The evolutionary trajectory of populations through time is influenced by the interplay of forces (biological, evolutionary, and anthropogenic) acting on the standing genetic variation. We used microsatellite and mitochondrial loci to examine the influence of population declines, of varying severity, on genetic diversity within two Hawaiian endemic waterbirds, the Hawaiian coot and Hawaiian gallinule, by comparing historical (samples collected in the late 1800s and early 1900s) and modern (collected in 2012–2013) populations. Population declines simultaneously experienced by Hawaiian coots and Hawaiian gallinules differentially shaped the evolutionary trajectory of these two populations. Within Hawaiian coot, large reductions (between −38.4% and −51.4%) in mitochondrial diversity were observed, although minimal differences were observed in the distribution of allelic and haplotypic frequencies between sampled time periods. Conversely, for Hawaiian gallinule, allelic frequencies were strongly differentiated between time periods, signatures of a genetic bottleneck were detected, and biases in means of the effective population size were observed at microsatellite loci. The strength of the decline appears to have had a greater influence on genetic diversity within Hawaiian gallinule than Hawaiian coot, coincident with the reduction in census size. These species exhibit similar life history characteristics and generation times; therefore, we hypothesize that differences in behavior and colonization history are likely playing a large role in how allelic and haplotypic frequencies are being shaped through time. Furthermore, differences in patterns of genetic diversity within Hawaiian coot and Hawaiian gallinule highlight the influence of demographic and evolutionary processes in shaping how species respond genetically to ecological stressors.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3530","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Underwood, J.G., 2017, Genetic implications of bottleneck effects of differing severities on genetic diversity in naturally recovering populations: An example from Hawaiian coot and Hawaiian gallinule: Ecology and Evolution, v. 7, no. 23, p. 9925-9934, https://doi.org/10.1002/ece3.3530.","productDescription":"10 p.","startPage":"9925","endPage":"9934","ipdsId":"IP-085014","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":469288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3530","text":"Publisher Index Page"},{"id":352990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"23","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-20","publicationStatus":"PW","scienceBaseUri":"5afee79ee4b0da30c1bfc318","contributors":{"authors":[{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","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":732031,"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":732032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Underwood, Jared G.","contributorId":198606,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":732033,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195381,"text":"70195381 - 2017 - Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests","interactions":[],"lastModifiedDate":"2020-09-01T14:26:56.11934","indexId":"70195381","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests","docAbstract":"For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.
","language":"English","publisher":"EGU","doi":"10.5194/bg-14-4663-2017","usgsCitation":"Clark, D., Asao, S., Fisher, R.A., Reed, S.C., Reich, P.B., Ryan, M.G., Wood, T.E., and Yang, X., 2017, Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests: Biogeosciences, v. 14, p. 4663-4690, https://doi.org/10.5194/bg-14-4663-2017.","productDescription":"28 p.","startPage":"4663","endPage":"4690","ipdsId":"IP-086986","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469257,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-14-4663-2017","text":"Publisher Index Page"},{"id":351527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc33d","contributors":{"authors":[{"text":"Clark, Deborah A.","contributorId":202368,"corporation":false,"usgs":false,"family":"Clark","given":"Deborah A.","affiliations":[{"id":36397,"text":"Department of Biology, University of Missouri-St. Louis","active":true,"usgs":false}],"preferred":false,"id":728279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asao, Shinichi","contributorId":202369,"corporation":false,"usgs":false,"family":"Asao","given":"Shinichi","email":"","affiliations":[{"id":7230,"text":"Natural Resource Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":728280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Rosie A.","contributorId":147090,"corporation":false,"usgs":false,"family":"Fisher","given":"Rosie","email":"","middleInitial":"A.","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":728281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":728278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reich, Peter B.","contributorId":202370,"corporation":false,"usgs":false,"family":"Reich","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":36398,"text":"Department of Forest Resources, University of Minnesota, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":728282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryan, Michael G.","contributorId":202371,"corporation":false,"usgs":false,"family":"Ryan","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":33176,"text":"Rocky Mountain Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":728283,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Tana E.","contributorId":202372,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","email":"","middleInitial":"E.","affiliations":[{"id":36399,"text":"International Institute of Tropical Forestry, USDA Forest Service, Rio Piedras, PR","active":true,"usgs":false}],"preferred":false,"id":728284,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yang, Xiaojuan","contributorId":146256,"corporation":false,"usgs":false,"family":"Yang","given":"Xiaojuan","email":"","affiliations":[{"id":16649,"text":"Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN 37831-6335, USA","active":true,"usgs":false}],"preferred":false,"id":728285,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70196136,"text":"70196136 - 2017 - Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","interactions":[],"lastModifiedDate":"2018-03-21T13:25:45","indexId":"70196136","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","title":"Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits","docAbstract":"Organic sulfur compounds are ubiquitous in natural oil and gas fields and moderate-low temperature sulfide ore deposits. Previous studies have shown that organic sulfur compounds are important in enhancing the rates of thermochemical sulfate reduction (TSR) reactions, but the details of these reaction mechanisms remain unclear. In order to assess the extent of sulfate reduction in the presence of labile sulfur species at temperature conditions near to those where TSR occurs in nature, we conducted a series of