Using Landsat satellite data, scientists with the U.S. Geological Survey have helped to refine a technique called evapotranspiration mapping to measure how much water crops are using across landscapes and through time. These water-use maps are created using a computer model that integrates Landsat and weather data.
Crucial to the process is the thermal (infrared) band from Landsat. Using the Landsat thermal band with its 100-meter resolution, water-use maps can be created at a scale detailed enough to show how much water crops are using at the level of individual fields anywhere in the world.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163037","collaboration":"Prepared in cooperation with the National Aeronautics and Space Administration","usgsCitation":"U.S. Geological Survey, 2016, Mapping water use—Landsat and water resources in the United States (ver. 1.1, September 2019): U.S. Geological Survey Fact Sheet 2016–3037, 2 p., https://doi.org/10.3133/fs20163037.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075235","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":367504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3037/fs20163037_2.pdf","text":"Report","size":"5.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3037"},{"id":324411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3037/coverthb2.jpg"},{"id":367505,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2016/3037/versionHist.txt","size":"1.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"edition":"Version 1.0: June 27, 2016; Version 1.1 September 18, 2019","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.advwatres.2015.09.001","usgsCitation":"Carr, J., D’Odorico, P., McGlathery, K., and Wiberg, P.L., 2016, Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth: Advances in Water Resources, v. 93, Part B, p. 315-325, https://doi.org/10.1016/j.advwatres.2015.09.001.","productDescription":"21 p.","startPage":"315","endPage":"325","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067162","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2015.09.001","text":"Publisher Index Page"},{"id":324539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324494,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S030917081500202X"}],"volume":"93, Part B","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb7e4b07657d1a90d66","contributors":{"authors":[{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":641019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Odorico, Paul","contributorId":172510,"corporation":false,"usgs":false,"family":"D’Odorico","given":"Paul","email":"","affiliations":[],"preferred":false,"id":641079,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGlathery, Karen","contributorId":36057,"corporation":false,"usgs":true,"family":"McGlathery","given":"Karen","affiliations":[],"preferred":false,"id":641080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wiberg, Patricia L.","contributorId":72716,"corporation":false,"usgs":true,"family":"Wiberg","given":"Patricia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":641081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178788,"text":"70178788 - 2016 - Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps","interactions":[],"lastModifiedDate":"2016-12-07T17:17:02","indexId":"70178788","displayToPublicDate":"2016-06-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps","docAbstract":"Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of “Decomposition Functional Types” (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with rigorous testing of analytical results; using point measurements and realistic forcing variables to constrain process-based models; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1380","usgsCitation":"Bond-Lamberty, B., Epron, D., Harden, J.W., Harmon, M.E., Hoffman, F., Kumar, J., McGuire, A.D., and Vargas, R., 2016, Estimating heterotrophic respiration at large scales: Challenges, approaches, and next steps: Ecosphere, v. 7, no. 6, Article e01380; 13 p., https://doi.org/10.1002/ecs2.1380.","productDescription":"Article e01380; 13 p.","ipdsId":"IP-070883","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1380","text":"Publisher Index Page"},{"id":331662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"58492df3e4b06d80b7b093a6","chorus":{"doi":"10.1002/ecs2.1380","url":"http://dx.doi.org/10.1002/ecs2.1380","publisher":"Wiley-Blackwell","authors":"Bond-Lamberty Ben, Epron Daniel, Harden Jennifer, Harmon Mark E., Hoffman Forrest, Kumar Jitendra, David McGuire Anthony, Vargas Rodrigo","journalName":"Ecosphere","publicationDate":"6/2016"},"contributors":{"authors":[{"text":"Bond-Lamberty, Ben","contributorId":172028,"corporation":false,"usgs":false,"family":"Bond-Lamberty","given":"Ben","email":"","affiliations":[{"id":33852,"text":"Univ of Maryland, College Park, MD","active":true,"usgs":false},{"id":13566,"text":"Joint