{"pageNumber":"510","pageRowStart":"12725","pageSize":"25","recordCount":40778,"records":[{"id":70158602,"text":"70158602 - 2016 - Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896)","interactions":[],"lastModifiedDate":"2016-08-17T08:46:44","indexId":"70158602","displayToPublicDate":"2015-10-01T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896)","docAbstract":"

The Central Texas endemic freshwater mussel, Quadrula mitchelli (Simpson in Dall, 1896), had been presumed extinct until relict populations were recently rediscovered. To help guide ongoing and future conservation efforts focused on Q. mitchelli we set out to resolve several uncertainties regarding its evolutionary history, specifically its unknown generic position and untested species boundaries. We designed a molecular matrix consisting of two loci (cytochrome c oxidase subunit I and internal transcribed spacer I) and 57 terminal taxa to test the generic position of Q. mitchelli using Bayesian inference and maximum likelihood phylogenetic reconstruction. We also employed two Bayesian species validation methods to test five a priori species models (i.e. hypotheses of species delimitation). Our study is the first to test the generic position of Q.mitchelli and we found robust support for its inclusion in the genusFusconaia. Accordingly, we introduce the binomial, Fusconaia mitchelli comb. nov., to accurately represent the systematic position of the species. We resolved F. mitchelli individuals in two well supported and divergent clades that were generally distinguished as distinct species using Bayesian species validation methods, although alternative hypotheses of species delineation were also supported. Despite strong evidence of genetic isolation within F. mitchelli, we do not advocate for species-level status of the two clades as they are allopatrically distributed and no morphological, behavioral, or ecological characters are known to distinguish them. These results are discussed in the context of the systematics, distribution, and conservation ofF. mitchelli.

","language":"English","publisher":"Kluwer Academic Publishers","publisherLocation":"Dordrecht","doi":"10.1007/s10592-015-0780-7","usgsCitation":"Pfeiffer, J.M., Johnson, N.A., Randklev, C.R., Howells, R.G., and Williams, J.D., 2016, Generic reclassification and species boundaries in the rediscovered freshwater mussel ‘Quadrula’ mitchelli (Simpson in Dall, 1896): Conservation Genetics, v. 17, no. 2, p. 279-292, https://doi.org/10.1007/s10592-015-0780-7.","productDescription":"14 p.","startPage":"279","endPage":"292","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059406","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":309395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-26","publicationStatus":"PW","scienceBaseUri":"563486b7e4b048076347fb22","contributors":{"authors":[{"text":"Pfeiffer, John M. III","contributorId":148964,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John","suffix":"III","email":"","middleInitial":"M.","affiliations":[{"id":17607,"text":"Cherokee Nation Technology Solutions, Contracted to U.S. Geological Survey, Southeast Ecological Science Center","active":true,"usgs":false}],"preferred":false,"id":576273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":576272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Randklev, Charles R.","contributorId":25470,"corporation":false,"usgs":true,"family":"Randklev","given":"Charles","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":576274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howells, Robert G.","contributorId":21072,"corporation":false,"usgs":true,"family":"Howells","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":576275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, James D.","contributorId":17690,"corporation":false,"usgs":false,"family":"Williams","given":"James","email":"","middleInitial":"D.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":576276,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173663,"text":"70173663 - 2016 - Animal movement constraints improve resource selection inference in the presence of telemetry error","interactions":[],"lastModifiedDate":"2016-06-07T15:20:38","indexId":"70173663","displayToPublicDate":"2015-10-01T00:00:00","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":"Animal movement constraints improve resource selection inference in the presence of telemetry error","docAbstract":"

Multiple factors complicate the analysis of animal telemetry location data. Recent advancements address issues such as temporal autocorrelation and telemetry measurement error, but additional challenges remain. Difficulties introduced by complicated error structures or barriers to animal movement can weaken inference. We propose an approach for obtaining resource selection inference from animal location data that accounts for complicated error structures, movement constraints, and temporally autocorrelated observations. We specify a model for telemetry data observed with error conditional on unobserved true locations that reflects prior knowledge about constraints in the animal movement process. The observed telemetry data are modeled using a flexible distribution that accommodates extreme errors and complicated error structures. Although constraints to movement are often viewed as a nuisance, we use constraints to simultaneously estimate and account for telemetry error. We apply the model to simulated data, showing that it outperforms common ad hoc approaches used when confronted with measurement error and movement constraints. We then apply our framework to an Argos satellite telemetry data set on harbor seals (Phoca vitulina) in the Gulf of Alaska, a species that is constrained to move within the marine environment and adjacent coastlines.

","language":"English","publisher":"Ecological Society of America, Wiley","doi":"10.1890/15-0472.1","usgsCitation":"Brost, B.M., Hooten, M., Hanks, E., and Small, R.J., 2016, Animal movement constraints improve resource selection inference in the presence of telemetry error: Ecology, v. 96, no. 10, p. 2590-2597, https://doi.org/10.1890/15-0472.1.","productDescription":"8 p.","startPage":"2590","endPage":"2597","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060441","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/15-0472.1","text":"Publisher Index Page"},{"id":323199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5757f02ee4b04f417c24da1b","contributors":{"authors":[{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":637471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanks, Ephraim M.","contributorId":104630,"corporation":false,"usgs":true,"family":"Hanks","given":"Ephraim M.","affiliations":[],"preferred":false,"id":637596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Small, Robert J.","contributorId":171486,"corporation":false,"usgs":false,"family":"Small","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":637597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168681,"text":"70168681 - 2016 - Evaluating abundance and trends in a Hawaiian avian community using state-space analysis","interactions":[],"lastModifiedDate":"2018-01-04T12:37:05","indexId":"70168681","displayToPublicDate":"2015-09-30T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1048,"text":"Bird Conservation International","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating abundance and trends in a Hawaiian avian community using state-space analysis","docAbstract":"

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge","doi":"10.1017/S0959270915000088","usgsCitation":"Camp, R., Brinck, K., Gorresen, P.M., and Paxton, E., 2016, Evaluating abundance and trends in a Hawaiian avian community using state-space analysis: Bird Conservation International, v. 26, no. 2, p. 225-242, https://doi.org/10.1017/S0959270915000088.","productDescription":"18 p.","startPage":"225","endPage":"242","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064721","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":318360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.467529296875,\n 19.427743935948932\n ],\n [\n -155.467529296875,\n 19.89330573274471\n ],\n [\n -155.15167236328125,\n 19.89330573274471\n ],\n [\n -155.15167236328125,\n 19.427743935948932\n ],\n [\n -155.467529296875,\n 19.427743935948932\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-30","publicationStatus":"PW","scienceBaseUri":"56cee261e4b015c306ec5ebf","contributors":{"authors":[{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":621250,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W.","contributorId":78215,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","affiliations":[],"preferred":false,"id":621251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorresen, P. M. mgorresen@usgs.gov","contributorId":18552,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":621252,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":621249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157236,"text":"70157236 - 2016 - Blind identification of the Millikan Library from earthquake data considering soil–structure interaction","interactions":[],"lastModifiedDate":"2016-06-17T09:37:01","indexId":"70157236","displayToPublicDate":"2015-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5007,"text":"Structural Control and Health Monitoring","active":true,"publicationSubtype":{"id":10}},"title":"Blind identification of the Millikan Library from earthquake data considering soil–structure interaction","docAbstract":"

The Robert A. Millikan Library is a reinforced concrete building with a basement level and nine stories above the ground. Located on the campus of California Institute of Technology (Caltech) in Pasadena California, it is among the most densely instrumented buildings in the U.S. From the early dates of its construction, it has been the subject of many investigations, especially regarding soil–structure interaction effects. It is well accepted that the structure is significantly interacting with the surrounding soil, which implies that the true foundation input motions cannot be directly recorded during earthquakes because of inertial effects. Based on this limitation, input–output modal identification methods are not applicable to this soil–structure system. On the other hand, conventional output-only methods are typically based on the unknown input signals to be stationary whitenoise, which is not the case for earthquake excitations. Through the use of recently developed blind identification (i.e. output-only) methods, it has become possible to extract such information from only the response signals because of earthquake excitations. In the present study, we employ such a blind identification method to extract the modal properties of the Millikan Library. We present some modes that have not been identified from force vibration tests in several studies to date. Then, to quantify the contribution of soil–structure interaction effects, we first create a detailed Finite Element (FE) model using available information about the superstructure; and subsequently update the soil–foundation system's dynamic stiffnesses at each mode such that the modal properties of the entire soil–structure system agree well with those obtained via output-only modal identification.