experiments using the fused silica capillary capsule (FCSS) method. The tested systems containing labile sulfur species are MgSO4 + 1-pentanethiol (C5H11SH) + 1-octene (C8H16), MgSO4 + 1-octene (C8H16), MgSO4 + 1-pentanethiol (C5H11SH), 1-pentanethiol (C5H11SH)+H2O, and MgSO4 + 1-pentanethiol (C5H11SH) + ZnBr2 systems. Our results show that: (1) intermediate oxidized carbon species (ethanol and acetic acid) are formed during TSR simulation experiments when 1-pentanethiol is present; (2) in the presence of ZnBr2, 1-pentanethiol can be oxidized by sulfate to CO2 at 200 °C, which is within the temperature range observed in natural TSR; and (3) the precipitation of sulfide minerals may significantly promote the rate of TSR, indicating that the rates of in situ TSR reactions in ore deposits could be much faster than previously thought. This may be important for understanding the possibility of in situ TSR as a mechanism for the precipitation of metal sulfides in some ore deposits. These findings provide important experimental evidence for understanding the role of organic sulfur compounds in TSR reactions and the pathway of TSR reactions initiated by organic sulfur compounds under natural conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2017.11.003","usgsCitation":"Yuan, S., Ellis, G.S., Chou, I., and Burruss, R., 2017, Experimental investigation on thermochemical sulfate reduction in the presence of 1-pentanethiol at 200 and 250 °C: Implications for in situ TSR processes occurring in some MVT deposits: Ore Geology Reviews, v. 91, p. 57-65, https://doi.org/10.1016/j.oregeorev.2017.11.003.","productDescription":"9 p.","startPage":"57","endPage":"65","ipdsId":"IP-059524","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":352700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7aae4b0da30c1bfc32f","contributors":{"authors":[{"text":"Yuan, Shunda","contributorId":203441,"corporation":false,"usgs":false,"family":"Yuan","given":"Shunda","email":"","affiliations":[{"id":36622,"text":"Institute of Mineral Resources, Chinese Academy of Geological Sciences","active":true,"usgs":false}],"preferred":false,"id":731495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731494,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chou, I-Ming 0000-0001-5233-6479 imchou@usgs.gov","orcid":"https://orcid.org/0000-0001-5233-6479","contributorId":882,"corporation":false,"usgs":true,"family":"Chou","given":"I-Ming","email":"imchou@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burruss, Robert 0000-0001-6827-804X burruss@usgs.gov","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":146833,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"burruss@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":731497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196741,"text":"70196741 - 2017 - Sampling bees in tropical forests and agroecosystems: A review","interactions":[],"lastModifiedDate":"2018-04-30T10:18:21","indexId":"70196741","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2356,"text":"Journal of Insect Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Sampling bees in tropical forests and agroecosystems: A review","docAbstract":"Bees are the predominant pollinating taxa, providing a critical ecosystem service upon which many angiosperms rely for successful reproduction. Available data suggests that bee populations worldwide are declining, but scarce data in tropical regions precludes assessing their status and distribution, impact on ecological services, and response to management actions. Herein, we reviewed >150 papers that used six common sampling methods (pan traps, baits, Malaise traps, sweep nets, timed observations and aspirators) to better understand their strengths and weaknesses, and help guide method selection to meet research objectives and development of multi-species monitoring approaches. Several studies evaluated the effectiveness of sweep nets, pan traps, and malaise traps, but only one evaluated timed observations, and none evaluated aspirators. Only five studies compared two or more of the remaining four sampling methods to each other. There was little consensus regarding which method would be most reliable for sampling multiple species. However, we recommend that if the objective of the study is to estimate abundance or species richness, malaise traps, pan traps and sweep nets are the most effective sampling protocols in open tropical systems; conversely, malaise traps, nets and baits may be the most effective in forests. Declining bee populations emphasize the critical need in method standardization and reporting precision. Moreover, we recommend reporting a catchability coefficient, a measure of the interaction between the resource (bee) abundance and catching effort. Melittologists could also consider existing methods, such as occupancy models, to quantify changes in distribution and abundance after modeling heterogeneity in trapping probability, and consider the possibility of developing monitoring frameworks that draw from multiple sources of data.
","language":"English","publisher":"Springer","doi":"10.1007/s10841-017-0018-8","usgsCitation":"Prado, S.G., Ngo, H.T., Florez, J.A., and Collazo, J., 2017, Sampling bees in tropical forests and agroecosystems: A review: Journal of Insect Conservation, v. 21, no. 5-6, p. 753-770, https://doi.org/10.1007/s10841-017-0018-8.","productDescription":"18 p.","startPage":"753","endPage":"770","ipdsId":"IP-082870","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469286,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10841-017-0018-8","text":"Publisher Index Page"},{"id":353848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"5-6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-22","publicationStatus":"PW","scienceBaseUri":"5afee79de4b0da30c1bfc30c","contributors":{"authors":[{"text":"Prado, Sara G.","contributorId":204504,"corporation":false,"usgs":false,"family":"Prado","given":"Sara","email":"","middleInitial":"G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":734202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ngo, Hien T.","contributorId":204505,"corporation":false,"usgs":false,"family":"Ngo","given":"Hien","email":"","middleInitial":"T.","affiliations":[{"id":36950,"text":"United Nations, Bonn","active":true,"usgs":false}],"preferred":false,"id":734203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Florez, Jaime A.","contributorId":204506,"corporation":false,"usgs":false,"family":"Florez","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":734204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":734201,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195325,"text":"70195325 - 2017 - A statistical method to predict flow permanence in dryland streams from time series of stream temperature","interactions":[],"lastModifiedDate":"2018-02-08T13:51:52","indexId":"70195325","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A statistical method to predict flow permanence in dryland streams from time series of stream temperature","docAbstract":"Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.
