When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.
Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.
In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.
Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.
Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip172","usgsCitation":"Young, S.M., 2017, Land Change Monitoring, Assessment, and Projection (LCMAP) revolutionizes land cover and land change research: U.S. Geological Survey General Information Product 172, 4 p., https://doi.org/10.3133/gip172.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-083103","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":340452,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0172/coverthb.jpg"},{"id":340453,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0172/gip172.pdf","size":"7.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 172"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Agassiz’s desert tortoise (Gopherus agassizii) is a conservation-reliant species with populations north and west of the Colorado River protected as threatened under the Endangered Species Act (Averill-Murray et al. 2012). Since it was listed under this category in 1990, a great deal has been learned about the natural history of the species, and it is now one of the best-studied turtles in the United States (Lovich and Ennen 2013). However, the accumulated body of scientific data available for the species has not yet been translated into recovery or delisting of the species. Successful conservation of any species requires knowledge of their natural history and how vital rates affect their ability to maintain stable populations in the face of natural and anthropogenic stresses.
Agassiz’s desert tortoises occur from southwestern Utah to near the Mexican border in California – a distance of over 450 km – but population densities vary greatly across this immense landscape (U.S. Fish and Wildlife Service 2015). Tortoises occur in the Sonoran Desert of California, including the eastern and western ends of the Coachella Valley, where it is one of 27 species covered under the Coachella Valley Multiple Species Habitat Conservation Plan and Natural Community Conservation Plan (CVMSHCP/NCCP). The southern portion of Joshua Tree National Park (JTNP) lies within this 1.1 million acre planning area, and was predicted to be an area of low-density tortoise populations using habitat suitability modeling (Barrows 2011). JTNP is near the southern distributional limit of G. agassizii, yet very little has been published regarding the ecology of tortoises in the Sonoran Desert of California.
Reproductive output is an important gross measure of the ability of a population to persist. When integrated with data on fertility and survivorship, this information forms a foundation for assessing population status and formulating effective management strategies (e.g., Congdon et al. 1993, 1994), especially for imperiled species. One aspect of the biology of G. agassizii that has been particularly well-studied is reproductive output. However, most of what we know about this topic comes from research in the Mojave Desert portion of the species’ range (Ernst and Lovich 2009). Comparatively little has been published on the reproductive ecology of populations living in the Sonoran Desert ecosystem of California. Publications by Lovich et al. (1999, 2011, 2012, 2014, 2015) constitute the main body of literature on desert tortoise reproductive ecology in the Sonoran Desert of California, with one study population located at the western end of the CVMSHCP/NCCP area. Collecting data on Agassiz’s desert tortoise ecology in the Sonoran Desert ecosystem is important due to significant differences between the two adjacent desert ecosystems, especially the timing and amounts of annual precipitation, and their potential effects on reproductive output (e.g., Lovich et al. 5 2015). There are also differences in the vulnerability of tortoises to the effects of a warming, drying climate between the two deserts (Barrows 2011; Zylstra et al. 2012).
The overall goal of this study was to collect data on demography, reproductive output, and genetic affinities at a study site in the Sonoran Desert portion of JTNP in the eastern end of the CVMSHCP/NCCP area. Specific objectives included: 1) Collect data to establish baselines on tortoise populations and/or their habitat suitability in core habitat within the CVNCCP area, including biotic and abiotic variables affecting persistence of tortoise populations; 2) Compare and contrast with data collected on desert tortoises at USGS/BLM study site near Palm Springs over 16 years; 3) Support long-term modeling efforts needed to determine tortoise population viability; 4) Refine modeled relationships with identified threats such as fire, invasive species and climate change; and 5) Prioritize adaptive management needs for the desert tortoise in and beyond the CVNCCP area. The data from this study will aid in determining baseline estimates of the desert tortoise population size within the planning area as well as establish a marked population of Agassiz’s desert tortoises for future monitoring. Data will be integrated with habitat modeling in order to refine model output. Genetic data will be collected on both the north and south sides of Interstate 10 to determine the potential effects of habitat fragmentation and genetic mixing. Analyses are ongoing and results beyond those presented in this report will be published in peer-reviewed scientific journals following inclusion of additional data collected on the south side of Shavers Valley in 2017-2018.
","language":"English","publisher":"Coachella Valley Conservation Commission","usgsCitation":"Lovich, J.E., and Puffer, S., 2017, Developing an effective Agassiz's Desert Tortoise monitoring program: Final report to the Coachella Valley Conservation Commission, 26 p.","productDescription":"26 p.","ipdsId":"IP-088374","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":358690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358644,"type":{"id":11,"text":"Document"},"url":"https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=152890&inline"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10ac2ce4b034bf6a7e6966","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":749276,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70261470,"text":"70261470 - 2017 - Annual review 2016: Exploration review","interactions":[],"lastModifiedDate":"2024-12-11T16:58:29.035525","indexId":"70261470","displayToPublicDate":"2017-05-01T10:56:34","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Annual review 2016: Exploration review","docAbstract":"This summary of international mineral exploration activities for the year 2016 draws upon information from industry sources, published literature, SNL Metals & Mining (SNL), an offering of S&P Global Market Intelligence (New York, NY), and specialists in the U.S. Geological Survey (USGS) National Minerals Information Center. Three types of information are reported and analyzed in this annual review of international exploration: 1) budgetary statistics expressed in U.S. dollars provided by SNL; 2) regional and site-specific exploration activities that took place in 2016 as compiled by the USGS and 3) regional events and legislation that affected exploration activities including economic, social and political conditions, which were derived from published sources and discussions with USGS and industry specialists. Commodity and regional compilations are presented in this summary. Because multiple sources were used to develop commodity and regional compilations, statistics may vary depending on the source and type of data that are being reported.","language":"English","publisher":"Society for Mining, Metallurgy, & Exploration","usgsCitation":"Karl, N.A., and Wilburn, D.R., 2017, Annual review 2016: Exploration review: Mining Engineering, v. 69, no. 5, p. 28-49.","productDescription":"22 p.","startPage":"28","endPage":"49","ipdsId":"IP-085928","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":464992,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://me.smenet.org/abstract.cfm?preview=1&articleID=7513&page=28","linkFileType":{"id":5,"text":"html"}},{"id":465021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karl, Nick A 0000-0003-2858-2498","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":246006,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"","middleInitial":"A","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920668,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70248093,"text":"70248093 - 2017 - Tell me a story! A plea for more compelling conference presentations","interactions":[],"lastModifiedDate":"2023-09-05T11:53:40.283936","indexId":"70248093","displayToPublicDate":"2017-05-01T06:52:52","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16694,"text":"The Condor: Ornithological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Tell me a story! A plea for more compelling conference presentations","docAbstract":"Effective communication with other scientists is an essential component of the scientific process, underlying success in publishing papers, building collaborations, securing grants and jobs, and stimulating further research. Oral presentations at professional meetings provide an opportunity to share research findings with a relatively broad scientific audience. However, many scientists give talks that are crowded with methods and data, accompanied by poor visuals, and, most unfortunately, lacking in narrative arc. Here, I provide strategies for distilling research findings into a short-format talk, capturing the audience's attention, and delivering a compelling and visually engaging story. I argue that the material should be designed to interest a wide range of meeting attendees, not just experts in a narrow field. I also advocate principles of good storytelling, with the aim of leading the audience through a compelling journey of discovery that concludes with a memorable takeaway message.