","language":"English","publisher":"International Association for Structural Control and Monitoring","publisherLocation":"Chichester, UK","doi":"10.1002/stc.1803","usgsCitation":"Ghahari, S.F., Abazarsa, F., Avci, O., Çelebi, M., and Taciroglu, E., 2016, Blind identification of the Millikan Library from earthquake data considering soil–structure interaction: Structural Control and Health Monitoring, v. 23, no. 4, p. 684-706, https://doi.org/10.1002/stc.1803.","productDescription":"23 p.","startPage":"684","endPage":"706","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068999","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471450,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/stc.1803","text":"Publisher Index Page"},{"id":318538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Pasadena","otherGeospatial":"Robert A. Millikan Library, California Insttitute of Technology","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.12946319580077,\n 34.13136240467381\n ],\n [\n -118.12946319580077,\n 34.14203648796777\n ],\n [\n -118.12130928039551,\n 34.14203648796777\n ],\n [\n -118.12130928039551,\n 34.13136240467381\n ],\n [\n -118.12946319580077,\n 34.13136240467381\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-29","publicationStatus":"PW","scienceBaseUri":"56d96e3ce4b015c306f7644c","contributors":{"authors":[{"text":"Ghahari, S. F.","contributorId":147707,"corporation":false,"usgs":false,"family":"Ghahari","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abazarsa, F.","contributorId":147708,"corporation":false,"usgs":false,"family":"Abazarsa","given":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avci, O.","contributorId":147709,"corporation":false,"usgs":false,"family":"Avci","given":"O.","email":"","affiliations":[{"id":16914,"text":"University of Qatar","active":true,"usgs":false}],"preferred":false,"id":572367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Çelebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":3205,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":572364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taciroglu, E.","contributorId":147710,"corporation":false,"usgs":false,"family":"Taciroglu","given":"E.","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":572368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176942,"text":"70176942 - 2016 - Precipitation regime classification for the Mojave Desert: Implications for fire occurrence","interactions":[],"lastModifiedDate":"2017-04-07T13:55:04","indexId":"70176942","displayToPublicDate":"2015-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation regime classification for the Mojave Desert: Implications for fire occurrence","docAbstract":"

Long periods of drought or above-average precipitation affect Mojave Desert vegetation condition, biomass and susceptibility to fire. Changes in the seasonality of precipitation alter the likelihood of lightning, a key ignition source for fires. The objectives of this study were to characterize the relationship between recent, historic, and future precipitation patterns and fire. Classifying monthly precipitation data from 1971 to 2010 reveals four precipitation regimes: low winter/low summer, moderate winter/moderate summer, high winter/low summer and high winter/high summer. Two regimes with summer monsoonal precipitation covered only 40% of the Mojave Desert ecoregion but contain 88% of the area burned and 95% of the repeat burn area. Classifying historic precipitation for early-century (wet) and mid-century (drought) periods reveals distinct shifts in regime boundaries. Early-century results are similar to current, while the mid-century results show a sizeable reduction in area of regimes with a strong monsoonal component. Such a shift would suggest that fires during the mid-century period would be minimal and anecdotal records confirm this. Predicted precipitation patterns from downscaled global climate models indicate numerous epochs of high winter precipitation, inferring higher fire potential for many multi-decade periods during the next century.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2015.09.002","usgsCitation":"Tagestad, J., Brooks, M.L., Cullinan, V., Downs, J., and McKinley, R., 2016, Precipitation regime classification for the Mojave Desert: Implications for fire occurrence: Journal of Arid Environments, v. 124, p. 388-397, https://doi.org/10.1016/j.jaridenv.2015.09.002.","productDescription":"10 p.","startPage":"388","endPage":"397","numberOfPages":"10","ipdsId":"IP-063012","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":329530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.817138671875,\n 33.47727218776036\n ],\n [\n -118.817138671875,\n 37.96152331396614\n ],\n [\n -112.664794921875,\n 37.96152331396614\n ],\n [\n -112.664794921875,\n 33.47727218776036\n ],\n [\n -118.817138671875,\n 33.47727218776036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf6","contributors":{"authors":[{"text":"Tagestad, Jerry","contributorId":175339,"corporation":false,"usgs":false,"family":"Tagestad","given":"Jerry","email":"","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":650819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cullinan, Valerie","contributorId":175340,"corporation":false,"usgs":false,"family":"Cullinan","given":"Valerie","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Janelle","contributorId":175341,"corporation":false,"usgs":false,"family":"Downs","given":"Janelle","email":"","affiliations":[{"id":27560,"text":"PNNL","active":true,"usgs":false}],"preferred":false,"id":650822,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKinley, Randy 0000-0001-7644-6365 rmckinley@usgs.gov","orcid":"https://orcid.org/0000-0001-7644-6365","contributorId":1354,"corporation":false,"usgs":true,"family":"McKinley","given":"Randy","email":"rmckinley@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":650823,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211939,"text":"70211939 - 2016 - Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics","interactions":[],"lastModifiedDate":"2021-04-27T18:50:22.024529","indexId":"70211939","displayToPublicDate":"2015-09-28T11:43:50","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics","docAbstract":"
  1. Abundance of the young‐of‐the‐year (YOY) fish can vary greatly among years and it may be driven by several key biological processes (i.e. adult spawning, egg survival and fry survival) that span several months. However, the relative influence of seasonal weather patterns on YOY abundance is poorly understood.
  2. We assessed the importance of seasonal air temperature (a surrogate for stream temperature) and precipitation (a surrogate for stream flow) on brook trout (Salvelinus fontinalis) YOY summer abundance using a 29‐year data set from 115 sites in Shenandoah National Park, Virginia, U.S.A. We used a Bayesian hierarchical model that allowed the effect of seasonal weather covariates to vary among sites and accounted for imperfect detection of individuals.
  3. Summer YOY abundance was affected by preceding seasonal air temperature and precipitation, and these regional‐scale drivers led to spatial synchrony in YOY abundance dynamics across the 170‐km‐long study area. Mean winter precipitation had the greatest effect on YOY abundance and the relationship was negative. Mean autumn precipitation, and winter and spring temperature had significantly positive effects on YOY abundance, and mean autumn temperature had a significant negative effect. In addition, the effect of summer precipitation differed along a latitudinal gradient, with YOY abundance at more northern sites being more responsive to inter‐annual variation in summer precipitation.
  4. Strong YOY years resulted in high abundance of adults (>age 1 + fish) in the subsequent year at more than half of sites. However, higher adult abundance did not result in higher YOY abundance in the subsequent year at any of the study sites (i.e. no positive stock–recruitment relationship).
  5. Our results indicate that YOY abundance is a key driver of brook trout population dynamics that is mediated by seasonal weather patterns. A reliable assessment of climate change impacts on brook trout needs to account for how alternations in seasonal weather patterns impact YOY abundance and how such relationships may differ across the range of brook trout distribution.
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12682","usgsCitation":"Kanno, Y., Pregler, K.C., Hitt, N.P., Letcher, B., Hocking, D., and Wofford, J.E., 2016, Seasonal temperature and precipitation regulate brook trout young-of-the-year abundance and population dynamics: Freshwater Biology, v. 61, no. 1, p. 88-99, https://doi.org/10.1111/fwb.12682.","productDescription":"12 p.","startPage":"88","endPage":"99","ipdsId":"IP-063610","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.25561523437499,\n 39.04478604850143\n ],\n [\n -79.21142578125,\n 37.95286091815649\n ],\n [\n -79.6893310546875,\n 37.56199695314352\n ],\n [\n -79.486083984375,\n 37.42688834526727\n ],\n [\n -78.695068359375,\n 37.92686760148135\n ],\n [\n -77.904052734375,\n 38.6897975322717\n ],\n [\n -77.95898437499999,\n 39.0533181067413\n ],\n [\n -78.25561523437499,\n 39.04478604850143\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2015-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":795888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pregler, Kasey C.","contributorId":149616,"corporation":false,"usgs":false,"family":"Pregler","given":"Kasey","email":"","middleInitial":"C.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":795889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":795890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":169305,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":795891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hocking, Daniel 0000-0003-1889-9184 dhocking@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-9184","contributorId":149618,"corporation":false,"usgs":true,"family":"Hocking","given":"Daniel","email":"dhocking@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":795892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wofford, John E. B.","contributorId":38951,"corporation":false,"usgs":false,"family":"Wofford","given":"John","email":"","middleInitial":"E. B.","affiliations":[],"preferred":false,"id":795893,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157212,"text":"70157212 - 2016 - Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use","interactions":[],"lastModifiedDate":"2016-12-14T12:24:51","indexId":"70157212","displayToPublicDate":"2015-09-25T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1844,"text":"Global and Planetary Change","active":true,"publicationSubtype":{"id":10}},"title":"Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use","docAbstract":"

Although fire was arguably the primary tool used by the Maya to alter the landscape and extract resources, little attention has been paid to biomass burning in paleoenvironmental reconstructions from the Maya lowlands. Here we report two new well-dated, high-resolution records of biomass burning based on analysis of macroscopic fossil charcoal recovered from lacustrine sediment cores. The records extend from the early Holocene, through the full arc of Maya prehistory, the Colonial, and post-Colonial periods (~ 9000 cal yr BP to the present). (Hereafter BP) The study sites, Lago Paixban and Lago Puerto Arturo, are located in northern Peten, Guatemala. Results provide the first quantitative analysis from the region demonstrating that frequent fires have occurred in the closed canopy forests since at least the early Holocene (~ 9000 BP), prior to occupation by sedentary agriculturalists. Following the arrival of agriculture around 4600 BP, the system transitioned from climate controlled to anthropogenic control. During the Maya period, changes in fire regime are muted and do not appear to be driven by changes in climate conditions. Low charcoal influx and fire frequency in the Earliest Preclassic period suggest that land use strategies may have included intensive agriculture much earlier than previously thought. Preliminary results showing concentrations of soot/black-carbon during the middle and late Preclassic periods are lower than modern background values, providing intriguing implications regarding the efficiency of Maya fuel consumption.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2015.09.012","usgsCitation":"Anderson, L., and Wahl, D.B., 2016, Two Holocene paleofire records from Peten, Guatemala: Implications for natural fire regime and prehispanic Maya land use: Global and Planetary Change, v. 138, p. 82-92, https://doi.org/10.1016/j.gloplacha.2015.09.012.","productDescription":"11 p.","startPage":"82","endPage":"92","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060515","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gloplacha.2015.09.012","text":"Publisher Index Page"},{"id":312843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Guatemala","state":"Peten","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.72235107421874,\n 17.808841135842886\n ],\n [\n -89.6649169921875,\n 17.808841135842886\n ],\n [\n -89.61822509765625,\n 17.371610024104744\n ],\n [\n -89.83795166015625,\n 17.041029311689186\n ],\n [\n -90.13732910156249,\n 17.012141149739257\n ],\n [\n -90.60150146484375,\n 17.012141149739257\n ],\n [\n -90.79925537109375,\n 17.27984137051228\n ],\n [\n -90.72235107421874,\n 17.808841135842886\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"138","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3c1e4b0a04ef491a226","chorus":{"doi":"10.1016/j.gloplacha.2015.09.012","url":"http://dx.doi.org/10.1016/j.gloplacha.2015.09.012","publisher":"Elsevier BV","authors":"Anderson Lysanna, Wahl David","journalName":"Global and Planetary Change","publicationDate":"3/2016"},"contributors":{"authors":[{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":572278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, David B. 0000-0002-0451-3554 dwahl@usgs.gov","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":3433,"corporation":false,"usgs":true,"family":"Wahl","given":"David","email":"dwahl@usgs.gov","middleInitial":"B.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true}],"preferred":true,"id":572279,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156410,"text":"70156410 - 2016 - Copahue volcano and its regional magmatic setting","interactions":[],"lastModifiedDate":"2018-08-24T12:29:54","indexId":"70156410","displayToPublicDate":"2015-09-22T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Copahue volcano and its regional magmatic setting","docAbstract":"