","language":"English","publisher":"MDPI","doi":"10.3390/w9120946","usgsCitation":"Arismendi, I., Dunham, J.B., Heck, M., Schultz, L., and Hockman-Wert, D., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 1-13, https://doi.org/10.3390/w9120946.","productDescription":"Article 946; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-087892","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469281,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w9120946","text":"Publisher Index Page"},{"id":438137,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ0ZW2","text":"USGS data release","linkHelpText":"Stream temperature and drying data from Willow/Whitehorse watersheds, southeast Oregon, 2014-16, and Willow/Rock/Frazer watersheds, northern Nevada, 2015-2016"},{"id":351364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 42\n ],\n [\n -118,\n 42.33\n ],\n [\n -118.33,\n 42.33\n ],\n [\n -118.33,\n 42\n ],\n [\n -118,\n 42\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.33,\n 41.1667\n ],\n [\n -116.8333,\n 41.1667\n ],\n [\n -116.8333,\n 41.4167\n ],\n [\n -116.33,\n 41.4167\n ],\n [\n -116.33,\n 41.1667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-05","publicationStatus":"PW","scienceBaseUri":"5a7d6ffee4b00f54eb2441c0","contributors":{"authors":[{"text":"Arismendi, Ivan 0000-0002-8774-9350","orcid":"https://orcid.org/0000-0002-8774-9350","contributorId":202207,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":727859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Luke 0000-0002-6751-4626 lschultz@usgs.gov","orcid":"https://orcid.org/0000-0002-6751-4626","contributorId":193171,"corporation":false,"usgs":true,"family":"Schultz","given":"Luke","email":"lschultz@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hockman-Wert, David 0000-0003-2436-6237 dhockman-wert@usgs.gov","orcid":"https://orcid.org/0000-0003-2436-6237","contributorId":3891,"corporation":false,"usgs":true,"family":"Hockman-Wert","given":"David","email":"dhockman-wert@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":727862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192753,"text":"70192753 - 2017 - Turtles: Freshwater","interactions":[],"lastModifiedDate":"2018-02-12T14:16:43","indexId":"70192753","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Turtles: Freshwater","docAbstract":"With their iconic shells, turtles are morphologically distinct in being the only extant or extinct vertebrate animals to have their shoulders and hips inside their rib cages. By the time an asteroid hit the earth 65.5 million years ago, causing the extinction of dinosaurs, turtles were already an ancient lineage that was 70% through their evolutionary history to date. The remarkable evolutionary success of turtles over 220 million years is due to a combination of both conservative and effective life history traits and an essentially unchanging morphology that withstood the test of time. However, the life history traits of many species make them particularly susceptible to overharvest and habitat destruction in the modern world, and a majority of the world’s species face serious conservation challenges with several extinctions documented in modern times. The global plight of turtles is underscored by the fact that the percentage of imperiled species exceeds that of even the critically endangered primates.
Freshwater turtles, with over 260 recognized species, have become a focus on a worldwide scale for many conservation issues. This article is a synthesis of a diverse body of information on the general biology of freshwater turtles, with particular emphasis on the extensive research on ecology, life history, and behavior that has been accomplished in the last half century. Much of the research has been applicable to the aforementioned conservation challenges. The studies presented include a combination of laboratory and field experiments and observational studies on this intriguing group of animals.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in life sciences","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-809633-8.01218-8","usgsCitation":"Gibbons, J.W., Lovich, J.E., and Bowden, R., 2017, Turtles: Freshwater, chap. of Reference module in life sciences, p. 462-468, https://doi.org/10.1016/B978-0-12-809633-8.01218-8.","productDescription":"7 p.","startPage":"462","endPage":"468","ipdsId":"IP-078442","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":351498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee7abe4b0da30c1bfc34f","contributors":{"authors":[{"text":"Gibbons, J. Whitfield","contributorId":198690,"corporation":false,"usgs":false,"family":"Gibbons","given":"J.","email":"","middleInitial":"Whitfield","affiliations":[],"preferred":false,"id":716834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":716833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, R.M.","contributorId":198691,"corporation":false,"usgs":false,"family":"Bowden","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":716835,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191867,"text":"70191867 - 2017 - Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time","interactions":[],"lastModifiedDate":"2018-03-29T13:31:29","indexId":"70191867","displayToPublicDate":"2017-12-01T00:00:00","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":"Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time","title":"Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time","docAbstract":"Habitat use can be complex, as tradeoffs among physiology, resource abundance, and predator avoidance affect the suitability of different environments for different species. Green sturgeon (Acipenser medirostris), an imperiled species along the west coast of North America, undertake extensive coastal migrations and occupy estuaries during the summer and early