{"pageNumber":"509","pageRowStart":"12700","pageSize":"25","recordCount":40778,"records":[{"id":70159856,"text":"70159856 - 2016 - Annual variation in recruitment of freshwater mussels and its relationship with river discharge","interactions":[],"lastModifiedDate":"2016-08-12T11:02:18","indexId":"70159856","displayToPublicDate":"2015-12-01T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Annual variation in recruitment of freshwater mussels and its relationship with river discharge","docAbstract":"
    \n
  1. Vital rates such as mortality, growth, and recruitment are important tools to evaluate the status of threatened populations and identify their vulnerabilities, leading to enhanced conservation strategies.
    2. \n
  2. Native freshwater mussels are a guild of largely sedentary, filter-feeding bivalves currently facing worldwide declines. Lack of recruitment has been identified as a major threat to mussel populations.
    3. \n
  3. A mussel bed in the Upper Mississippi River was sampled for 5 years (2008–2012). A trend analysis showed a significant decline in the percentage of species with juvenile representatives.
    4. \n
  4. Species were grouped into equilibrium and periodic life history strategies to assess past recruitment. Residuals from catch-curve regressions quantified past year-class strength of both strategists and Amblema plicata over a 13-year period (1994–2006), and identified strong and weak year-classes.
    5. \n
  5. Generalized linear regression models containing July maximum discharge and April minimum discharge explained 64% of the variation in recruitment strength of A. plicata. The best model for the equilibrium strategists explained 86% of the variation in recruitment and contained the same variables as A. plicata, but also incorporated the 7-day minimum discharge. For the periodic strategists, the model containing the number of low-flow pulses and the mean duration of high-flow pulses explained 56% of the variation in recruitment strength.
    6. \n
  6. Understanding variation in recruitment dynamics of native mussels and its relationship to river discharge will be useful in designing effective management strategies to enhance conservation of this imperilled fauna.
    7. \n
","language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1002/aqc.2590","usgsCitation":"Ries, P.R., Newton, T., Haro, R.J., Zigler, S.J., and Davis, M., 2016, Annual variation in recruitment of freshwater mussels and its relationship with river discharge: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 26, no. 4, p. 703-714, https://doi.org/10.1002/aqc.2590.","productDescription":"12 p.","startPage":"703","endPage":"714","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-057339","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":311759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Mississippi River, West Newton Chute","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.93050384521483,\n 44.26241249401097\n ],\n [\n -91.93050384521483,\n 44.28748597164118\n ],\n [\n -91.89170837402342,\n 44.28748597164118\n ],\n [\n -91.89170837402342,\n 44.26241249401097\n ],\n [\n -91.93050384521483,\n 44.26241249401097\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-11","publicationStatus":"PW","scienceBaseUri":"565ec4aee4b071e7ea544405","contributors":{"authors":[{"text":"Ries, Patricia R. pries@usgs.gov","contributorId":5954,"corporation":false,"usgs":true,"family":"Ries","given":"Patricia","email":"pries@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":580690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newton, Teresa 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":150098,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":580689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":580691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zigler, Steven J. 0000-0002-4153-0652 szigler@usgs.gov","orcid":"https://orcid.org/0000-0002-4153-0652","contributorId":2410,"corporation":false,"usgs":true,"family":"Zigler","given":"Steven","email":"szigler@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":580692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Mike","contributorId":150099,"corporation":false,"usgs":false,"family":"Davis","given":"Mike","email":"","affiliations":[{"id":17913,"text":"River Studies Center, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":580693,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170134,"text":"70170134 - 2016 - Brook trout passage performance through culverts","interactions":[],"lastModifiedDate":"2016-04-08T09:09:39","indexId":"70170134","displayToPublicDate":"2015-12-01T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Brook trout passage performance through culverts","docAbstract":"

Culverts can restrict access to habitat for stream-dwelling fishes. We used passive integrated transponder telemetry to quantify passage performance of >1000 wild brook trout (Salvelinus fontinalis) attempting to pass 13 culverts in Quebec under a range of hydraulic and environmental conditions. Several variables influenced passage success, including complex interactions between physiology and behavior, hydraulics, and structural characteristics. The probability of successful passage was greater through corrugated metal culverts than through smooth ones, particularly among smaller fish. Trout were also more likely to pass at warmer temperatures, but this effect diminished above 15 °C. Passage was impeded at higher flows, through culverts with steep slopes, and those with deep downstream pools. This study provides insight on factors influencing brook trout capacity to pass culverts as well as a model to estimate passage success under various conditions, with an improved resolution and accuracy over existing approaches. It also presents methods that could be used to investigate passage success of other species, with implications for connectivity of the riverscape.

","language":"English","publisher":"National Research Council Canada","publisherLocation":"Ottawa","doi":"10.1139/cjfas-2015-0089","collaboration":"Institut National de la Recherche Scientifique (Quebec, Canada)","usgsCitation":"Goerig, E., Castro-Santos, T.R., and Bergeron, N., 2016, Brook trout passage performance through culverts: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 1, p. 94-104, https://doi.org/10.1139/cjfas-2015-0089.","productDescription":"11 p.","startPage":"94","endPage":"104","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066023","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":471418,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0089","text":"External Repository"},{"id":319896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572485c1e4b0b13d39159359","contributors":{"authors":[{"text":"Goerig, Elsa","contributorId":168522,"corporation":false,"usgs":false,"family":"Goerig","given":"Elsa","email":"","affiliations":[{"id":25321,"text":"Institut National de la Recherche Scientifique","active":true,"usgs":false}],"preferred":false,"id":626256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":626255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergeron, Normand","contributorId":168523,"corporation":false,"usgs":false,"family":"Bergeron","given":"Normand","affiliations":[{"id":25321,"text":"Institut National de la Recherche Scientifique","active":true,"usgs":false}],"preferred":false,"id":626257,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193343,"text":"70193343 - 2016 - Groundwater science relevant to the Great Lakes Water Quality Agreement: A status report","interactions":[],"lastModifiedDate":"2017-12-21T10:23:12","indexId":"70193343","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Groundwater science relevant to the Great Lakes Water Quality Agreement: A status report","docAbstract":"

When the Great Lakes Water Quality Agreement (GLWQA) was signed in 1972 by the Governments of Canada and the United States (the “Parties”) (Environment Canada, 2013a), groundwater was not recognized as important to the water quality of the Lakes. At that time, groundwater and surface water were still considered as two separate systems, with almost no appreciation for their interaction. When the GLWQA was revised in 1978 (US Environmental Protection Agency (USEPA), 2012), groundwater contamination, such as that reported at legacy industrial sites such as those at Love Canal near the Niagara River, was squarely in the news. Consequently, the potential impacts of contaminated groundwater from such sites on Great Lakes water quality became a concern (Beck, 1979), and Annex 16 was added to the agreement, to address “pollution from contaminated groundwater” (Francis, 1989). However, no formal process for reporting under this annex was provided.

The GLWQA Protocol in 1987 modified Annex 16 and called for progress reports beginning in 1988 (USEPA, 1988). The Protocol in 2012 provided a new Annex 8 to address groundwater more holistically (Environment 2 Canada, 2013b). Annex 8 (Environment Canada, 2013b) commits the Parties to coordinate groundwater science and management actions; as a first step, to “publish a report on the relevant and available groundwater science” by February 2015 (this report); and to “identify priorities for science activities and actions for groundwater management, protection, and remediation…” The broader mandate of Annex 8 is to (1) “identify groundwater impacts on the chemical, physical and biological integrity of the Waters of the Great Lakes;” (2) “analyze contaminants, including nutrients in groundwater, derived from both point and non-point sources impacting the Waters of the Great Lakes;” (3) “assess information gaps and science needs related to groundwater to protect the quality of the Waters of the Great Lakes;” and (4) “analyze other factors, such as climate change, that individually or cumulatively affect groundwater’s impact on the quality of the Waters of the Great Lakes.” A binational Annex 8 Subcommittee was formed to lead efforts to fulfill the mandate of this annex (members listed on p. i of this report). In turn, this subcommittee has recruited a task team to prepare this report (listed as authors of each chapter). This report addresses all of the above four objectives, based on a compilation of the “relevant and available groundwater science.” Specifically, the second objective (to “analyze contaminants”) is addressed by incorporating information obtained in ongoing monitoring and research activities conducted by the Parties, and by various other members of the Great Lakes Executive Committee.