Copahue volcano (Province of Neuquen, Argentina) has produced lavas and strombolian deposits over several 100,000s of years, building a rounded volcano with a 3 km elevation. The products are mainly basaltic andesites, with the 2000–2012 eruptive products the most mafic. The geochemistry of Copahue products is compared with those of the main Andes arc (Llaima, Callaqui, Tolhuaca), the older Caviahue volcano directly east of Copahue, and the back arc volcanics of the Loncopue graben. The Caviahue rocks resemble the main Andes arc suite, whereas the Copahue rocks are characterized by lower Fe and Ti contents and higher incompatible element concentrations. The rocks have negative Nb-Ta anomalies, modest enrichments in radiogenic Sr and Pb isotope ratios and slightly depleted Nd isotope ratios. The combined trace element and isotopic data indicate that Copahue magmas formed in a relatively dry mantle environment, with melting of a subducted sediment residue. The back arc basalts show a wide variation in isotopic composition, have similar water contents as the Copahue magmas and show evidence for a subducted sedimentary component in their source regions. The low 206Pb/204Pb of some backarc lava flows suggests the presence of a second endmember with an EM1 flavor in its source. The overall magma genesis is explained within the context of a subducted slab with sediment that gradually looses water, water-mobile elements, and then switches to sediment melt extracts deeper down in the subduction zone. With the change in element extraction mechanism with depth comes a depletion and fractionation of the subducted complex that is reflected in the isotope and trace element signatures of the products from the main arc to Copahue to the back arc basalts.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Copahue Volcano","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Heidelburg, Germany","doi":"10.1007/978-3-662-48005-2_5","usgsCitation":"Varekamp, J.C., Zareski, J.E., Camfield, L.M., and Todd, E., 2016, Copahue volcano and its regional magmatic setting, chap. of Copahue Volcano, p. 81-117, https://doi.org/10.1007/978-3-662-48005-2_5.","productDescription":"37 p.","startPage":"81","endPage":"117","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068587","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":318956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, Chile","otherGeospatial":"Copahue volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.18831634521484,\n -37.87878283303809\n ],\n [\n -71.18831634521484,\n -37.84273253222221\n ],\n [\n -71.13407135009766,\n -37.84273253222221\n ],\n [\n -71.13407135009766,\n -37.87878283303809\n ],\n [\n -71.18831634521484,\n -37.87878283303809\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-22","publicationStatus":"PW","scienceBaseUri":"56ed26afe4b0f59b85db09ec","contributors":{"authors":[{"text":"Varekamp, J. C.","contributorId":146816,"corporation":false,"usgs":false,"family":"Varekamp","given":"J.","email":"","middleInitial":"C.","affiliations":[{"id":16751,"text":"Earth and Environmental Sciences Wesleyan Univeristy Middletown, CT","active":true,"usgs":false}],"preferred":false,"id":569058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zareski, J. E.","contributorId":146817,"corporation":false,"usgs":false,"family":"Zareski","given":"J.","email":"","middleInitial":"E.","affiliations":[{"id":16751,"text":"Earth and Environmental Sciences Wesleyan Univeristy Middletown, CT","active":true,"usgs":false}],"preferred":false,"id":569059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camfield, L. M.","contributorId":146818,"corporation":false,"usgs":false,"family":"Camfield","given":"L.","email":"","middleInitial":"M.","affiliations":[{"id":16751,"text":"Earth and Environmental Sciences Wesleyan Univeristy Middletown, CT","active":true,"usgs":false}],"preferred":false,"id":569060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Erin 0000-0002-4871-9730 etodd@usgs.gov","orcid":"https://orcid.org/0000-0002-4871-9730","contributorId":202811,"corporation":false,"usgs":true,"family":"Todd","given":"Erin","email":"etodd@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":569057,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160492,"text":"70160492 - 2016 - Transforming ecosystems: When, where, and how to restore contaminated sites","interactions":[],"lastModifiedDate":"2017-03-03T09:08:43","indexId":"70160492","displayToPublicDate":"2015-09-15T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Transforming ecosystems: When, where, and how to restore contaminated sites","docAbstract":"

Chemical contamination has impaired ecosystems, reducing biodiversity and the provisioning of functions and services. This has spurred a movement to restore contaminated ecosystems and develop and implement national and international regulations that require it. Nevertheless, ecological restoration remains a young and rapidly growing discipline and its intersection with toxicology is even more nascent and underdeveloped. Consequently, we provide guidance to scientists and practitioners on when, where, and how to restore contaminated ecosystems. Although restoration has many benefits, it also can be expensive, and in many cases systems can recover without human intervention. Hence, the first question we address is: “When should we restore contaminated ecosystems?” Second, we provide suggestions on what to restore—biodiversity, functions, services, all 3, or something else—and where to restore given expected changes to habitats driven by global climate change. Finally, we provide guidance on how to restore contaminated ecosystems. To do this, we analyze critical aspects of the literature dealing with the ecology of restoring contaminated ecosystems. Additionally, we review approaches for translating the science of restoration to on-the-ground actions, which includes discussions of market incentives and the finances of restoration, stakeholder outreach and governance models for ecosystem restoration, and working with contractors to implement restoration plans. By explicitly considering the mechanisms and strategies that maximize the success of the restoration of contaminated sites, we hope that our synthesis serves to increase and improve collaborations between restoration ecologists and ecotoxicologists and set a roadmap for the restoration of contaminated ecosystems.

","language":"English","publisher":"SETAC","publisherLocation":"Pensacola, FL","doi":"10.1002/ieam.1668","collaboration":"University of South Florida; University of Toronto-Scarborough; Colorado State University; Indiana Department Environmental Management; Dewberry, Inc.; ExxonMobil Biomedical Sciences","usgsCitation":"Rohr, J.R., Farag, A.M., Cadotte, M.W., Clements, W.H., Smith, J.R., Ulrich, C.P., and Woods, R., 2016, Transforming ecosystems: When, where, and how to restore contaminated sites: Integrated Environmental Assessment and Management, v. 12, no. 2, p. 273-283, https://doi.org/10.1002/ieam.1668.","productDescription":"11 p.","startPage":"273","endPage":"283","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063292","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":471457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1668","text":"Publisher Index Page"},{"id":312567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-01","publicationStatus":"PW","scienceBaseUri":"567930d7e4b0da412f4fb5b4","chorus":{"doi":"10.1002/ieam.1668","url":"http://dx.doi.org/10.1002/ieam.1668","publisher":"Wiley-Blackwell","authors":"Rohr Jason R, Farag Aïda M, Cadotte Marc W, Clements William H, Smith James R, Ulrich Cheryl P, Woods Richard","journalName":"Integrated Environmental Assessment and Management","publicationDate":"9/15/2015","auditedOn":"9/25/2015"},"contributors":{"authors":[{"text":"Rohr, Jason R.","contributorId":18502,"corporation":false,"usgs":true,"family":"Rohr","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":582994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farag, Aida M. 0000-0003-4247-6763 aida_farag@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6763","contributorId":1139,"corporation":false,"usgs":true,"family":"Farag","given":"Aida","email":"aida_farag@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":582993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cadotte, Marc W.","contributorId":150761,"corporation":false,"usgs":false,"family":"Cadotte","given":"Marc","email":"","middleInitial":"W.","affiliations":[{"id":18096,"text":"University of Toronto-Scarborough, Biological Sciences, Scarborough, ON, M1C","active":true,"usgs":false}],"preferred":false,"id":582995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clements, William H.","contributorId":39504,"corporation":false,"usgs":true,"family":"Clements","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":582996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, James R.","contributorId":150762,"corporation":false,"usgs":false,"family":"Smith","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":18097,"text":"Indiana Department Environmental Management, Office of Land Quality, 100 N. Senate Ave., Indianapolis, IN","active":true,"usgs":false}],"preferred":false,"id":582997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ulrich, Cheryl P.","contributorId":150763,"corporation":false,"usgs":false,"family":"Ulrich","given":"Cheryl","email":"","middleInitial":"P.","affiliations":[{"id":18098,"text":"Dewberry, Inc., 7220 Financial Way, Suite 200, Jacksonville, FL","active":true,"usgs":false}],"preferred":false,"id":582998,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woods, Richard","contributorId":150764,"corporation":false,"usgs":false,"family":"Woods","given":"Richard","email":"","affiliations":[{"id":18099,"text":"ExxonMobil Biomedical Sciences Inc. 1545 RT 22 East, Annandale NJ","active":true,"usgs":false}],"preferred":false,"id":582999,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159174,"text":"70159174 - 2016 - Bayesian data analysis in population ecology: motivations, methods, and benefits","interactions":[],"lastModifiedDate":"2016-07-11T15:42:38","indexId":"70159174","displayToPublicDate":"2015-09-07T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3103,"text":"Population Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian data analysis in population ecology: motivations, methods, and benefits","docAbstract":"

During the 20th century ecologists largely relied on the frequentist system of inference for the analysis of their data. However, in the past few decades ecologists have become increasingly interested in the use of Bayesian methods of data analysis. In this article I provide guidance to ecologists who would like to decide whether Bayesian methods can be used to improve their conclusions and predictions. I begin by providing a concise summary of Bayesian methods of analysis, including a comparison of differences between Bayesian and frequentist approaches to inference when using hierarchical models. Next I provide a list of problems where Bayesian methods of analysis may arguably be preferred over frequentist methods. These problems are usually encountered in analyses based on hierarchical models of data. I describe the essentials required for applying modern methods of Bayesian computation, and I use real-world examples to illustrate these methods. I conclude by summarizing what I perceive to be the main strengths and weaknesses of using Bayesian methods to solve ecological inference problems.