fall. Warm water and abundant prey in estuaries may afford a growth opportunity. We applied a bioenergetics model to investigate how variation in estuarine temperature, spawning frequency, and duration of estuarine residence affect consumption and growth potential for individual green sturgeon. We assumed that green sturgeon achieve observed annual growth by feeding solely in conditions represented by Willapa Bay, Washington, an estuary annually frequented by green sturgeon and containing extensive tidal flats that harbor a major prey source (burrowing shrimp, Neotrypaea californiensis). Modeled consumption rates increased little with reproductive investment (<0.4%), but responded strongly (10–50%) to water temperature and duration of residence, as higher temperatures and longer residence required greater consumption to achieve equivalent growth. Accordingly, although green sturgeon occupy Willapa Bay from May through September, acoustically-tagged individuals are observed over much shorter durations (34 d + 41 d SD, N = 89). Simulations of <34 d estuarine residence required unrealistically high consumption rates to achieve observed growth, whereas longer durations required sustained feeding, and therefore higher total intake, to compensate for prolonged exposure to warm temperatures. Model results provide a range of per capita consumption rates by green sturgeon feeding in estuaries to inform management decisions regarding resource and habitat protection for this protected species.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-017-0665-3","usgsCitation":"Borin, J.M., Moser, M.L., Hansen, A.G., Beauchamp, D.A., Corbett, S.C., Dumbauld, B.R., Pruitt, C., Ruesink, J.L., and Donoghue, C., 2017, Energetic requirements of green sturgeon (Acipenser medirostris) feeding on burrowing shrimp (Neotrypaea californiensis) in estuaries: importance of temperature, reproductive investment, and residence time: Environmental Biology of Fishes, v. 100, no. 12, p. 1561-1573, https://doi.org/10.1007/s10641-017-0665-3.","productDescription":"13 p.","startPage":"1561","endPage":"1573","ipdsId":"IP-087984","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":488604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10641-017-0665-3","text":"Publisher Index Page"},{"id":352947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","scienceBaseUri":"5afee7abe4b0da30c1bfc353","contributors":{"authors":[{"text":"Borin, Joshua M.","contributorId":197414,"corporation":false,"usgs":false,"family":"Borin","given":"Joshua","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moser, Mary L.","contributorId":195100,"corporation":false,"usgs":false,"family":"Moser","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":713460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corbett, Stephen C.","contributorId":197416,"corporation":false,"usgs":false,"family":"Corbett","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":713461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dumbauld, Brett R.","contributorId":197417,"corporation":false,"usgs":false,"family":"Dumbauld","given":"Brett","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pruitt, Casey","contributorId":197418,"corporation":false,"usgs":false,"family":"Pruitt","given":"Casey","email":"","affiliations":[],"preferred":false,"id":713463,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ruesink, Jennifer L.","contributorId":197419,"corporation":false,"usgs":false,"family":"Ruesink","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713464,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Donoghue, Cinde","contributorId":197420,"corporation":false,"usgs":false,"family":"Donoghue","given":"Cinde","email":"","affiliations":[],"preferred":false,"id":713465,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70191906,"text":"70191906 - 2017 - Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California","interactions":[],"lastModifiedDate":"2019-06-13T10:31:01","indexId":"70191906","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California","docAbstract":"The U.S. Army Fort Irwin National Training Center (NTC), in the Mojave Desert, obtains all of its potable water supply from three groundwater basins (Irwin, Langford, and Bicycle) within the NTC boundaries (fig. 1; California Department of Water Resources, 2003). Because of increasing water demands at the NTC, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army, completed several studies to evaluate water resources in the developed and undeveloped groundwater basins underlying the NTC. In all of the developed basins, groundwater withdrawals exceed natural recharge, resulting in water-level declines. However, artificial recharge of treated wastewater has had some success in offsetting water-level declines in Irwin Basin. Additionally, localized water-quality changes have occurred in some parts of Irwin Basin as a result of human activities (i.e., wastewater disposal practices, landscape irrigation, and/or leaking pipes). As part of the multi-faceted NTC-wide studies, traditional datacollection methods were used and include lithological and geophysical logging at newly drilled boreholes, hydrologic data collection (i.e. water-level, water-quality, aquifer tests, wellbore flow). Because these data cover a small portion of the 1,177 square-mile (mi2 ) NTC, regional mapping, including geologic, gravity, aeromagnetic, and InSAR, also were done. In addition, ground and airborne electromagnetic surveys were completed and analyzed to provide more detailed subsurface information on a regional, base-wide scale. The traditional and regional ground and airborne data are being analyzed and will be used to help develop preliminary hydrogeologic framework and groundwater-flow models in all basins. This report is intended to provide an overview of recent water-resources and land-surface deformation studies at the NTC.