","language":"English","publisher":" Environment and Climate Change Canada and U.S. Environmental Protection Agency","usgsCitation":"2016, Groundwater science relevant to the Great Lakes Water Quality Agreement: A status report, vi, 100 p.","productDescription":"vi, 100 p.","ipdsId":"IP-066382","costCenters":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":350155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350154,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://binational.net/2016/06/13/groundwater-science-f/"}],"country":"Canada, United States","state":"Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Ontario, Pennsylvania, Wisconsin","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.59716796875,\n 45.413876460821086\n ],\n [\n -77.67333984375,\n 46.6795944656402\n ],\n [\n -80.5517578125,\n 47.025206001585396\n ],\n [\n -83.51806640624999,\n 47.931066347509784\n ],\n [\n -85.78125,\n 49.35375571830993\n ],\n [\n -87.4072265625,\n 49.439556958940855\n ],\n [\n -88.3740234375,\n 49.439556958940855\n ],\n [\n -90.41748046874999,\n 49.167338606291075\n ],\n [\n -92.5048828125,\n 47.502358951968574\n ],\n [\n -92.70263671874999,\n 46.392411189814645\n ],\n [\n -91.318359375,\n 46.40756396630067\n ],\n [\n -89.69238281249999,\n 45.398449976304086\n ],\n [\n -89.07714843749999,\n 43.77109381775651\n ],\n [\n -88.43994140625,\n 42.87596410238256\n ],\n [\n -87.73681640625,\n 41.409775832009565\n ],\n [\n -86.7919921875,\n 41.541477666790286\n ],\n [\n -85.80322265625,\n 41.75492216766298\n ],\n [\n -84.00146484374999,\n 41.376808565702355\n ],\n [\n -82.59521484375,\n 41.04621681452063\n ],\n [\n -80.61767578124999,\n 41.393294288784865\n ],\n [\n -79.25537109375,\n 42.114523952464246\n ],\n [\n -78.0029296875,\n 42.601619944327965\n ],\n [\n -76.04736328125,\n 43.004647127794435\n ],\n [\n -74.619140625,\n 43.929549935614595\n ],\n [\n -73.71826171874999,\n 44.512176171071054\n ],\n [\n -74.59716796875,\n 45.413876460821086\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fda4e4b06e28e9c25293","contributors":{"editors":[{"text":"Grannemann, Norman G. nggranne@usgs.gov","contributorId":4823,"corporation":false,"usgs":true,"family":"Grannemann","given":"Norman","email":"nggranne@usgs.gov","middleInitial":"G.","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":725312,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Van Stempvoort, Dale","contributorId":199351,"corporation":false,"usgs":false,"family":"Van Stempvoort","given":"Dale","email":"","affiliations":[],"preferred":false,"id":725313,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":70159748,"text":"70159748 - 2016 - Unusually large tsunamis frequent a currently creeping part of the Aleutian megathrust","interactions":[],"lastModifiedDate":"2016-02-01T13:26:02","indexId":"70159748","displayToPublicDate":"2015-11-30T01:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Unusually large tsunamis frequent a currently creeping part of the Aleutian megathrust","docAbstract":"

Current models used to assess earthquake and tsunami hazards are inadequate where creep dominates a subduction megathrust. Here we report geological evidence for large tsunamis, occurring on average every 300–340 years, near the source areas of the 1946 and 1957 Aleutian tsunamis. These areas bookend a postulated seismic gap over 200 km long where modern geodetic measurements indicate that the megathrust is currently creeping. At Sedanka Island, evidence for large tsunamis includes six sand sheets that blanket a lowland facing the Pacific Ocean, rise to 15 m above mean sea level, contain marine diatoms, cap terraces, adjoin evidence for scour, and date from the past 1700 years. The youngest sheet, and modern drift logs found as far as 800 m inland and >18 m elevation, likely record the 1957 tsunami. Modern creep on the megathrust coexists with previously unrecognized tsunami sources along this part of the Aleutian Subduction Zone.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL066083","usgsCitation":"Witter, R., Carver, G.A., Briggs, R.W., Gelfenbaum, G.R., Koehler, R., La Selle, S., Bender, A.M., Engelhart, S., Hemphill-Haley, E., and Hill, T.D., 2016, Unusually large tsunamis frequent a currently creeping part of the Aleutian megathrust: Geophysical Research Letters, v. 43, no. 1, p. 76-84, https://doi.org/10.1002/2015GL066083.","productDescription":"9 p.","startPage":"76","endPage":"84","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064550","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":471420,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://durham-repository.worktribe.com/output/1285504","text":"Publisher Index Page"},{"id":311726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.67578125,\n 58.44773280389084\n ],\n [\n -170.15625,\n 54.213861000644926\n ],\n [\n -174.55078125,\n 53.38332836757156\n ],\n [\n -178.41796874999997,\n 53.12040528310657\n ],\n [\n -181.93359375,\n 53.12040528310657\n ],\n [\n -185.44921875,\n 52.482780222078205\n ],\n [\n -183.515625,\n 50.62507306341435\n ],\n [\n -176.66015625,\n 50.3454604086048\n ],\n [\n -161.015625,\n 53.12040528310657\n ],\n [\n -154.248046875,\n 56.31653672211301\n ],\n [\n -150.29296875,\n 58.768200159239576\n ],\n [\n -151.34765625,\n 59.57885104663186\n ],\n [\n -152.9296875,\n 60.45721779774397\n ],\n [\n -155.7421875,\n 60.50052541051131\n ],\n [\n -157.67578125,\n 58.44773280389084\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-06","publicationStatus":"PW","scienceBaseUri":"565d732ce4b071e7ea54344f","contributors":{"authors":[{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":580323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carver, G. A.","contributorId":80762,"corporation":false,"usgs":false,"family":"Carver","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":580324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":580325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":580326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koehler, R.D.","contributorId":55925,"corporation":false,"usgs":true,"family":"Koehler","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":580327,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Selle, SeanPaul M. slaselle@usgs.gov","contributorId":5317,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul M.","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":580328,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bender, Adrian M. 0000-0001-7469-1957 abender@usgs.gov","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":4963,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","email":"abender@usgs.gov","middleInitial":"M.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580329,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Engelhart, S.E.","contributorId":88586,"corporation":false,"usgs":true,"family":"Engelhart","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":580330,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hemphill-Haley, E.","contributorId":69309,"corporation":false,"usgs":true,"family":"Hemphill-Haley","given":"E.","email":"","affiliations":[],"preferred":false,"id":580331,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hill, Troy D.","contributorId":150000,"corporation":false,"usgs":false,"family":"Hill","given":"Troy","email":"","middleInitial":"D.","affiliations":[{"id":17883,"text":"Yale School of Forestry and Environmental Studies, New Haven, CT","active":true,"usgs":false}],"preferred":false,"id":580332,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70159802,"text":"70159802 - 2016 - A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios","interactions":[],"lastModifiedDate":"2017-11-22T17:37:32","indexId":"70159802","displayToPublicDate":"2015-11-24T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios","docAbstract":"

Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-015-9934-1","usgsCitation":"Kranabetter, J.M., McLauchlan, K.K., Enders, S.K., Fraterrigo, J.M., Higuera, P., Morris, J.L., Rastetter, E.B., Barnes, R., Buma, B., Gavin, D.G., Gerhart, L.M., Gillson, L., Hietz, P., Mack, M., McNeil, B., and Perakis, S.S., 2016, A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios: Ecosystems, v. 19, no. 3, p. 387-395, https://doi.org/10.1007/s10021-015-9934-1.","productDescription":"9 p.","startPage":"387","endPage":"395","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065126","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":471424,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7970","text":"External Repository"},{"id":311683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"56558a2ce4b071e7ea53ded9","contributors":{"authors":[{"text":"Kranabetter, J. 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Mountainous areas surrounding the Campanian Plain and the Somma-Vesuvius volcano (southern Italy) are among the most risky areas of Italy due to the repeated occurrence of rainfallinduced debris flows along ash-fall pyroclastic soil-mantled slopes. In this geomorphological framework, rainfall patterns, hydrological processes taking place within multi-layered ash-fall pyroclastic deposits and soil antecedent moisture status are the principal factors to be taken into account to assess triggering rainfall conditions and the related hazard. This paper presents the outcomes of an experimental study based on integrated analyses consisting of the reconstruction of physical models of landslides, in situ hydrological monitoring, and hydrological and slope stability modeling, carried out on four representative source areas of debris flows that occurred in May 1998 in the Sarno Mountain Range. The hydrological monitoring was carried out during 2011 using nests of tensiometers and Watermark pressure head sensors and also through a rainfall and air temperature recording station. Time series of measured pressure head were used to calibrate a hydrological numerical model of the pyroclastic soil mantle for 2011, which was re-run for a 12-year period beginning in 2000, given the availability of rainfall and air temperature monitoring data. Such an approach allowed us to reconstruct the regime of pressure head at a daily time scale for a long period, which is representative of about 11 hydrologic years with different meteorological conditions. Based on this simulated time series, average winter and summer hydrological conditions were chosen to carry out hydrological and stability modeling of sample slopes and to identify Intensity- Duration rainfall thresholds by a deterministic approach. Among principal results, the opposing winter and summer antecedent pressure head (soil moisture) conditions were found to exert a significant control on intensity and duration of rainfall triggering events. Going from winter to summer conditions requires a strong increase of intensity and/or duration to induce landslides. The results identify an approach to account for different hazard conditions related to seasonality of hydrological processes inside the ash-fall pyroclastic soil mantle. Moreover, they highlight another important factor of uncertainty that potentially affects rainfall thresholds triggering shallow landslides reconstructed by empirical approaches.