","language":"English","publisher":"Springer Japan","publisherLocation":"Tokyo, Japan","doi":"10.1007/s10144-015-0503-4","usgsCitation":"Dorazio, R., 2016, Bayesian data analysis in population ecology: motivations, methods, and benefits: Population Ecology, v. 58, no. 1, p. 31-44, https://doi.org/10.1007/s10144-015-0503-4.","productDescription":"14 p.","startPage":"31","endPage":"44","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060523","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":310033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","publicComments":"This manuscript was submitted for the special feature based on a symposium in Tsukuba, Japan, held on 11 October 2014.","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-07","publicationStatus":"PW","scienceBaseUri":"5626143be4b0fb9a11dd75f1","contributors":{"authors":[{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":149286,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":577750,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187374,"text":"70187374 - 2016 - Multi‐season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population","interactions":[],"lastModifiedDate":"2019-12-30T09:19:56","indexId":"70187374","displayToPublicDate":"2015-09-07T13:12:14","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi‐season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population","title":"Multi‐season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population","docAbstract":"

Critical information for evaluating the effectiveness of management strategies for species of concern include distinguishing seldom occupied (or low‐quality) habitat from habitat that is frequently occupied and thus contributes substantially to population trends. Using multi‐season models that account for imperfect detection and a long‐term (1981–2002) dataset on migratory Arctic Peregrine Falcons Falco peregrinus tundrius nesting along the Colville River, Alaska, we quantified the effects of previous year's productivity (i.e. site quality), amount of prey habitat, topography, climate, competition and year on occupancy dynamics across two spatial scales (nest‐sites, cliffs) during recovery of the population. Initial occupancy probability was positively correlated with area of surrounding prey habitat and height of nest‐sites above the Colville River. Colonization probability was positively correlated with nest height and negatively correlated with date of snowmelt. Local extinction probability was negatively correlated with productivity, area of prey habitat and nest height. Colonization and local extinction probabilities were also positively and negatively correlated, respectively, with year. Our results suggest that nest‐sites (or cliffs) along the Colville River do not need equal protection measures. Nest‐sites and cliffs with historically higher productivity were occupied most frequently and had lower probability of local extinction. These sites were on cliffs high above the river drainage, surrounded by adequate prey habitat and with southerly aspects associated with early snowmelt and warmer microclimates in spring. Protecting these sites is likely to encourage continued occupancy by Arctic Peregrine Falcons along the Colville River and other similar areas. Our findings also illustrate the importance of evaluating fitness parameters along with climate and habitat features when analysing occupancy dynamics, particularly with a long‐term dataset spanning a range of annual climate variation.

","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12313","usgsCitation":"Bruggeman, J.E., Swem, T., Andersen, D., Kennedy, P.L., and Debora Nigro, 2016, Multi‐season occupancy models identify biotic and abiotic factors influencing a recovering Arctic Peregrine Falcon Falco peregrinus tundrius population: Ibis, v. 158, no. 1, p. 61-74, https://doi.org/10.1111/ibi.12313.","productDescription":"14 p.","startPage":"61","endPage":"74","ipdsId":"IP-050764","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":370113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Colville River Special Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.521728515625,\n 68.31002672261663\n ],\n [\n -151.11694335937497,\n 68.31002672261663\n ],\n [\n -151.11694335937497,\n 70.11422207508899\n ],\n [\n -158.521728515625,\n 70.11422207508899\n ],\n [\n -158.521728515625,\n 68.31002672261663\n ]\n ]\n ]\n }\n }\n ]\n}\n","volume":"158","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Bruggeman, Jason E.","contributorId":18983,"corporation":false,"usgs":false,"family":"Bruggeman","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":776972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swem, Ted","contributorId":64463,"corporation":false,"usgs":true,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":776973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":2168,"corporation":false,"usgs":true,"family":"Andersen","given":"David E.","email":"dea@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":true,"id":693637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Patricia L.","contributorId":172826,"corporation":false,"usgs":false,"family":"Kennedy","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":776974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Debora Nigro","contributorId":217532,"corporation":false,"usgs":false,"family":"Debora Nigro","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":776975,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162240,"text":"70162240 - 2016 - Assessing the robustness of quantitative fatty acid signature analysis to assumption violations","interactions":[],"lastModifiedDate":"2016-01-20T12:38:41","indexId":"70162240","displayToPublicDate":"2015-09-06T12:30:00","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":"Assessing the robustness of quantitative fatty acid signature analysis to assumption violations","docAbstract":"

 

\n
    \n
  1. Knowledge of animal diets can provide important insights into life history and ecology, relationships among species in a community and potential response to ecosystem change or perturbation. Quantitative fatty acid signature analysis (QFASA) is a method of estimating diets from data on the composition, or signature, of fatty acids stored in adipose tissue. Given data on signatures of potential prey, a predator diet is estimated by minimizing the distance between its signature and a mixture of prey signatures. Calibration coefficients, constants derived from feeding trials, are used to account for differential metabolism of individual fatty acids. QFASA has been widely applied since its introduction and several variants of the original estimator have appeared in the literature. However, work to compare the statistical properties of QFASA estimators has been limited.
    2. \n
  2. One important characteristic of an estimator is its robustness to violations of model assumptions. The primary assumptions of QFASA are that prey signature data contain representatives of all prey types consumed and the calibration coefficients are known without error. We investigated the robustness of two QFASA estimators to a range of violations of these assumptions using computer simulation and recorded the resulting bias in diet estimates.
    3. \n
  3. We found that the Aitchison distance measure was most robust to errors in the calibration coefficients. Conversely, the Kullback–Leibler distance measure was most robust to the consumption of prey without representation in the prey signature data.
    4. \n
  4. In most QFASA applications, investigators will generally have some knowledge of the prey available to predators and be able to assess the completeness of prey signature data and sample additional prey as necessary. Conversely, because calibration coefficients are derived from feeding trials with captive animals and their values may be sensitive to consumer physiology and nutritional status, their applicability to free-ranging animals is difficult to establish. We therefore recommend that investigators first make any improvements to the prey signature data that seem warranted and then base estimation on the Aitchison distance measure, as it appears to minimize risk from violations of the assumption that is most difficult to verify.
    5. \n
","language":"English","publisher":"John Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/2041-210X.12456","usgsCitation":"Bromaghin, J.F., Budge, S.M., Thiemann, G.W., and Rode, K.D., 2016, Assessing the robustness of quantitative fatty acid signature analysis to assumption violations: Methods in Ecology and Evolution, v. 7, no. 1, p. 51-59, https://doi.org/10.1111/2041-210X.12456.","productDescription":"9 p.","startPage":"51","endPage":"59","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064116","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471459,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.12456","text":"Publisher Index Page"},{"id":438651,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7T2W","text":"USGS data release","linkHelpText":"Assessing the robustness of quantitative fatty acid signature analysis to assumption violations (Supplementary data)"},{"id":438650,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7N877TK","text":"USGS data release","linkHelpText":"QFASA Robustness to Assumption Violations: Computer Code"},{"id":314526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-06","publicationStatus":"PW","scienceBaseUri":"56a0bdc6e4b0961cf280dc10","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":588963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budge, Suzanne M.","contributorId":92168,"corporation":false,"usgs":false,"family":"Budge","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":589117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":589118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":589119,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157074,"text":"70157074 - 2016 - Seasonal and spatial patterns of growth of rainbow trout in the Colorado River in Grand Canyon, AZ","interactions":[],"lastModifiedDate":"2016-05-25T16:26:44","indexId":"70157074","displayToPublicDate":"2015-09-01T12:15:00","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":"Seasonal and spatial patterns of growth of rainbow trout in the Colorado River in Grand Canyon, AZ","docAbstract":"

Rainbow trout (Oncorhynchus mykiss) have been purposely introduced in many regulated rivers, with inadvertent consequences on native fishes. We describe how trout growth rates and condition could be influencing trout population dynamics in a 130 km section of the Colorado River below Glen Canyon Dam based on a large-scale mark–recapture program where ∼8000 rainbow trout were recaptured over a 3-year period (2012–2014). There were strong temporal and spatial variations in growth in both length and weight as predicted from von Bertalanffy and bioenergetic models, respectively. There was more evidence for seasonal variation in the growth coefficient and annual variation in the asymptotic length. Bioenergetic models showed more variability for growth in weight across seasons and years than across reaches. These patterns were consistent with strong seasonal variation in invertebrate drift and effects of turbidity on foraging efficiency. Highest growth rates and relative condition occurred in downstream reaches with lower trout densities. Results indicate that reduction in rainbow trout abundance in Glen Canyon will likely increase trout size in the tailwater fishery and may reduce downstream dispersal into Grand Canyon.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0102","usgsCitation":"Yard, M.D., Korman, J., Walters, C.J., and Kennedy, T., 2016, Seasonal and spatial patterns of growth of rainbow trout in the Colorado River in Grand Canyon, AZ: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 1, p. 125-139, https://doi.org/10.1139/cjfas-2015-0102.","productDescription":"15 p.","startPage":"125","endPage":"139","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063595","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488749,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/70979","text":"External Repository"},{"id":307998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.313232421875,\n 35.97356075349624\n ],\n [\n -112.313232421875,\n 36.99816565700228\n ],\n [\n -111.1651611328125,\n 36.99816565700228\n ],\n [\n -111.1651611328125,\n 35.97356075349624\n ],\n [\n -112.313232421875,\n 35.97356075349624\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f15832e4b0dacf699eb978","contributors":{"authors":[{"text":"Yard, Micheal D. myard@usgs.gov","contributorId":147386,"corporation":false,"usgs":true,"family":"Yard","given":"Micheal","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":571505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korman, Josh","contributorId":29922,"corporation":false,"usgs":true,"family":"Korman","given":"Josh","affiliations":[],"preferred":false,"id":571506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Carl J.","contributorId":25122,"corporation":false,"usgs":true,"family":"Walters","given":"Carl","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":571507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, T.A.","contributorId":86155,"corporation":false,"usgs":true,"family":"Kennedy","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":571804,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157483,"text":"70157483 - 2016 - 1DTempPro V2: new features for inferring groundwater/surface-water exchange","interactions":[],"lastModifiedDate":"2016-05-12T10:28:50","indexId":"70157483","displayToPublicDate":"2015-09-01T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1866,"text":"Groundwater Monitoring & Remediation","active":true,"publicationSubtype":{"id":10}},"title":"1DTempPro V2: new features for inferring groundwater/surface-water exchange","docAbstract":"