Global Change Research Institute, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":655178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Epron, Daniel","contributorId":177277,"corporation":false,"usgs":false,"family":"Epron","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":655179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":655180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harmon, Mark E.","contributorId":96961,"corporation":false,"usgs":true,"family":"Harmon","given":"Mark","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Forrest","contributorId":177278,"corporation":false,"usgs":false,"family":"Hoffman","given":"Forrest","email":"","affiliations":[],"preferred":false,"id":655132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Jitendra","contributorId":177279,"corporation":false,"usgs":false,"family":"Kumar","given":"Jitendra","email":"","affiliations":[],"preferred":false,"id":655182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, Anthony D. 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":2493,"corporation":false,"usgs":true,"family":"McGuire","given":"Anthony","email":"ffadm@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":655183,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vargas, Rodrigo","contributorId":172036,"corporation":false,"usgs":false,"family":"Vargas","given":"Rodrigo","affiliations":[],"preferred":false,"id":655184,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174329,"text":"70174329 - 2016 - Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.","interactions":[],"lastModifiedDate":"2016-07-08T11:45:45","indexId":"70174329","displayToPublicDate":"2016-06-26T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2884,"text":"North American Fauna","active":true,"publicationSubtype":{"id":10}},"title":"Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.","docAbstract":"Spectacled eider Somateria fischeri numbers have declined and they are considered threatened in accordance with the US Endangered Species Act throughout their range. We synthesized the available information for spectacled eiders to construct deterministic, stochastic, and metapopulation models for this species that incorporated current estimates of vital rates such as nest success, adult survival, and the impact of lead poisoning on survival. Elasticities of our deterministic models suggested that the populations would respond most dramatically to changes in adult female survival and that the reductions in adult female survival related to lead poisoning were locally important. We also examined the sensitivity of the population to changes in lead exposure rates. With the knowledge that some vital rates vary with environmental conditions, we cast stochastic models that mimicked observed variation in productivity. We also used the stochastic model to examine the probability that a specific population will persist for periods of up to 50 y. Elasticity analysis of these models was consistent with that for the deterministic models, with perturbations to adult female survival having the greatest effect on population projections. When used in single population models, demographic data for some localities predicted rapid declines that were inconsistent with our observations in the field. Thus, we constructed a metapopulation model and examined the predictions for local subpopulations and the metapopulation over a wide range of dispersal rates. Using the metapopulation model, we were able to simulate the observed stability of local subpopulations as well as that of the metapopulation. Finally, we developed a global metapopulation model that simulates periodic winter habitat limitation, similar to that which might be experienced in years of heavy sea ice in the core wintering area of spectacled eiders in the central Bering Sea. Our metapopulation analyses suggested that no subpopulation is independent and that future management actions may be improved through a metapopulation framework. For example, management actions could include displacement of breeding females from\"sink\" areas that reduce the growth potential of the population as a whole. However, this action is contingent upon dispersal among local populations, for which there is limited information. Thus, we recommend that researchers examine dispersal behavior among areas on the Yukon-Kuskokwim Delta in western Alaska. The metapopulation framework could also be applied at the rangewide scale to address the density-dependent limitation of available polynya habitat during winter that may limit the recovery of small subpopulations, such as that on the Yukon-Kuskokwim Delta. Reductions in other subpopulations may be necessary to ensure an increase in the Yukon-Kuskokwim Delta population. Thus, we recommend that managers consider the interpopulation dynamics of spectacled eiders at different spatial scales in future management actions.