","language":"English","publisher":"Springer","doi":"10.1007/s10346-015-0647-5","usgsCitation":"Napolitano, E., Fusco, F., Baum, R.L., Godt, J.W., and De Vita, P., 2016, Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy): Landslides, v. 13, no. 5, p. 967-983, https://doi.org/10.1007/s10346-015-0647-5.","productDescription":"17 p.","startPage":"967","endPage":"983","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070130","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":311642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Campania","otherGeospatial":"Sarno Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.616279602050781,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.89950086329285\n ],\n [\n 14.684257507324219,\n 40.84550208206526\n ],\n [\n 14.616279602050781,\n 40.84550208206526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"565438a8e4b071e7ea53d490","contributors":{"authors":[{"text":"Napolitano, E.","contributorId":97401,"corporation":false,"usgs":true,"family":"Napolitano","given":"E.","email":"","affiliations":[],"preferred":false,"id":580432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fusco, F","contributorId":150020,"corporation":false,"usgs":false,"family":"Fusco","given":"F","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":580433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":580434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":580435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Vita, P.","contributorId":26207,"corporation":false,"usgs":true,"family":"De Vita","given":"P.","affiliations":[],"preferred":false,"id":580436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156837,"text":"70156837 - 2016 - Effect of permafrost thaw on the dynamics of lakes recharged by ice-jam floods: case study in Yukon Flats, Alaska","interactions":[],"lastModifiedDate":"2017-04-07T13:55:54","indexId":"70156837","displayToPublicDate":"2015-11-21T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effect of permafrost thaw on the dynamics of lakes recharged by ice-jam floods: case study in Yukon Flats, Alaska","docAbstract":"

Large river floods are a key water source for many lakes in fluvial periglacial settings. Where permeable sediments occur, the distribution of permafrost may play an important role in the routing of floodwaters across a floodplain. This relationship is explored for lakes in the discontinuous permafrost of Yukon Flats, interior Alaska, using an analysis that integrates satellite-derived gradients in water surface elevation, knowledge of hydrogeology, and hydrologic modeling. We observed gradients in water surface elevation between neighboring lakes ranging from 0.001 to 0.004. These high gradients, despite a ubiquitous layer of continuous shallow gravel across the flats, are consistent with limited groundwater flow across lake basins resulting from the presence of permafrost. Permafrost impedes the propagation of floodwaters in the shallow subsurface and constrains transmission to “fill-and-spill” over topographic depressions (surface sills), as we observed for the Twelvemile-Buddy Lake pair following a May 2013 ice-jam flood on the Yukon River. Model results indicate that permafrost table deepening of 1–11 m in gravel, depending on watershed geometry and subsurface properties, could shift important routing of floodwater to lakes from overland flow (fill-and-spill) to shallow groundwater flow (“fill-and-seep”). Such a shift is possible in the next several hundred years of ground surface warming, and may bring about more synchronous water level changes between neighboring lakes following large flood events. This relationship offers a potentially useful tool, well-suited to remote sensing, for identifying long-term changes in shallow groundwater flow resulting from thawing of permafrost.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10756","usgsCitation":"Jepsen, S.M., Walvoord, M.A., Voss, C.I., and Rover, J.R., 2016, Effect of permafrost thaw on the dynamics of lakes recharged by ice-jam floods: case study in Yukon Flats, Alaska: Hydrological Processes, v. 30, no. 11, p. 1782-1795, https://doi.org/10.1002/hyp.10756.","productDescription":"14 p.","startPage":"1782","endPage":"1795","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063664","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":312749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats Wildlife Refuge of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.74365234374997,\n 66.26243417754857\n ],\n [\n -147.85400390625,\n 66.95587684341999\n ],\n [\n -147.06298828125,\n 67.02458758377148\n ],\n [\n -145.83251953125,\n 66.6137614931809\n ],\n [\n -145.546875,\n 66.64426812270932\n ],\n [\n -145.096435546875,\n 67.31021400255845\n ],\n [\n -144.16259765624997,\n 67.48333834982645\n ],\n [\n -143.492431640625,\n 67.1614280966097\n ],\n [\n -142.97607421875,\n 67.11874849517986\n ],\n [\n -141.844482421875,\n 67.15716352923295\n ],\n [\n -141.61376953125,\n 66.10271940699756\n ],\n [\n -142.965087890625,\n 65.98227002980873\n ],\n [\n -143.50341796875,\n 66.39915999849539\n ],\n [\n -144.107666015625,\n 66.32868478255796\n ],\n [\n -144.38232421875,\n 66.28453710088559\n ],\n [\n -143.931884765625,\n 65.9061387565849\n ],\n [\n -145.601806640625,\n 65.80277639340238\n ],\n [\n -147.1728515625,\n 65.93303449689425\n ],\n [\n -148.46923828125,\n 65.78475783804785\n ],\n [\n -149.117431640625,\n 65.70351820774201\n ],\n [\n -149.74365234374997,\n 66.26243417754857\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-29","publicationStatus":"PW","scienceBaseUri":"567a823ae4b0a04ef490fcde","contributors":{"authors":[{"text":"Jepsen, Steve M.","contributorId":147212,"corporation":false,"usgs":false,"family":"Jepsen","given":"Steve","email":"","middleInitial":"M.","affiliations":[{"id":16805,"text":"University of California, Merced","active":true,"usgs":false}],"preferred":false,"id":570776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":570775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":570777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":570778,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160541,"text":"70160541 - 2016 - Water availability and land subsidence in the Central Valley, California, USA","interactions":[],"lastModifiedDate":"2016-04-28T13:06:13","indexId":"70160541","displayToPublicDate":"2015-11-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Water availability and land subsidence in the Central Valley, California, USA","docAbstract":"

The Central Valley in California (USA) covers about 52,000 km2 and is one of the most productive agricultural regions in the world. This agriculture relies heavily on surface-water diversions and groundwater pumpage to meet irrigation water demand. Because the valley is semi-arid and surface-water availability varies substantially, agriculture relies heavily on local groundwater. In the southern two thirds of the valley, the San Joaquin Valley, historic and recent groundwater pumpage has caused significant and extensive drawdowns, aquifer-system compaction and subsidence. During recent drought periods (2007–2009 and 2012-present), groundwater pumping has increased owing to a combination of decreased surface-water availability and land-use changes. Declining groundwater levels, approaching or surpassing historical low levels, have caused accelerated and renewed compaction and subsidence that likely is mostly permanent. The subsidence has caused operational, maintenance, and construction-design problems for water-delivery and flood-control canals in the San Joaquin Valley. Planning for the effects of continued subsidence in the area is important for water agencies. As land use, managed aquifer recharge, and surface-water availability continue to vary, long-term groundwater-level and subsidence monitoring and modelling are critical to understanding the dynamics of historical and continued groundwater use resulting in additional water-level and groundwater storage declines, and associated subsidence. Modeling tools such as the Central Valley Hydrologic Model, can be used in the evaluation of management strategies to mitigate adverse impacts due to subsidence while also optimizing water availability. This knowledge will be critical for successful implementation of recent legislation aimed toward sustainable groundwater use.

","language":"English","publisher":"Springer","doi":"10.1007/s10040-015-1339-x","usgsCitation":"Faunt, C., Sneed, M., Traum, J.A., and Brandt, J.T., 2016, Water availability and land subsidence in the Central Valley, California, USA: Hydrogeology Journal, v. 24, no. 3, p. 675-684, https://doi.org/10.1007/s10040-015-1339-x.","productDescription":"10 p.","startPage":"675","endPage":"684","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067128","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-015-1339-x","text":"Publisher Index Page"},{"id":312732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.26684570312499,\n 40.85537053192494\n ],\n [\n -121.86035156249999,\n 40.75557964275591\n ],\n [\n -121.75048828124999,\n 40.538851525354644\n ],\n [\n -121.640625,\n 40.26276066437183\n ],\n [\n -121.4208984375,\n 39.757879992021756\n ],\n [\n -121.014404296875,\n 39.0533181067413\n ],\n [\n -120.70678710937499,\n 38.38472766885085\n ],\n [\n -120.11352539062499,\n 37.83148014503288\n ],\n [\n -119.72900390625001,\n 37.43997405227057\n ],\n [\n -118.927001953125,\n 36.76529191711624\n ],\n [\n -118.564453125,\n 36.2354121683998\n ],\n [\n -118.43261718749999,\n 35.60371874069731\n ],\n [\n -118.487548828125,\n 35.06597313798418\n ],\n [\n -119.00390625,\n 34.786739162702524\n ],\n [\n -119.69604492187499,\n 34.939985151560435\n ],\n [\n -120.59692382812499,\n 35.8356283888737\n ],\n [\n -121.73950195312499,\n 37.43997405227057\n ],\n [\n -122.44262695312501,\n 38.70265930723801\n ],\n [\n -123.211669921875,\n 40.111688665595956\n ],\n [\n -123.06884765625,\n 40.85537053192494\n ],\n [\n -122.67333984374999,\n 41.03793062246529\n ],\n [\n -122.26684570312499,\n 40.85537053192494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-17","publicationStatus":"PW","scienceBaseUri":"567a8246e4b0a04ef490fd20","contributors":{"authors":[{"text":"Faunt, Claudia C. 0000-0001-5659-7529 ccfaunt@usgs.gov","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":150147,"corporation":false,"usgs":true,"family":"Faunt","given":"Claudia C.","email":"ccfaunt@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583088,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583089,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":583090,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159490,"text":"70159490 - 2016 - Application of a fluidized bed reactor charged with aragonite for control of alkalinity, pH and carbon dioxide in marine recirculating aquaculture systems","interactions":[],"lastModifiedDate":"2016-02-15T16:01:04","indexId":"70159490","displayToPublicDate":"2015-11-12T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":852,"text":"Aquacultural Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Application of a fluidized bed reactor charged with aragonite for control of alkalinity, pH and carbon dioxide in marine recirculating aquaculture systems","docAbstract":"

