Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water. The Basin and Range basin-fill aquifers constitute one of the important areas being evaluated. One or more inorganic constituents with human-health benchmarks were detected at high concentrations in about 20 percent of the study area and at moderate concentrations in about 49 percent. Organic constituents were not detected at high concentrations in the study area. One or more organic constituents with human-health benchmarks were detected at moderate concentrations in about 3 percent of the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163080","collaboration":"National Water Quality ProgramNAWQA Chief Scientist
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
http://water.usgs.gov/nawqa/
Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water. The Valley and Ridge and Piedmont and Blue Ridge carbonate-rock aquifers constitute two of the important areas being evaluated. One or more inorganic constituents with human-health benchmarks were detected at high concentrations in about 15 percent of the study area and at moderate concentrations in about 17 percent. Organic constituents were not detected at high concentrations in the study area. One or more organic constituents with human-health benchmarks were detected at moderate concentrations in about 2 percent of the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163079","collaboration":"National Water Quality ProgramNAWQA Chief Scientist
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192-0002
http://water.usgs.gov/nawqa/
Wind energy generation holds the potential to adversely affect wildlife populations. Species-wide effects are difficult to study and few, if any, studies examine effects of wind energy generation on any species across its entire range. One species that may be affected by wind energy generation is the endangered Indiana bat (Myotis sodalis), which is found in the eastern and midwestern United States. In addition to mortality from wind energy generation, the species also faces range-wide threats from the emerging infectious fungal disease, white-nose syndrome (WNS). White-nose syndrome, caused by Pseudogymnoascus destructans, disturbs hibernating bats leading to high levels of mortality. We used a spatially explicit full-annual-cycle model to investigate how wind turbine mortality and WNS may singly and then together affect population dynamics of this species. In the simulation, wind turbine mortality impacted the metapopulation dynamics of the species by causing extirpation of some of the smaller winter colonies. In general, effects of wind turbines were localized and focused on specific spatial subpopulations. Conversely, WNS had a depressive effect on the species across its range. Wind turbine mortality interacted with WNS and together these stressors had a larger impact than would be expected from either alone, principally because these stressors together act to reduce species abundance across the spectrum of population sizes. Our findings illustrate the importance of not only prioritizing the protection of large winter colonies as is currently done, but also of protecting metapopulation dynamics and migratory connectivity.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.2830","usgsCitation":"Erickson, R.A., Thogmartin, W.E., Diffendorfer, J., Russell, R.E., and Szymanski, J.A., 2016, Effects of wind energy generation and white-nose syndrome on the viability of the Indiana bat: PeerJ, p. 1-19, https://doi.org/10.7717/peerj.2830.","productDescription":"e2830; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-066589","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470274,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.2830","text":"Publisher Index Page"},{"id":333324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335420,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F75M63TN","text":"Indiana Bat 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wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":658722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":658723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":658724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szymanski, Jennifer A.","contributorId":51593,"corporation":false,"usgs":true,"family":"Szymanski","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":658725,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179687,"text":"70179687 - 2016 - Using spatial capture–recapture to elucidate population processes and space-use in herpetological studies","interactions":[],"lastModifiedDate":"2017-01-11T12:44:15","indexId":"70179687","displayToPublicDate":"2017-01-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Using spatial capture–recapture to elucidate population processes and space-use in herpetological studies","docAbstract":"The cryptic behavior and ecology of herpetofauna make estimating the impacts of environmental change on demography difficult; yet, the ability to measure demographic relationships is essential for elucidating mechanisms leading to the population declines reported for herpetofauna worldwide. Recently developed spatial capture–recapture (SCR) methods are well suited to standard herpetofauna monitoring approaches. Individually identifying animals and their locations allows accurate estimates of population densities and survival. Spatial capture–recapture methods also allow estimation of parameters describing space-use and movement, which generally are expensive or difficult to obtain using other methods. In this paper, we discuss the basic components of SCR models, the available software for conducting analyses, and the experimental designs based on common herpetological survey methods. We then apply SCR models to Red-backed Salamander (Plethodon cinereus), to determine differences in density, survival, dispersal, and space-use between adult male and female salamanders. By highlighting the capabilities of SCR, and its advantages compared to traditional methods, we hope to give herpetologists the resource they need to apply SCR in their own systems.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","publisherLocation":"Riverside, CA","doi":"10.1670/15-166","usgsCitation":"Munoz, D.J., Miller, D.A., Sutherland, C., and Grant, E., 2016, Using spatial capture–recapture to elucidate population processes and space-use in herpetological studies: Journal of Herpetology, v. 50, no. 4, p. 570-581, https://doi.org/10.1670/15-166.","productDescription":"12 p.","startPage":"570","endPage":"581","ipdsId":"IP-069319","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":333056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58772078e4b0315b4c11fe2c","contributors":{"authors":[{"text":"Munoz, David J.","contributorId":178213,"corporation":false,"usgs":false,"family":"Munoz","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":658226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":658227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":658228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grant, Evan H. Campbell ehgrant@usgs.gov","contributorId":146545,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","email":"ehgrant@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":658229,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179686,"text":"70179686 - 2016 - Evaluating within-population variability in behavior and demography for the adaptive potential of a dispersal-limited species to climate change","interactions":[],"lastModifiedDate":"2017-01-11T13:08:24","indexId":"70179686","displayToPublicDate":"2017-01-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating within-population variability in behavior and demography for the adaptive potential of a dispersal-limited species to climate change","docAbstract":"Multiple pathways exist for species to respond to changing climates. However, responses of dispersal-limited species will be more strongly tied to ability to adapt within existing populations as rates of environmental change will likely exceed movement rates. Here, we assess adaptive capacity in Plethodon cinereus, a dispersal-limited woodland salamander. We quantify plasticity in behavior and variation in demography to observed variation in environmental variables over a 5-year period. We found strong evidence that temperature and rainfall influence P. cinereus surface presence, indicating changes in climate are likely to affect seasonal activity patterns. We also found that warmer summer temperatures reduced individual growth rates into the autumn, which is likely to have negative demographic consequences. Reduced growth rates may delay reproductive maturity and lead to reductions in size-specific fecundity, potentially reducing population-level persistence. To better understand within-population variability in responses, we examined differences between two common color morphs. Previous evidence suggests that the color polymorphism may be linked to physiological differences in heat and moisture tolerance. We found only moderate support for morph-specific differences for the relationship between individual growth and temperature. Measuring environmental sensitivity to climatic variability is the first step in predicting species' responses to climate change. Our results suggest phenological shifts and changes in growth rates are likely responses under scenarios where further warming occurs, and we discuss possible adaptive strategies for resulting selective pressures.
