating the risks for adverse effects of total phosphorus in receiving streams with the Stochastic Empirical Loading and Dilution Model (SELDM), <i>in</i> Proceedings of the 2015 International Conference on Ecology and Transportation (ICOET 2015), Raleigh, NC, September 20, 2015, p. 1-19.","productDescription":"19 p.","startPage":"1","endPage":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065909","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":311831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566175cae4b06a3ea36c56a5","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":147346,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":false,"id":579637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":579638,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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