Control of alkalinity, dissolved carbon dioxide (dCO2), and pH are critical in marine recirculating aquaculture systems (RAS) in order to maintain health and maximize growth. A small-scale prototype aragonite sand filled fluidized bed reactor was tested under varying conditions of alkalinity and dCO2 to develop and model the response of dCO2 across the reactor. A large-scale reactor was then incorporated into an operating marine recirculating aquaculture system to observe the reactor as the system moved toward equilibrium. The relationship between alkalinity dCO2, and pH across the reactor are described by multiple regression equations. The change in dCO2 across the small-scale reactor indicated a strong likelihood that an equilibrium alkalinity would be maintained by using a fluidized bed aragonite reactor. The large-scale reactor verified this observation and established equilibrium at an alkalinity of approximately 135 mg/L as CaCO3, dCO2 of 9 mg/L, and a pH of 7.0 within 4 days that was stable during a 14 day test period. The fluidized bed aragonite reactor has the potential to simplify alkalinity and pH control, and aid in dCO2 control in RAS design and operation. Aragonite sand, purchased in bulk, is less expensive than sodium bicarbonate and could reduce overall operating production costs.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaeng.2015.10.001","usgsCitation":"Wills, P.S., Pfeiffer, T., Baptiste, R., and Watten, B.J., 2016, Application of a fluidized bed reactor charged with aragonite for control of alkalinity, pH and carbon dioxide in marine recirculating aquaculture systems: Aquacultural Engineering, v. 70, p. 81-85, https://doi.org/10.1016/j.aquaeng.2015.10.001.","startPage":"81","endPage":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068459","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":471430,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquaeng.2015.10.001","text":"Publisher Index Page"},{"id":311210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5645b885e4b0e2669b30f1c6","contributors":{"authors":[{"text":"Wills, Paul S","contributorId":149707,"corporation":false,"usgs":false,"family":"Wills","given":"Paul","email":"","middleInitial":"S","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":579207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pfeiffer, Timothy","contributorId":149708,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"Timothy","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":579208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baptiste, Richard","contributorId":149709,"corporation":false,"usgs":false,"family":"Baptiste","given":"Richard","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":579209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watten, Barnaby J. 0000-0002-2227-8623 bwatten@usgs.gov","orcid":"https://orcid.org/0000-0002-2227-8623","contributorId":2002,"corporation":false,"usgs":true,"family":"Watten","given":"Barnaby","email":"bwatten@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":579206,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159585,"text":"70159585 - 2016 - Aquatic pollution increases use of terrestrial prey subsidies by stream fish","interactions":[],"lastModifiedDate":"2018-08-07T12:27:39","indexId":"70159585","displayToPublicDate":"2015-11-12T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Aquatic pollution increases use of terrestrial prey subsidies by stream fish","docAbstract":"
    \n
  1. Stream food webs are connected with their riparian zones through cross-ecosystem movements of energy and nutrients. The use and impact of terrestrial subsidies on aquatic consumers is determined in part by in situ biomass of aquatic prey. Thus, stressors such as aquatic pollutants that greatly reduce aquatic secondary production could increase the need for and reliance of stream consumers on terrestrial resource subsidies.
    2. \n
  2. To test this hypothesis, we surveyed stream fish, their diets and resource availability in 16 subalpine streams over a regional gradient of trace metals known to strongly impact aquatic insect communities (i.e. fish prey) in the Colorado Rocky Mountains, USA.
    3. \n
  3. Fish increased their reliance on terrestrial insect prey as stream metals increased. Relative biomass of terrestrial insects in stomach contents of Brook and Brown Trout increased with respect to aquatic insect biomass and total stomach contents. Drifting insect biomass showed a declining trend for aquatic, but not terrestrial insects, over the metal gradient. Trout densities were unrelated to metal concentrations in streams where we found fish.
    4. \n
  4. Synthesis and applications. Our results indicate that diets of aquatic consumers can become more terrestrial as aquatic stressors that limit in situ food production increase and that these subsidies may compensate for loss of aquatic resources. This work implies an important connection between preserving aquatic–terrestrial linkages and management of fish populations in stressed watersheds. Specifically, intact riparian zones and aquatic–terrestrial linkages are likely to be important for maintaining trout production in streams with moderate metal contamination.
    5. \n
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12543","usgsCitation":"Kraus, J.M., Pomeranz, J., Todd, A.S., Walters, D., Schmidt, T., and Wanty, R.B., 2016, Aquatic pollution increases use of terrestrial prey subsidies by stream fish: Journal of Applied Ecology, v. 53, no. 1, p. 44-53, https://doi.org/10.1111/1365-2664.12543.","productDescription":"10 p.","startPage":"44","endPage":"53","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059561","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471431,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12543","text":"Publisher Index Page"},{"id":311202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.6827392578125,\n 38.74444410121545\n ],\n [\n -106.6827392578125,\n 39.68499660118128\n ],\n [\n -105.88623046874999,\n 39.68499660118128\n ],\n [\n -105.88623046874999,\n 38.74444410121545\n ],\n [\n -106.6827392578125,\n 38.74444410121545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-27","publicationStatus":"PW","scienceBaseUri":"5645b885e4b0e2669b30f1c8","chorus":{"doi":"10.1111/1365-2664.12543","url":"http://dx.doi.org/10.1111/1365-2664.12543","publisher":"Wiley-Blackwell","authors":"Kraus Johanna M., Pomeranz Justin F., Todd Andrew S., Walters David M., Schmidt Travis S., Wanty Richard B.","journalName":"Journal of Applied Ecology","publicationDate":"10/27/2015","auditedOn":"11/17/2015"},"contributors":{"authors":[{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":579584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pomeranz, Justin F.","contributorId":149789,"corporation":false,"usgs":false,"family":"Pomeranz","given":"Justin F.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":579585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, Andrew S. atodd@usgs.gov","contributorId":1022,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew","email":"atodd@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":579586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David M. 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":4444,"corporation":false,"usgs":true,"family":"Walters","given":"David M.","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":579587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wanty, Richard B. 0000-0002-2063-6423 rwanty@usgs.gov","orcid":"https://orcid.org/0000-0002-2063-6423","contributorId":443,"corporation":false,"usgs":true,"family":"Wanty","given":"Richard","email":"rwanty@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":579588,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159584,"text":"70159584 - 2016 - Density dependence, whitebark pine, and vital rates of grizzly bears","interactions":[],"lastModifiedDate":"2016-04-13T12:09:01","indexId":"70159584","displayToPublicDate":"2015-11-10T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Density dependence, whitebark pine, and vital rates of grizzly bears","docAbstract":"

Understanding factors influencing changes in population trajectory is important for effective wildlife management, particularly for populations of conservation concern. Annual population growth of the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem, USA has slowed from 4.2–7.6% during 1983–2001 to 0.3–2.2% during 2002–2011. Substantial changes in availability of a key food source and bear population density have occurred. Whitebark pine (Pinus albicaulis), the seeds of which are a valuable but variable fall food for grizzly bears, has experienced substantial mortality primarily due to a mountain pine beetle (Dendroctonus ponderosae) outbreak that started in the early 2000s. Positive growth rates of grizzly bears have resulted in populations reaching high densities in some areas and have contributed to continued range expansion. We tested research hypotheses to examine if changes in vital rates detected during the past decade were more associated with whitebark pine decline or, alternatively, increasing grizzly bear density. We focused our assessment on known-fate data to estimate survival of cubs-of-the-year (cubs), yearlings, and independent bears (≥2 yrs), and reproductive transition of females from having no offspring to having cubs. We used spatially and temporally explicit indices for grizzly bear density and whitebark pine mortality as individual covariates. Models indicated moderate support for an increase in survival of independent male bears over 1983–2012, whereas independent female survival did not change. Cub survival, yearling survival, and reproductive transition from no offspring to cubs all changed during the 30-year study period, with lower rates evident during the last 10–15 years. Cub survival and reproductive transition were negatively associated with an index of grizzly bear density, indicating greater declines where bear densities were higher. Our analyses did not support a similar relationship for the index of whitebark pine mortality. The results of our study support the interpretation that slowing of population growth during the last decade was associated more with increasing grizzly bear density than the decline in whitebark pine. Grizzly bear density and its potential effect on vital rates and population trajectory warrant consideration for management of the grizzly bear population in the Greater Yellowstone Ecosystem.