","language":"English","publisher":"Blackwell Pub. Ltd.","publisherLocation":"Oxford","doi":"10.1002/ece3.2573","usgsCitation":"Munoz, D.J., Miller Hesed, K., Grant, E., and Miller, D.A., 2016, Evaluating within-population variability in behavior and demography for the adaptive potential of a dispersal-limited species to climate change: Ecology and Evolution, v. 6, no. 24, p. 8740-8755, https://doi.org/10.1002/ece3.2573.","productDescription":"16 p.","startPage":"8740","endPage":"8755","ipdsId":"IP-075389","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2573","text":"Publisher Index Page"},{"id":333058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"24","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-17","publicationStatus":"PW","scienceBaseUri":"58772078e4b0315b4c11fe2e","contributors":{"authors":[{"text":"Munoz, David J.","contributorId":178213,"corporation":false,"usgs":false,"family":"Munoz","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":658222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller Hesed, Kyle","contributorId":178214,"corporation":false,"usgs":false,"family":"Miller Hesed","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":658223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Evan H. Campbell ehgrant@usgs.gov","contributorId":3696,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","email":"ehgrant@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":658221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":658224,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179639,"text":"70179639 - 2016 - Climatic drivers for multidecadal shifts in solute transport and methane production zones within a large peat basin","interactions":[],"lastModifiedDate":"2018-10-17T09:12:30","indexId":"70179639","displayToPublicDate":"2017-01-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Climatic drivers for multidecadal shifts in solute transport and methane production zones within a large peat basin","docAbstract":"Northern peatlands are an important source for greenhouse gases, but their capacity to produce methane remains uncertain under changing climatic conditions. We therefore analyzed a 43 year time series of the pore-water chemistry to determine if long-term shifts in precipitation altered the vertical transport of solutes within a large peat basin in northern Minnesota. These data suggest that rates of methane production can be finely tuned to multidecadal shifts in precipitation that drive the vertical penetration of labile carbon substrates within the Glacial Lake Agassiz Peatlands. Tritium and cation profiles demonstrate that only the upper meter of these peat deposits was flushed by downwardly moving recharge from 1965 to 1983 during a Transitional Dry-to-Moist Period. However, a shift to a moister climate after 1984 drove surface waters much deeper, largely flushing the pore waters of all bogs and fens to depths of 2 m. Labile carbon compounds were transported downward from the rhizosphere to the basal peat at this time producing a substantial enrichment of methane in Δ14C with respect to the solid-phase peat from 1991 to 2008. These data indicate that labile carbon substrates can fuel deep production zones of methanogenesis that more than doubled in thickness across this large peat basin after 1984. Moreover, the entire peat profile apparently has the capacity to produce methane from labile carbon substrates depending on climate-driven modes of solute transport. Future changes in precipitation may therefore play a central role in determining the source strength of peatlands in the global methane cycle.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GB005397","usgsCitation":"Glaser, P.H., Siegel, D.I., Chanton, J.P., Reeve, A.S., Rosenberry, D.O., Corbett, J.E., Dasgupta, S., and Levy, Z., 2016, Climatic drivers for multidecadal shifts in solute transport and methane production zones within a large peat basin: Global Biogeochemical Cycles, v. 30, no. 11, p. 1578-1598, https://doi.org/10.1002/2016GB005397.","productDescription":"21 p.","startPage":"1578","endPage":"1598","ipdsId":"IP-078603","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470277,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005397","text":"Publisher Index Page"},{"id":332983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Glacial Lake Agassiz Peatlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.6667,\n 48.065232067568\n ],\n [\n -95.6667,\n 48.73083222613515\n ],\n [\n -93.8232421875,\n 48.73083222613515\n ],\n [\n -93.8232421875,\n 48.065232067568\n ],\n [\n -95.6667,\n 48.065232067568\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-03","publicationStatus":"PW","scienceBaseUri":"5874b0ace4b0a829a320bb61","contributors":{"authors":[{"text":"Glaser, Paul H.","contributorId":178129,"corporation":false,"usgs":false,"family":"Glaser","given":"Paul","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":658005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siegel, Donald I.","contributorId":178130,"corporation":false,"usgs":false,"family":"Siegel","given":"Donald","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":658006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chanton, Jeffrey P.","contributorId":178131,"corporation":false,"usgs":false,"family":"Chanton","given":"Jeffrey","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":658007,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeve, Andrew S.","contributorId":178132,"corporation":false,"usgs":false,"family":"Reeve","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":658008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":658004,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corbett, J. Elizabeth","contributorId":178133,"corporation":false,"usgs":false,"family":"Corbett","given":"J.","email":"","middleInitial":"Elizabeth","affiliations":[],"preferred":false,"id":658009,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dasgupta, Soumitri","contributorId":178134,"corporation":false,"usgs":false,"family":"Dasgupta","given":"Soumitri","email":"","affiliations":[],"preferred":false,"id":658010,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Levy, Zeno","contributorId":178135,"corporation":false,"usgs":false,"family":"Levy","given":"Zeno","affiliations":[],"preferred":false,"id":658011,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70179578,"text":"70179578 - 2016 - Introduction: Special issue on advances in topobathymetric mapping, models, and applications","interactions":[],"lastModifiedDate":"2017-01-17T19:01:51","indexId":"70179578","displayToPublicDate":"2017-01-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Introduction: Special issue on advances in topobathymetric mapping, models, and applications","docAbstract":"Detailed knowledge of near-shore topography and bathymetry is required for many geospatial data applications in the coastal environment. New data sources and processing methods are facilitating development of seamless, regional-scale topobathymetric digital elevation models. These elevation models integrate disparate multi-sensor, multi-temporal topographic and bathymetric datasets to provide a coherent base layer for coastal science applications such as wetlands mapping and monitoring, sea-level rise assessment, benthic habitat mapping, erosion monitoring, and storm impact assessment. The focus of this special issue is on recent advances in the source data, data processing and integration methods, and applications of topobathymetric datasets.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-001","usgsCitation":"Gesch, D.B., Brock, J., Parrish, C.E., Rogers, J.N., and Wright, C., 2016, Introduction: Special issue on advances in topobathymetric mapping, models, and applications: Journal of Coastal Research, v. Special Issue 76, p. 1-3, https://doi.org/10.2112/SI76-001.","productDescription":"3 p.","startPage":"1","endPage":"3","ipdsId":"IP-079356","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470278,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.2112/SI76-001","text":"External Repository"},{"id":332922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586f69a8e4b01a71ba0bc909","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":657801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":657802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parrish, Christopher E.","contributorId":178021,"corporation":false,"usgs":false,"family":"Parrish","given":"Christopher","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Jeffrey N.","contributorId":178022,"corporation":false,"usgs":false,"family":"Rogers","given":"Jeffrey","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":657804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":178023,"corporation":false,"usgs":true,"family":"Wright","given":"C. Wayne","email":"wwright@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":657805,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179581,"text":"70179581 - 2016 - Final Laurentide ice-sheet deglaciation and Holocene climate-sea level change","interactions":[],"lastModifiedDate":"2017-01-05T10:01:22","indexId":"70179581","displayToPublicDate":"2017-01-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Final Laurentide ice-sheet deglaciation and Holocene climate-sea level change","docAbstract":"Despite elevated summer insolation forcing during the early Holocene, global ice sheets retained nearly half of their volume from the Last Glacial Maximum, as indicated by deglacial records of global mean sea level (GMSL). Partitioning the GMSL rise among potential sources requires accurate dating of ice-sheet extent to estimate ice-sheet volume. Here, we date the final retreat of the Laurentide Ice Sheet with 10Be surface exposure ages for the Labrador Dome, the largest of the remnant Laurentide ice domes during the Holocene. We show that the Labrador Dome deposited moraines during North Atlantic cold events at ∼10.3 ka, 9.3 ka and 8.2 ka, suggesting that these regional climate events helped stabilize the retreating Labrador Dome in the early Holocene. After Hudson Bay became seasonally ice free at ∼8.2 ka, the majority of Laurentide ice-sheet melted abruptly within a few centuries. We demonstrate through high-resolution regional climate model simulations that the thermal properties of a seasonally ice-free Hudson Bay would have increased Laurentide ice-sheet ablation and thus contributed to the subsequent rapid Labrador Dome retreat. Finally, our new 10Be chronology indicates full Laurentide ice-sheet had completely deglaciated by 6.7 ± 0.4 ka, which re quires that Antarctic ice sheets contributed 3.6–6.5 m to GMSL rise since 6.3–7.1 ka.