","language":"English","publisher":"Oxford Academic","doi":"10.1650/CONDOR-16-209.1","usgsCitation":"Langin, K., 2017, Tell me a story! A plea for more compelling conference presentations: The Condor: Ornithological Applications, v. 119, p. 321-326, https://doi.org/10.1650/CONDOR-16-209.1.","productDescription":"6 p.","startPage":"321","endPage":"326","ipdsId":"IP-081258","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-209.1","text":"Publisher Index Page"},{"id":420463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Langin, Kathryn 0000-0002-1799-1942 klangin@usgs.gov","orcid":"https://orcid.org/0000-0002-1799-1942","contributorId":221128,"corporation":false,"usgs":true,"family":"Langin","given":"Kathryn","email":"klangin@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881834,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70179386,"text":"70179386 - 2017 - Divergence and gene flow in the globally distributed blue-winged ducks","interactions":[],"lastModifiedDate":"2017-06-07T10:39:02","indexId":"70179386","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Divergence and gene flow in the globally distributed blue-winged ducks","docAbstract":"The ability to disperse over long distances can result in a high propensity for colonizing new geographic regions, including uninhabited continents, and lead to lineage diversification via allopatric speciation. However, high vagility can also result in gene flow between otherwise allopatric populations, and in some cases, parapatric or divergence-with-gene-flow models might be more applicable to widely distributed lineages. Here, we use five nuclear introns and the mitochondrial control region along with Bayesian models of isolation with migration to examine divergence, gene flow, and phylogenetic relationships within a cosmopolitan lineage comprising six species, the blue-winged ducks (genus Anas), which inhabit all continents except Antarctica. We found two primary sub-lineages, the globally-distributed shoveler group and the New World blue-winged/cinnamon teal group. The blue-winged/cinnamon sub-lineage is composed of sister taxa from North America and South America, and taxa with parapatric distributions are characterized by low to moderate levels of gene flow. In contrast, our data support strict allopatry for most comparisons within the shovelers. However, we found evidence of gene flow from the migratory, Holarctic northern shoveler (A. clypeata) and the more sedentary, African Cape shoveler (A. smithii) into the Australasian shoveler (A. rhynchotis), although we could not reject strict allopatry. Given the diverse mechanisms of speciation within this complex, the shovelers and blue-winged/cinnamon teals can serve as an effective model system for examining how the genome diverges under different evolutionary processes and how genetic variation is partitioned among highly dispersive taxa.","language":"English","publisher":"Wiley","doi":"10.1111/jav.00998","usgsCitation":"Nelson, J., Wilson, R.E., McCracken, K.G., Cumming, G., Joseph, L., Guay, P., and Peters, J., 2017, Divergence and gene flow in the globally distributed blue-winged ducks: Journal of Avian Biology, v. 48, no. 5, p. 640-649, https://doi.org/10.1111/jav.00998.","productDescription":"10 p.","startPage":"640","endPage":"649","ipdsId":"IP-071068","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":502591,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Divergence_and_gene_flow_in_the_globally_distributed_blue-winged_ducks/20599113","text":"External Repository"},{"id":438356,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7T72FK7","text":"USGS data release","linkHelpText":"Specimen and Genetic Information for Phylogeny of Blue-winged Ducks (Anas spp.), 2001-2011"},{"id":332672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"586781f7e4b0cd2dabe7c715","contributors":{"authors":[{"text":"Nelson, Joel","contributorId":177777,"corporation":false,"usgs":false,"family":"Nelson","given":"Joel","email":"","affiliations":[],"preferred":false,"id":657014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":657013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCracken, Kevin G.","contributorId":72309,"corporation":false,"usgs":false,"family":"McCracken","given":"Kevin","email":"","middleInitial":"G.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":657015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cumming, Graeme","contributorId":177778,"corporation":false,"usgs":false,"family":"Cumming","given":"Graeme","affiliations":[],"preferred":false,"id":657016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joseph, Leo","contributorId":173726,"corporation":false,"usgs":false,"family":"Joseph","given":"Leo","affiliations":[],"preferred":false,"id":657017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guay, Patrick-Jean","contributorId":177779,"corporation":false,"usgs":false,"family":"Guay","given":"Patrick-Jean","email":"","affiliations":[],"preferred":false,"id":657018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peters, Jeffrey","contributorId":177780,"corporation":false,"usgs":false,"family":"Peters","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":657019,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188109,"text":"70188109 - 2017 - Climate legacy and lag effects on dryland plant communities in the southwestern U.S.","interactions":[],"lastModifiedDate":"2017-05-31T13:23:34","indexId":"70188109","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Climate legacy and lag effects on dryland plant communities in the southwestern U.S.","docAbstract":"Climate change effects on vegetation will likely be strong in the southwestern U.S., which is projected to experience large increases in temperature and changes in precipitation. Plant communities in the southwestern U.S. may be particularly vulnerable to climate change as the productivity of many plant species is strongly water-limited. This study examines the relationship between climate and vegetation condition using a time-series of Landsat imagery across grassland, shrubland, and woodland communities on the Colorado Plateau, USA. We improve on poorly understood inter-annual climate-vegetation relationships by exploring how the responses of different plant communities depend on climate legacies (>12 months) and lag behind shorter-term (3–12 month) changes in water availability. Our results show a prolonged drying trend on the Colorado Plateau since the early 1990s that was punctuated in several years by intense droughts. In areas that experienced sustained dry conditions or a drying trend, vegetation greenness (a proxy for production) increased linearly when conditions were interrupted by wetting events. In contrast, in areas that experienced sustained wet conditions or a wetting trend, vegetation greenness was weakly or not related to wetting events, indicating that production may saturate if vegetation experiences sufficient water availability. Shrubland and woodland communities had stronger relationships with climate at long lags (6–12 months) and many maintained greenness under sustained water deficit, whereas grassland communities had stronger relationships at short lags (3–6 months) and lost greenness even in periods of short-term drought. The results of our study show the importance of identifying climate legacies and lags when assessing indicators of ecological drought, which can be used to improve forecasts of which plant communities will be vulnerable under future climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.10.024","usgsCitation":"Bunting, E., Munson, S.M., and Villarreal, M.L., 2017, Climate legacy and lag effects on dryland plant communities in the southwestern U.S.: Ecological Indicators, v. 74, p. 216-229, https://doi.org/10.1016/j.ecolind.2016.10.024.","productDescription":"14 p.","startPage":"216","endPage":"229","ipdsId":"IP-080256","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438355,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90CRK5N","text":"USGS data release","linkHelpText":"Dataset for climate legacy and lag effects on dryland plant communities in the southwestern U.S."