{"pageNumber":"1061","pageRowStart":"26500","pageSize":"25","recordCount":165485,"records":[{"id":70174104,"text":"70174104 - 2016 - Small-scale barriers mitigate desertification processes and enhance plant recruitment in a degraded semiarid grassland","interactions":[],"lastModifiedDate":"2016-07-12T16:30:53","indexId":"70174104","displayToPublicDate":"2016-06-27T20:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Small-scale barriers mitigate desertification processes and enhance plant recruitment in a degraded semiarid grassland","docAbstract":"

Anthropogenic desertification is a problem that plagues drylands globally; however, the factors which maintain degraded states are often unclear. In Canyonlands National Park on the Colorado Plateau of southeastern Utah, many degraded grasslands have not recovered structure and function >40 yr after release from livestock grazing pressure, necessitating active restoration. We hypothesized that multiple factors contribute to the persistent degraded state, including lack of seed availability, surficial soil-hydrological properties, and high levels of spatial connectivity (lack of perennial vegetation and other surface structure to retain water, litter, seed, and sediment). In combination with seeding and surface raking treatments, we tested the effect of small barrier structures (“ConMods”) designed to disrupt the loss of litter, seed and sediment in degraded soil patches within the park. Grass establishment was highest when all treatments (structures, seed addition, and soil disturbance) were combined, but only in the second year after installation, following favorable climatic conditions. We suggest that multiple limiting factors were ameliorated by treatments, including seed limitation and microsite availability, seed removal by harvester ants, and stressful abiotic conditions. Higher densities of grass seedlings on the north and east sides of barrier structures following the summer months suggest that structures may have functioned as artificial “nurse-plants”, sheltering seedlings from wind and radiation as well as accumulating wind-blown resources. Barrier structures increased the establishment of both native perennial grasses and exotic annuals, although there were species-specific differences in mortality related to spatial distribution of seedlings within barrier structures. The unique success of all treatments combined, and even then only under favorable climatic conditions and in certain soil patches, highlights that restoration success (and potentially, natural regeneration) often is contingent on many interacting factors.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1354","usgsCitation":"Fick, S., Decker, C.E., Duniway, M.C., and Miller, M.E., 2016, Small-scale barriers mitigate desertification processes and enhance plant recruitment in a degraded semiarid grassland: Ecosphere, v. 7, no. 6, e01354; 16 p., https://doi.org/10.1002/ecs2.1354.","productDescription":"e01354; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069023","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470829,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1354","text":"Publisher Index Page"},{"id":324488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Needles District of Canyonlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.7,\n 38.1\n ],\n [\n -109.7,\n 38.2\n ],\n [\n -109.8,\n 38.2\n ],\n [\n -109.8,\n 38.1\n ],\n [\n -109.7,\n 38.1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-24","publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a793a3","contributors":{"authors":[{"text":"Fick, Stephen E.","contributorId":172490,"corporation":false,"usgs":false,"family":"Fick","given":"Stephen E.","affiliations":[{"id":27054,"text":"Department of Plant Sciences, University of California, Davis, CA, 95616 USA. E-mail: sfick@ucdavis.edu","active":true,"usgs":false}],"preferred":false,"id":640945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Decker, Cheryl E.","contributorId":86051,"corporation":false,"usgs":false,"family":"Decker","given":"Cheryl","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":640946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":640947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":640948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171552,"text":"sir20165080 - 2016 - Groundwater-flow model for the Wood River Valley aquifer system, south-central Idaho","interactions":[],"lastModifiedDate":"2016-08-22T09:04:33","indexId":"sir20165080","displayToPublicDate":"2016-06-27T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5080","title":"Groundwater-flow model for the Wood River Valley aquifer system, south-central Idaho","docAbstract":"

A three-dimensional numerical model of groundwater flow was developed for the Wood River Valley (WRV) aquifer system, Idaho, to evaluate groundwater and surface-water availability at the regional scale. This mountain valley is located in Blaine County and has a drainage area of about 2,300 square kilometers (888 square miles). The model described in this report can serve as a tool for water-rights administration and water-resource management and planning. The model was completed with support from the Idaho Department of Water Resources, and is part of an ongoing U.S. Geological Survey effort to characterize the groundwater resources of the WRV. A highly reproducible approach was taken for constructing the WRV groundwater-flow model. The collection of datasets, source code, and processing instructions used to construct and analyze the model was distributed as an R statistical-computing and graphics package.

\n

Flow in the WRV aquifer was simulated using the MODFLOW-USG groundwater flow model. The transient flow model simulates groundwater flow between 1995 and 2010. The model uses a 100-meter (328-feet) uniform grid spacing with 54,922 active model cells distributed over three model layers. A confining unit in the south-central part of the Bellevue fan necessitated the use of a multi-layer model. Specified-flow boundaries were used to simulate the groundwater inflows from each of the major tributary basins (also known as tributary basin underflow) and the areal recharge of precipitation and applied irrigation. Head‑dependent flow boundaries were used to simulate the stream-aquifer flow exchange in river reaches and the groundwater discharge at the outlet boundaries of Stanton Crossing and Silver Creek. The model was calibrated by adjusting aquifer hydraulic properties to match simulated and measured water levels and stream-aquifer flow exchange, using the parameter-estimation program PEST. The model reasonably simulated the measured water-table elevation, orientation, and gradients. Stream-aquifer flow exchange along river reaches also was reasonably simulated by the model.

\n

Inflow into the WRV aquifer system originates from three sources (from largest to smallest):

\n
    \n
  1. Streamflow loss from the Big Wood River and Silver Creek,
    2. \n
  2. Areal recharge of precipitation and applied irrigation, and
    3. \n
  3. Tributary basin underflow.
    4. \n
\n

Outflow from the WRV aquifer system originates from five sources (from largest to smallest):

\n
    \n
  1. Aquifer discharge into the Big Wood River and Silver Creek,
    2. \n
  2. Production-well pumping,
    3. \n
  3. Discharge across the water table into the vadose zone,
    4. \n
  4. Subsurface outflow beneath Silver Creek near Picabo, and
    5. \n
  5. Subsurface outflow beneath the Big Wood River near Stanton Crossing.
    6. \n
\n

Temporal changes in aquifer storage are most affected by areal recharge and groundwater pumping, and also contribute to changes in streamflow gains.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165080","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Fisher, J.C., Bartolino, J.R., Wylie, A.H., Sukow, Jennifer, and McVay, Michael, 2016, Groundwater-flow model of the Wood River Valley aquifer system, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2016–5080, 71 p., https://dx.doi.org/10.3133/sir20165080.","productDescription":"Report: viii, 71 p.; Appendixes A-H; Model Archive; Data Repository","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039541","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324425,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixE.pdf","text":"Appendix E","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix E","linkHelpText":"Tributary Basin Underflow into the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324424,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixD.pdf","text":"Appendix D","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix D","linkHelpText":"Uncalibrated Groundwater-Flow Model for the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324426,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixF.pdf","text":"Appendix F","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix F","linkHelpText":"Natural Groundwater Recharge and Discharge in the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324428,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixH.pdf","text":"Appendix H","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix H","linkHelpText":"Calibration of the Wood River Valley Groundwater Flow Model"},{"id":324427,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixG.pdf","text":"Appendix G","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix G","linkHelpText":"Incidental Groundwater Recharge and Pumping Demand in the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324430,"rank":12,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/USGS-R/wrv","text":"R-package repository"},{"id":324423,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixC.pdf","text":"Appendix C","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix C","linkHelpText":"Creating Datasets for the R-Package ‘wrv’"},{"id":324429,"rank":11,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F7C827DT","text":"Model Archive"},{"id":324419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5080/coverthb.jpg"},{"id":324420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Report PDF"},{"id":324421,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixA.pdf","text":"Appendix A","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix A","linkHelpText":"An Introduction to the R-Package ‘wrv’"},{"id":324422,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixB.pdf","text":"Appendix B","size":"525 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix B","linkHelpText":"Manual for Functions and Datasets in the R-Package ‘wrv’"}],"country":"United States","state":"Idaho","otherGeospatial":"Wood River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.47753906249999,\n 43.30119623257966\n ],\n [\n -114.47753906249999,\n 43.82065657651685\n ],\n [\n -114.04083251953124,\n 43.82065657651685\n ],\n [\n -114.04083251953124,\n 43.30119623257966\n ],\n [\n -114.47753906249999,\n 43.30119623257966\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-06-27","noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a79377","contributors":{"authors":[{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":631755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartolino, James R. 0000-0002-2166-7803 jrbartol@usgs.gov","orcid":"https://orcid.org/0000-0002-2166-7803","contributorId":2548,"corporation":false,"usgs":true,"family":"Bartolino","given":"James","email":"jrbartol@usgs.gov","middleInitial":"R.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":631754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Allan H.","contributorId":67176,"corporation":false,"usgs":true,"family":"Wylie","given":"Allan","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":631756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sukow, Jennifer","contributorId":170003,"corporation":false,"usgs":false,"family":"Sukow","given":"Jennifer","email":"","affiliations":[{"id":7225,"text":"Idaho Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":631758,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McVay, Michael","contributorId":170002,"corporation":false,"usgs":false,"family":"McVay","given":"Michael","email":"","affiliations":[{"id":7225,"text":"Idaho Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":631757,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174108,"text":"70174108 - 2016 - Threshold sensitivity of shallow Arctic lakes and sublake permafrost to changing winter climate","interactions":[],"lastModifiedDate":"2016-07-15T15:05:05","indexId":"70174108","displayToPublicDate":"2016-06-27T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Threshold sensitivity of shallow Arctic lakes and sublake permafrost to changing winter climate","docAbstract":"