","language":"English","doi":"10.3996/nafa.81.0001","usgsCitation":"Flint, P.L., Grand, J.B., Petersen, M.R., and Rockwell, R.F., 2016, Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.: North American Fauna, v. 81, p. 1-41, https://doi.org/10.3996/nafa.81.0001.","productDescription":"iii, 44 p.","startPage":"1","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057251","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470842,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/nafa.81.0001","text":"Publisher Index Page"},{"id":438607,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74B2ZCK","text":"USGS data release","linkHelpText":"Spectacled Eider (Somateria fischeri) Nest, Capture, and Resight Records Yukon-Kuskokwim Delta, Alaska"},{"id":324910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.85546875,\n 59.80063426102869\n ],\n [\n -145.283203125,\n 60.02095215374802\n ],\n [\n -146.25,\n 60.02095215374802\n ],\n [\n -147.744140625,\n 59.57885104663186\n ],\n [\n -150.205078125,\n 59.0405546167585\n ],\n [\n -151.435546875,\n 57.32652122521709\n ],\n [\n -153.45703125,\n 56.26776108757582\n ],\n [\n -163.65234374999997,\n 52.482780222078205\n ],\n [\n -177.36328125,\n 50.064191736659104\n ],\n [\n -186.15234374999997,\n 50.12057809796008\n ],\n [\n -195.64453125,\n 54.67383096593114\n ],\n [\n -196.5234375,\n 57.938183012205315\n ],\n [\n -202.060546875,\n 62.471723714758724\n ],\n [\n -222.626953125,\n 72.18180355624855\n ],\n [\n -228.69140625,\n 75.67219739055291\n ],\n [\n -228.603515625,\n 76.51681887717322\n ],\n [\n -219.375,\n 77.13761179723426\n ],\n [\n -210.76171875,\n 77.19617635994676\n ],\n [\n -195.64453125,\n 77.2156395545647\n ],\n [\n -179.912109375,\n 76.78065491639973\n ],\n [\n -162.0703125,\n 75.47513069090051\n ],\n [\n -149.23828125,\n 74.18805166460048\n ],\n [\n -140.888671875,\n 69.7485511291223\n ],\n [\n -141.85546875,\n 59.80063426102869\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-22","publicationStatus":"PW","scienceBaseUri":"5780ceb6e4b0811616822315","contributors":{"authors":[{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":641925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grand, J. 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S. alterniflora is a foundation species, whose loss decreases ecosystem services and potentiates ecosystem state change. Long-term records of the potential environmental drivers of dieback such as precipitation and tidal inundation did not evidence any particular anomalies, although Hurricane Isabel in fall 2003 may have been related to dieback. Transects were established across the interface between the dieback area and apparently healthy areas of marsh. Plant condition was classified based on ground cover within transects as dieback, intermediate and healthy. Numerous characteristics of S. alterniflora culms within each condition class were assessed including biomass, morphology and spectral attributes associated with photosynthetic pigments. Plants demonstrated evidence of stress in 2004 and 2005 beyond areas of obvious dieback and resilience at a multi-year scale. Resilience of the plants was evident in recovery of ground cover and biomass largely within 3 y, although a small remnant of dieback persisted for 8 y. Culms surviving within the dieback and areas of intermediate impact had modified morphological traits and spectral response that reflected stress. These morphometric and spectral differences among plant cover condition classes serve as guidelines for monitoring of dieback initiation, effects and subsequent recovery. Although a number of environmental and biotic parameters were assessed relative to causation, the reason for this particular dieback remains largely unknown, however.
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III 0000-0002-4518-5796 ramseye@usgs.gov","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":2883,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah","suffix":"III","email":"ramseye@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":648002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":648006,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175641,"text":"70175641 - 2016 - Elucidation of taste- and odor-producing bacteria and toxigenic cyanobacteria in a Midwestern drinking water supply reservoir by shotgun metagenomics analysis","interactions":[],"lastModifiedDate":"2016-08-18T09:29:57","indexId":"70175641","displayToPublicDate":"2016-06-24T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Elucidation of taste- and odor-producing bacteria and toxigenic cyanobacteria in a Midwestern drinking water supply reservoir by shotgun metagenomics analysis","docAbstract":"While commonplace in clinical settings, DNA-based assays for identification or enumeration of drinking water pathogens and other biological contaminants remain widely unadopted by the monitoring community. In this study, shotgun metagenomics was used to identify taste-and-odor producers and toxin-producing cyanobacteria over a 2-year period in a drinking water reservoir. The sequencing data implicated several cyanobacteria, including Anabaena spp.,Microcystis spp., and an unresolved member of the order Oscillatoriales as the likely principal producers of geosmin, microcystin, and 2-methylisoborneol (MIB), respectively. To further demonstrate this, quantitative PCR (qPCR) assays targeting geosmin-producing Anabaena and microcystin-producing Microcystis were utilized, and these data were fitted using generalized linear models and compared with routine monitoring data, including microscopic cell counts, sonde-based physicochemical analyses, and assays of all inorganic and organic nitrogen and phosphorus forms and fractions. The qPCR assays explained the greatest variation in observed geosmin (adjusted R2 = 0.71) and microcystin (adjusted R2 = 0.84) concentrations over the study period, highlighting their potential for routine monitoring applications. The origin of the monoterpene cyclase required for MIB biosynthesis was putatively linked to a periphytic cyanobacterial mat attached to the concrete drinking water inflow structure. We conclude that shotgun metagenomics can be used to identify microbial agents involved in water quality deterioration and to guide PCR assay selection or design for routine monitoring purposes. Finally, we offer estimates of microbial diversity and metagenomic coverage of our data sets for reference to others wishing to apply shotgun metagenomics to other lacustrine systems.