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2016.09.014","usgsCitation":"Ullman, D.J., Carlson, A.E., Hostetler, S.W., Clark, P.U., Cuzzone, J., Milne, G.A., Winsor, K., and Caffee, M.A., 2016, Final Laurentide ice-sheet deglaciation and Holocene climate-sea level change: Quaternary Science Reviews, v. 152, p. 49-59, https://doi.org/10.1016/j.quascirev.2016.09.014.","productDescription":"11 p.","startPage":"49","endPage":"59","ipdsId":"IP-072855","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470280,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2016.09.014","text":"Publisher Index Page"},{"id":332921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586f69a8e4b01a71ba0bc907","contributors":{"authors":[{"text":"Ullman, David J.","contributorId":178024,"corporation":false,"usgs":false,"family":"Ullman","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Anders E.","contributorId":178025,"corporation":false,"usgs":false,"family":"Carlson","given":"Anders","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":657807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Peter U.","contributorId":178026,"corporation":false,"usgs":false,"family":"Clark","given":"Peter","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":657810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuzzone, Joshua","contributorId":178027,"corporation":false,"usgs":false,"family":"Cuzzone","given":"Joshua","email":"","affiliations":[],"preferred":false,"id":657811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Milne, Glenn A.","contributorId":178028,"corporation":false,"usgs":false,"family":"Milne","given":"Glenn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":657812,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winsor, Kelsey","contributorId":178029,"corporation":false,"usgs":false,"family":"Winsor","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":657813,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Caffee, Marc A.","contributorId":36048,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":657824,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70179582,"text":"70179582 - 2016 - Implementation and evaluation of a monthly water balance model over the US on an 800 m grid","interactions":[],"lastModifiedDate":"2017-01-19T13:42:38","indexId":"70179582","displayToPublicDate":"2017-01-05T00:00:00","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":"Implementation and evaluation of a monthly water balance model over the US on an 800 m grid","docAbstract":"We simulate the 1950–2010 water balance for the conterminous U.S. (CONUS) with a monthly water balance model (MWBM) using the 800 m Parameter-elevation Regression on Independent Slopes Model (PRISM) data set as model input. We employed observed snow and streamflow data sets to guide modification of the snow and potential evapotranspiration components in the default model and to evaluate model performance. Based on various metrics and sensitivity tests, the modified model yields reasonably good simulations of seasonal snowpack in the West (range of bias of ±50 mm at 68% of 713 SNOTEL sites), the gradients and magnitudes of actual evapotranspiration, and runoff (median correlation of 0.83 and median Nash-Sutcliff efficiency of 0.6 between simulated and observed annual time series at 1427 USGS gage sites). The model generally performs well along the Pacific Coast, the high elevations of the Basin and Range and over the Midwest and East, but not as well over the dry areas of the Southwest and upper Plains regions due, in part, to the apportioning of direct versus delayed runoff. Sensitivity testing and application of the MWBM to simulate the future water balance at four National Parks when driven by 30 climate models from the Climate Model Intercomparison Program Phase 5 (CMIP5) demonstrate that the model is useful for evaluating first-order, climate driven hydrologic change on monthly and annual time scales.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR018665","usgsCitation":"Hostetler, S.W., and Alder, J.R., 2016, Implementation and evaluation of a monthly water balance model over the US on an 800 m grid: Water Resources Research, v. 52, no. 12, p. 9600-9620, https://doi.org/10.1002/2016WR018665.","productDescription":"20 p.","startPage":"9600","endPage":"9620","ipdsId":"IP-072570","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":332920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-27","publicationStatus":"PW","scienceBaseUri":"586f69a3e4b01a71ba0bc8fd","contributors":{"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":657814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":657815,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179598,"text":"70179598 - 2016 - Depth calibration and validation of the Experimental Advanced Airborne Research Lidar, EAARL-B","interactions":[],"lastModifiedDate":"2020-02-13T10:03:10","indexId":"70179598","displayToPublicDate":"2017-01-05T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Depth calibration and validation of the Experimental Advanced Airborne Research Lidar, EAARL-B","docAbstract":"The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research\nLidar (EAARL), was extensively modified to increase the spatial sampling density and improve performance in\nwater ranging from 3–44 m. The new (EAARL-B) sensor features a 300% increase in spatial density, which was\nachieved by optically splitting each laser pulse into 3 pulses spatially separated by 1.6 m along the flight track and\n2.0 m across-track on the water surface when flown at a nominal altitude of 300 m. Improved depth capability was\nachieved by increasing the total peak laser power by a factor of 10, and incorporating a new “deep-water” receiver,\noptimized to exclusively receive refracted and scattered light from deeper water (15–44 m). Two clear-water\nmissions were conducted to determine the EAARL-B depth calibration coefficients. The calibration mission was\nconducted over the U.S. Navy’s South Florida Testing Facility (SFTF), an established lidar calibration range located\nin the coastal waters southeast of Fort Lauderdale, Florida. A second mission was conducted over Lang Bank, St.\nCroix, U.S. Virgin Islands. The EAARL-B survey was spatially and temporally coincident with multibeam sonar\nsurveys conducted by the National Oceanic and Atmospheric Administration (NOAA) ship Nancy Foster. The\nNOAA depth data range from 10–100 m, whereas the EAARL-B captured data from 0–41 m. Coefficients derived\nfrom the SFTF calibration mission were used to correct the EAARL-B data from both missions. The resulting\ncalibrated EAARL-B data were then compared with the original reference dataset, a jet-ski-based single beam sonar\ndataset from the SFTF site, and the deeper NOAA data from St. Croix. Additionally, EAARL-B depth accuracy was\nevaluated by comparing the depth results to International Hydrographic Organization (IHO) standards. Results show\ngood agreement between the calibrated EAARL-B data and all three reference datasets, with 95% confidence levels\nwell within the maximum allowable total vertical uncertainty for IHO Order 1 surveys.","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-002","usgsCitation":"Wright, C., Kranenburg, C.J., Battista, T.A., and Parrish, C., 2016, Depth calibration and validation of the Experimental Advanced Airborne Research Lidar, EAARL-B: Journal of Coastal Research, v. Special Issue 76, p. 4-17, https://doi.org/10.2112/SI76-002.","productDescription":"Report: 14 p.; 2 Data Releases","startPage":"4","endPage":"17","ipdsId":"IP-066550","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470279,"rank":4,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/50788","text":"External Repository"},{"id":332919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372320,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"USGS data release","linkHelpText":"EAARL-B Submerged Topography—Fort Lauderdale, Florida, 2014"},{"id":372321,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F73T9F86","text":"USGS data release ","linkHelpText":"EAARL-B Submerged Topography—Saint Croix, U.S. Virgin Islands, 2014"}],"volume":"Special Issue 76","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586f69a6e4b01a71ba0bc905","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":178023,"corporation":false,"usgs":true,"family":"Wright","given":"C. Wayne","email":"wwright@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":657816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranenburg, Christine J. 0000-0002-2955-0167 