},{"id":341940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.115234375,\n 35.8356283888737\n ],\n [\n -106.94091796875,\n 35.8356283888737\n ],\n [\n -106.94091796875,\n 40.96330795307353\n ],\n [\n -113.115234375,\n 40.96330795307353\n ],\n [\n -113.115234375,\n 35.8356283888737\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592fd63ce4b0e9bd0ea896e6","contributors":{"authors":[{"text":"Bunting, Erin 0000-0001-9103-6065 ebunting@usgs.gov","orcid":"https://orcid.org/0000-0001-9103-6065","contributorId":168488,"corporation":false,"usgs":true,"family":"Bunting","given":"Erin","email":"ebunting@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":696775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":696776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":696777,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187393,"text":"70187393 - 2017 - Population trends and distribution of Common Murre Uria aalge colonies in Washington, 1996-2015","interactions":[],"lastModifiedDate":"2019-12-17T09:28:42","indexId":"70187393","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"title":"Population trends and distribution of Common Murre Uria aalge colonies in Washington, 1996-2015","docAbstract":"Periodic assessments of population trends and changes in spatial distribution are valuable for managing marine birds and their breeding habitats, particularly when evaluating long-term response to threats such as oil spills, predation pressure, and changing ocean conditions. We evaluated recent trends in abundance and distribution of the Common Murre Uria aalge within Copalis, Quillayute Needles, and Flattery Rocks National Wildlife Refuges, which include all murre colonies in Washington except one, off-refuge, on Tatoosh Island. In 1996-2001 and 2010-2015, aerial photographic surveys were conducted during the incubation phase (mid-June through mid-July) each year. Using images from film (1996-2001) and digital (2010-2015) cameras that included all parts of each colony, we manually counted murres. We estimated population trend as annual percent change in whole-colony counts using an overdispersed Poisson regression model. Overall, numbers of murres counted at breeding colonies in Washington increased by 8.8% per year (95% CI 3.0%-14.9%) during 1996–2015. The overall statewide increase was driven by an increase at colonies in northern Washington of approximately 11% per year (95% CI 4.5%-17.8%). Despite an increasing trend, abundance remains lower than levels in the late 1970s, and the spatial distribution has changed. Colonies in southern Washington - where murres were historically the most abundant - are no longer active, or only minimally so, whereas colonies in the north - which were rarely active in the early 1970s - are now the largest. There was high variability in spatial distribution among years, a pattern that indicates a need for coordinated monitoring and movement studies throughout the California Current System to understand dispersal and colonization. Our results indicate that future management of refuge islands could protect both current and historic colony locations, given the patterns of colony dynamics and the uncertainty about long-term effects of a changing ocean ecosystem and predation pressure on the status of murres.
","language":"English","publisher":"Marine Ornithology","usgsCitation":"Thomas, S., and Lyons, J.E., 2017, Population trends and distribution of Common Murre Uria aalge colonies in Washington, 1996-2015: Marine Ornithology: Journal of Seabird Research and Conservation, v. 45, no. 1, p. 95-102.","productDescription":"8 p.","startPage":"95","endPage":"102","ipdsId":"IP-079216","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":340686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340685,"type":{"id":15,"text":"Index Page"},"url":"https://www.marineornithology.org/content/get.cgi?rn=1206"}],"country":"United 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\"}}]}","volume":"45","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5908491ee4b0fc4e448ffd3c","contributors":{"authors":[{"text":"Thomas, Susan M","contributorId":191668,"corporation":false,"usgs":false,"family":"Thomas","given":"Susan M","affiliations":[],"preferred":false,"id":693777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":693776,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187357,"text":"70187357 - 2017 - Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013","interactions":[],"lastModifiedDate":"2017-06-07T10:16:29","indexId":"70187357","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013","docAbstract":"Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12520","usgsCitation":"Driscoll, J.M., Hay, L.E., and Bock, A.R., 2017, Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013: Journal of the American Water Resources Association, v. 53, no. 3, p. 655-666, https://doi.org/10.1111/1752-1688.12520.","productDescription":"12 p.","startPage":"655","endPage":"666","ipdsId":"IP-079682","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":340646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"53","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-13","publicationStatus":"PW","scienceBaseUri":"59084922e4b0fc4e448ffd3e","contributors":{"authors":[{"text":"Driscoll, Jessica M. 0000-0003-3097-9603 jdriscoll@usgs.gov","orcid":"https://orcid.org/0000-0003-3097-9603","contributorId":167585,"corporation":false,"usgs":true,"family":"Driscoll","given":"Jessica","email":"jdriscoll@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":693604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":693605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188091,"text":"70188091 - 2017 - Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences","interactions":[],"lastModifiedDate":"2017-05-31T12:36:37","indexId":"70188091","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences","title":"Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences","docAbstract":"Rationale
Perchlorate (ClO4−) is a common trace constituent of water, soils, and plants; it has both natural and synthetic sources and is subject to biodegradation. The stable isotope ratios of Cl and O provide three independent quantities for ClO4− source attribution and natural attenuation studies: δ37Cl, δ18O, and δ17O (or Δ17O or 17Δ) values. Documented reference materials, calibration schemes, methods, and interferences will improve the reliability of such studies.
Methods
Three large batches of KClO4 with contrasting isotopic compositions were synthesized and analyzed against VSMOW-SLAP, atmospheric O2, and international nitrate and chloride reference materials. Three analytical methods were tested for O isotopes: conversion of ClO4− to CO for continuous-flow IRMS (CO-CFIRMS), decomposition to O2 for dual-inlet IRMS (O2-DIIRMS), and decomposition to O2 with molecular-sieve trap (O2-DIIRMS+T). For Cl isotopes, KCl produced by thermal decomposition of KClO4 was reprecipitated as AgCl and converted into CH3Cl for DIIRMS.
Results
KClO4 isotopic reference materials (USGS37, USGS38, USGS39) represent a wide range of Cl and O isotopic compositions, including non-mass-dependent O isotopic variation. Isotopic fractionation and exchange can affect O isotope analyses of ClO4− depending on the decomposition method. Routine analyses can be adjusted for such effects by normalization, using reference materials prepared and analyzed as samples. Analytical errors caused by SO42−, NO3−, ReO42−, and C-bearing contaminants include isotope mixing and fractionation effects on CO and O2, plus direct interference from CO2 in the mass spectrometer. The results highlight the importance of effective purification of ClO4− from environmental samples.
Conclusions
KClO4 reference materials are available for testing methods and calibrating isotopic data for ClO4− and other substances with widely varying Cl or O isotopic compositions. Current ClO4−extraction, purification, and analysis techniques provide relative isotope-ratio measurements with uncertainties much smaller than the range of values in environmental ClO4−, permitting isotopic evaluation of environmental ClO4− sources and natural attenuation.