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"California State University Desert Studies Center","usgsCitation":"Densmore, J.N., Dishart, J.E., Miller, D., Buesch, D.C., Ball, L.B., Bedrosian, P.A., Woolfenden, L.R., Cromwell, G., Burgess, M.K., Nawikas, J., O’Leary, D., Kjos, A., Sneed, M., and Brandt, J.T., 2017, Water-resources and land-surface deformation evaluation studies at Fort Irwin National Training Center, Mojave Desert, California, in 2017 Desert Symposium Field Guide and Proceedings - ECSZ does it: Revisiting the eastern California Shear Zone, p. 290-298.","productDescription":"9 p.","startPage":"290","endPage":"298","ipdsId":"IP-083966","costCenters":[{"id":154,"text":"California Water Science 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60faf9e4b06e28e9c22a64","contributors":{"authors":[{"text":"Densmore, Jill N. 0000-0002-5345-6613 jidensmo@usgs.gov","orcid":"https://orcid.org/0000-0002-5345-6613","contributorId":197491,"corporation":false,"usgs":true,"family":"Densmore","given":"Jill","email":"jidensmo@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dishart, Justine E.","contributorId":197492,"corporation":false,"usgs":false,"family":"Dishart","given":"Justine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David M. 0000-0003-3711-0441 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- Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","interactions":[],"lastModifiedDate":"2017-12-04T10:30:46","indexId":"sir20175072","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5072","title":"Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada","docAbstract":"The groundwater model described in this report is a new version of previously published steady-state numerical groundwater flow models of the Great Basin carbonate and alluvial aquifer system, and was developed in conjunction with U.S. Geological Survey studies in Parowan, Pine, and Wah Wah Valleys, Utah. This version of the model is GBCAAS v. 3.0 and supersedes previous versions. The objectives of the model for Parowan Valley were to simulate revised conceptual estimates of recharge and discharge, to estimate simulated aquifer storage properties and the amount of reduction in storage as a result of historical groundwater withdrawals, and to assess reduction in groundwater withdrawals necessary to mitigate groundwater-level declines in the basin. The objectives of the model for the area near Pine and Wah Wah Valleys were to recalibrate the model using new observations of groundwater levels and evapotranspiration of groundwater; to provide new estimates of simulated recharge, hydraulic conductivity, and interbasin flow; and to simulate the effects of proposed groundwater withdrawals on the regional flow system. Meeting these objectives required the addition of 15 transient calibration stress periods and 14 projection stress periods, aquifer storage properties, historical withdrawals in Parowan Valley, and observations of water-level changes in Parowan Valley.
Recharge in Parowan Valley and withdrawal from wells in Parowan Valley and two nearby wells in Cedar City Valley vary for each calibration stress period representing conditions from March 1940 to November 2013. Stresses, including recharge, are the same in each stress period as in the steady-state stress period for all areas outside of Parowan Valley. The model was calibrated to transient conditions only in Parowan Valley. Simulated storage properties outside of Parowan Valley were set the same as the Parowan Valley properties and are not considered calibrated.
Model observations in GBCAAS v. 3.0 are groundwater levels at wells and discharge locations; water-level changes; and discharge to springs, evapotranspiration of groundwater, rivers, and lakes. All observations in the model outside of Parowan Valley are considered to represent steady-state conditions. Composite scaled sensitivities indicate the observations of discharge to rivers and springs provide more information about model parameters in the model focus area than do water-level observations. Water levels and water-level changes, however, provide the only information about specific yield and specific storage parameters and provide more information about recharge and withdrawals in Parowan Valley than any other observation group.
Comparisons of simulated water levels and measured water levels in Parowan Valley indicated that the model fits the overall trend of declining water levels and provides reasonable estimates of long-term reduction in storage and of storage changes from 2012 to 2013. The conceptual and simulated groundwater budgets for Parowan Valley from November 2012 to November 2013 are similar, with recharge of about 20,000 acre-feet and discharge of about 45,000 acre-feet. In the simulation, historical withdrawals averaging about 28,000 acre-feet per year (acre-ft/yr) cause major changes in the groundwater system in Parowan Valley. These changes include the cessation of almost all natural discharge in the valley and the long-term removal of water from storage.
Simulated recharge in Pine Valley of 11,000 acre-ft/yr and in Wah Wah Valley of 3,200 acre-ft/yr is substantially less in GBCAAS v. 3.0 than that simulated by previous model versions. In addition, the valleys have less simulated inflow from and outflow to other hydrographic areas than were simulated by previous model versions. The effects of groundwater development in these valleys, however, are independent of the amount of water recharging in and flowing through the valleys. Groundwater withdrawals in Pine and Wah Wah Valleys will decrease groundwater storage (causing drawdown) until discharge in surrounding areas and mountain springs around the two valleys is reduced by the rate of withdrawal.