","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.1005","usgsCitation":"van Manen, F.T., Haroldson, M.A., Bjornlie, D., Ebinger, M.R., Thompson, D.J., Costello, C., and White, G.C., 2016, Density dependence, whitebark pine, and vital rates of grizzly bears: Journal of Wildlife Management, v. 80, no. 2, p. 300-313, https://doi.org/10.1002/jwmg.1005.","productDescription":"14 p.","startPage":"300","endPage":"313","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059669","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.1005","text":"Publisher Index Page"},{"id":311170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Grand Teton National Park, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.181396484375,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 45.69083283645816\n ],\n [\n -108.62182617187499,\n 42.44778143462245\n ],\n [\n -112.181396484375,\n 42.44778143462245\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"56431532e4b0aafbcd017fa0","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":579580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":579581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":579582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, Gary C.","contributorId":26256,"corporation":false,"usgs":true,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":579583,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70162412,"text":"70162412 - 2016 - Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois","interactions":[],"lastModifiedDate":"2016-01-25T11:07:39","indexId":"70162412","displayToPublicDate":"2015-11-10T12:00:00","publicationYear":"2016","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":"Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois","docAbstract":"

We use a numerical model to analyze the impact of climate change--in particular higher air temperatures--on a nuclear power station that recirculates the water from a reservoir for cooling. The model solves the hydrodynamics, the transfer of heat in the reservoir, and the energy balance at the surface. We use the numerical model to (i) quantify the heat budget in the reservoir and determine how this budget is affected by the combined effect of the power station and climate change and (ii) quantify the impact of climate change on both the downstream thermal pollution and the power station capacity. We consider four different scenarios of climate change. Results of simulations show that climate change will reduce the ability to dissipate heat to the atmosphere and therefore the cooling capacity of the reservoir. We observed an increase of 25% in the thermal load downstream of the reservoir, and a reduction in the capacity of the power station of 18% during the summer months for the worst-case climate change scenario tested. These results suggest that climate change is an important threat for both the downstream thermal pollution and the generation of electricity by power stations that use lentic systems for cooling.

","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b04094","collaboration":"University of Illinois","usgsCitation":"Quijano, J.C., Jackson, P., Santacruz, S., Morales, V.M., and Garcia, M., 2016, Implications of climate change on the heat budget of lentic systems used for power station cooling: Case study Clinton Lake, Illinois: Environmental Science & Technology, v. 50, no. 1, p. 478-488, https://doi.org/10.1021/acs.est.5b04094.","productDescription":"11 p.","startPage":"478","endPage":"488","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068749","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":314749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Clinton Lake","geographicExtents":"{\n \"type\": 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Understanding and predicting plant response to disturbance is of paramount importance in our changing world. Resprouting ability is often considered a simple qualitative trait and used in many ecological studies. Our aim is to show some of the complexities of resprouting while highlighting cautions that need be taken in using resprouting ability to predict vegetation responses across disturbance types and biomes. There are marked differences in resprouting depending on the disturbance type, and fire is often the most severe disturbance because it includes both defoliation and lethal temperatures. In the Mediterranean biome, there are differences in functional strategies to cope with water deficit between resprouters (dehydration avoiders) and nonresprouters (dehydration tolerators); however, there is little research to unambiguously extrapolate these results to other biomes. Furthermore, predictions of vegetation responses to changes in disturbance regimes require consideration not only of resprouting, but also other relevant traits (e.g. seeding, bark thickness) and the different correlations among traits observed in different biomes; models lacking these details would behave poorly at the global scale. Overall, the lessons learned from a given disturbance regime and biome (e.g. crown-fire Mediterranean ecosystems) can guide research in other ecosystems but should not be extrapolated at the global scale.

","language":"English","publisher":"Wiley","doi":"10.1111/nph.13644","usgsCitation":"Pausas, J.G., Pratt, R., Keeley, J.E., Jacobsen, A.L., Ramirez, A.R., Vilagrosa, A., Paula, S., Kanekua-Pia, I.N., and Davis, S.D., 2016, Towards understanding resprouting at the global scale: New Phytologist, v. 209, no. 3, p. 945-954, https://doi.org/10.1111/nph.13644.","productDescription":"10 p.","startPage":"945","endPage":"954","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066488","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.13644","text":"Publisher Index Page"},{"id":311153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-07","publicationStatus":"PW","scienceBaseUri":"56431535e4b0aafbcd017fb8","contributors":{"authors":[{"text":"Pausas, Juli G.","contributorId":91347,"corporation":false,"usgs":true,"family":"Pausas","given":"Juli","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":579550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, R. Brandon","contributorId":149778,"corporation":false,"usgs":false,"family":"Pratt","given":"R. Brandon","affiliations":[{"id":17822,"text":"CA State U., Bakersfield, CA","active":true,"usgs":false}],"preferred":false,"id":579551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":579549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacobsen, Anna L.","contributorId":149779,"corporation":false,"usgs":false,"family":"Jacobsen","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":17823,"text":"CA State U, Bakersfield, CA","active":true,"usgs":false}],"preferred":false,"id":579552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramirez, Aaron R.","contributorId":149780,"corporation":false,"usgs":false,"family":"Ramirez","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":17824,"text":"UC Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":579553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vilagrosa, Alberto","contributorId":149781,"corporation":false,"usgs":false,"family":"Vilagrosa","given":"Alberto","email":"","affiliations":[{"id":17825,"text":"CEAM-Universitat d'Alacant, Alacant, Spain","active":true,"usgs":false}],"preferred":false,"id":579554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paula, Susana","contributorId":149782,"corporation":false,"usgs":false,"family":"Paula","given":"Susana","email":"","affiliations":[{"id":17826,"text":"ICAE, Universidad Austral de Chile, Valdivia, Chile","active":true,"usgs":false}],"preferred":false,"id":579555,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanekua-Pia, Iolana N.","contributorId":149783,"corporation":false,"usgs":false,"family":"Kanekua-Pia","given":"Iolana","email":"","middleInitial":"N.","affiliations":[{"id":17827,"text":"Pepperdine U, Malibu, CA","active":true,"usgs":false}],"preferred":false,"id":579556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davis, Stephen D.","contributorId":149784,"corporation":false,"usgs":false,"family":"Davis","given":"Stephen","email":"","middleInitial":"D.","affiliations":[{"id":17827,"text":"Pepperdine U, Malibu, CA","active":true,"usgs":false}],"preferred":false,"id":579557,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159536,"text":"70159536 - 2016 - Effects of dam removal on Tule Fall Chinook salmon spawning habitat in the White Salmon River, Washington","interactions":[],"lastModifiedDate":"2016-09-06T14:12:05","indexId":"70159536","displayToPublicDate":"2015-11-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of dam removal on Tule Fall Chinook salmon spawning habitat in the White Salmon River, Washington","docAbstract":"

Condit Dam is one of the largest hydroelectric dams ever removed in the USA. Breached in a single explosive event in October 2011, hundreds-of-thousands of cubic metres of sediment washed down the White Salmon River onto spawning grounds of a threatened species, Columbia River tule fall Chinook salmon Oncorhynchus tshawytscha. We investigated over a 3-year period (2010–2012) how dam breaching affected channel morphology, river hydraulics, sediment composition and tule fall Chinook salmon (hereafter ‘tule salmon’) spawning habitat in the lower 1.7 km of the White Salmon River (project area). As expected, dam breaching dramatically affected channel morphology and spawning habitat due to a large load of sediment released from Northwestern Lake. Forty-two per cent of the project area that was previously covered in water was converted into islands or new shoreline, while a large pool near the mouth filled with sediments and a delta formed at the mouth. A two-dimensional hydrodynamic model revealed that pool area decreased 68.7% in the project area, while glides and riffles increased 659% and 530%, respectively. A spatially explicit habitat model found the mean probability of spawning habitat increased 46.2% after dam breaching due to an increase in glides and riffles. Shifting channels and bank instability continue to negatively affect some spawning habitat as sediments continue to wash downstream from former Northwestern Lake, but 300 m of new spawning habitat (river kilometre 0.6 to 0.9) that formed immediately post-breach has persisted into 2015. Less than 10% of tule salmon have spawned upstream of the former dam site to date, but the run sizes appear healthy and stable. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1002/rra.2982","usgsCitation":"Hatten, J.R., Batt, T.R., Skalicky, J., Engle, R., Barton, G., Fosness, R.L., and Warren, J., 2016, Effects of dam removal on Tule Fall Chinook salmon spawning habitat in the White Salmon River, Washington: River Research and Applications, v. 32, no. 7, p. 1481-1492, https://doi.org/10.1002/rra.2982.","productDescription":"12 p.","startPage":"1481","endPage":"1492","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061792","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":311133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Condit Dam, Lower White Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.4916229248047,\n 45.931572625309286\n ],\n [\n -121.47033691406249,\n 45.92488619186047\n ],\n [\n -121.49642944335938,\n 45.891919851282076\n ],\n [\n -121.48475646972656,\n 45.84362946735877\n ],\n [\n -121.47994995117188,\n 45.821621922335794\n ],\n [\n -121.50054931640625,\n 45.821621922335794\n ],\n [\n -121.52595520019531,\n 45.86132487333675\n ],\n [\n -121.52595520019531,\n 45.897654534346884\n ],\n [\n -121.49642944335938,\n 45.924408558629004\n ],\n [\n -121.4916229248047,\n 45.931572625309286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-04","publicationStatus":"PW","scienceBaseUri":"5641d1bde4b0831b7d62e737","contributors":{"authors":[{"text":"Hatten, James R. 0000-0003-4676-8093 jhatten@usgs.gov","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":3431,"corporation":false,"usgs":true,"family":"Hatten","given":"James","email":"jhatten@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Batt, Thomas R. tbatt@usgs.gov","contributorId":3432,"corporation":false,"usgs":true,"family":"Batt","given":"Thomas","email":"tbatt@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skalicky, Joseph J.","contributorId":91386,"corporation":false,"usgs":true,"family":"Skalicky","given":"Joseph J.","affiliations":[],"preferred":false,"id":579454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engle, Rod","contributorId":149763,"corporation":false,"usgs":false,"family":"Engle","given":"Rod","affiliations":[{"id":17818,"text":"USFWS, Columbia River Fisheries Program Office","active":true,"usgs":false}],"preferred":false,"id":579455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barton, Gary J. gbarton@usgs.gov","contributorId":1147,"corporation":false,"usgs":true,"family":"Barton","given":"Gary J.","email":"gbarton@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":579457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warren, Joe jwarren@usgs.gov","contributorId":149764,"corporation":false,"usgs":true,"family":"Warren","given":"Joe","email":"jwarren@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":579458,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159600,"text":"70159600 - 2016 - A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management","interactions":[],"lastModifiedDate":"2016-06-22T12:01:51","indexId":"70159600","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management","docAbstract":"