","language":"English","publisher":"Wiley","doi":"10.1002/rcm.7751","usgsCitation":"Bohlke, J., Mroczkowski, S.J., Sturchio, N.C., Heraty, L.J., Richman, K.W., Sullivan, D.B., Griffith, K.N., Gu, B., and Hatzinger, P., 2017, Stable isotope analyses of oxygen (18O:17O:16O) and chlorine (37Cl:35Cl) in perchlorate: reference materials, calibrations, methods, and interferences: Rapid Communications in Mass Spectrometry, v. 31, no. 1, p. 85-110, https://doi.org/10.1002/rcm.7751.","productDescription":"26 p.","startPage":"85","endPage":"110","ipdsId":"IP-079870","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":341925,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-12","publicationStatus":"PW","scienceBaseUri":"592fd63de4b0e9bd0ea896e9","contributors":{"authors":[{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":696640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mroczkowski, Stanley J. 0000-0001-8026-6025 smroczko@usgs.gov","orcid":"https://orcid.org/0000-0001-8026-6025","contributorId":2628,"corporation":false,"usgs":true,"family":"Mroczkowski","given":"Stanley","email":"smroczko@usgs.gov","middleInitial":"J.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":696641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturchio, Neil C.","contributorId":149375,"corporation":false,"usgs":false,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":696642,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heraty, Linnea J.","contributorId":192520,"corporation":false,"usgs":false,"family":"Heraty","given":"Linnea","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":696643,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richman, Kent W.","contributorId":192519,"corporation":false,"usgs":false,"family":"Richman","given":"Kent","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":696644,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Donald B.","contributorId":192517,"corporation":false,"usgs":false,"family":"Sullivan","given":"Donald","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696645,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griffith, Kris N.","contributorId":192518,"corporation":false,"usgs":false,"family":"Griffith","given":"Kris","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":696646,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gu, Baohua","contributorId":15504,"corporation":false,"usgs":true,"family":"Gu","given":"Baohua","affiliations":[],"preferred":false,"id":696648,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hatzinger, Paul B.","contributorId":43204,"corporation":false,"usgs":true,"family":"Hatzinger","given":"Paul B.","affiliations":[],"preferred":false,"id":696647,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70187423,"text":"70187423 - 2017 - Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus)","interactions":[],"lastModifiedDate":"2018-01-03T11:17:55","indexId":"70187423","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus)","docAbstract":"Pseudogymnoascus destructans is a psychrophilic (cold-loving) fungus that causes white-nose syndrome (WNS), an emerging disease of North American bats that has caused unprecedented population declines. The fungus is believed to have been introduced to North America from Europe or Asia (where it is present but does not cause significant mortality), but the full extent of its native range is unknown. The route of introduction is also unknown. In North America, hibernating bats become infected with P. destructans when body temperature decreases during winter torpor into the range permissive for growth of this fungus. Infected bats may develop visible fungal growth on the nose or wings, awaken more frequently from torpor, and experience a cascade of physiologic changes that result in weight loss, dehydration, electrolyte imbalances, and death. P. destructans persists in the environments of underground bat hibernation sites (hibernacula) and is believed to spread primarily by natural movements of infected bats. The first evidence of WNS in North America is from a photograph of a hibernating bat taken during winter of 2005-2006 in a hibernaculum near Albany, New York. P. destructans subsequently spread rapidly from the northeastern United States throughout much of the eastern portions of the United States and Canada, and most recently (as of May 2017) was detected in Washington State. It has killed millions of bats, threatening some species with regional extirpation and putting at risk the valuable environmental services that bats provide by eating harmful insects.","largerWorkTitle":"Invasive species compendium","language":"English","publisher":"Centre for Agriculture and Biosciences International","usgsCitation":"Blehert, D.S., and Lankau, E.W., 2017, Datasheet: Pseudogymnoascus destructans (white-nose syndrome fungus), chap. of Invasive species compendium, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-084223","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":340751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340748,"type":{"id":15,"text":"Index Page"},"url":"https://www.cabi.org/isc/datasheet/119002"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157e8","contributors":{"authors":[{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140397,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":693988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lankau, Emily W. 0000-0002-7094-7780 elankau@usgs.gov","orcid":"https://orcid.org/0000-0002-7094-7780","contributorId":175270,"corporation":false,"usgs":true,"family":"Lankau","given":"Emily","email":"elankau@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":693989,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187141,"text":"ofr20171029 - 2017 - Guidelines for preparation of State water-use estimates for 2015","interactions":[],"lastModifiedDate":"2017-05-02T08:59:14","indexId":"ofr20171029","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1029","title":"Guidelines for preparation of State water-use estimates for 2015","docAbstract":"The U.S. Geological Survey (USGS) has estimated the use of water in the United States at 5-year intervals since 1950. This report describes the water-use categories and data elements used for the national water-use compilation conducted as part of the USGS National Water-Use Science Project. The report identifies sources of water-use information, provides standard methods and techniques for estimating water use at the county level, and outlines steps for preparing documentation for the United States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.
As part of this USGS program to document water use on a national scale, estimates of water withdrawals for the categories of public supply, self-supplied domestic, industrial, irrigation, and thermoelectric power are prepared for each county in each State, District, or territory by using the guidelines in this report. County estimates of water withdrawals for aquaculture, livestock, and mining are prepared for each State by using a county-based national model, although water-use programs in each State or Water Science Center have the option of producing independent county estimates of water withdrawals for these categories. Estimates of water withdrawals and consumptive use for thermoelectric power will be aggregated to the county level for each State by the national project; additionally, irrigation consumptive use at the county level will also be provided, although study chiefs in each State have the option of producing independent county estimates of water withdrawals and consumptive use for these categories.
Estimates of deliveries of water from public supplies for domestic use by county also will be prepared for each State. As a result, total domestic water use can be determined for each State by combining self-supplied domestic withdrawals and public-supplied domestic deliveries. Fresh groundwater and surface-water estimates will be prepared for all categories of use, and saline groundwater and surface-water estimates by county will be prepared for the categories of public supply, industrial, mining, and thermoelectric power. Power production for thermoelectric power and irrigated acres by irrigation system type will be compiled. If data are available, reclaimed-wastewater use will be compiled for the public-supply, industrial, mining, thermoelectric-power, and irrigation categories.
Optional water-use categories are commercial, hydroelectric power, and wastewater treatment. Optional data elements are public-supply deliveries to commercial, industrial, and thermoelectric-power users; consumptive use (for categories other than thermoelectric power and irrigation); irrigation conveyance loss; and number of facilities. Aggregation of water-use data by stream basin (eight-digit hydrologic unit code) and principal aquifers also is optional.