ckranenburg@usgs.gov","orcid":"https://orcid.org/0000-0002-2955-0167","contributorId":169234,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine","email":"ckranenburg@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":657817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battista, Timothy A.","contributorId":178030,"corporation":false,"usgs":false,"family":"Battista","given":"Timothy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":657818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parrish, Christopher","contributorId":98635,"corporation":false,"usgs":true,"family":"Parrish","given":"Christopher","affiliations":[],"preferred":false,"id":657819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70180390,"text":"70180390 - 2016 - Dissolved organic matter composition of Arctic rivers: Linking permafrost and parent material to riverine carbon","interactions":[],"lastModifiedDate":"2017-01-30T09:36:37","indexId":"70180390","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Dissolved organic matter composition of Arctic rivers: Linking permafrost and parent material to riverine carbon","docAbstract":"Recent climate change in the Arctic is driving permafrost thaw, which has important implications for regional hydrology and global carbon dynamics. Permafrost is an important control on groundwater dynamics and the amount and chemical composition of dissolved organic matter (DOM) transported by high-latitude rivers. The consequences of permafrost thaw for riverine DOM dynamics will likely vary across space and time, due in part to spatial variation in ecosystem properties in Arctic watersheds. Here we examined watershed controls on DOM composition in 69 streams and rivers draining heterogeneous landscapes across a broad region of Arctic Alaska. We characterized DOM using bulk dissolved organic carbon (DOC) concentration, optical properties, and chemical fractionation and classified watersheds based on permafrost characteristics (mapping of parent material and ground ice content, modeling of thermal state) and ecotypes. Parent material and ground ice content significantly affected the amount and composition of DOM. DOC concentrations were higher in watersheds underlain by fine-grained loess compared to watersheds underlain by coarse-grained sand or shallow bedrock. DOC concentration was also higher in rivers draining ice-rich landscapes compared to rivers draining ice-poor landscapes. Similarly, specific ultraviolet absorbance (SUVA254, an index of DOM aromaticity) values were highest in watersheds underlain by fine-grained deposits or ice-rich permafrost. We also observed differences in hydrophobic organic acids, hydrophilic compounds, and DOM fluorescence across watersheds. Both DOC concentration and SUVA254 were negatively correlated with watershed active layer thickness, as determined by high-resolution permafrost modeling. Together, these findings highlight how spatial variations in permafrost physical and thermal properties can influence riverine DOM.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GB005482","usgsCitation":"O’Donnell, J.A., Aiken, G.R., Swanson, D.K., Santosh, P., Butler, K.D., and Baltensperger, A.P., 2016, Dissolved organic matter composition of Arctic rivers: Linking permafrost and parent material to riverine carbon: Global Biogeochemical Cycles, v. 30, no. 12, p. 1811-1826, https://doi.org/10.1002/2016GB005482.","productDescription":"16 p","startPage":"1811","endPage":"1826","ipdsId":"IP-081691","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470284,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005482","text":"Publisher Index Page"},{"id":334279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-19","publicationStatus":"PW","scienceBaseUri":"58905ef1e4b072a7ac0cad35","contributors":{"authors":[{"text":"O’Donnell, Jonathan A.","contributorId":178151,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":661502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":661501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swanson, David K.","contributorId":178902,"corporation":false,"usgs":false,"family":"Swanson","given":"David","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":661503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Santosh, Panda","contributorId":178903,"corporation":false,"usgs":false,"family":"Santosh","given":"Panda","email":"","affiliations":[],"preferred":false,"id":661504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butler, Kenna D. 0000-0001-9604-4603 kebutler@usgs.gov","orcid":"https://orcid.org/0000-0001-9604-4603","contributorId":178885,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":661506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baltensperger, Andrew P.","contributorId":178904,"corporation":false,"usgs":false,"family":"Baltensperger","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":661505,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179599,"text":"70179599 - 2016 - Defining resilience: A preliminary integrative literature review","interactions":[],"lastModifiedDate":"2017-01-06T14:04:07","indexId":"70179599","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Defining resilience: A preliminary integrative literature review","docAbstract":"The term “resilience” is ubiquitous in technical literature; it appears in numerous forms, such as resilience, resiliency, or resilient, and each use may have a different definition depending on the interpretation of the writer. This creates difficulties in understanding what is meant by ‘resilience’ in any given use case, especially in discussions of interdisciplinary research. To better understand this problem, this research constructs a preliminary integrative literature review to map different definitions, applications and calculation methods of resilience invoked within critical infrastructure applications. The preliminary review uses a State-of-the-Art Matrix (SAM) analysis to characterize differences in definition across disciplines and between regions. Qualifying the various usages of resilience will produce a greater precision in the literature and a deeper insight into types of data required for its evaluation, particularly with respect to critical infrastructure calculations and how such data may be analyzed. Results from this SAM analysis will create a framework of key concepts as part of the most common applications for “resilient critical infrastructure” modeling.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the American Society for Engineering Management 2016","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"American Society for Engineering Management","usgsCitation":"Wilt, B., Long, S.K., and Shoberg, T.G., 2016, Defining resilience: A preliminary integrative literature review, in Proceedings of the American Society for Engineering Management 2016, 10 p.","productDescription":"10 p.","ipdsId":"IP-076921","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":332951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58772079e4b0315b4c11fe32","contributors":{"authors":[{"text":"Wilt, Bonnie","contributorId":178032,"corporation":false,"usgs":false,"family":"Wilt","given":"Bonnie","email":"","affiliations":[],"preferred":false,"id":657821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Suzanna K.","contributorId":146270,"corporation":false,"usgs":false,"family":"Long","given":"Suzanna","email":"","middleInitial":"K.","affiliations":[{"id":16655,"text":"Dept. of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":657822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoberg, Thomas G. 0000-0003-0173-1246 tshoberg@usgs.gov","orcid":"https://orcid.org/0000-0003-0173-1246","contributorId":3764,"corporation":false,"usgs":true,"family":"Shoberg","given":"Thomas","email":"tshoberg@usgs.gov","middleInitial":"G.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":657820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179630,"text":"70179630 - 2016 - A new biogeographically disjunct giant gecko (Gehyra: Gekkonidae: Reptilia) from the East Melanesian Islands ","interactions":[],"lastModifiedDate":"2017-01-10T11:19:34","indexId":"70179630","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3814,"text":"Zootaxa","onlineIssn":"1175-5334","printIssn":"1175-5326","active":true,"publicationSubtype":{"id":10}},"title":"A new biogeographically disjunct giant gecko (Gehyra: Gekkonidae: Reptilia) from the East Melanesian Islands ","docAbstract":"The East Melanesian Islands have been a focal area for research into island biogeography and community ecology. However, previously undescribed and biogeographically significant new species endemic to this region continue to be discovered. Here we describe a phylogenetically distinct (~20% divergence at the mitochondrial ND2 gene) and biogeographically disjunct new species of gecko in the genus Gehyra, from the Admiralty and St Matthias Islands. Gehyra rohan sp. nov. can be distinguished from all congeners by the combination of its very large size, ring of bright orange scales around the eye, moderate degree of lateral folding on the limbs and body, and aspects of head, body and tail scalation. Molecular data indicate mid to late Miocene divergence of the new species from nearest relatives occurring nearly 2000 kilometres away in Vanuatu and Fiji. Large Gehyra have not been recorded on the intervening large islands of the Bismark Archipelago (New Britain and New Ireland) and the Solomon Islands, suggesting this dispersal pre-dated the current configuration of these islands, extinction in intervening regions, or potentially elements of both. Conversely, low genetic divergence between disjunct samples on Manus and Mussau implies recent overseas dispersal via either natural or anthropogenic means.