Interactions and feedbacks between abundant surface waters and permafrost fundamentally shape lowland Arctic landscapes. Sublake permafrost is maintained when the maximum ice thickness (MIT) exceeds lake depth and mean annual bed temperatures (MABTs) remain below freezing. However, declining MIT since the 1970s is likely causing talik development below shallow lakes. Here we show high-temperature sensitivity to winter ice growth at the water-sediment interface of shallow lakes based on year-round lake sensor data. Empirical model experiments suggest that shallow (1 m depth) lakes have warmed substantially over the last 30 years (2.4°C), with MABT above freezing 5 of the last 7 years. This is in comparison to slower rates of warming in deeper (3 m) lakes (0.9°C), with already well-developed taliks. Our findings indicate that permafrost below shallow lakes has already begun crossing a critical thawing threshold approximately 70 years prior to predicted terrestrial permafrost thaw in northern Alaska.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL068506","usgsCitation":"Arp, C.D., Jones, B.M., Grosse, G., Bondurant, A.C., Romanovksy, V.E., Hinkel, K.M., and Parsekian, A.D., 2016, Threshold sensitivity of shallow Arctic lakes and sublake permafrost to changing winter climate: Geophysical Research Letters, v. 43, no. 12, p. 6358-6365, https://doi.org/10.1002/2016GL068506.","productDescription":"8 p.","startPage":"6358","endPage":"6365","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073772","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":470830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068506","text":"Publisher Index Page"},{"id":324491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Teshekpuk Lake, Umiat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 69\n ],\n [\n -150,\n 72\n ],\n [\n -158,\n 72\n ],\n [\n -158,\n 69\n ],\n [\n -150,\n 69\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-24","publicationStatus":"PW","scienceBaseUri":"57724023e4b07657d1a793b8","chorus":{"doi":"10.1002/2016gl068506","url":"http://dx.doi.org/10.1002/2016gl068506","publisher":"Wiley-Blackwell","authors":"Arp Christopher D., Jones Benjamin M., Grosse Guido, Bondurant Allen C., Romanovsky Vladimir E., Hinkel Kenneth M., Parsekian Andrew D.","journalName":"Geophysical Research Letters","publicationDate":"6/24/2016","publiclyAccessibleDate":"6/24/2016"},"contributors":{"authors":[{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":640934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":640933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":640935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bondurant, Allen C.","contributorId":172493,"corporation":false,"usgs":false,"family":"Bondurant","given":"Allen","email":"","middleInitial":"C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":640936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romanovksy, Vladimir E.","contributorId":172494,"corporation":false,"usgs":false,"family":"Romanovksy","given":"Vladimir","email":"","middleInitial":"E.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":640937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hinkel, Kenneth M.","contributorId":15405,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parsekian, Andrew D.","contributorId":23829,"corporation":false,"usgs":false,"family":"Parsekian","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":640939,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171556,"text":"sir20165079 - 2016 - A spatially explicit suspended-sediment load model for western Oregon","interactions":[],"lastModifiedDate":"2016-07-20T09:48:24","indexId":"sir20165079","displayToPublicDate":"2016-06-27T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5079","title":"A spatially explicit suspended-sediment load model for western Oregon","docAbstract":"

We calibrated the watershed model SPARROW (Spatially Referenced Regressions on Watershed attributes) to give estimates of suspended-sediment loads for western Oregon and parts of northwestern California. Estimates of suspended-sediment loads were derived from a nonlinear least squares regression that related explanatory variables representing landscape and transport conditions to measured suspended-sediment loads at 68 measurement stations. The model gives estimates of model coefficients and their uncertainty within a spatial framework defined by the National Hydrography Dataset Plus hydrologic network. The resulting model explained 64 percent of the variability in suspended-sediment yield and had a root mean squared error value of 0.737. The predictor variables selected for the final model were (1) generalized lithologic province, (2) mean annual precipitation, and (3) burned area (by recent wildfire). Other landscape characteristics also were considered, but they were not significant predictors of sediment transport, were strongly correlated with another predictor variable, or were not as significant as the predictors selected for the final model.

\n

The northern Oregon coastal drainages had the highest predicted suspended sediment yields (median yield 475 kilograms per hectare per year) and the Klamath River Basin had the lowest (median yield 53 kilograms per hectare per year). Quaternary deposits were, on average, the largest contributor to incremental suspended-sediment yield even though this lithologic province only makes up 17 percent of the modeling domain. Coast Range sedimentary rocks and Coast Range volcanic rocks had high suspended-sediment yields whereas, in addition to the Klamath terrane, the Western Cascade and High Cascade lithologic provinces had low suspended-sediment yields. Precipitation and the area affected by recent wildfire both positively correlated with suspended-sediment load.

\n

Suspended-sediment transport rates predicted by this SPARROW model are less than historical (1956–73) and long‑term (thousands of years) geological rates. This difference likely results, in part, from biases in the data underlying the SPARROW model, probably resulting in predicted suspended-sediment estimates that underestimate actual transport rates. However, the differences also likely owe to natural and human-caused variation in suspended-sediment yields as they respond to changes in climate, vegetation, fire frequency, and land use. In particular, decreases in mean annual suspended-sediment yields within the Umpqua River Basin since 1956–73 may owe to less intense forest harvest, passage of the Oregon Forest Practices Act of 1971, and increased emphasis in habitat protection in recent decades. Such sensitivity may have implications for the spatial and temporal distributions of aquatic and riparian habitats.

\n

Knowledge of the regionally important patterns and factors in suspended-sediment sources and transport could support broad-scale, water-quality management objectives and priorities. Because of biases and limitations of this model, however, these results are most applicable for general comparisons and for broad areas such as large watersheds. For example, despite having similar area, precipitation, and land-use, the Umpqua River Basin generates 68 percent more suspended sediment than the Rogue River Basin, chiefly because of the large area of Coast Range sedimentary province in the Umpqua River Basin. By contrast, the Rogue River Basin contains a much larger area of Klamath terrane rocks, which produce significantly less suspended load, although recent fire disturbance (in 2002) has apparently elevated suspended sediment yields in the tributary Illinois River watershed. Fine-scaled analysis, however, will require more intensive, locally focused measurements.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165079","usgsCitation":"Wise, D.R., and O’Connor, J.E., 2016, A spatially explicit suspended-sediment load model for western Oregon: U.S. Geological Survey Scientific Investigations Report 2016–5079, 25 p., https://dx.doi.org/10.3133/sir20165079.","productDescription":"Report: v, 25 p.; Appendix A; Companion File","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064150","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":324455,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5079/coverthb.jpg"},{"id":324458,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079_NHDV2_predict_data.txt","text":"Mean annual suspended loads estimated by the SPARROW model","size":"1 MB","linkFileType":{"id":2,"text":"txt"}},{"id":324456,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5079 Report PDF"},{"id":324457,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079_appendixa.xlsx","text":"Appendix A ","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5079 Appendix A","linkHelpText":"Summary of Calibration Data for the Suspended Sediment Sparrow Model Developed for Western Oregon and Northwestern California"}],"contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov

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The U.S. Geological Survey, in cooperation with the Idaho Transportation Department, updated regional regression equations to estimate peak-flow statistics at ungaged sites on Idaho streams using recent streamflow (flow) data and new statistical techniques. Peak-flow statistics with 80-, 67-, 50-, 43-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (1.25-, 1.50-, 2.00-, 2.33-, 5.00-, 10.0-, 25.0-, 50.0-, 100-, 200-, and 500-year recurrence intervals, respectively) were estimated for 192 streamgages in Idaho and bordering States with at least 10 years of annual peak-flow record through water year 2013. The streamgages were selected from drainage basins with little or no flow diversion or regulation. The peak-flow statistics were estimated by fitting a log-Pearson type III distribution to records of annual peak flows and applying two additional statistical methods: (1) the Expected Moments Algorithm to help describe uncertainty in annual peak flows and to better represent missing and historical record; and (2) the generalized Multiple Grubbs Beck Test to screen out potentially influential low outliers and to better fit the upper end of the peak-flow distribution. Additionally, a new regional skew was estimated for the Pacific Northwest and used to weight at-station skew at most streamgages. The streamgages were grouped into six regions (numbered 1_2, 3, 4, 5, 6_8, and 7, to maintain consistency in region numbering with a previous study), and the estimated peak-flow statistics were related to basin and climatic characteristics to develop regional regression equations using a generalized least squares procedure. Four out of 24 evaluated basin and climatic characteristics were selected for use in the final regional peak-flow regression equations.

Overall, the standard error of prediction for the regional peak-flow regression equations ranged from 22 to 132 percent. Among all regions, regression model fit was best for region 4 in west-central Idaho (average standard error of prediction=46.4 percent; pseudo-R2>92 percent) and region 5 in central Idaho (average standard error of prediction=30.3 percent; pseudo-R2>95 percent). Regression model fit was poor for region 7 in southern Idaho (average standard error of prediction=103 percent; pseudo-R2<78 percent) compared to other regions because few streamgages in region 7 met the criteria for inclusion in the study, and the region’s semi-arid climate and associated variability in precipitation patterns causes substantial variability in peak flows.

A drainage area ratio-adjustment method, using ratio exponents estimated using generalized least-squares regression, was presented as an alternative to the regional regression equations if peak-flow estimates are desired at an ungaged site that is close to a streamgage selected for inclusion in this study. The alternative drainage area ratio-adjustment method is appropriate for use when the drainage area ratio between the ungaged and gaged sites is between 0.5 and 1.5.