Water-use data compiled by the States will be stored in the USGS Aggregate Water-Use Data System (AWUDS). This database is a comprehensive aggregated database designed to store mandatory and optional data elements. AWUDS contains several routines that can be used for quality assurance and quality control of the data, and AWUDS produces tables of water-use data from the previous compilations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171029","collaboration":"National Water-Use Science Project","usgsCitation":"Bradley, M.W., comp., 2017, Guidelines for preparation of State water-use estimates for 2015: U.S. Geological Survey Open-File Report 2017–1029, 54 p., https://doi.org/10.3133/ofr20171029.","productDescription":"viii, 54 p.","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-078880","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":340450,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb2.jpg"},{"id":340259,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1029/ofr20171029.pdf","text":"Report","size":"719 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1029"},{"id":340258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1029/coverthb.jpg"}],"contact":"Director, Lower Mississippi-Gulf Water Science Center—Tennessee
640 Grassmere Park
Suite 100
Nashville, TN 37211
A probabilistic mineral resource assessment of metal resources in undiscovered porphyry copper deposits of the Ural Mountains in Russia and Kazakhstan was done using a quantitative form of mineral resource assessment. Permissive tracts were delineated on the basis of mapped and inferred subsurface distributions of igneous rocks assigned to tectonic zones that include magmatic arcs where the occurrence of porphyry copper deposits within 1 km of the Earth's surface are possible. These permissive tracts outline four north-south trending volcano-plutonic belts in major structural zones of the Urals. From west to east, these include permissive lithologies for porphyry copper deposits associated with Paleozoic subduction-related island-arc complexes preserved in the Tagil and Magnitogorsk arcs, Paleozoic island-arc fragments and associated tonalite-granodiorite intrusions in the East Uralian zone, and Carboniferous continental-margin arcs developed on the Kazakh craton in the Transuralian zone. The tracts range from about 50,000 to 130,000 km2 in area. The Urals host 8 known porphyry copper deposits with total identified resources of about 6.4 million metric tons of copper, at least 20 additional porphyry copper prospect areas, and numerous copper-bearing skarns and copper occurrences.
Probabilistic estimates predict a mean of 22 undiscovered porphyry copper deposits within the four permissive tracts delineated in the Urals. Combining estimates with established grade and tonnage models predicts a mean of 82 million metric tons of undiscovered copper. Application of an economic filter suggests that about half of that amount could be economically recoverable based on assumed depth distributions, availability of infrastructure, recovery rates, current metals prices, and investment environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2016.09.007","usgsCitation":"Hammarstrom, J.M., Mihalasky, M.J., Ludington, S., Phillips, J., Berger, B.R., Denning, P., Dicken, C., Mars, J.C., Zientek, M.L., Herrington, R.J., and Seltmann, R., 2017, Undiscovered porphyry copper resources in the Urals—A probabilistic mineral resource assessment: Ore Geology Reviews, v. 85, p. 181-203, https://doi.org/10.1016/j.oregeorev.2016.09.007.","productDescription":"23 p.","startPage":"181","endPage":"203","ipdsId":"IP-068679","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2016.09.007","text":"Publisher Index Page"},{"id":346315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Kazakhstan, Russia","otherGeospatial":"Urals","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 56,\n 50\n ],\n [\n 68,\n 50\n ],\n [\n 68,\n 70\n ],\n [\n 56,\n 70\n ],\n [\n 56,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59d35026e4b05fe04cc34d54","contributors":{"authors":[{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science 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slud@usgs.gov","orcid":"https://orcid.org/0000-0002-6265-4996","contributorId":172672,"corporation":false,"usgs":true,"family":"Ludington","given":"Stephen","email":"slud@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":711716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":711717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berger, Byron R. bberger@usgs.gov","contributorId":1490,"corporation":false,"usgs":true,"family":"Berger","given":"Byron","email":"bberger@usgs.gov","middleInitial":"R.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":711718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Denning, Paul pdenning@usgs.gov","contributorId":168842,"corporation":false,"usgs":true,"family":"Denning","given":"Paul","email":"pdenning@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dicken, Connie cdicken@usgs.gov","contributorId":172878,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie","email":"cdicken@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711720,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mars, John C. 0000-0002-0421-1388 jmars@usgs.gov","orcid":"https://orcid.org/0000-0002-0421-1388","contributorId":178265,"corporation":false,"usgs":true,"family":"Mars","given":"John","email":"jmars@usgs.gov","middleInitial":"C.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":711721,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":711722,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Herrington, Richard J.","contributorId":70688,"corporation":false,"usgs":true,"family":"Herrington","given":"Richard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":711723,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seltmann, Reimar","contributorId":73450,"corporation":false,"usgs":true,"family":"Seltmann","given":"Reimar","email":"","affiliations":[],"preferred":false,"id":711724,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189491,"text":"70189491 - 2017 - Continued feeding on Diporeia by deepwater sculpin in Lake Huron","interactions":[],"lastModifiedDate":"2018-03-28T11:17:16","indexId":"70189491","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Continued feeding on Diporeia by deepwater sculpin in Lake Huron","title":"Continued feeding on Diporeia by deepwater sculpin in Lake Huron","docAbstract":"Monitoring changes in diets of fish is essential to understanding how food web dynamics respond to changes in native prey abundances. In the Great Lakes, Diporeia, a benthic macroinvertebrate and primary food of native benthivores, declined following the introduction of invasive Dreissena mussels and these changes were reflected in fish diets. We examined the diets of deepwater sculpin Myoxocephalus thompsonii collected in bottom trawls during 2010–2014 in the main basin of Lake Huron, and compared these results to an earlier diet study (2003–2005) to assess if their diets have continued to change after a prolonged period of Dreissena mussel invasion and declined Diporeia densities. Diporeia, Mysis, Bythotrephes, and Chironomidae were consumed regularly and other diet items included ostracods, copepods, sphaerid clams, and fish eggs. The prey-specific index of relative importance calculated for each prey group indicated that Mysis importance increased at shallow (≤55 m) and mid (64–73 m) depths, while Diporeia importance increased offshore (≥82 m). The average number of Diporeia consumed per fish increased by 10.0% and Mysis decreased by 7.5%, while the frequency of occurrence of Diporeia and Mysis remained comparable between time periods. The weight of adult deepwater sculpin (80 mm and 100 mm TL bins) increased between time periods; however, the change in weight was only significant for the 80 mm TL group (p < 0.01). Given the historical importance of Diporeia in the Great Lakes, the examination of deepwater sculpin diets provides unique insight into the trophic dynamics of the benthic community in Lake Huron.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-016-0568-8","usgsCitation":"Thompson, P., Roseman, E., Keeler, K.M., O’Brien, T.P., and Bowser, D., 2017, Continued feeding on Diporeia by deepwater sculpin in Lake Huron: Environmental Biology of Fishes, v. 100, no. 4, p. 407-419, https://doi.org/10.1007/s10641-016-0568-8.","productDescription":"13 p.","startPage":"407","endPage":"419","ipdsId":"IP-071146","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":344138,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FX77MK","text":"Diets of Deepwater Sculpin collected from fall forage (2003-05 and 2010-14) in Lake Huron"},{"id":343825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.847412109375,\n 42.79540065303723\n ],\n [\n -81.090087890625,\n 42.79540065303723\n ],\n [\n -81.090087890625,\n 46.46813299215554\n ],\n [\n -84.847412109375,\n 46.46813299215554\n ],\n [\n -84.847412109375,\n 42.79540065303723\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2016-12-28","publicationStatus":"PW","scienceBaseUri":"5968869de4b0d1f9f05f5974","contributors":{"authors":[{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":704903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":534,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":704904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeler, Kevin M. 0000-0002-8118-0060 kkeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":4377,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","email":"kkeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bowser, Dustin dbowser@usgs.gov","contributorId":145563,"corporation":false,"usgs":true,"family":"Bowser","given":"Dustin","email":"dbowser@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":704907,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191541,"text":"70191541 - 2017 - Coal-tar-based pavement sealants—a potent source of PAHs","interactions":[],"lastModifiedDate":"2017-10-17T11:03:27","indexId":"70191541","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2593,"text":"Lakeline","active":true,"publicationSubtype":{"id":10}},"title":"Coal-tar-based pavement sealants—a potent source of PAHs","docAbstract":"P avement sealants are applied to the asphalt pavement of many parking lots, driveways, and even playgrounds in North America (Figure 1), where, when first applied, they render the pavement glossy black and looking like new. Sealant products used commercially in the central, eastern, and northern United States typically are coal-tarbased, whereas those used in the western United States typically are asphalt-based. Although the products look similar, they are chemically different. Coal-tarbased pavement sealants typically are 25-35 percent (by weight) coal tar or coal-tar pitch, materials that are known human carcinogens and that contain high concentrations of polycyclic aromatic hydrocarbons (PAHs) and related chemicals (unless otherwise noted, all Figure 1. Pavement sealant is commonly used to seal parking lots, playgrounds, and driveways throughout the United States. Sealants used in the central, northern, eastern, and southern United States typically contain coal tar or coal-tar pitch, both of which are known human carcinogens. Photos by the U.S. Geological Survey. data in this article are from Mahler et al. 2012 and references therein).