Chytridiomycosis is an emerging disease caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) that poses a serious threat to frog populations worldwide. Several studies have shown that inoculation of bacterial species Janthinobacterium lividum (Jl) can mitigate the impact of the disease. However, there are many questions regarding this interaction. A mathematical model of a frog population infected with chytridiomycosis is developed to investigate how the inoculation of Jl could reduce the impact of Bd disease on frogs. The model also illustrates the important role of temperature in disease dynamics. The model simulation results suggest possible control strategies for Jl to limit the impact of Bd in various scenarios. However, a better knowledge of Jl life cycle is needed to fully understand the interaction of Jl, Bd, temperature and frogs.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2015.09.015","usgsCitation":"Ackleh, A.S., Carter, J., Chellamuthu, V.K., and Ma, B., 2016, A model for the interaction of frog population dynamics with Batrachochytrium dendrobaties, Janthinobacterium lividium and temperature and its implication for chytridiomycosis management: Ecological Modelling, v. 320, p. 158-169, https://doi.org/10.1016/j.ecolmodel.2015.09.015.","productDescription":"12 p.","startPage":"158","endPage":"169","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066659","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471435,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2015.09.015","text":"Publisher Index Page"},{"id":311197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"320","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5645b87ae4b0e2669b30f1c4","contributors":{"authors":[{"text":"Ackleh, Azmy S.","contributorId":119949,"corporation":false,"usgs":true,"family":"Ackleh","given":"Azmy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":579653,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chellamuthu, Vinodh K.","contributorId":149806,"corporation":false,"usgs":false,"family":"Chellamuthu","given":"Vinodh","email":"","middleInitial":"K.","affiliations":[{"id":17830,"text":"Department of Mathematics, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":579655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Baoling","contributorId":149807,"corporation":false,"usgs":false,"family":"Ma","given":"Baoling","email":"","affiliations":[{"id":17830,"text":"Department of Mathematics, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":579656,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159441,"text":"70159441 - 2016 - A quantitative framework for estimating risk of collision between marine mammals and boats","interactions":[],"lastModifiedDate":"2016-07-17T23:21:24","indexId":"70159441","displayToPublicDate":"2015-10-29T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A quantitative framework for estimating risk of collision between marine mammals and boats","docAbstract":"

Speed regulations of watercraft in protected areas are designed to reduce lethal collisions with wildlife but can have economic consequences. We present a quantitative framework for investigating the risk of deadly collisions between boats and wildlife.

\n

We apply encounter rate theory to demonstrate how marine mammal-boat encounter rate can be used to predict the expected number of deaths associated with management scenarios. We illustrate our approach with management scenarios for two endangered species: the Florida manatee Trichechus manatus latirostris and the North Atlantic right whale Eubalaena glacialis. We used a Monte Carlo simulation approach to demonstrate the uncertainty that is associated with our estimate of relative mortality.

\n

We show that encounter rate increased with vessel speed but that the expected number of encounters varies depending on the boating activities considered. For instance, in a scenario involving manatees and boating activities such as water skiing, the expected number of encounters in a given area (in a fixed time interval) increased with vessel speed. In another scenario in which a vessel made a transit of fixed length the expected number of encounters decreases slightly with boat speed. In both cases the expected number of encounters increased with distanced travelled by the boat. For whales, we found a slight reduction (~0.1%) in the number of encounters under a scenario where speed is unregulated; this reduction, however, is negligible, and overall expected relative mortality was ~30% lower under the scenario with speed regulation. The probability of avoidance by the animal or vessel was set to 0 because of lack of data, but we explored the importance of this parameter on the model predictions. In fact, expected relative mortality under speed regulations decreases even further when the probability of avoidance is a decreasing function of vessel speed.

\n

By applying encounter rate theory to the case of boat collisions with marine mammals, we gained new insights about encounter processes between wildlife and watercraft. Our work emphasizes the importance of considering uncertainty when estimating wildlife mortality. Finally, our findings are relevant to other systems and ecological processes involving the encounter between moving agents.

","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12447","usgsCitation":"Martin, J., Sabatier, Q., Gowan, T.A., Giraud, C., Gurarie, E., Calleson, S., Ortega-Ortiz, J.G., Deutsch, C., Rycyk, A., and Koslovsky, S., 2016, A quantitative framework for estimating risk of collision between marine mammals and boats: Methods in Ecology and Evolution, v. 7, no. 1, p. 42-50, https://doi.org/10.1111/2041-210X.12447.","productDescription":"9 p.","startPage":"42","endPage":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060059","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12447","text":"Publisher Index Page"},{"id":310761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-12","publicationStatus":"PW","scienceBaseUri":"5633357ce4b048076347ee95","contributors":{"authors":[{"text":"Martin, Julien 0000-0002-7375-129X julienmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":5785,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","email":"julienmartin@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":578671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sabatier, Quentin","contributorId":149517,"corporation":false,"usgs":false,"family":"Sabatier","given":"Quentin","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gowan, Timothy A.","contributorId":138595,"corporation":false,"usgs":false,"family":"Gowan","given":"Timothy","email":"","middleInitial":"A.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":578673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giraud, Christophe","contributorId":149518,"corporation":false,"usgs":false,"family":"Giraud","given":"Christophe","email":"","affiliations":[{"id":17764,"text":"Universite Paris Sud","active":true,"usgs":false}],"preferred":false,"id":578674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gurarie, Eliezer","contributorId":149519,"corporation":false,"usgs":false,"family":"Gurarie","given":"Eliezer","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":578675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calleson, Scott","contributorId":149520,"corporation":false,"usgs":false,"family":"Calleson","given":"Scott","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578676,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ortega-Ortiz, Joel G.","contributorId":149521,"corporation":false,"usgs":false,"family":"Ortega-Ortiz","given":"Joel","email":"","middleInitial":"G.","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":578677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Deutsch, Charles J.","contributorId":64135,"corporation":false,"usgs":true,"family":"Deutsch","given":"Charles J.","affiliations":[],"preferred":false,"id":578678,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rycyk, Athena","contributorId":149522,"corporation":false,"usgs":false,"family":"Rycyk","given":"Athena","email":"","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":578679,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koslovsky, Stacie M.","contributorId":149523,"corporation":false,"usgs":false,"family":"Koslovsky","given":"Stacie M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":578680,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70159434,"text":"70159434 - 2016 - A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation","interactions":[],"lastModifiedDate":"2016-06-15T16:07:28","indexId":"70159434","displayToPublicDate":"2015-10-29T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation","docAbstract":"

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 days of flight with a mean seasonal survivorship of 90.5% (95% CI = 89.2%, 91.9%) whereas spring migration took a mean of 23.5 days of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1,036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1947","usgsCitation":"Lonsdorf, E.V., Thogmartin, W.E., Jacobi, S., Coppen, J., Davis, A.Y., Fox, T.J., Heglund, P.J., Johnson, R., Jones, T., Kenow, K.P., Lyons, J., Luke, K.E., Still, S., and Tavernia, B., 2016, A generalizable energetics-based model of avian migration to facilitate continental-scale waterbird conservation: Ecological Applications, v. 26, no. 4, p. 1136-1153, https://doi.org/10.1890/14-1947.","productDescription":"18 p.","startPage":"1136","endPage":"1153","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059704","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":310752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"56333578e4b048076347ee93","contributors":{"authors":[{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":578611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science 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Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.