The updated regional peak-flow regression equations had lower total error (standard error of prediction) than all regression equations presented in a 1982 study and in four of six regions presented in 2002 and 2003 studies in Idaho. A more extensive streamgage screening process used in the current study resulted in fewer streamgages used in the current study than in the 1982, 2002, and 2003 studies. Fewer streamgages used and the selection of different explanatory variables were likely causes of increased error in some regions compared to previous studies, but overall, regional peak‑flow regression model fit was generally improved for Idaho. The revised statistical procedures and increased streamgage screening applied in the current study most likely resulted in a more accurate representation of natural peak-flow conditions.

The updated, regional peak-flow regression equations will be integrated in the U.S. Geological Survey StreamStats program to allow users to estimate basin and climatic characteristics and peak-flow statistics at ungaged locations of interest. StreamStats estimates peak-flow statistics with quantifiable certainty only when used at sites with basin and climatic characteristics within the range of input variables used to develop the regional regression equations. Both the regional regression equations and StreamStats should be used to estimate peak-flow statistics only in naturally flowing, relatively unregulated streams without substantial local influences to flow, such as large seeps, springs, or other groundwater-surface water interactions that are not widespread or characteristic of the respective region.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165083","collaboration":"Prepared in cooperation with Idaho Transportation Department","usgsCitation":"Wood, M.S., Fosness, R.L., Skinner, K.D., and Veilleux, A.G., 2016, Estimating peak-flow frequency statistics for selected gaged and ungaged sites in naturally flowing streams and rivers in Idaho (ver. 1.1, April 2017): U.S. Geological Survey Scientific Investigations Report 2016–5083, 56 p., https://doi.org/10.3133/sir20165083.","productDescription":"Report: vi, 56 p.; Appendix A","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046287","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5083/sir20165083.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5083 Report PDF"},{"id":324443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5083/coverthb2.jpg"},{"id":324460,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5083/sir20165083_appendixa.xlsx","text":"Appendix A ","size":"145 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5083 Appendix A","linkHelpText":"Supplemental Information for the Development of Regional Peak-Flow Regression Equations in Idaho"},{"id":340486,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5083/versionHist.txt","description":"SIR 2016-5083 Version History"}],"country":"United 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\"}}]}","edition":"Version 1.0: Originally posted June 27, 2016; Version 1.1: April 26, 2017","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
https://id.water.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-06-27","revisedDate":"2017-04-26","noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a79370","contributors":{"authors":[{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":637745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":637746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":1836,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":637747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":637748,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174074,"text":"70174074 - 2016 - The role of habitat filtering in the leaf economics spectrum and plant susceptibility to pathogen infection","interactions":[],"lastModifiedDate":"2016-10-21T13:33:48","indexId":"70174074","displayToPublicDate":"2016-06-27T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The role of habitat filtering in the leaf economics spectrum and plant susceptibility to pathogen infection","docAbstract":"

1.The Leaf Economics Spectrum (LES) describes global covariation in the traits of plant leaves. The LES is thought to arise from biophysical constraints and habitat filtering (ecological selection against unfit trait combinations along environmental gradients). However, the role of habitat filtering in generating the LES has not been tested experimentally.

\n

2.If the process of habitat filtering plays a role in generating the LES, the LES could weaken in communities that have yet to be filtered by the current environment, for example after abiotic environmental change. LES traits are commonly used to predict community and ecosystem processes, and if the LES weakens in unfiltered communities, LES-based models may no longer apply.

\n

3.In the greenhouse, we experimentally simulated three stages of habitat filtering in response to abiotic change: from unfiltered, to semi-filtered, to completely filtered communities. In each stage, we quantified the strength of the LES and assessed the accuracy of trait-based models of an important ecological process, pathogen infection.

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4.The strength of the LES increased with the completeness of habitat filtering, as did the accuracy of trait-based models of plant susceptibility to pathogen infection.

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5.Synthesis. Our results suggest that habitat filtering plays a fundamental role in strengthening the trait correlations of the LES, and that trait-based models may be less accurate when communities have not been filtered by the current environment, for example, following rapid environmental change.

","language":"English","publisher":"Wiley","doi":"10.1111/1365-2745.12632","usgsCitation":"Welsh, M.E., Cronin, J.P., and Mitchell, C., 2016, The role of habitat filtering in the leaf economics spectrum and plant susceptibility to pathogen infection: Journal of Ecology, v. 104, no. 6, p. 1768-1777, https://doi.org/10.1111/1365-2745.12632.","productDescription":"10 p.","startPage":"1768","endPage":"1777","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065238","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.12632","text":"Publisher Index Page"},{"id":324433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-02","publicationStatus":"PW","scienceBaseUri":"57724023e4b07657d1a793b5","chorus":{"doi":"10.1111/1365-2745.12632","url":"http://dx.doi.org/10.1111/1365-2745.12632","publisher":"Wiley-Blackwell","authors":"Welsh Miranda E., Cronin James Patrick, Mitchell Charles E.","journalName":"Journal of Ecology","publicationDate":"8/2/2016"},"contributors":{"authors":[{"text":"Welsh, Miranda E","contributorId":172466,"corporation":false,"usgs":false,"family":"Welsh","given":"Miranda","email":"","middleInitial":"E","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":640817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, James P. 0000-0001-6791-5828 jcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-6791-5828","contributorId":5834,"corporation":false,"usgs":true,"family":"Cronin","given":"James","email":"jcronin@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":640816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mitchell, Charles E.","contributorId":99689,"corporation":false,"usgs":true,"family":"Mitchell","given":"Charles E.","affiliations":[],"preferred":false,"id":640818,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174072,"text":"70174072 - 2016 - The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources","interactions":[],"lastModifiedDate":"2016-06-27T14:56:51","indexId":"70174072","displayToPublicDate":"2016-06-27T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3459,"text":"Special Paper of the Geological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources","docAbstract":"

Groundwater is the source of drinking water for ∼1.4 million people in the Coastal Plain Province of Maryland (USA). In addition, groundwater is essential for commercial, industrial, and agricultural uses. Approximately 0.757 × 109 L d–1 (200 million gallons/d) were withdrawn in 2010. As a result of decades of withdrawals from the coastal plain confined aquifers, groundwater levels have declined by as much as 70 m (230 ft) from estimated prepumping levels. Other issues posing challenges to long-term groundwater sustainability include degraded water quality from both man-made and natural sources, reduced stream base flow, land subsidence, and changing recharge patterns (drought) caused by climate change. In Maryland, groundwater supply is managed primarily by the Maryland Department of the Environment, which seeks to balance reasonable use of the resource with long-term sustainability. The chief goal of groundwater management in Maryland is to ensure safe and adequate supplies for all current and future users through the implementation of appropriate usage, planning, and conservation policies. To assist in that effort, the geographic information system (GIS)–based Maryland Coastal Plain Aquifer Information System was developed as a tool to help water managers access and visualize groundwater data for use in the evaluation of groundwater allocation and use permits. The system, contained within an ESRI ArcMap desktop environment, includes both interpreted and basic data for 16 aquifers and 14 confining units. Data map layers include aquifer and ­confining unit layer surfaces, aquifer extents, borehole information, hydraulic properties, time-series groundwater-level data, well records, and geophysical and lithologic logs. The aquifer and confining unit layer surfaces were generated specifically for the GIS system. The system also contains select groundwater-quality data and map layers that quantify groundwater and surface-water withdrawals. The aquifer information system can serve as a pre- and postprocessing environment for groundwater-flow models for use in water-supply planning, development, and management. The system also can be expanded to include features that evaluate constraints to groundwater development, such as insufficient available drawdown, degraded groundwater quality, insufficient aquifer yields, and well-field interference. Ultimately, the aquifer information system is intended to function as an interactive Web-based utility that provides a broad array of information related to groundwater resources in Maryland’s coastal plain to a wide-ranging audience, including well drillers, consultants, academia, and the general public.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2520(15)","usgsCitation":"Andreasen, D., Nardi, M.R., Staley, A., Achmad, G., and Grace, J.W., 2016, The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources: Special Paper of the Geological Society of America, v. 520, p. 159-170, https://doi.org/10.1130/2016.2520(15).","productDescription":"12 p.","startPage":"159","endPage":"170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068540","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":324417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"520","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57724023e4b07657d1a793b0","contributors":{"authors":[{"text":"Andreasen, David C.","contributorId":59003,"corporation":false,"usgs":true,"family":"Andreasen","given":"David C.","affiliations":[],"preferred":false,"id":640806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nardi, Mark R. 0000-0002-7310-8050 mrnardi@usgs.gov","orcid":"https://orcid.org/0000-0002-7310-8050","contributorId":1859,"corporation":false,"usgs":true,"family":"Nardi","given":"Mark","email":"mrnardi@usgs.gov","middleInitial":"R.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staley, Andrew W.","contributorId":43319,"corporation":false,"usgs":true,"family":"Staley","given":"Andrew W.","affiliations":[],"preferred":false,"id":640807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Achmad, Grufron","contributorId":172464,"corporation":false,"usgs":false,"family":"Achmad","given":"Grufron","email":"","affiliations":[{"id":25435,"text":"Maryland Geological Survey","active":true,"usgs":false}],"preferred":false,"id":640808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, John W.","contributorId":172465,"corporation":false,"usgs":false,"family":"Grace","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":27050,"text":"Maryland Department of the Environment","active":true,"usgs":false}],"preferred":false,"id":640809,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174058,"text":"70174058 - 2016 - Mercury risk to avian piscivores across western United States and Canada","interactions":[],"lastModifiedDate":"2018-08-06T13:09:16","indexId":"70174058","displayToPublicDate":"2016-06-27T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Mercury risk to avian piscivores across western United States and Canada","docAbstract":"