","language":"English","publisher":"North American Lake Management Society","usgsCitation":"Mahler, B., and Van Metre, P., 2017, Coal-tar-based pavement sealants—a potent source of PAHs: Lakeline, v. 37, no. 1, p. 13-18.","productDescription":"6 p.","startPage":"13","endPage":"18","ipdsId":"IP-082495","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346647,"type":{"id":15,"text":"Index Page"},"url":"https://www.nalms.org/lakeline-magazine/"}],"volume":"37","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e71691e4b05fe04cd331a9","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":712708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":172246,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":false,"id":712709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192035,"text":"70192035 - 2017 - Low stress drops observed for aftershocks of the 2011 Mw 5.7 Prague, Oklahoma, earthquake","interactions":[],"lastModifiedDate":"2017-10-24T14:13:06","indexId":"70192035","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","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":"Low stress drops observed for aftershocks of the 2011 Mw 5.7 Prague, Oklahoma, earthquake","docAbstract":"In November 2011, three Mw ≥ 4.8 earthquakes and thousands of aftershocks occurred along the structurally complex Wilzetta fault system near Prague, Oklahoma. Previous studies suggest that wastewater injection induced a Mw 4.8 foreshock, which subsequently triggered a Mw 5.7 mainshock. We examine source properties of aftershocks with a standard Brune-type spectral model and jointly solve for seismic moment (M0), corner frequency (f0), and kappa (κ) with an iterative Gauss-Newton global downhill optimization method. We examine 934 earthquakes with initial moment magnitudes (Mw) between 0.33 and 4.99 based on the pseudospectral acceleration and recover reasonable M0, f0, and κ for 87 earthquakes with Mw 1.83–3.51 determined by spectral fit. We use M0 and f0 to estimate the Brune-type stress drop, assuming a circular fault and shear-wave velocity at the hypocentral depth of the event. Our observations suggest that stress drops range between 0.005 and 4.8 MPa with a median of 0.2 MPa (0.03–26.4 MPa with a median of 1.1 MPa for Madariaga-type), which is significantly lower than typical eastern United States intraplate events (>10 MPa). We find that stress drops correlate weakly with hypocentral depth and magnitude. Additionally, we find the stress drops increase with time after the mainshock, although temporal variation in stress drop is difficult to separate from spatial heterogeneity and changing event locations. The overall low median stress drop suggests that the fault segments may have been primed to fail as a result of high pore fluid pressures, likely related to nearby wastewater injection.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JB013153","usgsCitation":"Sumy, D.F., Neighbors, C.J., Cochran, E.S., and Keranen, K.M., 2017, Low stress drops observed for aftershocks of the 2011 Mw 5.7 Prague, Oklahoma, earthquake: Journal of Geophysical Research B: Solid Earth, v. 122, no. 5, p. 3813-3834, https://doi.org/10.1002/2016JB013153.","productDescription":"22 p.","startPage":"3813","endPage":"3834","ipdsId":"IP-075342","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469876,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jb013153","text":"Publisher Index Page"},{"id":347249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Prague","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.5,\n 34.5\n ],\n [\n -95.5,\n 34.5\n ],\n [\n -95.5,\n 36.5\n ],\n [\n -97.5,\n 36.5\n ],\n [\n -97.5,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-21","publicationStatus":"PW","scienceBaseUri":"59f05122e4b0220bbd9a1d9a","contributors":{"authors":[{"text":"Sumy, Danielle F.","contributorId":108025,"corporation":false,"usgs":true,"family":"Sumy","given":"Danielle","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":713942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neighbors, Corrie J.","contributorId":197629,"corporation":false,"usgs":false,"family":"Neighbors","given":"Corrie","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keranen, Katie M.","contributorId":197630,"corporation":false,"usgs":false,"family":"Keranen","given":"Katie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713944,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190561,"text":"70190561 - 2017 - Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert","interactions":[],"lastModifiedDate":"2017-09-07T12:26:55","indexId":"70190561","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert","docAbstract":"Public land policies manage multiple uses while striving to protect vulnerable plant and wildlife habitats from degradation; yet the effectiveness of such policies are infrequently evaluated, particularly for remote landscapes that are difficult to monitor. We assessed the use and impacts of recreational vehicles on Mojave Desert washes (intermittent streams) in the Chemehuevi Desert Wildlife Management Area (DWMA) of southern California. Wash zones designated as open and closed to off-highway vehicle (OHV) activity were designed in part to protect Mojave desert tortoise (Gopherus agassizii) habitat while allowing recreation in designated areas. OHV tracks were monitored in washes located near access roads during winter and early spring holidays – when recreation is typically high – and at randomly dispersed locations away from roads. Washes near access roads had fewer vehicle tracks within closed than open zones; further away from roads, OHV tracks were infrequent and their occurrence was not different between wash designations. Washes were in better condition in closed zones following major holidays as indicated by less vegetation damage, presence of trash, and wash bank damage. Furthermore, the frequency of washes with live tortoises and their sign was marginally greater in closed than open wash zones. Collectively, these results suggest that low impacts to habitats in designated closed wash zones reflect public compliance with federal OHV policy and regulations in the Chemehuevi DWMA during our study. Future monitoring to contrast wash use and impacts during other seasons as well as in other DWMAs will elucidate spatial and temporal patterns of recreation in these important conservation areas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.02.033","usgsCitation":"Custer, N., Defalco, L., Nussear, K.E., and Esque, T., 2017, Drawing a line in the sand: Effectiveness of off-highway vehicle management in California's Sonoran desert: Journal of Environmental Management, v. 193, p. 448-457, https://doi.org/10.1016/j.jenvman.2017.02.033.","productDescription":"10 p.","startPage":"448","endPage":"457","ipdsId":"IP-053017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469885,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2017.02.033","text":"Publisher Index Page"},{"id":345546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sonoran Desert","volume":"193","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b25b00e4b020cdf7db1fbb","contributors":{"authors":[{"text":"Custer, Nathan ncuster@usgs.gov","contributorId":5561,"corporation":false,"usgs":true,"family":"Custer","given":"Nathan","email":"ncuster@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":709811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defalco, Lesley A. ldefalco@usgs.gov","contributorId":138961,"corporation":false,"usgs":true,"family":"Defalco","given":"Lesley A.","email":"ldefalco@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":709813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":138964,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709814,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192624,"text":"70192624 - 2017 - Do we need demographic data to forecast plant population dynamics?","interactions":[],"lastModifiedDate":"2017-11-10T10:59:58","indexId":"70192624","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Do we need demographic data to forecast plant population dynamics?","docAbstract":"Burn area and the frequency of extreme fire events have been increasing during recent decades in North America, and this trend is expected to continue over the 21st century. While many aspects of the North American carbon budget have been intensively studied, the net contribution of fire disturbance to the overall net carbon flux at the continental scale remains uncertain. Based on national scale, spatially explicit and long-term fire data, along with the improved model parameterization in a process-based ecosystem model, we simulated the impact of fire disturbance on both direct carbon emissions and net terrestrial ecosystem carbon balance in North America. Fire-caused direct carbon emissions were 106.55 ± 15.98 Tg C/yr during 1990–2012; however, the net ecosystem carbon balance associated with fire was −26.09 ± 5.22 Tg C/yr, indicating that most of the emitted carbon was resequestered by the terrestrial ecosystem. Direct carbon emissions showed an increase in Alaska and Canada during 1990–2012 as compared to prior periods due to more extreme fire events, resulting in a large carbon source from these two regions. Among biomes, the largest carbon source was found to be from the boreal forest, primarily due to large reductions in soil organic matter during, and with slower recovery after, fire events. The interactions between fire and environmental factors reduced the fire-caused ecosystem carbon source. Fire disturbance only caused a weak carbon source as compared to the best estimate terrestrial carbon sink in North America owing to the long-term legacy effects of historical burn area coupled with fast ecosystem recovery during 1990–2012.
","language":"English","publisher":"AGU","doi":"10.1002/2016GB005548","usgsCitation":"Chen, G., Hayes, D.J., and McGuire, A.D., 2017, Contributions of wildland fire to terrestrial ecosystem carbon dynamics in North America from 1990 to 2012: Global Biogeochemical Cycles, v. 31, no. 5, p. 878-900, https://doi.org/10.1002/2016GB005548.","productDescription":"23 p.","startPage":"878","endPage":"900","ipdsId":"IP-084072","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005548","text":"Publisher Index Page"},{"id":348451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"31","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-27","publicationStatus":"PW","scienceBaseUri":"5a0425b9e4b0dc0b45b45388","contributors":{"authors":[{"text":"Chen, Guangsheng","contributorId":200153,"corporation":false,"usgs":false,"family":"Chen","given":"Guangsheng","email":"","affiliations":[],"preferred":false,"id":721156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716799,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192744,"text":"70192744 - 2017 - The history of mercury pollution near the Spolana chlor-alkali plant (Neratovice, Czech Republic) as recorded by Scots pine tree rings and other bioindicators","interactions":[],"lastModifiedDate":"2017-11-13T14:19:34","indexId":"70192744","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The history of mercury pollution near the Spolana chlor-alkali plant (Neratovice, Czech Republic) as recorded by Scots pine tree rings and other bioindicators","docAbstract":"We assessed > 100 years of mercury (Hg) pollution recorded in the tree rings of Scots Pine near a Czech chlor-alkali plant operating since 1941. Hg concentrations in tree rings increased with the launching of plant operations and decreased when Hg emissions decreased in 1975 due to an upgrade in production technology. Similar to traditional bioindicators of pollution such as pine needles, bark and forest floor humus, Hg concentrations in Scots Pine boles decreased with distance from the plant. Mean Hg in pine bole in the 1940s ranged from 32.5 μg/kg Hg at a distance of 0.5 km from the plant to 5.4 μg/kg at a distance of > 4.7 km, where tree ring Hg was the same as at a reference site, and other bioindicators also suggest that the effect of the plant was no longer discernible. Tree ring Hg concentrations decreased by 8–29 μg/kg since the 1940s at all study sites including the reference site. The lack of exact correspondence between changes at the plant and tree ring Hg indicated some smearing of the signal due to lateral translocation of Hg from sapwood to heartwood. Bole Hg concentrations reflected local and regional atmospheric Hg concentrations, and not Hg wet deposition.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2017.02.112","usgsCitation":"Navrátil, T., Simecek, M., Shanley, J.B., Rohovec, J., Hojdova, M., and Houska, J., 2017, The history of mercury pollution near the Spolana chlor-alkali plant (Neratovice, Czech Republic) as recorded by Scots pine tree rings and other bioindicators: Science of the Total Environment, v. 586, https://doi.org/10.1016/j.scitotenv.2017.02.112.","productDescription":"11 p.","startPage":"1192","ipdsId":"IP-083992","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":348713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Czech Republic","city":"Neratovice","otherGeospatial":"Spolana chlor-alkali plant","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.4580078125,\n 50.20898843999949\n ],\n [\n 14.590530395507812,\n 50.20898843999949\n ],\n [\n 14.590530395507812,\n 50.3077613106073\n ],\n [\n 14.4580078125,\n 50.3077613106073\n ],\n [\n 14.4580078125,\n 50.20898843999949\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"586","edition":"1182","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fbd6e4b06e28e9c236d7","contributors":{"authors":[{"text":"Navrátil, Tomáš","contributorId":149720,"corporation":false,"usgs":false,"family":"Navrátil","given":"Tomáš","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":716807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simecek, Martin","contributorId":198385,"corporation":false,"usgs":false,"family":"Simecek","given":"Martin","email":"","affiliations":[{"id":35216,"text":"Institute of Geology AS CR, v.v.i., Rozvojová 269, 165 00 Prague 6, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":716808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohovec, Jan","contributorId":149721,"corporation":false,"usgs":false,"family":"Rohovec","given":"Jan","email":"","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":716809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hojdova, Maria","contributorId":198685,"corporation":false,"usgs":false,"family":"Hojdova","given":"Maria","email":"","affiliations":[{"id":35739,"text":"Institute of Geology of CAS, v.v.i., Rozvojová 269, 165 00 Prague 6, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":716810,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houska, Jakub","contributorId":198386,"corporation":false,"usgs":false,"family":"Houska","given":"Jakub","email":"","affiliations":[{"id":29875,"text":"Czech University of Life Sciences, Praha 6-Suchdol, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":716811,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191275,"text":"70191275 - 2017 - National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","interactions":[],"lastModifiedDate":"2017-10-03T11:47:48","indexId":"70191275","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NETN/NRR—2017/1437","title":"National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project","docAbstract":"The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program.
Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project.
To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation.
A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA.
Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.
We use new and existing data to compile a record of ∼18 latest Quaternary large-magnitude surface-rupturing earthquakes on 7 fault zones in the northwestern Basin and Range Province of northwestern Nevada and northeastern California. The most recent earthquake on all faults postdates the ca. 18–15 ka last glacial highstand of pluvial Lake Lahontan and other pluvial lakes in the region. These lacustrine data provide a window in which we calculate latest Quaternary vertical slip rates and compare them with rates of modern deformation in a global positioning system (GPS) transect spanning the region. Average vertical slip rates on these fault zones range from 0.1 to 0.8 mm/yr and total ∼2 mm/yr across a 265-km-wide transect from near Paradise Valley, Nevada, to the Warner Mountains in California. We converted vertical slip rates to horizontal extension rates using fault dips of 30°–60°, and then compared the extension rates to GPS-derived rates of modern (last 7–9 yr) deformation. Our preferred fault dip values (45°–55°) yield estimated long-term extension rates (1.3–1.9 mm/yr) that underestimate our modern rate (2.4 mm/yr) by ∼21%–46%. The most likely sources of this underestimate are geologically unrecognizable deformation from moderate-sized earthquakes and unaccounted-for coseismic off-fault deformation from large surface-rupturing earthquakes. However, fault dip values of ≤40° yield long-term rates comparable to or greater than modern rates, so an alternative explanation is that fault dips are closer to 40° than our preferred values. We speculate that the large component of right-lateral shear apparent in the GPS signal is partitioned on faults with primary strike-slip displacement, such as the Long Valley fault zone, and as not easily detected oblique slip on favorably oriented normal faults in the region.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01380.1","usgsCitation":"Personius, S., Briggs, R.W., Maharrey, J.Z., Angster, S.J., and Mahan, S.A., 2017, A paleoseismic transect across the northwestern Basin and Range Province, northwestern Nevada and northeastern California, USA: Geosphere, v. 13, no. 3, p. 782-810, https://doi.org/10.1130/GES01380.1.","productDescription":"29 p.","startPage":"782","endPage":"810","ipdsId":"IP-082995","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":469881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01380.1","text":"Publisher Index Page"},{"id":347328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Basin and Range Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 41\n ],\n [\n -117.25,\n 41\n ],\n [\n -117.25,\n 42\n ],\n [\n -121,\n 42\n ],\n [\n -121,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-10","publicationStatus":"PW","scienceBaseUri":"59f1a2a5e4b0220bbd9d9f58","contributors":{"authors":[{"text":"Personius, Stephen 0000-0001-8347-7370 personius@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-7370","contributorId":150055,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":712839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maharrey, J. Zebulon","contributorId":20625,"corporation":false,"usgs":true,"family":"Maharrey","given":"J.","email":"","middleInitial":"Zebulon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":712840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angster, Stephen J. 0000-0001-9250-8415 sangster@usgs.gov","orcid":"https://orcid.org/0000-0001-9250-8415","contributorId":3885,"corporation":false,"usgs":true,"family":"Angster","given":"Stephen","email":"sangster@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":712841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":712842,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192786,"text":"70192786 - 2017 - Tropical river suspended sediment and solute dynamics in storms during an extreme drought","interactions":[],"lastModifiedDate":"2017-11-29T13:48:39","indexId":"70192786","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","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":"Tropical river suspended sediment and solute dynamics in storms during an extreme drought","docAbstract":"Droughts, which can strongly affect both hydrologic and biogeochemical systems, are projected to become more prevalent in the tropics in the future. We assessed the effects of an extreme drought during 2015 on stream water composition in the Luquillo Mountains of Puerto Rico. We demonstrated that drought base flow in the months leading up to the study was sourced from trade-wind orographic rainfall, suggesting a resistance to the effects of an otherwise extreme drought. In two catchments (Mameyes and Icacos), we sampled a series of four rewetting events that partially alleviated the drought. We collected and analyzed dissolved constituents (major cations and anions, organic carbon, and nitrogen) and suspended sediment (inorganic and organic matter (particulate organic carbon and particulate nitrogen)). The rivers appeared to be resistant to extreme drought, recovering quickly upon rewetting, as (1) the concentration-discharge (C-Q) relationships deviated little from the long-term patterns; (2) “new water” dominated streamflow during the latter events; (3) suspended sediment sources had accumulated in the channel during the drought flushed out during the initial events; and (4) the severity of the drought, as measured by the US drought monitor, was reduced dramatically after the rewetting events. Through this interdisciplinary study, we were able to investigate the impact of extreme drought through rewetting events on the river biogeochemistry.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR019737","usgsCitation":"Clark, K.E., Shanley, J.B., Scholl, M.A., Perdrial, N., Perdrial, J.N., Plante, A.F., and McDowell, W.H., 2017, Tropical river suspended sediment and solute dynamics in storms during an extreme drought: Water Resources Research, v. 53, no. 5, p. 3695-3712, https://doi.org/10.1002/2016WR019737.","productDescription":"18 p.","startPage":"3695","endPage":"3712","ipdsId":"IP-081947","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":349547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.83,\n 18.25\n ],\n [\n -65.72,\n 18.25\n ],\n [\n -65.72,\n 18.35\n ],\n [\n -65.83,\n 18.35\n ],\n [\n -65.83,\n 18.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"5","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"5a60fbd6e4b06e28e9c236d5","contributors":{"authors":[{"text":"Clark, Kathryn E.","contributorId":198717,"corporation":false,"usgs":false,"family":"Clark","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716932,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":716937,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perdrial, Nicolas","contributorId":198718,"corporation":false,"usgs":false,"family":"Perdrial","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":716933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perdrial, Julia N.","contributorId":177340,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":716934,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plante, Alain F.","contributorId":198719,"corporation":false,"usgs":false,"family":"Plante","given":"Alain","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":716935,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McDowell, William H.","contributorId":198684,"corporation":false,"usgs":false,"family":"McDowell","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":716936,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192626,"text":"70192626 - 2017 - A dynamic spatio-temporal model for spatial data","interactions":[],"lastModifiedDate":"2018-01-03T15:57:04","indexId":"70192626","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"A dynamic spatio-temporal model for spatial data","docAbstract":"Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.
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