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2016 - Assessing wildlife benefits and carbon storage from restored and natural coastal marshes in the Nisqually River Delta: Determining marsh net ecosystem carbon balance","interactions":[],"lastModifiedDate":"2016-07-07T14:50:33","indexId":"fs20163042","displayToPublicDate":"2016-06-24T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3042","title":"Assessing wildlife benefits and carbon storage from restored and natural coastal marshes in the Nisqually River Delta: Determining marsh net ecosystem carbon balance","docAbstract":"Working in partnership since 1996, the U.S. Fish and Wildlife Service and the Nisqually Indian Tribe have restored 902 acres of tidally influenced coastal marsh in the Nisqually River Delta (NRD), making it the largest estuary-restoration project in the Pacific Northwest to date. Marsh restoration increases the capacity of the estuary to support a diversity of wildlife species. Restoration also increases carbon (C) production of marsh plant communities that support food webs for wildlife and can help mitigate climate change through long-term C storage in marsh soils.
In 2015, an interdisciplinary team of U.S. Geological Survey (USGS) researchers began to study the benefits of carbon for wetland wildlife and storage in the NRD. Our primary goals are (1) to identify the relative importance of the different carbon sources that support juvenile chinook (Oncorhynchus tshawytscha) food webs and contribute to current and historic peat formation, (2) to determine the net ecosystem carbon balance (NECB) in a reference marsh and a restoration marsh site, and (3) to model the sustainability of the reference and restoration marshes under projected sea-level rise conditions along with historical vegetation change. In this fact sheet, we focus on the main C sources and exchanges to determine NECB, including carbon dioxide (CO2) uptake through plant photosynthesis, the loss of CO2 through plant and soil respiration, emissions of methane (CH4), and the lateral movement or leaching loss of C in tidal waters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163042","collaboration":"Prepared in cooperation with the U.S.G.S. Land Carbon Program and the U.S. Fish and Wildlife Service","usgsCitation":"Anderson, Frank, 2016, Assessing wildlife benefits and carbon from restored and natural coastal marshes in the Nisqually River delta: Determining marsh net ecosystem carbon balance: U.S. Geological Survey Fact Sheet 2016-3042, 2 p., https://dx.doi.org/10.3133/fs20163042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065411","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3042/coverthb.jpg"},{"id":324376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3042/fs20163042.pdf","text":"Report","size":"898 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3042"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73977279663085,\n 47.066497210333836\n ],\n [\n -122.73977279663085,\n 47.1214245689578\n ],\n [\n -122.66733169555663,\n 47.1214245689578\n ],\n [\n -122.66733169555663,\n 47.066497210333836\n ],\n [\n -122.73977279663085,\n 47.066497210333836\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.