","language":"English","publisher":"Magnolia Press","doi":"10.11646/zootaxa.4208.1.3","usgsCitation":"Oliver, P.M., Clegg, J.R., Fisher, R.N., Richards, S.J., Taylor, P.N., and Jocque, M.M., 2016, A new biogeographically disjunct giant gecko (Gehyra: Gekkonidae: Reptilia) from the East Melanesian Islands : Zootaxa, v. 4208, no. 1, p. 61-76, https://doi.org/10.11646/zootaxa.4208.1.3.","productDescription":"16 p.","startPage":"61","endPage":"76","ipdsId":"IP-080193","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470287,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.11646/zootaxa.4208.1.3","text":"Publisher Index Page"},{"id":333015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4208","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-14","publicationStatus":"PW","scienceBaseUri":"58760115e4b04eac8e0746db","contributors":{"authors":[{"text":"Oliver, Paul M.","contributorId":178111,"corporation":false,"usgs":false,"family":"Oliver","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":657957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clegg, Jonathan R.","contributorId":178112,"corporation":false,"usgs":false,"family":"Clegg","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":657958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":657956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Stephen J.","contributorId":178113,"corporation":false,"usgs":false,"family":"Richards","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Peter N.","contributorId":178114,"corporation":false,"usgs":false,"family":"Taylor","given":"Peter","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":657960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jocque, Merlijn M. T.","contributorId":178115,"corporation":false,"usgs":false,"family":"Jocque","given":"Merlijn","email":"","middleInitial":"M. T.","affiliations":[],"preferred":false,"id":657961,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70180048,"text":"70180048 - 2016 - Alternative source models of very low frequency events","interactions":[],"lastModifiedDate":"2017-01-23T15:00:01","indexId":"70180048","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Alternative source models of very low frequency events","docAbstract":"We present alternative source models for very low frequency (VLF) events, previously inferred to be radiation from individual slow earthquakes that partly fill the period range between slow slip events lasting thousands of seconds and low-frequency earthquakes (LFE) with durations of tenths of a second. We show that VLF events may emerge from bandpass filtering a sum of clustered, shorter duration, LFE signals, believed to be the components of tectonic tremor. Most published studies show VLF events occurring concurrently with tremor bursts and LFE signals. Our analysis of continuous data from Costa Rica detected VLF events only when tremor was also occurring, which was only 7% of the total time examined. Using analytic and synthetic models, we show that a cluster of LFE signals produces the distinguishing characteristics of VLF events, which may be determined by the cluster envelope. The envelope may be diagnostic of a single, dynamic, slowly slipping event that propagates coherently over kilometers or represents a narrowly band-passed version of nearly simultaneous arrivals of radiation from slip on multiple higher stress drop and/or faster propagating slip patches with dimensions of tens of meters (i.e., LFE sources). Temporally clustered LFE sources may be triggered by single or multiple distinct aseismic slip events or represent the nearly simultaneous chance occurrence of background LFEs. Given the nonuniqueness in possible source durations, we suggest it is premature to draw conclusions about VLF event sources or how they scale.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JB013001","usgsCitation":"Gomberg, J.S., Agnew, D., and Schwartz, S., 2016, Alternative source models of very low frequency events: Journal of Geophysical Research B: Solid Earth, v. 121, no. 9, p. 6722-6740, https://doi.org/10.1002/2016JB013001.","productDescription":"19 p.","startPage":"6722","endPage":"6740","ipdsId":"IP-073332","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470283,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.escholarship.org/uc/item/5t24b5fb","text":"External Repository"},{"id":333747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-24","publicationStatus":"PW","scienceBaseUri":"58872486e4b08aa8f945abc0","contributors":{"authors":[{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":660020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agnew, D.C.","contributorId":32186,"corporation":false,"usgs":true,"family":"Agnew","given":"D.C.","email":"","affiliations":[],"preferred":false,"id":660021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, S.Y.","contributorId":35342,"corporation":false,"usgs":true,"family":"Schwartz","given":"S.Y.","email":"","affiliations":[],"preferred":false,"id":660022,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70180015,"text":"70180015 - 2016 - A cytosolic carbonic anhydrase molecular switch occurs in the gills of metamorphic sea lamprey","interactions":[],"lastModifiedDate":"2017-01-23T11:03:10","indexId":"70180015","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"A cytosolic carbonic anhydrase molecular switch occurs in the gills of metamorphic sea lamprey","docAbstract":"Carbonic anhydrase plays a key role in CO2 transport, acid-base and ion regulation and metabolic processes in vertebrates. While several carbonic anhydrase isoforms have been identified in numerous vertebrate species, basal lineages such as the cyclostomes have remained largely unexamined. Here we investigate the repertoire of cytoplasmic carbonic anhydrases in the sea lamprey (Petromyzon marinus), that has a complex life history marked by a dramatic metamorphosis from a benthic filter-feeding ammocoete larvae into a parasitic juvenile which migrates from freshwater to seawater. We have identified a novel carbonic anhydrase gene (ca19) beyond the single carbonic anhydrase gene (ca18) that was known previously. Phylogenetic analysis and synteny studies suggest that both carbonic anhydrase genes form one or two independent gene lineages and are most likely duplicates retained uniquely in cyclostomes. Quantitative PCR of ca19 and ca18 and protein expression in gill across metamorphosis show that the ca19 levels are highest in ammocoetes and decrease during metamorphosis while ca18 shows the opposite pattern with the highest levels in post-metamorphic juveniles. We propose that a unique molecular switch occurs during lamprey metamorphosis resulting in distinct gill carbonic anhydrases reflecting the contrasting life modes and habitats of these life-history stages.