The widespread distribution of mercury (Hg) threatens wildlife health, particularly piscivorous birds. Western North America is a diverse region that provides critical habitat to many piscivorous bird species, and also has a well-documented history of mercury contamination from legacy mining and atmospheric deposition. The diversity of landscapes in the west limits the distribution of avian piscivore species, complicating broad comparisons across the region. Mercury risk to avian piscivores was evaluated across the western United States and Canada using a suite of avian piscivore species representing a variety of foraging strategies that together occur broadly across the region. Prey fish Hg concentrations were size-adjusted to the preferred size class of the diet for each avian piscivore (Bald Eagle = 36 cm, Osprey = 30 cm, Common and Yellow-billed Loon = 15 cm, Western and Clark's Grebe = 6 cm, and Belted Kingfisher = 5 cm) across each species breeding range. Using a combination of field and lab-based studies on Hg effect in a variety of species, wet weight blood estimates were grouped into five relative risk categories including: background (< 0.5 μg/g), low (0.5–1 μg/g), moderate (1–2 μg/g), high (2–3 μg/g), and extra high (> 3 μg/g). These risk categories were used to estimate potential mercury risk to avian piscivores across the west at a 1 degree-by-1 degree grid cell resolution. Avian piscivores foraging on larger-sized fish generally were at a higher relative risk to Hg. Habitats with a relatively high risk included wetland complexes (e.g., prairie pothole in Saskatchewan), river deltas (e.g., San Francisco Bay, Puget Sound, Columbia River), and arid lands (Great Basin and central Arizona). These results indicate that more intensive avian piscivore sampling is needed across Western North America to generate a more robust assessment of exposure risk.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.02.197","usgsCitation":"Jackson, A., Evers, D.C., Eagles-Smith, C.A., Ackerman, J., Willacker, J.J., Elliott, J., Lepak, J.M., Vander Pol, S.S., and Bryan, C.E., 2016, Mercury risk to avian piscivores across western United States and Canada: Science of the Total Environment, v. 568, p. 685-696, https://doi.org/10.1016/j.scitotenv.2016.02.197.","productDescription":"12 p.","startPage":"685","endPage":"696","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070590","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":470832,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Pharmaceutical contamination of contiguous groundwater is a substantial concern in wastewater-impacted streams, due to ubiquity in effluent, high aqueous mobility, designed bioactivity, and to effluent-driven hydraulic gradients. Wastewater treatment facility (WWTF) closures are rare environmental remediation events; offering unique insights into contaminant persistence, long-term wastewater impacts, and ecosystem recovery processes. The USGS conducted a combined pre/post-closure groundwater assessment adjacent to an effluent-impacted reach of Fourmile Creek, Ankeny, Iowa, USA. Higher surface-water concentrations, consistent surface-water to groundwater concentration gradients, and sustained groundwater detections tens of meters from the stream bank demonstrated the importance of WWTF effluent as the source of groundwater pharmaceuticals as well as the persistence of these contaminants under effluent-driven, pre-closure conditions. The number of analytes (110 total) detected in surface water decreased from 69 prior to closure down to 8 in the first post-closure sampling event approximately 30 d later, with a corresponding 2 order of magnitude decrease in the cumulative concentration of detected analytes. Post-closure cumulative concentrations of detected analytes were approximately 5 times higher in proximal groundwater than in surface water. About 40% of the 21 contaminants detected in a downstream groundwater transect immediately before WWTF closure exhibited rapid attenuation with estimated half-lives on the order of a few days; however, a comparable number exhibited no consistent attenuation during the year-long post-closure assessment. The results demonstrate the potential for effluent-impacted shallow groundwater systems to accumulate pharmaceutical contaminants and serve as long-term residual sources, further increasing the risk of adverse ecological effects in groundwater and the near-stream ecosystem.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.06.104","usgsCitation":"Bradley, P.M., Barber, L.B., Clark, J.M., Duris, J.W., Foreman, W., Furlong, E.T., Givens, C.E., Hubbard, L.E., Hutchinson, K.J., Journey, C.A., Keefe, S.H., and Kolpin, D.W., 2016, Pre/post-closure assessment of groundwater pharmaceutical fate in a wastewater‑facility-impacted stream reach: Science of the Total Environment, v. 568, p. 916-925, https://doi.org/10.1016/j.scitotenv.2016.06.104.","productDescription":"10 p.","startPage":"916","endPage":"925","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069485","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.06.104","text":"Publisher Index Page"},{"id":324408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Ankeny","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.61347198486328,\n 41.761196772309965\n ],\n [\n -93.61347198486328,\n 41.79172868968446\n ],\n [\n -93.5866928100586,\n 41.79172868968446\n ],\n [\n -93.5866928100586,\n 41.761196772309965\n ],\n [\n -93.61347198486328,\n 41.761196772309965\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"568","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a7939b","chorus":{"doi":"10.1016/j.scitotenv.2016.06.104","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.06.104","publisher":"Elsevier BV","authors":"Bradley Paul M., Barber Larry B., Clark Jimmy M., Duris Joseph W., Foreman William T., Furlong Edward T., Givens Carrie E., Hubbard Laura E., Hutchinson Kasey J., Journey Celeste A., Keefe Steffanie H., Kolpin Dana W.","journalName":"Science of The Total Environment","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":640744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. ","email":"wforeman@usgs.gov","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":false,"id":640747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":640748,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Givens, Carrie E. cgivens@usgs.gov","contributorId":5711,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","email":"cgivens@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640749,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640750,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hutchinson, Kasey J. khutchin@usgs.gov","contributorId":4223,"corporation":false,"usgs":true,"family":"Hutchinson","given":"Kasey","email":"khutchin@usgs.gov","middleInitial":"J.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640751,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640752,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":640753,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640754,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70133867,"text":"70133867 - 2016 - Growth rates and ages of deep-sea corals impacted by the Deepwater Horizon oil spill","interactions":[],"lastModifiedDate":"2016-06-27T15:02:15","indexId":"70133867","displayToPublicDate":"2016-06-27T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Growth rates and ages of deep-sea corals impacted by the Deepwater Horizon oil spill","docAbstract":"

The impact of the April 2010 Deepwater Horizon (DWH) spill on deep-sea coral communities in the Gulf of Mexico (GoM) is still under investigation, as is the potential for these communities to recover. Impacts from the spill include observation of corals covered with flocculent material, with bare skeleton, excessive mucous production, sloughing tissue, and subsequent colonization of damaged areas by hydrozoans. Information on growth rates and life spans of deep-sea corals is important for understanding the vulnerability of these ecosystems to both natural and anthropogenic perturbations, as well as the likely duration of any observed adverse impacts. We report radiocarbon ages and radial and linear growth rates based on octocorals (Paramuricea spp. and Chrysogorgia sp.) collected in 2010 and 2011 from areas of the DWH impact. The oldest coral radiocarbon ages were measured on specimens collected 11 km to the SW of the oil spill from the Mississippi Canyon (MC) 344 site: 599 and 55 cal yr BP, suggesting continuous life spans of over 600 years for Paramuricea biscaya, the dominant coral species in the region. Calculated radial growth rates, between 0.34 μm yr−1 and 14.20 μm yr−1, are consistent with previously reported proteinaceous corals from the GoM. Anomalously low radiocarbon (Δ14C) values for soft tissue from some corals indicate that these corals were feeding on particulate organic carbon derived from an admixture of modern surface carbon and a low 14C carbon source. Results from this work indicate fossil carbon could contribute 5–10% to the coral soft tissue Δ14C signal within the area of the spill impact. The influence of a low 14C carbon source (e.g., petro-carbon) on the particulate organic carbon pool was observed at all sites within 30 km of the spill site, with the exception of MC118, which may have been outside of the dominant northeast-southwest zone of impact. The quantitatively assessed extreme longevity and slow growth rates documented here highlight the vulnerability of these long-lived deep sea coral species to disturbance.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2014.10.021","usgsCitation":"Prouty, N.G., Fisher, C.R., Demopoulos, A., and Druffel, E.R., 2016, Growth rates and ages of deep-sea corals impacted by the Deepwater Horizon oil spill: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 129, https://doi.org/10.1016/j.dsr2.2014.10.021.","productDescription":"17 p.","startPage":"212","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056047","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470834,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.dsr2.2014.10.021","text":"Publisher Index Page"},{"id":296221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89,\n 30\n ],\n [\n -89,\n 27\n ],\n [\n -92,\n 27\n ],\n [\n -92,\n 30\n ],\n [\n -89,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","edition":"196","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"546db11ee4b0fc7976bf1e33","contributors":{"authors":[{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":525501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Charles R.","contributorId":127497,"corporation":false,"usgs":false,"family":"Fisher","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":525502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":371,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda W.J.","email":"ademopoulos@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":525503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Druffel, Ellen R. M.","contributorId":127498,"corporation":false,"usgs":false,"family":"Druffel","given":"Ellen","email":"","middleInitial":"R. M.","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":525504,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174061,"text":"70174061 - 2016 - Population ecology of the sea lamprey (Petromyzon marinus) as an invasive species in the Laurentian Great Lakes and an imperiled species in Europe","interactions":[],"lastModifiedDate":"2016-08-19T10:07:28","indexId":"70174061","displayToPublicDate":"2016-06-27T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Population ecology of the sea lamprey (Petromyzon marinus) as an invasive species in the Laurentian Great Lakes and an imperiled species in Europe","docAbstract":"

The sea lamprey Petromyzon marinus (Linnaeus) is both an invasive non-native species in the Laurentian Great Lakes of North America and an imperiled species in much of its native range in North America and Europe. To compare and contrast how understanding of population ecology is useful for control programs in the Great Lakes and restoration programs in Europe, we review current understanding of the population ecology of the sea lamprey in its native and introduced range. Some attributes of sea lamprey population ecology are particularly useful for both control programs in the Great Lakes and restoration programs in the native range. First, traps within fish ladders are beneficial for removing sea lampreys in Great Lakes streams and passing sea lampreys in the native range. Second, attractants and repellants are suitable for luring sea lampreys into traps for control in the Great Lakes and guiding sea lamprey passage for conservation in the native range. Third, assessment methods used for targeting sea lamprey control in the Great Lakes are useful for targeting habitat protection in the native range. Last, assessment methods used to quantify numbers of all life stages of sea lampreys would be appropriate for measuring success of control in the Great Lakes and success of conservation in the native range.