A new version of the computer program 1DTempPro extends the original code to include new capabilities for (1) automated parameter estimation, (2) layer heterogeneity, and (3) time-varying specific discharge. The code serves as an interface to the U.S. Geological Survey model VS2DH and supports analysis of vertical one-dimensional temperature profiles under saturated flow conditions to assess groundwater/surface-water exchange and estimate hydraulic conductivity for cases where hydraulic head is known.

","language":"English","publisher":"National Ground Water Association","publisherLocation":"Worthington, OH","doi":"10.1111/gwat.12369","collaboration":"US EPA; USGS Groundwater Resources Program; USGS Toxic Substances Hydrology Program","usgsCitation":"Koch, F.W., Voytek, E.B., Day-Lewis, F.D., Healy, R.W., Briggs, M.A., Lane, J.W., and Werkema, D.D., 2016, 1DTempPro V2: new features for inferring groundwater/surface-water exchange: Groundwater Monitoring & Remediation, v. 54, no. 3, p. 434-439, https://doi.org/10.1111/gwat.12369.","productDescription":"6 p.","startPage":"434","endPage":"439","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066878","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":438652,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76T0JQS","text":"USGS data release","linkHelpText":"1DTempPro: A program for analysis of vertical one-dimensional (1D) temperature profiles"},{"id":309369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-15","publicationStatus":"PW","scienceBaseUri":"560d07abe4b058f706e542f3","contributors":{"authors":[{"text":"Koch, Franklin W.","contributorId":147929,"corporation":false,"usgs":false,"family":"Koch","given":"Franklin","email":"","middleInitial":"W.","affiliations":[{"id":16958,"text":"USGS, OGW Branch of Geophysics & Univ. of Calgary","active":true,"usgs":false}],"preferred":false,"id":573286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voytek, Emily B. 0000-0003-0981-453X ebvoytek@usgs.gov","orcid":"https://orcid.org/0000-0003-0981-453X","contributorId":3575,"corporation":false,"usgs":true,"family":"Voytek","given":"Emily","email":"ebvoytek@usgs.gov","middleInitial":"B.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":573285,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":573287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":573288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":573289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":573290,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":573291,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169235,"text":"70169235 - 2016 - Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area","interactions":[],"lastModifiedDate":"2016-05-17T16:10:22","indexId":"70169235","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1350,"text":"Cryosphere Discussions","active":true,"publicationSubtype":{"id":10}},"title":"Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area","docAbstract":"

 We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future permafrost distribution can be made for the Tibetan Plateau.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/tc-10-287-2016","usgsCitation":"Wang, A., Moore, J., Cui, X., Ji, D., Li, Q., Zhang, N., Wang, C., Zhang, S., Lawrence, D., McGuire, A., Zhang, W., Delire, C., Koven, C., Saito, K., MacDougall, A., Burke, E., and Decharme, B., 2016, Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area: Cryosphere Discussions, v. 10, no. 1, p. 287-306, https://doi.org/10.5194/tc-10-287-2016.","productDescription":"20 p.","startPage":"287","endPage":"306","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063587","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471461,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-10-287-2016","text":"Publisher Index Page"},{"id":319368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Tibeta Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.68242645263672,\n 46.13036330589103\n ],\n [\n -89.68242645263672,\n 46.150107913663334\n ],\n [\n -89.65873718261719,\n 46.150107913663334\n ],\n [\n -89.65873718261719,\n 46.13036330589103\n ],\n [\n -89.68242645263672,\n 46.13036330589103\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.73096370697021,\n 45.77300107536654\n ],\n [\n -89.73096370697021,\n 45.78153149170592\n ],\n [\n -89.71843242645264,\n 45.78153149170592\n ],\n [\n -89.71843242645264,\n 45.77300107536654\n ],\n [\n -89.73096370697021,\n 45.77300107536654\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 77.82714843749999,\n 28.729130483430154\n ],\n [\n 77.82714843749999,\n 40.04443758460859\n ],\n [\n 105.5126953125,\n 40.04443758460859\n ],\n [\n 105.5126953125,\n 28.729130483430154\n ],\n [\n 77.82714843749999,\n 28.729130483430154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-05","publicationStatus":"PW","scienceBaseUri":"56f50fb7e4b0f59b85e1ead7","contributors":{"authors":[{"text":"Wang, A.","contributorId":46735,"corporation":false,"usgs":true,"family":"Wang","given":"A.","email":"","affiliations":[],"preferred":false,"id":623699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, J.C.","contributorId":95141,"corporation":false,"usgs":true,"family":"Moore","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":623700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cui, Xingquan","contributorId":150229,"corporation":false,"usgs":false,"family":"Cui","given":"Xingquan","email":"","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":623701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ji, D.","contributorId":167827,"corporation":false,"usgs":false,"family":"Ji","given":"D.","email":"","affiliations":[],"preferred":false,"id":623702,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Q.","contributorId":85397,"corporation":false,"usgs":true,"family":"Li","given":"Q.","affiliations":[],"preferred":false,"id":623703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, N.","contributorId":26520,"corporation":false,"usgs":true,"family":"Zhang","given":"N.","email":"","affiliations":[],"preferred":false,"id":623704,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, C.","contributorId":50689,"corporation":false,"usgs":true,"family":"Wang","given":"C.","email":"","affiliations":[],"preferred":false,"id":623705,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhang, S.","contributorId":51064,"corporation":false,"usgs":true,"family":"Zhang","given":"S.","email":"","affiliations":[],"preferred":false,"id":623706,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lawrence, D.M.","contributorId":98608,"corporation":false,"usgs":true,"family":"Lawrence","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":623707,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McGuire, A. D.","contributorId":16552,"corporation":false,"usgs":true,"family":"McGuire","given":"A. D.","affiliations":[],"preferred":false,"id":623708,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zhang, W.","contributorId":92399,"corporation":false,"usgs":true,"family":"Zhang","given":"W.","email":"","affiliations":[],"preferred":false,"id":623709,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Delire, C.","contributorId":167821,"corporation":false,"usgs":false,"family":"Delire","given":"C.","affiliations":[],"preferred":false,"id":623710,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Koven, C.","contributorId":39655,"corporation":false,"usgs":true,"family":"Koven","given":"C.","email":"","affiliations":[],"preferred":false,"id":623711,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Saito, K.","contributorId":167823,"corporation":false,"usgs":false,"family":"Saito","given":"K.","email":"","affiliations":[],"preferred":false,"id":623712,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"MacDougall, A.","contributorId":167822,"corporation":false,"usgs":false,"family":"MacDougall","given":"A.","affiliations":[],"preferred":false,"id":623713,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Burke, E.","contributorId":167820,"corporation":false,"usgs":false,"family":"Burke","given":"E.","affiliations":[],"preferred":false,"id":623714,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Decharme, B.","contributorId":167825,"corporation":false,"usgs":false,"family":"Decharme","given":"B.","affiliations":[],"preferred":false,"id":623715,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70159326,"text":"70159326 - 2016 - Prediction of plant vulnerability to salinity increase in a coastal ecosystem by stable isotopic composition (δ18O) of plant stem water: a model study","interactions":[],"lastModifiedDate":"2016-08-25T08:32:50","indexId":"70159326","displayToPublicDate":"2015-09-01T00:00:00","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":"Prediction of plant vulnerability to salinity increase in a coastal ecosystem by stable isotopic composition (δ18O) of plant stem water: a model study","docAbstract":"