The model was used to estimate that reducing withdrawals in Parowan Valley from 35,000 to about 22,000 acre-ft/yr would likely stabilize groundwater levels in the valley if recharge varies as it did from about 1950 to 2012. The model was also used to demonstrate that withdrawals of 15,000 acre-ft/yr from Pine Valley and 6,500 acre-ft/yr from Wah Wah Valley could ultimately cause long-term steady-state water-level declines of about 1,900 feet near the withdrawal wells and of more than 5 feet in an area of about 10,500 square miles. The timing of drawdown and capture and the ultimate amount of drawdown are dependent on the proximity to areas of simulated natural groundwater discharge, simulated transmissivity, and simulated storage properties. The model projections are a representation of possible effects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175072","collaboration":"Prepared in cooperation with the Utah Department of Natural Resources and the U.S. Bureau of Land Management","usgsCitation":"Brooks, L.E., 2017, Groundwater model of the Great Basin carbonate and alluvial aquifer system version 3.0: Incorporating revisions in southwestern Utah and east central Nevada: U.S. Geological Survey Scientific Investigations Report 2017–5072, 77 p., 2 appendixes, https://doi.org/10.3133/sir20175072.","productDescription":"Report: x, 77 p.; Appendix Tables; Data Release","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-073792","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":349442,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5072"},{"id":349441,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5072/coverthb.jpg"},{"id":349505,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/sir2017-5072.xml","text":"Data Release","description":"SIR 2017-5072","linkHelpText":"MODFLOW-LGR data sets for the Great Basin carbonate and alluvial aquifer system model version 3.0: Revisions in southwestern Utah and east central Nevada"},{"id":349444,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5072/sir20175072_appendix1table5_6.zip","text":"Appendix 1 Tables 5 and 6","size":"400 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2017-5072"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.25,\n 37.5\n ],\n [\n -111.75,\n 37.5\n ],\n [\n -111.75,\n 40\n ],\n [\n -114.25,\n 40\n ],\n [\n -114.25,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The science behind sustaining the world's most crucial resource","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-809330-6.00002-7","usgsCitation":"Myers, D.N., and Ludtke, A.S., 2017, Progress and lessons learned from water-quality monitoring networks, chap. of The science behind sustaining the world's most crucial resource: Chemistry and Water, p. 23-120, https://doi.org/10.1016/B978-0-12-809330-6.00002-7.","productDescription":"98 p.","startPage":"23","endPage":"120","ipdsId":"IP-079349","costCenters":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"links":[{"id":349508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a92","contributors":{"authors":[{"text":"Myers, Donna N. 0000-0001-6359-2865 dnmyers@usgs.gov","orcid":"https://orcid.org/0000-0001-6359-2865","contributorId":512,"corporation":false,"usgs":true,"family":"Myers","given":"Donna","email":"dnmyers@usgs.gov","middleInitial":"N.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":723988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ludtke, Amy S. asludtke@usgs.gov","contributorId":4735,"corporation":false,"usgs":true,"family":"Ludtke","given":"Amy","email":"asludtke@usgs.gov","middleInitial":"S.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":723989,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194473,"text":"70194473 - 2017 - Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization","interactions":[],"lastModifiedDate":"2017-11-29T10:34:41","indexId":"70194473","displayToPublicDate":"2017-11-29T00:00:00","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":"Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization","docAbstract":"Physics-based models of volcanic eruptions track conduit processes as functions of depth and time. When used in inversions, these models permit integration of diverse geological and geophysical data sets to constrain important parameters of magmatic systems. We develop a 1-D steady state conduit model for effusive eruptions including equilibrium crystallization and gas transport through the conduit and compare with the quasi-steady dome growth phase of Mount St. Helens in 2005. Viscosity increase resulting from pressure-dependent crystallization leads to a natural transition from viscous flow to frictional sliding on the conduit margin. Erupted mass flux depends strongly on wall rock and magma permeabilities due to their impact on magma density. Including both lateral and vertical gas transport reveals competing effects that produce nonmonotonic behavior in the mass flux when increasing magma permeability. Using this physics-based model in a Bayesian inversion, we link data sets from Mount St. Helens such as extrusion flux and earthquake depths with petrological data to estimate unknown model parameters, including magma chamber pressure and water content, magma permeability constants, conduit radius, and friction along the conduit walls. Even with this relatively simple model and limited data, we obtain improved constraints on important model parameters. We find that the magma chamber had low (<5wt%) total volatiles and that the magma permeability scale is well constrained at ~10-11.4 m2 to reproduce observed dome rock porosities. Compared with previous results, higher magma overpressure and lower wall friction are required to compensate for increased viscous resistance while keeping extrusion rate at the observed value.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JB014343","usgsCitation":"Wong, Y., Segall, P., Bradley, A., and Anderson, K.R., 2017, Constraining the magmatic system at Mount St. Helens (2004–2008) using Bayesian inversion with physics-based models including gas escape and crystallization: Journal of Geophysical Research B: Solid Earth, v. 122, no. 10, p. 7789-7812, https://doi.org/10.1002/2017JB014343.","productDescription":"34 p.","startPage":"7789","endPage":"7812","ipdsId":"IP-086340","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469293,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1411224","text":"External Repository"},{"id":349506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63214111328125,\n 45.94160076422081\n ],\n [\n -121.77246093750001,\n 45.94160076422081\n ],\n [\n -121.77246093750001,\n 46.494610770689384\n ],\n [\n -122.63214111328125,\n 46.494610770689384\n ],\n [\n -122.63214111328125,\n 