","language":"English","publisher":"Springer","doi":"10.1007/s11160-016-9440-3","usgsCitation":"Hansen, M.J., Madenjian, C.P., Slade, J.W., Steeves, T.B., Almeida, P.R., and Quintella, B.R., 2016, Population ecology of the sea lamprey (Petromyzon marinus) as an invasive species in the Laurentian Great Lakes and an imperiled species in Europe: Reviews in Fish Biology and Fisheries, v. 26, no. 3, p. 509-535, https://doi.org/10.1007/s11160-016-9440-3.","productDescription":"27 p.","startPage":"509","endPage":"535","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075213","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11160-016-9440-3","text":"Publisher Index Page"},{"id":324399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-22","publicationStatus":"PW","scienceBaseUri":"57724021e4b07657d1a79394","contributors":{"authors":[{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":640757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":640758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slade, Jeffrey W.","contributorId":126760,"corporation":false,"usgs":false,"family":"Slade","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[{"id":6597,"text":"U.S. Fish and Wildlife Service, Ludington Biological Station","active":true,"usgs":false}],"preferred":false,"id":640759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steeves, Todd B.","contributorId":126761,"corporation":false,"usgs":false,"family":"Steeves","given":"Todd","email":"","middleInitial":"B.","affiliations":[{"id":6598,"text":"Department of Fisheries and Oceans, Canada, Sea Lamprey Control Centre","active":true,"usgs":false}],"preferred":false,"id":640760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Almeida, Pedro R.","contributorId":172443,"corporation":false,"usgs":false,"family":"Almeida","given":"Pedro","email":"","middleInitial":"R.","affiliations":[{"id":27044,"text":"MARE – Centro de Ciências do Mar e do Ambiente","active":true,"usgs":false}],"preferred":false,"id":640761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quintella, Bernardo R.","contributorId":172444,"corporation":false,"usgs":false,"family":"Quintella","given":"Bernardo","email":"","middleInitial":"R.","affiliations":[{"id":27044,"text":"MARE – Centro de Ciências do Mar e do Ambiente","active":true,"usgs":false}],"preferred":false,"id":640762,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174056,"text":"70174056 - 2016 - Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT)","interactions":[],"lastModifiedDate":"2016-06-27T11:23:51","indexId":"70174056","displayToPublicDate":"2016-06-27T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT)","docAbstract":"

Conventional, regression-based methods of inferring depth from passive optical image data undermine the advantages of remote sensing for characterizing river systems. This study introduces and evaluates a more flexible framework, Image-to-Depth Quantile Transformation (IDQT), that involves linking the frequency distribution of pixel values to that of depth. In addition, a new image processing workflow involving deep water correction and Minimum Noise Fraction (MNF) transformation can reduce a hyperspectral data set to a single variable related to depth and thus suitable for input to IDQT. Applied to a gravel bed river, IDQT avoided negative depth estimates along channel margins and underpredictions of pool depth. Depth retrieval accuracy (R25 0.79) and precision (0.27 m) were comparable to an established band ratio-based method, although a small shallow bias (0.04 m) was observed. Several ways of specifying distributions of pixel values and depths were evaluated but had negligible impact on the resulting depth estimates, implying that IDQT was robust to these implementation details. In essence, IDQT uses frequency distributions of pixel values and depths to achieve an aspatial calibration; the image itself provides information on the spatial distribution of depths. The approach thus reduces sensitivity to misalignment between field and image data sets and allows greater flexibility in the timing of field data collection relative to image acquisition, a significant advantage in dynamic channels. IDQT also creates new possibilities for depth retrieval in the absence of field data if a model could be used to predict the distribution of depths within a reach.

","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR018730","usgsCitation":"Legleiter, C.J., 2016, Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT): Water Resources Research, v. 52, no. 5, p. 3722-3741, https://doi.org/10.1002/2016WR018730.","productDescription":"20 p.","startPage":"3722","endPage":"3741","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072989","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018730","text":"Publisher Index Page"},{"id":324402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-14","publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a7937e","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":640728,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70174055,"text":"70174055 - 2016 - Storeria occipitomaculata obscura (Florida red-bellied snake)","interactions":[],"lastModifiedDate":"2016-06-27T11:26:38","indexId":"70174055","displayToPublicDate":"2016-06-27T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Storeria occipitomaculata obscura (Florida red-bellied snake)","docAbstract":"

USA: LOUISIANA: Vermilion Parish: Palmetto Island State Park (29.86335°N, 92.14848°W; WGS 84). 19 February 2016. Lindy J. Muse. Verified by Jeff Boundy. Florida Museum of Natural History (UF 177730, photo voucher). New parish record (Dundee and Rossman 1989. The Amphibians and Reptiles of Louisiana. Louisiana State University Press, Baton Rouge, Louisiana. 300 pp.). Storeria occipitomaculata obscura has not been documented in any of the coastal parishes of Louisiana (Boundy. 2006. Snakes of Louisiana. Louisiana Department of Wildlife & Fisheries, Baton Rouge, Louisiana. 40 pp.). However, this species can be difficult to find in southern Louisiana and other populations in coastal parishes may eventually be discovered. This adult individual (SVL = 292 mm; TL = 70 mm) was found under a log in a wet bottomland forest dominated by Dwarf Palmetto and Bald Cypress.

","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Muse, L.J., Glorioso, B.M., and Eaglestone, C.A., 2016, Storeria occipitomaculata obscura (Florida red-bellied snake): Herpetological Review, v. 47, no. 2, p. 266-266.","productDescription":"1 p.","startPage":"266","endPage":"266","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075568","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a793aa","contributors":{"authors":[{"text":"Muse, Lindy J.","contributorId":172438,"corporation":false,"usgs":false,"family":"Muse","given":"Lindy","email":"","middleInitial":"J.","affiliations":[{"id":27041,"text":"Cherokee at USGS-WARC Lafayette","active":true,"usgs":false}],"preferred":false,"id":640726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":640725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eaglestone, Chandler A. R.","contributorId":172439,"corporation":false,"usgs":false,"family":"Eaglestone","given":"Chandler","email":"","middleInitial":"A. R.","affiliations":[{"id":27042,"text":"Student Contractor at USGS-WARC Lafayette","active":true,"usgs":false}],"preferred":false,"id":640727,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174064,"text":"70174064 - 2016 - A synthesis of the basal thermal state of the Greenland Ice Sheet","interactions":[],"lastModifiedDate":"2016-08-12T10:17:20","indexId":"70174064","displayToPublicDate":"2016-06-27T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of the basal thermal state of the Greenland Ice Sheet","docAbstract":"

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

","language":"English","publisher":"Americal Geophysical Union","doi":"10.1002/2015JF003803","usgsCitation":"MacGregor, J.A., Fahnestock, M.A., Catania, G.A., Aschwanden, A., Clow, G.D., Colgan, W.T., Gogineni, P.S., Morlighem, M., Nowicki, S.M., Paden, J.D., Price, S., and Seroussi, H., 2016, A synthesis of the basal thermal state of the Greenland Ice Sheet: Journal of Geophysical Research F: Earth Surface, v. 121, no. 7, p. 1328-1350, https://doi.org/10.1002/2015JF003803.","productDescription":"23 p.","startPage":"1328","endPage":"1350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071124","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jf003803","text":"Publisher Index 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Center","active":true,"usgs":true}],"preferred":true,"id":640767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Colgan, William T.","contributorId":172448,"corporation":false,"usgs":false,"family":"Colgan","given":"William","email":"","middleInitial":"T.","affiliations":[{"id":27047,"text":"Dept of Earth and Space Science, York University, Toronto","active":true,"usgs":false}],"preferred":false,"id":640772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gogineni, Prasad S.","contributorId":141049,"corporation":false,"usgs":false,"family":"Gogineni","given":"Prasad","email":"","middleInitial":"S.","affiliations":[{"id":13661,"text":"Center for Remote Sensing of Ice Sheets, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":640773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morlighem, Mathieu","contributorId":141050,"corporation":false,"usgs":false,"family":"Morlighem","given":"Mathieu","email":"","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":640774,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nowicki, Sophie M .J.","contributorId":172451,"corporation":false,"usgs":false,"family":"Nowicki","given":"Sophie","email":"","middleInitial":"M .J.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":640775,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Paden, John D","contributorId":141046,"corporation":false,"usgs":false,"family":"Paden","given":"John","email":"","middleInitial":"D","affiliations":[{"id":13661,"text":"Center for Remote Sensing of Ice Sheets, University of Kansas","active":true,"usgs":false}],"preferred":false,"id":640776,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Price, Stephen F.","contributorId":169436,"corporation":false,"usgs":false,"family":"Price","given":"Stephen F.","affiliations":[],"preferred":false,"id":640777,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Seroussi, Helene","contributorId":141052,"corporation":false,"usgs":false,"family":"Seroussi","given":"Helene","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":640778,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70174057,"text":"70174057 - 2016 - Nitrogen enrichment regulates calcium sources in forests","interactions":[],"lastModifiedDate":"2017-11-22T17:26:41","indexId":"70174057","displayToPublicDate":"2016-06-27T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen enrichment regulates calcium sources in forests","docAbstract":"