","language":"English","publisher":"Elsevier","publisherLocation":"Oxford, UK","doi":"10.1016/j.jenvman.2015.10.011","usgsCitation":"Shively, D., Nevers, M., Breitenbach, C., Phanikumar, M., Przybyla-Kelly, K., Spoljaric, A., and Whitman, R.L., 2016, Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches: Journal of Environmental Management, v. 166, p. 285-293, https://doi.org/10.1016/j.jenvman.2015.10.011.","productDescription":"9 p.","startPage":"285","endPage":"293","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061853","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":311747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"Great Lakes, Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.65647888183594,\n 42.03552434403621\n ],\n [\n -87.62626647949217,\n 41.99011884096809\n ],\n [\n -87.615966796875,\n 41.91454130182335\n ],\n [\n -87.59193420410156,\n 41.89767733570708\n ],\n [\n -87.56309509277344,\n 41.80766096027984\n ],\n [\n -87.53700256347656,\n 41.7672146942102\n ],\n [\n -87.52601623535156,\n 41.75338543627463\n ],\n [\n -87.52670288085938,\n 41.73084248230534\n ],\n [\n -87.52395629882812,\n 41.70931682567252\n ],\n [\n -87.53837585449219,\n 41.699063978799174\n ],\n [\n -87.63107299804688,\n 41.840408844786396\n ],\n [\n -87.681884765625,\n 41.99522219923445\n ],\n [\n -87.69218444824219,\n 42.02838405374952\n ],\n [\n -87.68119812011717,\n 42.037054301883806\n ],\n [\n -87.659912109375,\n 42.03603433407788\n ],\n [\n -87.65647888183594,\n 42.03552434403621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"166","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565d8140e4b071e7ea543480","contributors":{"authors":[{"text":"Shively, Dawn","contributorId":150065,"corporation":false,"usgs":false,"family":"Shively","given":"Dawn","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":580617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breitenbach, Cathy","contributorId":150066,"corporation":false,"usgs":false,"family":"Breitenbach","given":"Cathy","email":"","affiliations":[{"id":17899,"text":"Chicago Park District","active":true,"usgs":false}],"preferred":false,"id":580619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":580623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Przybyla-Kelly, Kasia","contributorId":150067,"corporation":false,"usgs":false,"family":"Przybyla-Kelly","given":"Kasia","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580620,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley M.","contributorId":150068,"corporation":false,"usgs":false,"family":"Spoljaric","given":"Ashley M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":580621,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitman, Richard L.","contributorId":150069,"corporation":false,"usgs":false,"family":"Whitman","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":580622,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159410,"text":"70159410 - 2016 - Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","interactions":[],"lastModifiedDate":"2016-01-11T10:54:13","indexId":"70159410","displayToPublicDate":"2015-10-27T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management","docAbstract":"
\n

Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.

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Greater sage-grouse Centrocercus urophasianus, hereafter “sage-grouse” populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize use of available information.

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Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution, and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by > 35 500 independent telemetry locations from > 1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.

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We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance.

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Synthesis and applications. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance, and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species, and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

\n
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.12558","usgsCitation":"Coates, P.S., Casazza, M.L., Ricca, M.A., Brussee, B.E., Blomberg, E.J., Gustafson, K.B., Overton, C.T., Davis, D.M., Niell, L.E., Espinosa, S.P., Gardner, S., and Delehanty, D., 2016, Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management: Journal of Applied Ecology, v. 53, no. 1, p. 83-95, https://doi.org/10.1111/1365-2664.12558.","productDescription":"13 p.","startPage":"83","endPage":"95","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066697","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471441,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12558","text":"Publisher Index Page"},{"id":438648,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75D8PW8","text":"USGS data release","linkHelpText":"Integrating Spatially Explicit Indices of Abundance and Habitat Quality: An Applied Example for Greater Sage-grouse Management"},{"id":310666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.04907226562499,\n 41.9921602333763\n ],\n [\n -121.805419921875,\n 42.00848901572399\n ],\n [\n -120.0146484375,\n 39.436192999314095\n ],\n [\n -115.94970703125,\n 36.949891786813296\n ],\n [\n -114.0380859375,\n 36.949891786813296\n ],\n [\n -114.04907226562499,\n 41.9921602333763\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-27","publicationStatus":"PW","scienceBaseUri":"563092bae4b093cee78203cc","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ricca, Mark A. mark_ricca@usgs.gov","contributorId":2400,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":578442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":578444,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":5568,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":578445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":578446,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davis, Dawn M.","contributorId":81003,"corporation":false,"usgs":true,"family":"Davis","given":"Dawn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":578447,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Niell, Lara E.","contributorId":149448,"corporation":false,"usgs":false,"family":"Niell","given":"Lara","email":"","middleInitial":"E.","affiliations":[{"id":17737,"text":"Nevada Sagebrush Ecosystem Program; Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":578448,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Espinosa, Shawn P.","contributorId":48298,"corporation":false,"usgs":true,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":578449,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gardner, Scott C.","contributorId":80206,"corporation":false,"usgs":true,"family":"Gardner","given":"Scott C.","affiliations":[],"preferred":false,"id":578450,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Delehanty, David J.","contributorId":86683,"corporation":false,"usgs":true,"family":"Delehanty","given":"David J.","affiliations":[],"preferred":false,"id":578451,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70157213,"text":"70157213 - 2016 - A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae)","interactions":[],"lastModifiedDate":"2016-12-14T10:12:51","indexId":"70157213","displayToPublicDate":"2015-10-26T16:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"title":"A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae)","docAbstract":"

The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick.

","language":"English","publisher":"Oxford University Press","doi":"10.1093/jme/tjv150","usgsCitation":"Ludwig, A., Ginsberg, H., Hickling, G., and Ogden, N.H., 2016, A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae): Journal of Medical Entomology, v. 53, no. 1, p. 99-115, https://doi.org/10.1093/jme/tjv150.","productDescription":"17 p.","startPage":"99","endPage":"115","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":486932,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/144","text":"External Repository"},{"id":312845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-26","publicationStatus":"PW","scienceBaseUri":"567bd3bae4b0a04ef491a1ee","contributors":{"authors":[{"text":"Ludwig, Antoinette","contributorId":147666,"corporation":false,"usgs":false,"family":"Ludwig","given":"Antoinette","email":"","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":572281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hickling, Graham J.","contributorId":88639,"corporation":false,"usgs":true,"family":"Hickling","given":"Graham J.","affiliations":[],"preferred":false,"id":572283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":572284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177904,"text":"70177904 - 2016 - Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?","interactions":[],"lastModifiedDate":"2016-12-06T13:03:19","indexId":"70177904","displayToPublicDate":"2015-10-26T09:15:00","publicationYear":"2016","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":"Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?","docAbstract":"

Freshwater shrimps are an important biotic component of tropical ecosystems. However, they can have a low probability of detection when abundances are low. We sampled 3 of the most common freshwater shrimp species, Macrobrachium olfersii, Macrobrachium carcinus, and Macrobrachium heterochirus, and used occupancy modeling and logistic regression models to improve our limited knowledge of distribution of these cryptic species by investigating both local- and landscape-scale effects at La Selva Biological Station in Costa Rica. Local-scale factors included substrate type and stream size, and landscape-scale factors included presence or absence of regional groundwater inputs. Capture rates for 2 of the sampled species (M. olfersii and M. carcinus) were sufficient to compare the fit of occupancy models. Occupancy models did not converge for M. heterochirus, but M. heterochirus had high enough occupancy rates that logistic regression could be used to model the relationship between occupancy rates and predictors. The best-supported models for M. olfersii and M. carcinus included conductivity, discharge, and substrate parameters. Stream size was positively correlated with occupancy rates of all 3 species. High stream conductivity, which reflects the quantity of regional groundwater input into the stream, was positively correlated with M. olfersii occupancy rates. Boulder substrates increased occupancy rate of M. carcinus and decreased the detection probability of M. olfersii. Our models suggest that shrimp distribution is driven by factors that function at local (substrate and discharge) and landscape (conductivity) scales.

","language":"English","publisher":"Society for Freshwater Science","doi":"10.1086/684486","usgsCitation":"Snyder, M., Freeman, M., Purucker, S.T., and Pringle, C.M., 2016, Using occupancy modeling and logistic regression to assess the distribution of shrimp species in lowland streams, Costa Rica: Does regional groundwater create favorable habitat?: Freshwater Science, v. 35, no. 1, p. 80-90, https://doi.org/10.1086/684486.","productDescription":"11 p.","startPage":"80","endPage":"90","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062926","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":330405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"La Selva Biological Station, Saltito River, Salto River, Sura River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.09004211425781,\n 10.3270789193731\n ],\n [\n -84.09004211425781,\n 10.530007387221294\n ],\n [\n -83.92833709716797,\n 10.530007387221294\n ],\n [\n -83.92833709716797,\n 10.3270789193731\n ],\n [\n -84.09004211425781,\n 10.3270789193731\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f4e4b0f497e79a5a8d","contributors":{"authors":[{"text":"Snyder, Marcia","contributorId":176290,"corporation":false,"usgs":false,"family":"Snyder","given":"Marcia","affiliations":[],"preferred":false,"id":652095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":652094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Purucker, S. Thomas","contributorId":176291,"corporation":false,"usgs":false,"family":"Purucker","given":"S.","email":"","middleInitial":"Thomas","affiliations":[],"preferred":false,"id":652096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pringle, Catherine M.","contributorId":176292,"corporation":false,"usgs":false,"family":"Pringle","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652097,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159200,"text":"70159200 - 2016 - Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","interactions":[],"lastModifiedDate":"2016-01-11T10:52:23","indexId":"70159200","displayToPublicDate":"2015-10-20T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment","docAbstract":"