45.94160076422081\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a90","contributors":{"authors":[{"text":"Wong, Ying-Qi","contributorId":200978,"corporation":false,"usgs":false,"family":"Wong","given":"Ying-Qi","email":"","affiliations":[],"preferred":false,"id":723991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Segall, Paul","contributorId":75942,"corporation":false,"usgs":true,"family":"Segall","given":"Paul","affiliations":[],"preferred":false,"id":723992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Andrew","contributorId":200980,"corporation":false,"usgs":false,"family":"Bradley","given":"Andrew","affiliations":[],"preferred":false,"id":723993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":723990,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194477,"text":"70194477 - 2017 - The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA)","interactions":[],"lastModifiedDate":"2018-11-19T11:34:54","indexId":"70194477","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA)","docAbstract":"Black shales of the Late Devonian to Early Mississippian Bakken Formation are characterized by high concentrations of organic carbon and the hyper-enrichment (> 500 to 1000s of mg/kg) of V and Zn. Deposition of black shales resulted from shallow seafloor depths that promoted rapid development of euxinic conditions. Vanadium hyper-enrichments, which are unknown in modern environments, are likely the result of very high levels of dissolved H2S (~ 10 mM) in bottom waters or sediments. Because modern hyper-enrichments of Zn are documented only in Framvaren Fjord (Norway), it is likely that the biogeochemical trigger responsible for Zn hyper-enrichment in Framvaren Fjord was also present in the Bakken basin. With Framvaren Fjord as an analogue, we propose a causal link between the activity of phototrophic sulfide oxidizing bacteria, related to the development of photic-zone euxinia, and the hyper-enrichment of Zn in black shales of the Bakken Formation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.01.026","usgsCitation":"Scott, C., Slack, J.F., and Kelley, K.D., 2017, The hyper-enrichment of V and Zn in black shales of the Late Devonian-Early Mississippian Bakken Formation (USA): Chemical Geology, v. 452, p. 24-33, https://doi.org/10.1016/j.chemgeo.2017.01.026.","productDescription":"10 p.","startPage":"24","endPage":"33","ipdsId":"IP-078833","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":461343,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2017.01.026","text":"Publisher Index Page"},{"id":349501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Manitoba, Montana, North Dakota, Saskatchewan, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 43\n ],\n [\n -96,\n 43\n ],\n [\n -96,\n 50\n ],\n [\n -108,\n 50\n ],\n [\n -108,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"452","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafce4b06e28e9c22a87","contributors":{"authors":[{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen Duttweiler 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":192758,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"Duttweiler","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":724014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194441,"text":"70194441 - 2017 - Conceptual model for invasive bivalve control on wetland productivity","interactions":[],"lastModifiedDate":"2017-11-30T10:09:17","indexId":"70194441","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5573,"text":"Interagency Ecological Program Technical Report","active":true,"publicationSubtype":{"id":4}},"seriesNumber":"91","title":"Conceptual model for invasive bivalve control on wetland productivity","docAbstract":"Tidal wetlands were the historically dominant features of many coastal regions around the world, including the San Francisco Estuary (Callaway et al. 2011; Whipple et al. 2012). These mosaics of varied interconnected habitats (Mitsch and Gosselink 1993) provide a host of ecosystem services, including biodiversity maintenance, fish and wildlife habitat, water quality improvement, flood abatement, and carbon sequestration (Rabenhorst 1995; Costanza et al. 1997; Bottom et al. 2005; Zedler and Kercher 2005; Barbier et al. 2010). They also support human activities and values such as recreation and aesthetic appreciation (Barbier et al. 2010; Milligan and Kraus-Polk 2016). Despite their critical functions, many wetland landscapes have been destroyed or irreparably altered, either incidentally or intentionally, by human activities (Holland et al. 2004; Zedler and Kercher 2005; Callaway et al. 2011; Cloern and Jassby 2012; Whipple et al. 2012; Schile et al. 2014).
San Francisco Estuary (SFE) (see Figure 1) tidal wetlands were largely converted to other land uses in the late 1800s and early 1900s, with the extent of loss and new use varying by region. Wetland losses in the North, Central, and South San Francisco bays and Suisun Bay ranged from 70 percent to 93 percent to accommodate agricultural uses, salt production, managed waterfowl habitat, and urban development (Callaway et al. 2011). Landscape transformation within the most inland portion of the SFE, the Sacramento-San Joaquin Delta (Delta), was even more dramatic. Overall, today’s Delta contains 97 percent less freshwater tidal wetland than its historical state and nearly double the open water area (Whipple et al. 2012). The majority of the modern Delta consists of agricultural tracts protected from tidal waters by human-made dikes or levees, which are commonly armored with riprap. The de-watered, rich peat soils of these created islands have supported abundant agricultural production, but have oxidized, compacted, and blown away in the process, causing significant subsidence (Deverel and Leighton 2010). Occasional levee failures turn islands into lakes; a few large shallow lakes remain after accidental levee breaches were not repaired (Whipple et al. 2012).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of tidal wetland restoration on fish: A suite of conceptual models","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Interagency Ecological Program","usgsCitation":"Hartman, R., Brown, L.R., Thompson, J.K., and Parchaso, F., 2017, Conceptual model for invasive bivalve control on wetland productivity: Interagency Ecological Program Technical Report 91, 34 p.","productDescription":"34 p.","startPage":"225","endPage":"258","ipdsId":"IP-084615","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":349521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349520,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.water.ca.gov/iep/docs/tech_rpts/TR91.Wetland_CM_2Nov2017.pdf"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Francisco Bay-Delta Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.2720947265625,\n 37.02886944696474\n ],\n [\n -121.124267578125,\n 37.02886944696474\n ],\n [\n -121.124267578125,\n 38.65119833229951\n ],\n [\n -123.2720947265625,\n 38.65119833229951\n ],\n [\n -123.2720947265625,\n 