Nitrogen (N) is a key nutrient that shapes cycles of other essential elements in forests, including calcium (Ca). When N availability exceeds ecosystem demands, excess N can stimulate Ca leaching and deplete Ca from soils. Over the long term, these processes may alter the proportion of available Ca that is derived from atmospheric deposition vs. bedrock weathering, which has fundamental consequences for ecosystem properties and nutrient supply. We evaluated how landscape variation in soil N, reflecting long-term legacies of biological N fixation, influenced plant and soil Ca availability and ecosystem Ca sources across 22 temperate forests in Oregon. We also examined interactions between soil N and bedrock Ca using soil N gradients on contrasting basaltic vs. sedimentary bedrock that differed 17-fold in underlying Ca content. We found that low-N forests on Ca-rich basaltic bedrock relied strongly on Ca from weathering, but that soil N enrichment depleted readily weatherable mineral Ca and shifted forest reliance toward atmospheric Ca. Forests on Ca-poor sedimentary bedrock relied more consistently on atmospheric Ca across all levels of soil N enrichment. The broad importance of atmospheric Ca was unexpected given active regional uplift and erosion that are thought to rejuvenate weathering supply of soil minerals. Despite different Ca sources to forests on basaltic vs. sedimentary bedrock, we observed consistent declines in plant and soil Ca availability with increasing N, regardless of the Ca content of underlying bedrock. Thus, traditional measures of Ca availability in foliage and soil exchangeable pools may poorly reflect long-term Ca sources that sustain soil fertility. We conclude that long-term soil N enrichment can deplete available Ca and cause forests to rely increasingly on Ca from atmospheric deposition, which may limit ecosystem Ca supply in an increasingly N-rich world.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13335","usgsCitation":"Hynicka, J.D., Pett-Ridge, J.C., and Perakis, S.S., 2016, Nitrogen enrichment regulates calcium sources in forests: Global Change Biology, v. 22, no. 12, p. 4067-1079, https://doi.org/10.1111/gcb.13335.","productDescription":"13 p.","startPage":"4067","endPage":"1079","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065193","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":324400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"57724021e4b07657d1a7938a","contributors":{"authors":[{"text":"Hynicka, Justin D.","contributorId":79797,"corporation":false,"usgs":true,"family":"Hynicka","given":"Justin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":640733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pett-Ridge, Julie C.","contributorId":172441,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Julie","email":"","middleInitial":"C.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":640734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":640732,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174066,"text":"70174066 - 2016 - Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA","interactions":[],"lastModifiedDate":"2016-06-27T11:09:22","indexId":"70174066","displayToPublicDate":"2016-06-27T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA","docAbstract":"

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

","language":"English","publisher":"Springer","doi":"10.1007/s10584-015-1553-5","usgsCitation":"West, A., Kumar, S., and Jarnevich, C.S., 2016, Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA: Climatic Change, v. 134, no. 4, p. 565-577, https://doi.org/10.1007/s10584-015-1553-5.","productDescription":"13 p.","startPage":"565","endPage":"577","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067316","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470838,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://link.springer.com/10.1007/s10584-015-1553-5","text":"External Repository"},{"id":324396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, 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\"}}]}","volume":"134","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-11","publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a7939e","contributors":{"authors":[{"text":"West, Amanda M.","contributorId":139058,"corporation":false,"usgs":false,"family":"West","given":"Amanda M.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":640789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":640790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":640788,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174065,"text":"70174065 - 2016 - Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes","interactions":[],"lastModifiedDate":"2016-06-27T11:11:47","indexId":"70174065","displayToPublicDate":"2016-06-27T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes","docAbstract":"

Gravel-bed river floodplains in mountain landscapes disproportionately concentrate diverse habitats, nutrient cycling, productivity of biota, and species interactions. Although stream ecologists know that river channel and floodplain habitats used by aquatic organisms are maintained by hydrologic regimes that mobilize gravel-bed sediments, terrestrial ecologists have largely been unaware of the importance of floodplain structures and processes to the life requirements of a wide variety of species. We provide insight into gravel-bed rivers as the ecological nexus of glaciated mountain landscapes. We show why gravel-bed river floodplains are the primary arena where interactions take place among aquatic, avian, and terrestrial species from microbes to grizzly bears and provide essential connectivity as corridors for movement for both aquatic and terrestrial species. Paradoxically, gravel-bed river floodplains are also disproportionately unprotected where human developments are concentrated. Structural modifications to floodplains such as roads, railways, and housing and hydrologicaltering hydroelectric or water storage dams have severe impacts to floodplain habitat diversity and productivity, restrict local and regional connectivity, and reduce the resilience of both aquatic and terrestrial species, including adaptation to climate change. To be effective, conservation efforts in glaciated mountain landscapes intended to benefit the widest variety of organisms need a paradigm shift that has gravel-bed rivers and their floodplains as the central focus and that prioritizes the maintenance or restoration of the intact structure and processes of these critically important systems throughout their length and breadth.

","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/sciadv.1600026","usgsCitation":"Hauer, F.R., Locke, H., Dreitz, V., Hebblewhite, M., Lowe, W., Muhlfeld, C.C., Nelson, C., Proctor, M.F., and Rood, S.B., 2016, Gravel-bed river floodplains are the ecological nexus of glaciated mountain landscapes: Science Advances, v. 2, no. 6, e1600026; 13 p., https://doi.org/10.1126/sciadv.1600026.","productDescription":"e1600026; 13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068965","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.1600026","text":"Publisher Index Page"},{"id":324397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5772401fe4b07657d1a79373","contributors":{"authors":[{"text":"Hauer, F. Richard","contributorId":76892,"corporation":false,"usgs":true,"family":"Hauer","given":"F.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":640780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Locke, Harvey","contributorId":172456,"corporation":false,"usgs":false,"family":"Locke","given":"Harvey","email":"","affiliations":[{"id":27049,"text":"Yellowstone to Yukon Conservation Initiative","active":true,"usgs":false}],"preferred":false,"id":640781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreitz, Victoria","contributorId":172457,"corporation":false,"usgs":false,"family":"Dreitz","given":"Victoria","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":640782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hebblewhite, Mark","contributorId":69455,"corporation":false,"usgs":true,"family":"Hebblewhite","given":"Mark","affiliations":[],"preferred":false,"id":640783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Winsor","contributorId":115672,"corporation":false,"usgs":true,"family":"Lowe","given":"Winsor","affiliations":[],"preferred":false,"id":640784,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":640779,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Cara","contributorId":172458,"corporation":false,"usgs":false,"family":"Nelson","given":"Cara","email":"","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":640785,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Proctor, Michael F.","contributorId":150939,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":18147,"text":"Birchdale Ecological","active":true,"usgs":false}],"preferred":false,"id":640786,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rood, Stewart B.","contributorId":169010,"corporation":false,"usgs":false,"family":"Rood","given":"Stewart","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":640787,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70174054,"text":"70174054 - 2016 - Osteopilus septentrionalis (Cuban treefrog)","interactions":[],"lastModifiedDate":"2016-06-27T10:18:20","indexId":"70174054","displayToPublicDate":"2016-06-27T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Osteopilus septentrionalis (Cuban treefrog)","docAbstract":"

USA: LOUISIANA: St. Tammany Parish: on private property on Allen Road in Slidell (ca. 30.262°N, 89.741°W; WGS 84). 2 April 2013. Aaron Steece. Verified by Hardin Waddle. Florida Museum of Natural History (UF 177727, photo voucher). New parish record. This adult was found ca. 2 m high on a branch at the edge of a wooded area behind a house. It was photographed and released, as the species identity and significance was unknown. The origin of this individual is unknown. The homeowner stated that he bought nursery plants often, but checked them thoroughly as he put them indoors. Since this initial finding, the homeowner learned more about Cuban Treefrogs and searched for them on many occasions at this location for two years, but detected no additional Cuban Treefrogs.

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Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015","interactions":[],"lastModifiedDate":"2022-11-02T14:57:45.94871","indexId":"ds995","displayToPublicDate":"2016-06-27T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"995","title":"Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015","docAbstract":"

The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms (Morgan, 2009). On October 7–9, 2015, the USGS conducted an oblique aerial photographic survey of the coast from the South Carolina/North Carolina border to Montauk Point, New York (fig. 1), aboard a Cessna 182 (aircraft) at an altitude of 500 feet (ft) and approximately 1,200 ft offshore fig. 2. This mission was conducted to collect post-Hurricane Joaquin data for assessing incremental changes in the beach and nearshore area since the last surveys, mission flown in September 2014 (Virginia to New York: Morgan, 2015), November 2012 (northern North Carolina: Morgan and others, 2014) and May 2008 (southern North Carolina: unpublished report), and the data can be used to assess of future coastal change.

The photographs in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft at the time the photograph was taken and do not indicate the location of any feature in the images (see the Navigation Data page). These photographs document the state of the barrier islands and other coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.