","language":"English","publisher":"Nature","doi":"10.1038/srep33954","usgsCitation":"Ferreira-Martins, D., McCormick, S.D., Campos, A., Lopes-Marques, M., Osorio, H., Coimbra, J., Castro, L., and Wilson, J.M., 2016, A cytosolic carbonic anhydrase molecular switch occurs in the gills of metamorphic sea lamprey: Scientific Reports, v. 6, p. 1-11, https://doi.org/10.1038/srep33954.","productDescription":"Article 33954; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-068593","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":470288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep33954","text":"Publisher Index Page"},{"id":333696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-05","publicationStatus":"PW","scienceBaseUri":"58863a11e4b0cad700058b5b","contributors":{"authors":[{"text":"Ferreira-Martins, D.","contributorId":178547,"corporation":false,"usgs":false,"family":"Ferreira-Martins","given":"D.","affiliations":[],"preferred":false,"id":659765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":659764,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campos, A.","contributorId":178549,"corporation":false,"usgs":false,"family":"Campos","given":"A.","email":"","affiliations":[],"preferred":false,"id":659767,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopes-Marques, M.","contributorId":178550,"corporation":false,"usgs":false,"family":"Lopes-Marques","given":"M.","email":"","affiliations":[],"preferred":false,"id":659768,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osorio, H.","contributorId":178551,"corporation":false,"usgs":false,"family":"Osorio","given":"H.","email":"","affiliations":[],"preferred":false,"id":659769,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coimbra, J.","contributorId":178552,"corporation":false,"usgs":false,"family":"Coimbra","given":"J.","affiliations":[],"preferred":false,"id":659770,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castro, L.F.C.","contributorId":178553,"corporation":false,"usgs":false,"family":"Castro","given":"L.F.C.","email":"","affiliations":[],"preferred":false,"id":659771,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilson, Jonthan M","contributorId":178548,"corporation":false,"usgs":false,"family":"Wilson","given":"Jonthan","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":659766,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189535,"text":"70189535 - 2016 - 2016 update on induced earthquakes in the United States","interactions":[],"lastModifiedDate":"2017-07-17T11:26:57","indexId":"70189535","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"2016 update on induced earthquakes in the United States","docAbstract":"During the past decade people living in numerous locations across the central U.S. experienced many more small to moderate sized earthquakes than ever before. This earthquake activity began increasing about 2009 and peaked during 2015 and into early 2016. For example, prior to 2009 Oklahoma typically experienced 1 or 2 small earthquakes per year with magnitude greater than 3.0 but by 2015 this number rose to over 900 earthquakes per year of that size and over 30 earthquakes greater than 4.0. These earthquakes can cause damage. In 2011 a magnitude 5.6 earthquake struck near the town of Prague, Oklahoma on a preexisting fault and caused severe damage to several houses and school buildings. During the past 6 years more than 1500 reports of damaging shaking levels were reported in areas of induced seismicity. This rapid increase and the potential for damaging ground shaking from induced earthquakes caused alarm to about 8 million people living nearby and officials responsible for public safety. They wanted to understand why earthquakes were increasing and the potential threats to society and buildings located nearby.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2016 Britannica Book of the Year (A Review of 2015)","language":"English","publisher":"Encyclopedia Britannica","usgsCitation":"Petersen, M.D., 2016, 2016 update on induced earthquakes in the United States, chap. of 2016 Britannica Book of the Year (A Review of 2015).","ipdsId":"IP-077829","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":343938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596dcca3e4b0d1f9f0627561","contributors":{"authors":[{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705097,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70192155,"text":"70192155 - 2016 - Mineral resources: Reserves, peak production and the future","interactions":[],"lastModifiedDate":"2018-03-27T17:26:10","indexId":"70192155","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5507,"text":"Resources","printIssn":"2079-9276","active":true,"publicationSubtype":{"id":10}},"title":"Mineral resources: Reserves, peak production and the future","docAbstract":"The adequacy of mineral resources in light of population growth and rising standards of living has been a concern since the time of Malthus (1798), but many studies erroneously forecast impending peak production or exhaustion because they confuse reserves with “all there is”. Reserves are formally defined as a subset of resources, and even current and potential resources are only a small subset of “all there is”. Peak production or exhaustion cannot be modeled accurately from reserves. Using copper as an example, identified resources are twice as large as the amount projected to be needed through 2050. Estimates of yet-to-be discovered copper resources are up to 40-times more than currently-identified resources, amounts that could last for many centuries. Thus, forecasts of imminent peak production due to resource exhaustion in the next 20–30 years are not valid. Short-term supply problems may arise, however, and supply-chain disruptions are possible at any time due to natural disasters (earthquakes, tsunamis, hurricanes) or political complications. Needed to resolve these problems are education and exploration technology development, access to prospective terrain, better recycling and better accounting of externalities associated with production (pollution, loss of ecosystem services and water and energy use).
","language":"English","publisher":"MDPI","doi":"10.3390/resources5010014","usgsCitation":"Meinert, L.D., Robinson, G., and Nassar, N.T., 2016, Mineral resources: Reserves, peak production and the future: Resources, v. 5, no. 1, Article 14; 14 p., https://doi.org/10.3390/resources5010014.","productDescription":"Article 14; 14 p.","ipdsId":"IP-073442","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":470289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/resources5010014","text":"Publisher Index Page"},{"id":347133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"59eeffaae4b0220bbd988fbb","contributors":{"authors":[{"text":"Meinert, Lawrence D. lmeinert@usgs.gov","contributorId":1639,"corporation":false,"usgs":true,"family":"Meinert","given":"Lawrence","email":"lmeinert@usgs.gov","middleInitial":"D.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":714470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Gilpin 0000-0002-9676-9564 grobinso@usgs.gov","orcid":"https://orcid.org/0000-0002-9676-9564","contributorId":192163,"corporation":false,"usgs":true,"family":"Robinson","given":"Gilpin","email":"grobinso@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":714471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":714472,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187400,"text":"70187400 - 2016 - Water isotope systematics: Improving our palaeoclimate interpretations","interactions":[],"lastModifiedDate":"2017-05-01T15:51:05","indexId":"70187400","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Water isotope systematics: Improving our palaeoclimate interpretations","docAbstract":"The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability.
As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work.
This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison.
Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2015.11.014","usgsCitation":"Jones, M.D., Dee, S., Anderson, L., Baker, A., Bowen, G., and Noone, D., 2016, Water isotope systematics: Improving our palaeoclimate interpretations: Quaternary Science Reviews, v. 131, no. B, p. 243-249, https://doi.org/10.1016/j.quascirev.2015.11.014.","productDescription":"7 p.","startPage":"243","endPage":"249","ipdsId":"IP-071594","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470291,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.quascirev.2015.11.014","text":"External Repository"},{"id":340706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"B","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084923e4b0fc4e448ffd44","contributors":{"authors":[{"text":"Jones, M. D.","contributorId":191681,"corporation":false,"usgs":false,"family":"Jones","given":"M.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dee, S.","contributorId":191682,"corporation":false,"usgs":false,"family":"Dee","given":"S.","email":"","affiliations":[],"preferred":false,"id":693844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, L.","contributorId":22571,"corporation":false,"usgs":false,"family":"Anderson","given":"L.","affiliations":[],"preferred":false,"id":693845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, A.","contributorId":191683,"corporation":false,"usgs":false,"family":"Baker","given":"A.","affiliations":[],"preferred":false,"id":693846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowen, G.","contributorId":191684,"corporation":false,"usgs":false,"family":"Bowen","given":"G.","email":"","affiliations":[],"preferred":false,"id":693847,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noone, D.","contributorId":26916,"corporation":false,"usgs":true,"family":"Noone","given":"D.","email":"","affiliations":[],"preferred":false,"id":693848,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190859,"text":"70190859 - 2016 - Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics","interactions":[],"lastModifiedDate":"2017-09-20T10:39:26","indexId":"70190859","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics","docAbstract":"Distance metrics play significant roles in spatial modeling tasks, such as flood inundation (Tucker and Hancock 2010), stream extraction (Stanislawski et al. 2015), power line routing (Kiessling et al. 2003) and analysis of surface pollutants such as nitrogen (Harms et al. 2009). Avalanche risk is based on slope, aspect, and curvature, all directly computed from distance metrics (Gutiérrez 2012). Distance metrics anchor variogram analysis, kernel estimation, and spatial interpolation (Cressie 1993). Several approaches are employed to measure distance. Planar metrics measure straight line distance between two points (“as the crow flies”) and are simple and intuitive, but suffer from uncertainties. Planar metrics assume that Digital Elevation Model (DEM) pixels are rigid and flat, as tiny facets of ceramic tile approximating a continuous terrain surface. In truth, terrain can bend, twist and undulate within each pixel.
Work with Light Detection and Ranging (lidar) data or High Resolution Topography to achieve precise measurements present challenges, as filtering can eliminate or distort significant features (Passalacqua et al. 2015). The current availability of lidar data is far from comprehensive in developed nations, and non-existent in many rural and undeveloped regions. Notwithstanding computational advances, distance estimation on DEMs has never been systematically assessed, due to assumptions that improvements are so small that surface adjustment is unwarranted. For individual pixels inaccuracies may be small, but additive effects can propagate dramatically, especially in regional models (e.g., disaster evacuation) or global models (e.g., sea level rise) where pixels span dozens to hundreds of kilometers (Usery et al 2003). Such models are increasingly common, lending compelling reasons to understand shortcomings in the use of planar distance metrics. Researchers have studied curvature-based terrain modeling. Jenny et al. (2011) use curvature to generate hierarchical terrain models. Schneider (2001) creates a ‘plausibility’ metric for DEM-extracted structure lines. d’Oleire- Oltmanns et al. (2014) adopt object-based image processing as an alternative to working with DEMs; acknowledging the pre-processing involved in converting terrain into an object model is computationally intensive, and likely infeasible for some applications.
This paper compares planar distance with surface adjusted distance, evolving from distance “as the crow flies” to distance “as the horse runs”. Several methods are compared for DEMs spanning a range of resolutions for the study area and validated against a 3 meter (m) lidar data benchmark. Error magnitudes vary with pixel size and with the method of surface adjustment. The rate of error increase may also vary with landscape type (terrain roughness, precipitation regimes and land settlement patterns). Cross-scale analysis for a single study area is reported here. Additional areas will be presented at the conference.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Conference on GIScience: Short Paper Proceedings","doi":"10.21433/B3118rh987cz","usgsCitation":"Buttenfield, B., Ghandehari, M., Leyk, S., Stanislawski, L.V., Brantley, M.E., and Qiang, Y., 2016, Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics, p. 37-40, https://doi.org/10.21433/B3118rh987cz.","productDescription":"4 p.","startPage":"37","endPage":"40","ipdsId":"IP-078741","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":470295,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21433/b3118rh987cz","text":"Publisher Index Page"},{"id":345882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59c22cb4e4b091459a61b73d","contributors":{"authors":[{"text":"Buttenfield, Barbara P.","contributorId":145538,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":710649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghandehari, M","contributorId":196539,"corporation":false,"usgs":false,"family":"Ghandehari","given":"M","email":"","affiliations":[],"preferred":false,"id":710651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leyk, S","contributorId":196538,"corporation":false,"usgs":false,"family":"Leyk","given":"S","email":"","affiliations":[],"preferred":false,"id":710650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":710648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brantley, M E","contributorId":196540,"corporation":false,"usgs":false,"family":"Brantley","given":"M","email":"","middleInitial":"E","affiliations":[],"preferred":false,"id":710652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qiang, Yi","contributorId":196567,"corporation":false,"usgs":false,"family":"Qiang","given":"Yi","email":"","affiliations":[],"preferred":false,"id":710777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192029,"text":"70192029 - 2016 - Mapping presence and predicting phenological status of invasive buffelgrass in southern Arizona using MODIS, climate and citizen science observation data","interactions":[],"lastModifiedDate":"2017-10-24T13:55:10","indexId":"70192029","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping presence and predicting phenological status of invasive buffelgrass in southern Arizona using MODIS, climate and citizen science observation data","docAbstract":"The increasing spread and abundance of an invasive perennial grass, buffelgrass (Pennisetum ciliare), represents a critical threat to the native vegetation communities of the Sonoran desert in southern Arizona, USA, where buffelgrass eradication is a high priority for resource managers. Herbicidal treatment of buffelgrass is most effective when the vegetation is actively growing, but the remoteness of infestations and the erratic timing and length of the species’ growth periods confound effective treatment. The goal of our research is to promote buffelgrass management by using remote sensing data to detect where the invasive plants are located and when they are photosynthetically active. We integrated citizen scientist observations of buffelgrass phenology in the Tucson, Arizona area with PRISM precipitation data, eight-day composites of 250-m Moderate-resolution Imaging Spectroradiometer (MODIS) satellite imagery, and aerially-mapped polygons of buffelgrass presence to understand dynamics and relationships between precipitation and the timing and amount of buffelgrass greenness from 2011 to 2013. Our results show that buffelgrass responds quickly to antecedent rainfall: in pixels containing buffelgrass, higher correlations (R2 > 0.5) typically occur after two cumulative eight-day periods of rain, whereas in pixels dominated by native vegetation, four prior 8-day periods are required to reach that threshold. Using the new suite of phenometrics introduced here—Climate Landscape Response metrics—we accurately predicted the location of 49% to 55% of buffelgrass patches in Saguaro National Park. These metrics and the suggested guidelines for their use can be employed by resource managers to treat buffelgrass during optimal time periods.