Sea level rise and the subsequent intrusion of saline seawater can result in an increase in soil salinity, and potentially cause coastal salinity-intolerant vegetation (for example, hardwood hammocks or pines) to be replaced by salinity-tolerant vegetation (for example, mangroves or salt marshes). Although the vegetation shifts can be easily monitored by satellite imagery, it is hard to predict a particular area or even a particular tree that is vulnerable to such a shift. To find an appropriate indicator for the potential vegetation shift, we incorporated stable isotope 18O abundance as a tracer in various hydrologic components (for example, vadose zone, water table) in a previously published model describing ecosystem shifts between hammock and mangrove communities in southern Florida. Our simulations showed that (1) there was a linear relationship between salinity and the δ18O value in the water table, whereas this relationship was curvilinear in the vadose zone; (2) hammock trees with higher probability of being replaced by mangroves had higher δ18O values of plant stem water, and this difference could be detected 2 years before the trees reached a tipping point, beyond which future replacement became certain; and (3) individuals that were eventually replaced by mangroves from the hammock tree population with a 50% replacement probability had higher stem water δ18O values 3 years before their replacement became certain compared to those from the same population which were not replaced. Overall, these simulation results suggest that it is promising to track the yearly δ18O values of plant stem water in hammock forests to predict impending salinity stress and mortality.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-015-9916-3","usgsCitation":"Zhai, L., Jiang, J., DeAngelis, D.L., and Sternberg, L.D., 2016, Prediction of plant vulnerability to salinity increase in a coastal ecosystem by stable isotopic composition (δ18O) of plant stem water: a model study: Ecosystems, v. 19, no. 1, p. 32-49, https://doi.org/10.1007/s10021-015-9916-3.","productDescription":"18 p.","startPage":"32","endPage":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068438","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":310336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-21","publicationStatus":"PW","scienceBaseUri":"562a08e5e4b011227bf1fdbd","contributors":{"authors":[{"text":"Zhai, Lu","contributorId":147395,"corporation":false,"usgs":false,"family":"Zhai","given":"Lu","affiliations":[{"id":16839,"text":"Department of Biology, University of Miami, Coral Gables, Florida","active":true,"usgs":false}],"preferred":false,"id":578048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jiang, Jiang","contributorId":46838,"corporation":false,"usgs":true,"family":"Jiang","given":"Jiang","affiliations":[],"preferred":false,"id":578049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":578016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sternberg, Leonel d.S.L","contributorId":67051,"corporation":false,"usgs":true,"family":"Sternberg","given":"Leonel","email":"","middleInitial":"d.S.L","affiliations":[],"preferred":false,"id":578050,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156835,"text":"70156835 - 2016 - Experimental infection of six North American fish species with the North Carolina strain of spring Viremia of Carp Virus","interactions":[],"lastModifiedDate":"2016-12-19T11:46:49","indexId":"70156835","displayToPublicDate":"2015-08-31T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":853,"text":"Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Experimental infection of six North American fish species with the North Carolina strain of spring Viremia of Carp Virus","docAbstract":"

Spring viremia of carp virus (SVCV) is a rhabdoviral pathogen associated with disease outbreaks in cultured and wild fish worldwide. Common carp (Cyprinus carpio carp), and koi (C. carpio koi) suffer the highest mortalities from SVCV infections, while other cyprinid fish species have varying susceptibility. Although salmonid fish typically are considered refractory to infection by SVCV, there have been a few reports suggesting infection has occurred in rainbow trout (Oncorhynchus mykiss). There have been no reports of Percid fish being infected with SVCV. Since the first North American outbreak of SVCV at a North Carolina koi farm in 2002 there have been eight subsequent detections or outbreaks of SVCV among fish species from the families of Cyprinidae andCentrarchidae within the US and Canada. Thus, this exotic virus is considered a potential threat to native and cultured fish populations in North America. We performed multiple experimental challenges with fish species from three families (Salmonidae, Cyprinidae, and Percidae) to identify the potential risk associated with SVCV exposure of resident fish populations in North America.

\n

Three salmonid species, rainbow and steelhead trout (Oncorhynchus mykiss), Chinook salmon (O. tshawytscha), and sockeye salmon (O. nerka), were challenged by immersion or injection with the North Carolina SVCV isolate. Two cyprinid species, koi and fathead minnow (Pimephales promelas) and one percid species, yellow perch (Perca flavescens) were also challenged. Koi were highly susceptible to SVCV up to 11 months of age and fathead minnows had chronic disease expression with moderate mortality (29%). SVCV also induced moderate mortalities (33%) in yellow perch fry. Virus challenged salmonid fish had cumulative percent mortalities ranging from 0 to 100%, with sockeye salmon fry being the most vulnerable. A sub-sample of mortalities and survivors were screened for virus by plaque assay and reverse transcription polymerase chain reaction. In general, all mortalities tested positive for SVCV with high viral titers while survivors had variable persistence of SVCV with overall lower virus titers. Our SVCV challenges of multiple North American fish species suggested that host age is a key factor in determining disease outcome. Other factors, such as fish broodstock, virus strain, water temperature, and rearing conditions in association with the intrinsic level of species susceptibility may also impact infection dynamics. This is the first report of SVCV infecting a species (yellow perch) in the family Percidae and that sockeye salmon fry can suffer similarly high mortalities as the primary SVCV host species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaculture.2015.07.007","usgsCitation":"Emmenegger, E.J., Sanders, G.E., Conway, C.M., Binkowski, F.P., Winton, J., and Kurath, G., 2016, Experimental infection of six North American fish species with the North Carolina strain of spring Viremia of Carp Virus: Aquaculture, v. 450, p. 273-282, https://doi.org/10.1016/j.aquaculture.2015.07.007.","productDescription":"10 p.","startPage":"273","endPage":"282","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065791","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":471462,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquaculture.2015.07.007","text":"Publisher Index Page"},{"id":307724,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"450","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e56ca3e4b05561fa208670","chorus":{"doi":"10.1016/j.aquaculture.2015.07.007","url":"http://dx.doi.org/10.1016/j.aquaculture.2015.07.007","publisher":"Elsevier BV","authors":"Emmenegger Eveline J., Sanders George E., Conway Carla M., Binkowski Fred P., Winton James R., Kurath Gael","journalName":"Aquaculture","publicationDate":"1/2016"},"contributors":{"authors":[{"text":"Emmenegger, Eveline J. 0000-0001-5217-6030 eemmenegger@usgs.gov","orcid":"https://orcid.org/0000-0001-5217-6030","contributorId":2434,"corporation":false,"usgs":true,"family":"Emmenegger","given":"Eveline","email":"eemmenegger@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":570764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, George E.","contributorId":147207,"corporation":false,"usgs":false,"family":"Sanders","given":"George","email":"","middleInitial":"E.","affiliations":[{"id":16803,"text":"University of Washington, School of Medicine, Dept. of Comparative Medicine, T-160 Health Sciences Center, Seattle, WA 98195","active":true,"usgs":false}],"preferred":false,"id":570765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":570766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Binkowski, Fred P.","contributorId":147208,"corporation":false,"usgs":false,"family":"Binkowski","given":"Fred","email":"","middleInitial":"P.","affiliations":[{"id":16804,"text":"University of Wisconsin-Milwaukee, School of Freshwater Sciences, 600 E. Greenfield Ave., Milwaukee, Wisconsin 53204","active":true,"usgs":false}],"preferred":false,"id":570767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winton, James R. jwinton@usgs.gov","contributorId":147209,"corporation":false,"usgs":true,"family":"Winton","given":"James R.","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":570768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":570769,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155896,"text":"70155896 - 2016 - Effects of wind-energy facilities on grassland bird distributions","interactions":[],"lastModifiedDate":"2018-01-05T11:09:10","indexId":"70155896","displayToPublicDate":"2015-08-18T04:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of wind-energy facilities on grassland bird distributions","docAbstract":"

The contribution of renewable energy to meet worldwide demand continues to grow. Wind energy is one of the fastest growing renewable sectors, but new wind facilities are often placed in prime wildlife habitat. Long-term studies that incorporate a rigorous statistical design to evaluate the effects of wind facilities on wildlife are rare. We conducted a before-after-control-impact (BACI) assessment to determine if wind facilities placed in native mixed-grass prairies displaced breeding grassland birds. During 2003–2012, we monitored changes in bird density in 3 study areas in North Dakota and South Dakota (U.S.A.). We examined whether displacement or attraction occurred 1 year after construction (immediate effect) and the average displacement or attraction 2–5 years after construction (delayed effect). We tested for these effects overall and within distance bands of 100, 200, 300, and >300 m from turbines. We observed displacement for 7 of 9 species. One species was unaffected by wind facilities and one species exhibited attraction. Displacement and attraction generally occurred within 100 m and often extended up to 300 m. In a few instances, displacement extended beyond 300 m. Displacement and attraction occurred 1 year after construction and persisted at least 5 years. Our research provides a framework for applying a BACI design to displacement studies and highlights the erroneous conclusions that can be made without the benefit of adopting such a design. More broadly, species-specific behaviors can be used to inform management decisions about turbine placement and the potential impact to individual species. Additionally, the avoidance distance metrics we estimated can facilitate future development of models evaluating impacts of wind facilities under differing land-use scenarios.

","language":"English","publisher":"Wiley","doi":"10.1111/cobi.12569","usgsCitation":"Shaffer, J.A., and Buhl, D.A., 2016, Effects of wind-energy facilities on grassland bird distributions: Conservation Biology, v. 30, no. 1, p. 59-71, https://doi.org/10.1111/cobi.12569.","productDescription":"13 p.","startPage":"59","endPage":"71","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060722","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":438655,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T43SDG","text":"USGS data release","linkHelpText":"Effects of wind-energy facilities on breeding grassland bird distributions - data release"},{"id":306883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South 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Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":566675,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158933,"text":"70158933 - 2016 - The Upper Mississippi River floodscape: spatial patterns of flood inundation and associated plant community distributions","interactions":[],"lastModifiedDate":"2015-12-21T13:32:03","indexId":"70158933","displayToPublicDate":"2015-08-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":849,"text":"Applied Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"The Upper Mississippi River floodscape: spatial patterns of flood inundation and associated plant community distributions","docAbstract":"

Questions How is the distribution of different plant communities associated with patterns of flood inundation across a large floodplain landscape? Location Thirty-eight thousand nine hundred and seventy hectare of floodplain, spanning 320 km of the Upper Mississippi River (UMR). Methods High-resolution elevation data (Lidar) and 30 yr of daily river stage data were integrated to produce a ‘floodscape’ map of growing season flood inundation duration. The distributions of 16 different remotely sensed plant communities were quantified along the gradient of flood duration. Results Models fitted to the cumulative frequency of occurrence of different vegetation types as a function of flood duration showed that most types exist along a continuum of flood-related occurrence. The diversity of community types was greatest at high elevations (0–10 d of flooding), where both upland and lowland community types were found, as well as at very low elevations (70–180 d of flooding), where a variety of lowland herbaceous communities were found. Intermediate elevations (20–60 d of flooding) tended to be dominated by floodplain forest and had the lowest diversity of community types. Conclusions Although variation in flood inundation is often considered to be the main driver of spatial patterns in floodplain plant communities, few studies have quantified flood–vegetation relationships at broad scales. Our results can be used to identify targets for restoration of historical hydrological regimes or better anticipate hydro-ecological effects of climate change at broad scales.