","language":"English","publisher":"Taylor and Francis Group","doi":"10.1080/07011784.2016.1178601","collaboration":"International Joint Commission","usgsCitation":"Benoy, G.A., Jenkinson, R., Robertson, D.M., and Saad, D.A., 2016, Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model: Canadian Water Resources Journal, v. 41, no. 3, p. 429-447, https://doi.org/10.1080/07011784.2016.1178601.","productDescription":"19 p.","startPage":"429","endPage":"447","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068514","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":324322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324318,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1080/07011784.2016.1178601"}],"country":"Canada, United States","state":"Manitoba, Minnesota, Saskatchewan","otherGeospatial":"Assiniboine River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.152099609375,\n 50.064191736659104\n ],\n [\n -98.009033203125,\n 50.2612538275847\n ],\n [\n -99.47021484375,\n 50.162824333817284\n ],\n [\n -102.469482421875,\n 51.248163159055906\n ],\n [\n -104.8974609375,\n 50.597186230587035\n ],\n [\n -103.853759765625,\n 49.1888842152458\n ],\n [\n -101.898193359375,\n 48.04870994288686\n ],\n [\n -99.41528320312499,\n 48.268569112964336\n ],\n [\n -97.152099609375,\n 50.064191736659104\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-20","publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c62","contributors":{"authors":[{"text":"Benoy, Glenn A. 0000-0001-6530-7220","orcid":"https://orcid.org/0000-0001-6530-7220","contributorId":172405,"corporation":false,"usgs":false,"family":"Benoy","given":"Glenn","email":"","middleInitial":"A.","affiliations":[{"id":13361,"text":"International Joint Commission, Washington DC","active":true,"usgs":false}],"preferred":false,"id":640604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkinson, R. 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Wild waterfowl (family Anatidae), are reported as secondary transmitters of HPAIV, and primary reservoirs for low-pathogenic avian influenza viruses, yet spatial inputs for disease risk modeling for this group have been lacking. Using GIS and Monte Carlo simulations, we developed geospatial indices of waterfowl abundance at 1 and 30 km resolutions and for the breeding and wintering seasons for China, the epicenter of H5N1. Two spatial layers were developed: cumulative waterfowl abundance (WAB), a measure of predicted abundance across species, and cumulative abundance weighted by H5N1 prevalence (WPR), whereby abundance for each species was adjusted based on prevalence values then totaled across species. Spatial patterns of the model output differed between seasons, with higher WAB and WPR in the northern and western regions of China for the breeding season and in the southeast for the wintering season. Uncertainty measures indicated highest error in southeastern China for both WAB and WPR. We also explored the effect of resampling waterfowl layers from 1 km to 30 km resolution for multi-scale risk modeling. Results indicated low average difference (less than 0.16 and 0.01 standard deviations for WAB and WPR, respectively), with greatest differences in the north for the breeding season and southeast for the wintering season. This work provides the first geospatial models of waterfowl abundance available for China. The indices provide important inputs for modeling disease transmission risk at the interface of poultry and wild birds. These models are easily adaptable, have broad utility to both disease and conservation needs, and will be available to the scientific community for advanced modeling applications.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11125-050615-Reg","usgsCitation":"Prosser, D.J., Hungerford, L.L., Erwin, R.M., Ottinger, M.A., Takekawa, J.Y., Newman, S.H., Xiao, X., and Ellis, E.C., 2016, Spatial modeling of wild bird risk factors to investigate highly pathogenic A(H5N1) avian influenza virus transmission: Avian Diseases, v. 60, no. 1s, p. 329-336, https://doi.org/10.1637/11125-050615-Reg.","productDescription":"8 p.","startPage":"329","endPage":"336","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071327","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":438608,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B6ZDUR","text":"USGS data release","linkHelpText":"Spatial Models of Wild Bird Risk Factors for Highly Pathogenic A(H5N1) Avian Influenza Virus Transmission"},{"id":324325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c66","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":640624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hungerford, Laura L.","contributorId":14291,"corporation":false,"usgs":true,"family":"Hungerford","given":"Laura","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":640625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, R. 