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8070524","usgsCitation":"Wallace, C., Walker, J.J., Skirvin, S.M., Patrick-Birdwell, C., Weltzin, J., and Raichle, H., 2016, Mapping presence and predicting phenological status of invasive buffelgrass in southern Arizona using MODIS, climate and citizen science observation data: Remote Sensing, v. 8, no. 7, p. 1-24, https://doi.org/10.3390/rs8070524.","productDescription":"Article 524; 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-072868","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8070524","text":"Publisher Index Page"},{"id":347245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","city":"Tucson","otherGeospatial":"Saguaro National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.22421264648438,\n 32.04416879077791\n ],\n [\n -110.41534423828124,\n 32.04416879077791\n ],\n [\n -110.41534423828124,\n 32.36488325846306\n ],\n [\n -111.22421264648438,\n 32.36488325846306\n ],\n [\n -111.22421264648438,\n 32.04416879077791\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-24","publicationStatus":"PW","scienceBaseUri":"59f05123e4b0220bbd9a1dab","contributors":{"authors":[{"text":"Wallace, Cynthia S.A. cwallace@usgs.gov","contributorId":139089,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":713880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":713881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skirvin, Susan M.","contributorId":197598,"corporation":false,"usgs":false,"family":"Skirvin","given":"Susan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patrick-Birdwell, Caroline","contributorId":197599,"corporation":false,"usgs":false,"family":"Patrick-Birdwell","given":"Caroline","email":"","affiliations":[],"preferred":false,"id":713883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weltzin, Jake F. jweltzin@usgs.gov","contributorId":195442,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":137,"text":"Biomonitoring of Environmental Status and Trends Program","active":false,"usgs":true}],"preferred":false,"id":713884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raichle, Helen","contributorId":197600,"corporation":false,"usgs":false,"family":"Raichle","given":"Helen","affiliations":[],"preferred":false,"id":713885,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187362,"text":"70187362 - 2016 - Spatially explicit models of full-season productivity and implications for landscape management of Golden-winged Warblers in the western Great Lakes Region","interactions":[],"lastModifiedDate":"2020-08-20T20:11:21.12311","indexId":"70187362","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5103,"text":"Studies in Avian Biology","printIssn":"0197-9922","active":true,"publicationSubtype":{"id":24}},"chapter":"9","title":"Spatially explicit models of full-season productivity and implications for landscape management of Golden-winged Warblers in the western Great Lakes Region","docAbstract":"The relationship between landscape structure and composition and full-season productivity (FSP) is poorly understood for most birds. For species of high conservation concern, insight into how productivity is related to landscape structure and composition can be used to develop more effective conservation strategies that increase recruitment. We monitored nest productivity and fledgling survival of Golden-winged Warblers (Vermivora chrysoptera), a species of high conservation concern, in managed forest landscapes at two sites in northern Minnesota, and one site in southeastern Manitoba, Canada from 2010 to 2012. We used logistic exposure models to identify the influence of landscape structure and composition on nest productivity and fledgling survival. We used the models to predict spatially explicit, FSP across our study sites to identify areas of low relative productivity that could be targeted for management. We then used our models of spatially explicit, FSP to simulate the impact of potential management actions on our study sites with the goal of increasing total population productivity. Unlike previous studies that suggested wetland cover types provide higher quality breeding habitat for Golden-winged Warblers, our models predicted 14% greater productivity in upland cover types. Simulated succession of a 9-ha grassland patch to a shrubby upland suitable for nesting increased the total number of fledglings produced by that patch and adjacent upland shrublands by 30%, despite decreasing individual productivity by 13%. Further simulated succession of the same patch described above into deciduous forest reduced the total number of fledglings produced to independence on a landscape by 18% because of a decrease in the area available for nesting. Simulated reduction in the cumulative length of shrubby edge within a 50-m radius of any location in our landscapes from 0.6 to 0.3 km increased FSP by 5%. Our models demonstrated that the effects of any single management action depended on the context of the surrounding landscape. We conclude that spatially explicit, FSP models that incorporate data from both the nesting and postfledging periods are useful for informing breeding habitat management plans for Golden-winged Warblers and that similar models can benefit management planning for
many other species of conservation concern.
Climate change is causing extensive warming across Arctic regions resulting in permafrost degradation, alterations to regional hydrology and shifting amounts and composition of dissolved organic matter (DOM) transported by streams and rivers. Here, we characterize the DOM composition and optical properties of the six largest Arctic rivers draining into the Arctic Ocean to examine the ability of optical measurements to provide meaningful insights into terrigenous carbon export patterns and biogeochemical cycling. The chemical composition of aquatic DOM varied with season, spring months were typified by highest lignin phenol and dissolved organic carbon (DOC) concentrations with greater hydrophobic acid content, and lower proportions of hydrophilic compounds, relative to summer and winter months. Chromophoric DOM (CDOM) spectral slope (S275–295) tracked seasonal shifts in DOM composition across river basins. Fluorescence and parallel factor analysis identified seven components across the six Arctic rivers. The ratios of “terrestrial humic-like” vs. “marine humic-like” fluorescent components co-varied with lignin monomer ratios over summer and winter months, suggesting fluorescence may provide information on the age and degradation state of riverine DOM. CDOM absorbance (a350) proved a sensitive proxy for lignin phenol concentrations across all six river basins and over the hydrograph, enabling for the first time the development of a single pan-arctic relationship between a350 and terrigenous DOC (R2 = 0.93). Combining this lignin proxy with high-resolution monitoring of a350, pan-arctic estimates of annual lignin flux were calculated to range from 156 to 185 Gg, resulting in shorter and more constrained estimates of terrigenous DOM residence times in the Arctic Ocean (spanning 7 months to 2½ years). Furthermore, multiple linear regression models incorporating both absorbance and fluorescence variables proved capable of explaining much of the variability in lignin composition across rivers and seasons. Our findings suggest that synoptic, high-resolution optical measurements can provide improved understanding of northern high-latitude organic matter cycling and flux, and prove an important technique for capturing future climate-driven changes.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2016.00025","usgsCitation":"Mann, P.J., Spencer, R., Hernes, P.J., Six, J., Aiken, G.R., Tank, S.E., McClelland, J.W., Butler, K.D., Dyda, R.Y., and Holmes, R.M., 2016, Pan-arctic trends in terrestrial dissolved organic matter from optical measurements: Frontiers in Earth Science, v. 4, 25, 18 p., https://doi.org/10.3389/feart.2016.00025.","productDescription":"25, 18 p.","ipdsId":"IP-037336","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":461986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2016.00025","text":"Publisher Index Page"},{"id":346554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-17","publicationStatus":"PW","scienceBaseUri":"59e07f30e4b05fe04ccfcd1c","contributors":{"authors":[{"text":"Mann, Paul J.","contributorId":178897,"corporation":false,"usgs":false,"family":"Mann","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spencer, Robert G. 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