","language":"English","publisher":"International Association for Vegetation Science","doi":"10.1111/avsc.12189","usgsCitation":"De Jager, N.R., Rohweder, J.J., Yin, Y., and Hoy, E.E., 2016, The Upper Mississippi River floodscape: spatial patterns of flood inundation and associated plant community distributions: Applied Vegetation Science, v. 19, no. 1, p. 164-172, https://doi.org/10.1111/avsc.12189.","productDescription":"9 p.","startPage":"164","endPage":"172","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064126","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":309735,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/avsc.12189/abstract"},{"id":309799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River","volume":"19","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"5618e535e4b0cdb063e3fef0","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":576944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yin, Yao yyin@usgs.gov","contributorId":2170,"corporation":false,"usgs":true,"family":"Yin","given":"Yao","email":"yyin@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoy, Erin E. 0000-0002-2853-3242 ehoy@usgs.gov","orcid":"https://orcid.org/0000-0002-2853-3242","contributorId":4523,"corporation":false,"usgs":true,"family":"Hoy","given":"Erin","email":"ehoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":576946,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155835,"text":"70155835 - 2016 - Mid-Wisconsin to Holocene permafrost and landscape dynamics based on a drained lake basin core from the northern Seward Peninsula, northwest Alaska","interactions":[],"lastModifiedDate":"2016-03-03T10:52:25","indexId":"70155835","displayToPublicDate":"2015-08-11T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3032,"text":"Permafrost and Periglacial Processes","active":true,"publicationSubtype":{"id":10}},"title":"Mid-Wisconsin to Holocene permafrost and landscape dynamics based on a drained lake basin core from the northern Seward Peninsula, northwest Alaska","docAbstract":"

Permafrost-related processes drive regional landscape dynamics in the Arctic terrestrial system. A better understanding of past periods indicative of permafrost degradation and aggradation is important for predicting the future response of Arctic landscapes to climate change. Here, we used a multi-proxy approach to analyse a ~ 4 m long sediment core from a drained thermokarst lake basin on the northern Seward Peninsula in western Arctic Alaska (USA). Sedimentological, biogeochemical, geochronological, micropalaeontological (ostracoda, testate amoebae) and tephra analyses were used to determine the long-term environmental Early-Wisconsin to Holocene history preserved in our core for central Beringia. Yedoma accumulation dominated throughout the Early to Late-Wisconsin but was interrupted by wetland formation from 44.5 to 41.5 ka BP. The latter was terminated by the deposition of 1 m of volcanic tephra, most likely originating from the South Killeak Maar eruption at about 42 ka BP. Yedoma deposition continued until 22.5 ka BP and was followed by a depositional hiatus in the sediment core between 22.5 and 0.23 ka BP. We interpret this hiatus as due to intense thermokarst activity in the areas surrounding the site, which served as a sediment source during the Late-Wisconsin to Holocene climate transition. The lake forming the modern basin on the upland initiated around 0.23 ka BP and drained catastrophically in spring 2005. The present study emphasises that Arctic lake systems and periglacial landscapes are highly dynamic and that permafrost formation as well as degradation in central Beringia was controlled by regional to global climate patterns as well as by local disturbances.

","language":"English","publisher":"Wiley & Sons","publisherLocation":"Hoboken, NJ","doi":"10.1002/ppp.1848","usgsCitation":"Lenz, J., Grosse, G., Jones, B.M., Anthony, K.M., Bobrov, A., Wulf, S., and Wetterich, S., 2016, Mid-Wisconsin to Holocene permafrost and landscape dynamics based on a drained lake basin core from the northern Seward Peninsula, northwest Alaska: Permafrost and Periglacial Processes, v. 27, no. 1, p. 56-75, https://doi.org/10.1002/ppp.1848.","productDescription":"20 p.","startPage":"56","endPage":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063477","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471465,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ppp.1848","text":"External Repository"},{"id":306584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Seward Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.82763671875,\n 64.85360611714371\n ],\n [\n -165.82763671875,\n 66.67908684186773\n ],\n [\n -162.4658203125,\n 66.67908684186773\n ],\n [\n -162.4658203125,\n 64.85360611714371\n ],\n [\n -165.82763671875,\n 64.85360611714371\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-06","publicationStatus":"PW","scienceBaseUri":"55cb0ea3e4b08400b1fdd459","contributors":{"authors":[{"text":"Lenz, Josefine","contributorId":146181,"corporation":false,"usgs":false,"family":"Lenz","given":"Josefine","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":566545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":566546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":566544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Katey M. Walter","contributorId":82603,"corporation":false,"usgs":true,"family":"Anthony","given":"Katey","email":"","middleInitial":"M. Walter","affiliations":[],"preferred":false,"id":566547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bobrov, Anatoly","contributorId":146184,"corporation":false,"usgs":false,"family":"Bobrov","given":"Anatoly","email":"","affiliations":[{"id":16615,"text":"Moscow State University","active":true,"usgs":false}],"preferred":false,"id":566548,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wulf, Sabine","contributorId":146185,"corporation":false,"usgs":false,"family":"Wulf","given":"Sabine","email":"","affiliations":[{"id":16616,"text":"Helmholtz Center Potsdam","active":true,"usgs":false}],"preferred":false,"id":566549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wetterich, Sebastian","contributorId":146186,"corporation":false,"usgs":false,"family":"Wetterich","given":"Sebastian","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":566550,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156427,"text":"70156427 - 2016 - Mangrove sedimentation and response to relative sea-level rise","interactions":[],"lastModifiedDate":"2016-07-17T23:49:08","indexId":"70156427","displayToPublicDate":"2015-08-01T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":811,"text":"Annual Review of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Mangrove sedimentation and response to relative sea-level rise","docAbstract":"

Mangroves occur on upper intertidal shorelines in the tropics and subtropics. Complex hydrodynamic and salinity conditions influence mangrove distributions, primarily related to elevation and hydroperiod; this review considers how these adjust through time. Accumulation rates of allochthonous and autochthonous sediment, both inorganic and organic, vary between and within different settings. Abundant terrigenous sediment can form dynamic mudbanks; tides redistribute sediment, contrasting with mangrove peat in sediment-starved carbonate settings. Sediments underlying mangroves sequester carbon, but also contain paleoenvironmental records of adjustments to past sea-level changes. Radiometric dating indicates long-term sedimentation, whereas Surface Elevation Table-Marker Horizon measurements (SET-MH) provide shorter perspectives, indicating shallow subsurface processes of root growth and substrate autocompaction. Many tropical deltas also experience deep subsidence, which augments relative sea-level rise. The persistence of mangroves implies an ability to cope with moderately high rates of relative sea-level rise. However, many human pressures threaten mangroves, resulting in continuing decline in their extent throughout the tropics.

","language":"English","publisher":"Annual Reviews","publisherLocation":"Palo Alto, CA","doi":"10.1146/annurev-marine-122414-034025","usgsCitation":"Woodroffe, C., Rogers, K., McKee, K.L., Lovelock, C., Mendelssohn, I., and Saintilan, N., 2016, Mangrove sedimentation and response to relative sea-level rise: Annual Review of Marine Science, v. 8, p. 243-266, https://doi.org/10.1146/annurev-marine-122414-034025.","productDescription":"24 p.","startPage":"243","endPage":"266","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064728","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":307117,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d84bb9e4b0518e3546f022","contributors":{"authors":[{"text":"Woodroffe, CD","contributorId":146847,"corporation":false,"usgs":false,"family":"Woodroffe","given":"CD","affiliations":[{"id":16754,"text":"University of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":569137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogers, K.","contributorId":82823,"corporation":false,"usgs":true,"family":"Rogers","given":"K.","email":"","affiliations":[],"preferred":false,"id":569138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKee, Karen L. 0000-0001-7042-670X mckeek@usgs.gov","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":704,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"mckeek@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":569136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelock, CE","contributorId":146848,"corporation":false,"usgs":false,"family":"Lovelock","given":"CE","email":"","affiliations":[{"id":16755,"text":"University of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":569139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mendelssohn, IA","contributorId":146849,"corporation":false,"usgs":false,"family":"Mendelssohn","given":"IA","email":"","affiliations":[{"id":16756,"text":"Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":569140,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Saintilan, N.","contributorId":49490,"corporation":false,"usgs":true,"family":"Saintilan","given":"N.","email":"","affiliations":[],"preferred":false,"id":569141,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70156307,"text":"70156307 - 2016 - Compact development and VMT: environmental determinism, self-selection, or some of both?","interactions":[],"lastModifiedDate":"2016-08-03T13:08:49","indexId":"70156307","displayToPublicDate":"2015-08-01T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1526,"text":"Environment and Planning B: Planning and Design","active":true,"publicationSubtype":{"id":10}},"title":"Compact development and VMT: environmental determinism, self-selection, or some of both?","docAbstract":"

There is a long-running debate in the planning literature about the effects of the built environment on travel behavior and the degree to which apparent effects are due to the tendency of households to self-select into neighborhoods that reinforce their travel preferences. Those who want to walk will choose walkable neighborhoods, and those who want to use transit will choose transit-served neighborhoods. These households might have walked or used transit more than their neighbors wherever they lived. Most previous studies have shown that individual attitudes attenuate the relationship between the residential environment and travel choices, and so the effect of the built environment on travel may be overestimated. But there are other researchers who argue the reverse, claiming that residential preferences reinforce built environmental influences. This study assesses the relative importance of the built environment and residential preferences/travel attitudes for a sample of 962 households in the Greater Salt Lake region using structural equation modeling. For the sake of simplicity, we extracted two factors using principal component analysis, one representing the built environment and the other representing residential preferences/attitudes. Our findings are consistent with the view that the neighborhood built environment and residential preferences both influence household’s travel, that the built environment is the stronger influence, and that the built environment affects travel through two causal pathways, one direct and the other indirect, through attitudes.