37.02886944696474\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fafde4b06e28e9c22a9b","contributors":{"authors":[{"text":"Hartman, Rosemary","contributorId":200388,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":723822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":723821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":723823,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193408,"text":"70193408 - 2017 - Concepts and practices: Estimating abundance of prey species using hierarchical model-based approaches","interactions":[],"lastModifiedDate":"2017-11-30T10:12:37","indexId":"70193408","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Concepts and practices: Estimating abundance of prey species using hierarchical model-based approaches","docAbstract":"Tigers predominantly prey on large ungulate species, such as sambar (Cervus unicolor), red deer (Cervus elaphus), gaur (Bos gaurus), banteng (Bos javanicus), chital (Axis axis), muntjac (Muntiacus muntjak), wild pig (Sus scrofa), and bearded pig (Sus barbatus). The density of a tiger population is strongly correlated with the density of such prey species (Karanth et al. 2004). In the absence of direct hunting of tigers, abundance of prey in an area is the key determinant of the “carrying capacity” of that area for tigers (Chap. 2). Accurate estimates of prey abundance are often needed to assess the potential number of tigers a conservation area can support.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods for monitoring tiger and prey populations","language":"English","publisher":"Springer","doi":"10.1007/978-981-10-5436-5_8","usgsCitation":"Dorazio, R., Kumar, N.S., Royle, A., and Gopalaswamy, A.M., 2017, Concepts and practices: Estimating abundance of prey species using hierarchical model-based approaches, chap. of Methods for monitoring tiger and prey populations, p. 137-162, https://doi.org/10.1007/978-981-10-5436-5_8.","productDescription":"26 p.","startPage":"137","endPage":"162","ipdsId":"IP-083542","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-28","publicationStatus":"PW","scienceBaseUri":"5a60fafee4b06e28e9c22ab2","contributors":{"authors":[{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":172151,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":718927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, N. Samba","contributorId":199393,"corporation":false,"usgs":false,"family":"Kumar","given":"N.","email":"","middleInitial":"Samba","affiliations":[],"preferred":false,"id":718928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":718929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gopalaswamy, Arjun M.","contributorId":199394,"corporation":false,"usgs":false,"family":"Gopalaswamy","given":"Arjun","email":"","middleInitial":"M.","affiliations":[{"id":20302,"text":"Univeristy of Oxford","active":true,"usgs":false},{"id":35775,"text":"Indian Statistical Institute, Bangalore, India","active":true,"usgs":false}],"preferred":false,"id":718930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194483,"text":"70194483 - 2017 - Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","interactions":[],"lastModifiedDate":"2022-04-22T16:02:15.153901","indexId":"70194483","displayToPublicDate":"2017-11-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States","docAbstract":"Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for ~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000–2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9121181","usgsCitation":"Reitz, M., Senay, G., and Sanford, W.E., 2017, Combining remote sensing and water-balance evapotranspiration estimates for the conterminous United States: Remote Sensing, v. 9, no. 12, 1181, 17 p.; Data release, https://doi.org/10.3390/rs9121181.","productDescription":"1181, 17 p.; Data release","ipdsId":"IP-090961","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469292,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9121181","text":"Publisher Index Page"},{"id":349568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397955,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC02FK","text":"USGS data 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Maryland and Virginia","docAbstract":"After Hurricane Sandy, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center conducted a seasonal collection of estuarine, marsh, and sandy overwash surface sediments from Chincoteague Bay, Tom’s Cove, and the surrounding Assateague Island and Delmarva Peninsula in March–April and October 2014. Surplus surface sediment was analyzed for metals, percent carbon and nitrogen, δ13C, and δ15N as part of a complementary U.S. Geological Survey Coastal and Marine Geology Program Sea-level and Storm Impacts on Estuarine Environments and Shorelines project study. The geochemical subsample analyzed for metals and stable isotopes at each site may be used for comparison with past data sets, to create a modern baseline of the natural distribution of the area, to understand seasonal variability as it relates to the health of the local environment, and to assess marsh-to-bay interactions. The use of metals, stable carbon, and stable nitrogen isotopes allows for a more cohesive snapshot of factors influencing the environment and could aid in tracking environmental change.
This report serves as an archive for chemical data derived from the surface sediment. Data are available for a seasonal comparison between the March–April 2014 and October 2014 sampling trips. Downloadable data are available as Microsoft Excel spreadsheets. These additional files include formal Federal Geographic Data Committee metadata (data downloads).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1059","usgsCitation":"Ellis, A.M., and Smith, C.G., 2017, A seasonal and spatial comparison of metals, and stable carbon and nitrogen isotopes, in Chincoteague Bay and the marsh deposits of Assateague Island and the adjacent vicinity, Maryland and Virginia: U.S. Geological Survey Data Series 1059, https://doi.org/10.3133/ds1059.","productDescription":"HMTL Document; Data Downloads","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077432","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":347967,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ds1060","text":"Data Series 1060","linkHelpText":"- Distribution of foraminifera in Chincoteague Bay and the marshes of Assateague Island and the adjacent vicinity, Maryland and Virginia"},{"id":347964,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1059/","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1059"},{"id":347963,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1059/coverthb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Assateague Island, Chincoteague Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.42388916015625,\n 37.82931081282506\n ],\n [\n -75.0311279296875,\n 37.82931081282506\n ],\n [\n -75.0311279296875,\n 38.43422817624596\n ],\n [\n -75.42388916015625,\n 38.43422817624596\n ],\n [\n -75.42388916015625,\n 37.82931081282506\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701