In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML file was created using the photographic navigation files. This KML file can be found in the kml folder.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds995","usgsCitation":"Morgan, K.L.M., 2016, Post-Hurricane Joaquin coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Montauk Point, New York, October 7–9, 2015: U.S. Geological Survey Data Series 995, https://dx.doi.org/10.3133/ds995.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074292","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":321248,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0995"},{"id":324389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.55224609374999,\n 33.7243396617476\n ],\n [\n -77.816162109375,\n 33.76088200086917\n ],\n [\n -76.431884765625,\n 34.58799745550482\n ],\n [\n -75.41015624999999,\n 35.21869749632885\n ],\n [\n -75.333251953125,\n 35.7286770448517\n ],\n [\n -75.860595703125,\n 36.923547681089296\n ],\n [\n -75.552978515625,\n 37.448696585910376\n ],\n [\n -74.87182617187499,\n 38.53097889440026\n ],\n [\n -74.70703125,\n 39.00211029922512\n ],\n [\n -74.014892578125,\n 39.63953756436671\n ],\n [\n -73.89404296875,\n 40.51379915504413\n ],\n [\n -72.960205078125,\n 40.60561205826018\n ],\n [\n -71.630859375,\n 41.062786068733026\n ],\n [\n -71.817626953125,\n 41.1455697310095\n ],\n [\n -73.10302734375,\n 40.85537053192496\n ],\n [\n -73.948974609375,\n 40.73893324113603\n ],\n [\n -74.1357421875,\n 40.55554790286311\n ],\n [\n -74.38842773437499,\n 39.7240885773337\n ],\n [\n -75.047607421875,\n 39.00211029922512\n ],\n [\n -75.234375,\n 38.47939467327645\n ],\n [\n -76.256103515625,\n 36.94111143010772\n ],\n [\n -75.684814453125,\n 35.68407153314097\n ],\n [\n -75.69580078125,\n 35.38904996691167\n ],\n [\n -76.57470703125,\n 34.92197103616377\n ],\n [\n -77.376708984375,\n 34.7506398050501\n ],\n [\n -78.046875,\n 34.23451236236984\n ],\n [\n -78.837890625,\n 33.916013113401696\n ],\n [\n -78.55224609374999,\n 33.7243396617476\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-06-27","noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a79398","contributors":{"authors":[{"text":"Morgan, Karen L.M. 0000-0002-2994-5572 kmorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":169124,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","email":"kmorgan@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":628587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70174169,"text":"70174169 - 2016 - Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth","interactions":[],"lastModifiedDate":"2016-06-28T15:11:27","indexId":"70174169","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth","docAbstract":"

In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.advwatres.2015.09.001","usgsCitation":"Carr, J., D’Odorico, P., McGlathery, K., and Wiberg, P.L., 2016, Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth: Advances in Water Resources, v. 93, Part B, p. 315-325, https://doi.org/10.1016/j.advwatres.2015.09.001.","productDescription":"21 p.","startPage":"315","endPage":"325","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067162","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2015.09.001","text":"Publisher Index Page"},{"id":324539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324494,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S030917081500202X"}],"volume":"93, Part B","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb7e4b07657d1a90d66","contributors":{"authors":[{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Odorico, Paul","contributorId":172510,"corporation":false,"usgs":false,"family":"D’Odorico","given":"Paul","email":"","affiliations":[],"preferred":false,"id":641079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGlathery, Karen","contributorId":36057,"corporation":false,"usgs":true,"family":"McGlathery","given":"Karen","affiliations":[],"preferred":false,"id":641080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiberg, Patricia L.","contributorId":72716,"corporation":false,"usgs":true,"family":"Wiberg","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":641081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174167,"text":"70174167 - 2016 - A comparison of three macroinvertebrate sampling devices for use in conducting rapid-assessment procedures of Delmarva Peninsula wetlands","interactions":[],"lastModifiedDate":"2018-08-10T10:03:33","indexId":"70174167","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of three macroinvertebrate sampling devices for use in conducting rapid-assessment procedures of Delmarva Peninsula wetlands","docAbstract":"

Three types of macroinvertebrate collecting devices, Gerking box traps, D-shaped sweep nets, and activity traps, have commonly been used to sample macroinvertebrates when conducting rapid biological assessments of North American wetlands. We compared collections of macroinvertebrates identified to the family level made with these devices in 6 constructed and 2 natural wetlands on the Delmarva Peninsula of Maryland. We also assessed their potential efficacy in comparisons among wetlands using several proportional and richness attributes. Differences in median diversity among samples from the 3 devices were significant; the sweep-net samples had the greatest diversity and the activity-trap samples had the least diversity. Differences in median abundance were not significant between the Gerking box-trap samples and sweep-net samples, but median abundance among activity-trap samples was significantly lower than among samples of the other 2 devices. Within samples, the proportions of median diversity composed of major class and order groupings were similar among the 3 devices. However the proportions of median abundance composed of the major class and order groupings within activity-trap samples were not similar to those of the other 2 devices. There was a slight but significant increase in the total number of families captured when we combined activity-trap samples with Gerking box-trap samples or with sweep-net samples, and the per-sample median numbers of families of the combined activity-trap and sweep-net samples was significantly higher than that of the combined activity-trap and Gerking box-trap samples. We detected significant differences among wetlands for 4 macroinvertebrate attributes with the Gerking box-trap data, 6 attributes with sweep-net data, and 5 attributes with the activity-trap data. A small, but significant increase in the number of attributes showing differences among wetlands occurred when we combined activity-trap samples with those of the Gerking boxtrap or sweep net.

","language":"English","publisher":"Eagle Hill Institute","publisherLocation":"Steuben, ME","doi":"10.1656/045.023.0209","usgsCitation":"Lowe, T.P., Tebbs, K., and Sparling, D.W., 2016, A comparison of three macroinvertebrate sampling devices for use in conducting rapid-assessment procedures of Delmarva Peninsula wetlands: Northeastern Naturalist, v. 23, no. 2, p. 321-338, https://doi.org/10.1656/045.023.0209.","productDescription":"18 p.","startPage":"321","endPage":"338","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066463","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.629638671875,\n 37.04202441635081\n ],\n [\n -76.629638671875,\n 39.639537564366684\n ],\n [\n -74.9102783203125,\n 39.639537564366684\n ],\n [\n -74.9102783203125,\n 37.04202441635081\n ],\n [\n -76.629638671875,\n 37.04202441635081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"57739face4b07657d1a90c97","contributors":{"authors":[{"text":"Lowe, T. Peter plowe@usgs.gov","contributorId":172500,"corporation":false,"usgs":true,"family":"Lowe","given":"T.","email":"plowe@usgs.gov","middleInitial":"Peter","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tebbs, Kerry","contributorId":172511,"corporation":false,"usgs":false,"family":"Tebbs","given":"Kerry","email":"","affiliations":[],"preferred":false,"id":641082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sparling, Donald W.","contributorId":7220,"corporation":false,"usgs":true,"family":"Sparling","given":"Donald","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":641083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174046,"text":"fs20163037 - 2016 - Mapping water use—Landsat and water resources in the United States","interactions":[],"lastModifiedDate":"2019-09-20T10:50:09","indexId":"fs20163037","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3037","displayTitle":"Mapping Water Use—Landsat and Water Resources in the United States","title":"Mapping water use—Landsat and water resources in the United States","docAbstract":"

Using Landsat satellite data, scientists with the U.S. Geological Survey have helped to refine a technique called evapotranspiration mapping to measure how much water crops are using across landscapes and through time. These water-use maps are created using a computer model that integrates Landsat and weather data.

Crucial to the process is the thermal (infrared) band from Landsat. Using the Landsat thermal band with its 100-meter resolution, water-use maps can be created at a scale detailed enough to show how much water crops are using at the level of individual fields anywhere in the world. 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163037","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"U.S. Geological Survey, 2016, Mapping water use—Landsat and water resources in the United States (ver. 1.1, September 2019): U.S. Geological Survey Fact Sheet 2016–3037, 2 p., https://doi.org/10.3133/fs20163037.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075235","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":367504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3037/fs20163037_2.pdf","text":"Report","size":"5.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3037"},{"id":324411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3037/coverthb2.jpg"},{"id":367505,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2016/3037/versionHist.txt","size":"1.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"edition":"Version 1.0: June 27, 2016; Version 1.1 September 18, 2019","contact":"

Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2016-06-27","revisedDate":"2019-09-19","noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"57724020e4b07657d1a79381","contributors":{"authors":[{"text":"Johnson, Rebecca L. 0000-0002-8771-6161 rljohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-8771-6161","contributorId":178874,"corporation":false,"usgs":true,"family":"Johnson","given":"Rebecca","email":"rljohnson@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":640681,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70178788,"text":"70178788 - 2016 - Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps","interactions":[],"lastModifiedDate":"2016-12-07T17:17:02","indexId":"70178788","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps","docAbstract":"

Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of “Decomposition Functional Types” (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with rigorous testing of analytical results; using point measurements and realistic forcing variables to constrain process-based models; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1380","usgsCitation":"Bond-Lamberty, B., Epron, D., Harden, J.W., Harmon, M.E., Hoffman, F., Kumar, J., McGuire, A.D., and Vargas, R., 2016, Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps: Ecosphere, v. 7, no. 6, Article e01380; 13 p., https://doi.org/10.1002/ecs2.1380.","productDescription":"Article e01380; 13 p.","ipdsId":"IP-070883","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1380","text":"Publisher Index Page"},{"id":331662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"58492df3e4b06d80b7b093a6","chorus":{"doi":"10.1002/ecs2.1380","url":"http://dx.doi.org/10.1002/ecs2.1380","publisher":"Wiley-Blackwell","authors":"Bond-Lamberty Ben, Epron Daniel, Harden Jennifer, Harmon Mark E., Hoffman Forrest, Kumar Jitendra, David McGuire Anthony, Vargas Rodrigo","journalName":"Ecosphere","publicationDate":"6/2016"},"contributors":{"authors":[{"text":"Bond-Lamberty, Ben","contributorId":172028,"corporation":false,"usgs":false,"family":"Bond-Lamberty","given":"Ben","email":"","affiliations":[{"id":13566,"text":"Joint Global Change Research Institute, Pacific Northwest National Laboratory","active":true,"usgs":false},{"id":33852,"text":"Univ of Maryland, College Park, MD","active":true,"usgs":false}],"preferred":false,"id":655178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Epron, Daniel","contributorId":177277,"corporation":false,"usgs":false,"family":"Epron","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":655179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":655180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harmon, Mark E.","contributorId":96961,"corporation":false,"usgs":true,"family":"Harmon","given":"Mark","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Forrest","contributorId":177278,"corporation":false,"usgs":false,"family":"Hoffman","given":"Forrest","email":"","affiliations":[],"preferred":false,"id":655132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Jitendra","contributorId":177279,"corporation":false,"usgs":false,"family":"Kumar","given":"Jitendra","email":"","affiliations":[],"preferred":false,"id":655182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, Anthony D. 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":2493,"corporation":false,"usgs":true,"family":"McGuire","given":"Anthony","email":"ffadm@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":655183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vargas, Rodrigo","contributorId":172036,"corporation":false,"usgs":false,"family":"Vargas","given":"Rodrigo","affiliations":[],"preferred":false,"id":655184,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174329,"text":"70174329 - 2016 - Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.","interactions":[],"lastModifiedDate":"2016-07-08T11:45:45","indexId":"70174329","displayToPublicDate":"2016-06-26T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2884,"text":"North American Fauna","active":true,"publicationSubtype":{"id":10}},"title":"Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.","docAbstract":"

Spectacled eider Somateria fischeri numbers have declined and they are considered threatened in accordance with the US Endangered Species Act throughout their range. We synthesized the available information for spectacled eiders to construct deterministic, stochastic, and metapopulation models for this species that incorporated current estimates of vital rates such as nest success, adult survival, and the impact of lead poisoning on survival. Elasticities of our deterministic models suggested that the populations would respond most dramatically to changes in adult female survival and that the reductions in adult female survival related to lead poisoning were locally important. We also examined the sensitivity of the population to changes in lead exposure rates. With the knowledge that some vital rates vary with environmental conditions, we cast stochastic models that mimicked observed variation in productivity. We also used the stochastic model to examine the probability that a specific population will persist for periods of up to 50 y. Elasticity analysis of these models was consistent with that for the deterministic models, with perturbations to adult female survival having the greatest effect on population projections. When used in single population models, demographic data for some localities predicted rapid declines that were inconsistent with our observations in the field. Thus, we constructed a metapopulation model and examined the predictions for local subpopulations and the metapopulation over a wide range of dispersal rates. Using the metapopulation model, we were able to simulate the observed stability of local subpopulations as well as that of the metapopulation. Finally, we developed a global metapopulation model that simulates periodic winter habitat limitation, similar to that which might be experienced in years of heavy sea ice in the core wintering area of spectacled eiders in the central Bering Sea. Our metapopulation analyses suggested that no subpopulation is independent and that future management actions may be improved through a metapopulation framework. For example, management actions could include displacement of breeding females from\"sink\" areas that reduce the growth potential of the population as a whole. However, this action is contingent upon dispersal among local populations, for which there is limited information. Thus, we recommend that researchers examine dispersal behavior among areas on the Yukon-Kuskokwim Delta in western Alaska. The metapopulation framework could also be applied at the rangewide scale to address the density-dependent limitation of available polynya habitat during winter that may limit the recovery of small subpopulations, such as that on the Yukon-Kuskokwim Delta. Reductions in other subpopulations may be necessary to ensure an increase in the Yukon-Kuskokwim Delta population. Thus, we recommend that managers consider the interpopulation dynamics of spectacled eiders at different spatial scales in future management actions.

","language":"English","doi":"10.3996/nafa.81.0001","usgsCitation":"Flint, P.L., Grand, J.B., Petersen, M.R., and Rockwell, R.F., 2016, Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.: North American Fauna, v. 81, p. 1-41, https://doi.org/10.3996/nafa.81.0001.","productDescription":"iii, 44 p.","startPage":"1","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057251","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470842,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/nafa.81.0001","text":"Publisher Index Page"},{"id":438607,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74B2ZCK","text":"USGS data release","linkHelpText":"Spectacled Eider (Somateria fischeri) Nest, Capture, and Resight Records Yukon-Kuskokwim Delta, Alaska"},{"id":324910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.85546875,\n 59.80063426102869\n ],\n [\n -145.283203125,\n 60.02095215374802\n ],\n [\n -146.25,\n 60.02095215374802\n ],\n [\n -147.744140625,\n 59.57885104663186\n ],\n [\n -150.205078125,\n 59.0405546167585\n ],\n [\n -151.435546875,\n 57.32652122521709\n ],\n [\n -153.45703125,\n 56.26776108757582\n ],\n [\n -163.65234374999997,\n 52.482780222078205\n ],\n [\n -177.36328125,\n 50.064191736659104\n ],\n [\n -186.15234374999997,\n 50.12057809796008\n ],\n [\n -195.64453125,\n 54.67383096593114\n ],\n [\n -196.5234375,\n 57.938183012205315\n ],\n [\n -202.060546875,\n 62.471723714758724\n ],\n [\n -222.626953125,\n 72.18180355624855\n ],\n [\n -228.69140625,\n 75.67219739055291\n ],\n [\n -228.603515625,\n 76.51681887717322\n ],\n [\n -219.375,\n 77.13761179723426\n ],\n [\n -210.76171875,\n 77.19617635994676\n ],\n [\n -195.64453125,\n 77.2156395545647\n ],\n [\n -179.912109375,\n 76.78065491639973\n ],\n [\n -162.0703125,\n 75.47513069090051\n ],\n [\n -149.23828125,\n 74.18805166460048\n ],\n [\n -140.888671875,\n 69.7485511291223\n ],\n [\n -141.85546875,\n 59.80063426102869\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-22","publicationStatus":"PW","scienceBaseUri":"5780ceb6e4b0811616822315","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":641925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":641926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":641927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rockwell, Robert F.","contributorId":172752,"corporation":false,"usgs":false,"family":"Rockwell","given":"Robert","email":"","middleInitial":"F.","affiliations":[{"id":6989,"text":"American Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":641928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174335,"text":"70174335 - 2016 - Diadophis Puntatus Puntatus (Southern Ring-neck Snake) Predation","interactions":[],"lastModifiedDate":"2016-07-08T13:02:51","indexId":"70174335","displayToPublicDate":"2016-06-26T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Diadophis Puntatus Puntatus (Southern Ring-neck Snake) Predation","docAbstract":"

DIADOPHIS PUNCTATUS PUNCTATUS (Southern Ring-necked Snake). PREDATION. Here I present the first record of Buteo lineatus (Red-shouldered Hawk) predator on a Diadophis p. punctatus. At ca. 1100h on l2 February2 013,I observed a B. lineatus eating a katydid in Corkscrew Swamp Sanctuary (26.2730'N, 81.6079\"W;WGS 84), Collier Co., Florida, USA. The hawk was in a Pond Cypress tree on the edge of a small prairie bordered on one side by a cypress swamp and by pine woodland on the other. Immediately upon consuming the katydid, the hawk flew to the ground ca. 1.5 m from an elevated boardwalk to grab an adult D. punctatus. It then flew with the snake in its talons to a branch 3 m high ca. l0 m from the boardwalk. The hawk stretched and otherwise manipulated the struggling snake (Fig.1) before consuming the still moving snake. Although snakes are a well-known component of B. lineatus diet (Clark1 987A. Field Guide to the Hawks of North America. Houghton Mifflin Co. Boston, Massachusetts 198 pp.), I found only one literature reference to Red-shouldered Hawks eating Ring-neck Snakes (Fisher 1893.Hawks and Owls of the United States in their Relation to Agriculture. U.S. Dept. Agric., Div Ornith. Mamm. Bull. 3). That specimen was from Canton, New York (taken 26 Oct IBBB) and would be a D. p. edwardisii (Northern Ring-necked Snake), while the snake reported on here is a Diadophis p. punctatus (USNM Herp Image 2847a -c). Based on evidence presented by Fontanella et al. (2008. Mol. Phylogenet Evol.46:1049-1070), D. p. edwardisii and D. p. punctatus are likely different species.

","language":"English","usgsCitation":"Gotte, S.W., 2016, Diadophis Puntatus Puntatus (Southern Ring-neck Snake) Predation: Herpetological Review, v. 47, no. 2.","productDescription":"1 p.","startPage":"310","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074076","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Collier County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.87310791015625,\n 25.81101826700785\n ],\n [\n -81.3812255859375,\n 25.738055028213907\n ],\n [\n -81.63528442382812,\n 25.888878582127084\n ],\n [\n -81.66824340820312,\n 25.835741380387113\n ],\n [\n -81.6888427734375,\n 25.834505347339903\n ],\n [\n -81.83853149414062,\n 26.10858718364705\n ],\n [\n -81.84677124023438,\n 26.218287092329764\n ],\n [\n -81.85089111328125,\n 26.282333614751355\n ],\n [\n -81.58309936523438,\n 26.27248260209306\n ],\n [\n -81.58584594726562,\n 26.45090222367262\n ],\n [\n -81.44439697265624,\n 26.45090222367262\n ],\n [\n -80.848388671875,\n 26.433687518117914\n ],\n [\n -80.87310791015625,\n 25.81101826700785\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780ceb4e4b08116168222f9","contributors":{"authors":[{"text":"Gotte, Steve W. 0000-0001-5509-4495 sgotte@usgs.gov","orcid":"https://orcid.org/0000-0001-5509-4495","contributorId":4481,"corporation":false,"usgs":true,"family":"Gotte","given":"Steve","email":"sgotte@usgs.gov","middleInitial":"W.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641954,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}