A baseline assessment of the Missouri River fish community and species-specific habitat use patterns conducted from 1996 to 1998 provided the first comprehensive analysis of Missouri River benthic fish population trends and habitat use in the Missouri and Lower Yellowstone rivers, exclusive of reservoirs, and provided the foundation for the present Pallid Sturgeon Population Assessment Program (PSPAP). Data used in such studies are frequently zero inflated. To address this issue, the zero-inflated Poisson (ZIP) model was applied. This follow-up study is based on PSPAP data collected up to 15 years later along with new understanding of how habitat characteristics among and within bends affect habitat use of fish species targeted by PSPAP, including pallid sturgeon. This work demonstrated that a large-scale, large-river, PSPAP-type monitoring program can be an effective tool for assessing population trends and habitat usage of large-river fish species. Using multiple gears, PSPAP was effective in monitoring shovelnose and pallid sturgeons, sicklefin, shoal and sturgeon chubs, sand shiner, blue sucker and sauger. For all species, the relationship between environmental variables and relative abundance differed, somewhat, among river segments suggesting the importance of the overall conditions of Upper and Middle Missouri River and Lower Missouri and Kansas rivers on the habitat usage patterns exhibited. Shoal and sicklefin chubs exhibited many similar habitat usage patterns; blue sucker and shovelnose sturgeon also shared similar responses. For pallid sturgeon, the primary focus of PSPAP, relative abundance tended to increase in Upper and Middle Missouri River paralleling stocking efforts, whereas no evidence of an increasing relative abundance was found in the Lower Missouri River despite stocking.

","language":"English","publisher":"Wiley","doi":"10.1002/rra.2846","usgsCitation":"Wildhaber, M.L., Yang, W., and Arab, A., 2016, Population trends, bend use relative to available habitat and within-river-bend habitat use of eight indicator species of Missouri and Lower Kansas River benthic fishes: 15 years after baseline assessment: River Research and Applications, v. 32, p. 36-65, https://doi.org/10.1002/rra.2846.","productDescription":"30 p.","startPage":"36","endPage":"65","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055609","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":310114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Kansas River, Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.99414062499999,\n 45.72152152227954\n ],\n [\n -113.719482421875,\n 49.49667452747045\n ],\n [\n -99.7119140625,\n 49.01625665778159\n ],\n [\n -96.591796875,\n 45.90529985724796\n ],\n [\n -94.932861328125,\n 43.52465500687185\n ],\n [\n -93.09814453125,\n 40.60561205826018\n ],\n [\n -89.97802734375,\n 38.865374851611634\n ],\n [\n -89.835205078125,\n 36.50963615733049\n ],\n [\n -94.537353515625,\n 36.500805317604794\n ],\n [\n -102.095947265625,\n 39.99395569397331\n ],\n [\n -114.08203125,\n 43.96119063892024\n ],\n [\n -113.99414062499999,\n 45.72152152227954\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-04","publicationStatus":"PW","scienceBaseUri":"562757a8e4b0d158f5926505","contributors":{"authors":[{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":577837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Wen-Hsi","contributorId":45228,"corporation":false,"usgs":true,"family":"Yang","given":"Wen-Hsi","email":"","affiliations":[],"preferred":false,"id":577838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Ali","contributorId":75002,"corporation":false,"usgs":true,"family":"Arab","given":"Ali","email":"","affiliations":[],"preferred":false,"id":577839,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158932,"text":"70158932 - 2016 - Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model","interactions":[],"lastModifiedDate":"2016-06-02T10:32:38","indexId":"70158932","displayToPublicDate":"2015-10-13T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model","docAbstract":"

There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.

","language":"English","publisher":"Wiley","doi":"10.1111/ecog.01179","collaboration":"Prepared in collaboration with U.S. Fish and Wildlife Service","usgsCitation":"Crimmins, S.M., Walleser, L.R., Hertel, D.R., McKann, P., Rohweder, J.J., and Thogmartin, W.E., 2016, Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model: Ecography, v. 39, no. 6, p. 524-532, https://doi.org/10.1111/ecog.01179.","productDescription":"9 p.","startPage":"524","endPage":"532","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057940","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":309843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.8115234375,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 47.754097979680026\n ],\n [\n -93.71337890625,\n 42.71473218539458\n ],\n [\n -96.8115234375,\n 42.71473218539458\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-30","publicationStatus":"PW","scienceBaseUri":"561e1d28e4b0cdb063e59ca5","contributors":{"authors":[{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walleser, Liza R. lwalleser@usgs.gov","contributorId":4329,"corporation":false,"usgs":true,"family":"Walleser","given":"Liza","email":"lwalleser@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hertel, Dan R.","contributorId":149113,"corporation":false,"usgs":false,"family":"Hertel","given":"Dan","email":"","middleInitial":"R.","affiliations":[{"id":17647,"text":"United States Fish and Wildlife Service, Habitat and Population Evaluation Team","active":true,"usgs":false}],"preferred":false,"id":576940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKann, Patrick C.","contributorId":14940,"corporation":false,"usgs":true,"family":"McKann","given":"Patrick C.","affiliations":[],"preferred":false,"id":576941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":576942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576937,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70158679,"text":"70158679 - 2016 - Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California","interactions":[],"lastModifiedDate":"2016-03-17T13:43:39","indexId":"70158679","displayToPublicDate":"2015-10-06T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California","docAbstract":"

As marine management is moving towards the practice of protecting static areas, it is 44 important to make sure protected areas capture and protect persistent populations. Rocky reefs in 45 many temperate areas worldwide serve as habitat for canopy forming macroalgae and these 46 structure forming species of kelps (order Laminariales) often serve as important habitat for a great 47 diversity of species. Macrocystis pyrifera is the most common canopy forming kelp species found 48 along the coast of California but the distribution and abundance of M. pyrifera varies in space and 49 time. The purpose of this study is to determine what environmental parameters are correlated with 50 the spatial and temporal persistence of M. pyrifera along the central coast of California and how 51 well those environmental parameters can be used to predict areas where M. pyrifera is more likely 52 to persist. Nine environmental variables considered in this study included depth of the seafloor, 53 structure of the rocky reef, proportion of rocky reef, size of kelp patch, biomass of kelp within a 54 patch, distance from the edge of a kelp patch, sea surface temperature, wave orbital velocities, and 55 population connectivity of individual kelp patches. Using a generalized linear mixed effects model 56 (GLMM), the persistence of M. pyrifera was significantly associated with seven of the nine 57 variables considered: depth, complexity of the rocky reef, proportion of rock, patch biomass, 58 distance from the edge of a patch, population connectivity, and wave-orbital velocities. These 59 seven environmental variables were then used to predict the persistence of kelp across the central 60 coast and these predictions were compared to a reserved dataset of M. pyrifera persistence, which 61 was not used in the creation of the GLMM. The environmental variables were shown to accurately 62 predict the persistence of M. pyrifera within the central coast of California (r = 0.71, P<0.001). 63 Because persistence of giant kelp is important to the community structure of kelp forests, 64 understanding those factors that support persistent populations of M. pyrifera will enable more 65 effective management of these ecosystems.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0267.1","collaboration":"Prepared in collaboration with University of California at Santa Cruz, University of California at Los Angeles","usgsCitation":"Young, M.A., Cavanaugh, K.C., Bell, T.W., Raimondi, P.T., Edwards, C.A., Drake, P.T., Erikson, L., and Storlazzi, C.D., 2016, Environmental controls on spatial patterns in the long-term persistence of giant kelp in central California: Ecology, v. 86, no. 1, p. 45-60, https://doi.org/10.1890/15-0267.1.","productDescription":"16 p.","startPage":"45","endPage":"60","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063935","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502615,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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The subduction zone in northern Chile is a well-identified seismic gap that last ruptured in 1877. On 1 April 2014, this region was struck by a large earthquake following a two week long series of foreshocks. This study combines a wide range of observations, including geodetic, tsunami, and seismic data, to produce a reliable kinematic slip model of the Mw=8.1 main shock and a static slip model of the Mw=7.7 aftershock. We use a novel Bayesian modeling approach that accounts for uncertainty in the Green's functions, both static and dynamic, while avoiding nonphysical regularization. The results reveal a sharp slip zone, more compact than previously thought, located downdip of the foreshock sequence and updip of high-frequency sources inferred by back-projection analysis. Both the main shock and the Mw=7.7 aftershock did not rupture to the trench and left most of the seismic gap unbroken, leaving the possibility of a future large earthquake in the region.

","language":"English","publisher":"AGU","doi":"10.1002/2015GL065402","usgsCitation":"Duputel, Z., Jiang, J., Jolivet, R., Simons, M., Rivera, L., Ampuero, J., Riel, B., Owen, S.E., Moore, A.W., Samsonov, S.V., Ortega Culaciati, F., and Minson, S.E., 2016, The Iquique earthquake sequence of April 2014: Bayesian modeling accounting for prediction uncertainty: Geophysical Research Letters, v. 42, no. 19, p. 7949-7957, https://doi.org/10.1002/2015GL065402.","productDescription":"9 p.","startPage":"7949","endPage":"7957","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068742","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471446,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065402","text":"Publisher Index Page"},{"id":325568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, 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