","language":"English","publisher":"Pion Ltd.","publisherLocation":"London,UK","doi":"10.1177/0265813515594811","usgsCitation":"Ewing, R., Hamidi, S., and Grace, J.B., 2016, Compact development and VMT: environmental determinism, self-selection, or some of both?: Environment and Planning B: Planning and Design, v. 43, no. 4, p. 737-755, https://doi.org/10.1177/0265813515594811.","productDescription":"19 p.","startPage":"737","endPage":"755","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052483","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":307099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-03","publicationStatus":"PW","scienceBaseUri":"55d84bb2e4b0518e3546eff4","contributors":{"authors":[{"text":"Ewing, Reid","contributorId":106010,"corporation":false,"usgs":true,"family":"Ewing","given":"Reid","affiliations":[],"preferred":false,"id":569113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamidi, Shima","contributorId":30909,"corporation":false,"usgs":true,"family":"Hamidi","given":"Shima","affiliations":[],"preferred":false,"id":569114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"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":568622,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70150308,"text":"70150308 - 2016 - Corn stover harvest increases herbicide movement to subsurface drains: RZWQM simulations","interactions":[],"lastModifiedDate":"2016-04-28T12:51:11","indexId":"70150308","displayToPublicDate":"2015-07-31T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Corn stover harvest increases herbicide movement to subsurface drains: RZWQM simulations","docAbstract":"
\n

BACKGROUND

\n
\n

Crop residue removal for bioenergy production can alter soil hydrologic properties and the movement of agrochemicals to subsurface drains. The Root Zone Water Quality Model (RZWQM), previously calibrated using measured flow and atrazine concentrations in drainage from a 0.4 ha chisel-tilled plot, was used to investigate effects of 50 and 100% corn (Zea mays L.) stover harvest and the accompanying reductions in soil crust hydraulic conductivity and total macroporosity on transport of atrazine, metolachlor, and metolachlor oxanilic acid (OXA).

\n
\n
\n
\n

RESULTS

\n
\n

The model accurately simulated field-measured metolachlor transport in drainage. A 3-yr simulation indicated that 50% residue removal decreased subsurface drainage by 31% and increased atrazine and metolachlor transport in drainage 4 to 5-fold when surface crust conductivity and macroporosity were reduced by 25%. Based on its measured sorption coefficient, ~ 2-fold reductions in OXA losses were simulated with residue removal.

\n
\n
\n
\n

CONCLUSION

\n
\n

RZWQM indicated that if corn stover harvest reduces crust conductivity and soil macroporosity, losses of atrazine and metolachlor in subsurface drainage will increase due to reduced sorption related to more water moving through fewer macropores. Losses of the metolachlor degradation product OXA will decrease due to the more rapid movement of the parent compound into the soil.

\n
\n
","language":"English","publisher":"Wiley","doi":"10.1002/ps.4087","usgsCitation":"Shipitalo, M.J., Malone, R.W., Ma, L., Nolan, B.T., Kanwar, R.S., Shaner, D.L., and Pederson, C.H., 2016, Corn stover harvest increases herbicide movement to subsurface drains: RZWQM simulations: Pest Management Science, v. 72, no. 6, p. 1124-1132, https://doi.org/10.1002/ps.4087.","productDescription":"9 p.","startPage":"1124","endPage":"1132","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062269","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":487685,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/abe_eng_pubs/679","text":"External Repository"},{"id":306293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-14","publicationStatus":"PW","scienceBaseUri":"55bc8e20e4b033ef52100eff","contributors":{"authors":[{"text":"Shipitalo, Martin J.","contributorId":143670,"corporation":false,"usgs":false,"family":"Shipitalo","given":"Martin","email":"","middleInitial":"J.","affiliations":[{"id":15295,"text":"USDA-Agricultural Research Service, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":556685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":556686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ma, Liwang","contributorId":6751,"corporation":false,"usgs":false,"family":"Ma","given":"Liwang","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":556687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":556684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanwar, Rameshwar S.","contributorId":143671,"corporation":false,"usgs":false,"family":"Kanwar","given":"Rameshwar","email":"","middleInitial":"S.","affiliations":[{"id":15296,"text":"Iowa State University, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":556688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaner, Dale L.","contributorId":100766,"corporation":false,"usgs":true,"family":"Shaner","given":"Dale","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":556689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pederson, Carl H.","contributorId":143672,"corporation":false,"usgs":false,"family":"Pederson","given":"Carl","email":"","middleInitial":"H.","affiliations":[{"id":15296,"text":"Iowa State University, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":556690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170003,"text":"70170003 - 2016 - Movement analysis of free-grazing domestic ducks in Poyang Lake, China: A disease connection","interactions":[],"lastModifiedDate":"2021-08-24T15:52:33.356039","indexId":"70170003","displayToPublicDate":"2015-07-13T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2046,"text":"International Journal of Geographical Information Science","active":true,"publicationSubtype":{"id":10}},"title":"Movement analysis of free-grazing domestic ducks in Poyang Lake, China: A disease connection","docAbstract":"

Previous work suggests domestic poultry are important contributors to the emergence and transmission of highly pathogenic avian influenza throughout Asia. In Poyang Lake, China, domestic duck production cycles are synchronized with arrival and departure of thousands of migratory wild birds in the area. During these periods, high densities of juvenile domestic ducks are in close proximity to migratory wild ducks, increasing the potential for the virus to be transmitted and subsequently disseminated via migration. In this paper, we use GPS dataloggers and dynamic Brownian bridge models to describe movements and habitat use of free-grazing domestic ducks in the Poyang Lake basin and identify specific areas that may have the highest risk of H5N1 transmission between domestic and wild birds. Specifically, we determine relative use by free-grazing domestic ducks of natural wetlands, which are the most heavily used areas by migratory wild ducks, and of rice paddies, which provide habitat for resident wild ducks and lower densities of migratory wild ducks. To our knowledge, this is the first movement study on domestic ducks, and our data show potential for free-grazing domestic ducks from farms located near natural wetlands to come in contact with wild waterfowl, thereby increasing the risk for disease transmission. This study provides an example of the importance of movement ecology studies in understanding dynamics such as disease transmission on a complicated landscape.

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Mercury (Hg) biomonitoring of pinnipeds increasingly utilizes nonlethally collected tissues such as hair and blood. The relationship between total Hg concentrations ([THg]) in these tissues is not well understood for marine mammals, but it can be important for interpretation of tissue concentrations with respect to ecotoxicology and biomonitoring. We examined [THg] in blood and hair in multiple age classes of four pinniped species. For each species, we used paired blood and hair samples to quantify the ability of [THg] in hair to predict [THg] in blood at the time of sampling and examined the influence of varying ontogenetic phases and life history of the sampled animals. Overall, we found that the relationship between [THg] in hair and blood was affected by factors including age class, weaning status, growth, and the time difference between hair growth and sample collection. Hair [THg] was moderately to strongly predictive of current blood [THg] for adult female Steller sea lions (Eumetopias jubatus), adult female California sea lions (Zalophus californianus), and adult harbor seals (Phoca vitulina), whereas hair [THg] was poorly predictive or not predictive (different times of year) of blood [THg] for adult northern elephant seals (Mirounga angustirostris). Within species, except for very young pups, hair [THg] was a weaker predictor of blood [THg] for prereproductive animals than for adults likely due to growth, variability in foraging behavior, and transitions between ontogenetic phases. Our results indicate that the relationship between hair [THg] and blood [THg] in pinnipeds is variable and that ontogenetic phase and life history should be considered when interpreting [THg] in these tissues.

","language":"English","publisher":"Springer","publisherLocation":"New York, NY","doi":"10.1007/s00244-015-0174-3","usgsCitation":"Peterson, S.H., McHuron, E.A., Kennedy, S.N., Ackerman, J., Rea, L.D., Castellini, J., O'Hara, T., and Costa, D.P., 2016, Evaluating hair as a predictor of blood mercury: the influence of ontogenetic phase and life history in pinnipeds: Archives of Environmental Contamination and Toxicology, v. 70, no. 1, p. 28-45, https://doi.org/10.1007/s00244-015-0174-3.","productDescription":"18 p.","startPage":"28","endPage":"45","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062578","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":307836,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-07","publicationStatus":"PW","scienceBaseUri":"55e81db1e4b0dacf699e666b","contributors":{"authors":[{"text":"Peterson, Sarah H.","contributorId":141211,"corporation":false,"usgs":false,"family":"Peterson","given":"Sarah","email":"","middleInitial":"H.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":570197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHuron, Elizabeth A.","contributorId":103600,"corporation":false,"usgs":true,"family":"McHuron","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":570198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Stephanie N.","contributorId":147082,"corporation":false,"usgs":false,"family":"Kennedy","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":16783,"text":"Alaska DFG and University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":570199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":570196,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rea, Lorrie D.","contributorId":82143,"corporation":false,"usgs":false,"family":"Rea","given":"Lorrie","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":570200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castellini, J. Margaret","contributorId":32813,"corporation":false,"usgs":true,"family":"Castellini","given":"J. Margaret","affiliations":[],"preferred":false,"id":570201,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Hara, Todd M.","contributorId":34768,"corporation":false,"usgs":false,"family":"O'Hara","given":"Todd M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":570202,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Costa, Daniel P.","contributorId":141212,"corporation":false,"usgs":false,"family":"Costa","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":570203,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}