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We conducted a Bayesian analysis of historical (1951–2011) band-recovery data throughout North America to estimate annual survival and recovery rates for juvenile and adult male and female lesser scaup to determine if increasing harvest or declining survival rates have contributed to population changes and to determine if harvest has been primarily additive or compensatory. Annual recovery rates were low, ranging from 1% to 4% for adults and 2% to 10% for juveniles during most years, with trend models indicating that recovery rates have declined through time for all age–sex classes. Annual survival (mid-Aug to mid-Aug) averaged 0.402 (σ ̂ 0.043) for juvenile males, 0.416 (σ ̂ 0.067) for juvenile females, 0.689 (σ ̂ 0.109) for adult males, and 0.602 (σ ̂ 0.115) for adult females, where σ ̂ represents an estimate of annual process variation in each survival rate. Annual survival rates exhibited no evidence of long-term declines or negative correlations with annual recovery rates (i.e., an index of harvest intensity) for any age–sex class, suggesting that declining fecundity was the most likely explanation for population declines during 1975–2005. We conclude that hunting mortality played a minor role in affecting population dynamics of lesser scaup and waterfowl managers could take a less cautious approach in managing harvest, especially if recruiting or maintaining waterfowl hunters are viewed as important management objectives.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21074","usgsCitation":"Arnold, T.W., Afton, A.D., Anteau, M.J., Koons, D.N., and Nicolai, C., 2016, Temporal variation in survival and recovery rates of lesser scaup: Journal of Wildlife Management, v. 80, no. 5, p. 850-861, https://doi.org/10.1002/jwmg.21074.","productDescription":"12 p.","startPage":"850","endPage":"861","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071708","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-13","publicationStatus":"PW","scienceBaseUri":"576cfa1de4b07657d1a33c68","contributors":{"authors":[{"text":"Arnold, Todd W.","contributorId":36058,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd","email":"","middleInitial":"W.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":640563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":640564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":640562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koons, David N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":640565,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nicolai, Chris","contributorId":169592,"corporation":false,"usgs":true,"family":"Nicolai","given":"Chris","affiliations":[],"preferred":false,"id":640566,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174020,"text":"70174020 - 2016 - Waterbird nest-site selection is influenced by neighboring nests and island topography","interactions":[],"lastModifiedDate":"2017-12-13T17:45:48","indexId":"70174020","displayToPublicDate":"2016-06-23T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Waterbird nest-site selection is influenced by neighboring nests and island topography","docAbstract":"Avian nest-site selection is influenced by factors operating across multiple spatial scales. Identifying preferred physical characteristics (e.g., topography, vegetation structure) can inform managers to improve nesting habitat suitability. However, social factors (e.g., attraction, territoriality, competition) can complicate understanding physical characteristics preferred by nesting birds. We simultaneously evaluated the physical characteristics and social factors influencing selection of island nest sites by colonial-nesting American avocets (Recurvirostra americana) and Forster's terns (Sterna forsteri) at 2 spatial scales in San Francisco Bay, 2011–2012. At the larger island plot (1 m2) scale, we used real-time kinematics to produce detailed topographies of nesting islands and map the distribution of nests. Nesting probability was greatest in island plots between 0.5 m and 1.5 m above the water surface, at distances <10 m from the water's edge, and of moderately steep (avocets) or flat (terns) slopes. Further, avocet and tern nesting probability increased as the number of nests initiated in adjacent plots increased up to a peak of 11–12 tern nests, and then decreased thereafter. Yet, avocets were less likely to nest in plots adjacent to plots with nesting avocets, suggesting an influence of intra-specific territoriality. At the smaller microhabitat scale, or the area immediately surrounding the nest, we compared topography, vegetation, and distance to nearest nest between nest sites and paired random sites. Topography had little influence on selection of the nest microhabitat. Instead, nest sites were more likely to have vegetation present, and greater cover, than random sites. Finally, avocet, and to a lesser extent tern, nest sites were closer to other active conspecific or heterospecific nests than random sites, indicating that social attraction played a role in selection of nest microhabitat. Our results demonstrate key differences in nest-site selection between co-occurring avocets and terns, and indicate the effects of physical characteristics and social factors on selection of nesting habitat are dependent on the spatial scale examined. Moreover, these results indicate that islands with abundant area between 0.5 m and 1.5 m above the water surface, within 10 m of the water's edge, and containing a mosaic of slopes ranging from flat to moderately steep would provide preferred nesting habitat for avocets and terns. © 2016 The Wildlife Society.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21105","usgsCitation":"Hartman, C.A., Ackerman, J., Takekawa, J.Y., and Herzog, M.P., 2016, Waterbird nest-site selection is influenced by neighboring nests and island topography: Journal of Wildlife Management, v. 80, no. 7, p. 1267-1279, https://doi.org/10.1002/jwmg.21105.","productDescription":"13 p.","startPage":"1267","endPage":"1279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062454","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11235046386717,\n 37.56362983491151\n ],\n [\n -122.06153869628906,\n 37.57070524233116\n ],\n [\n -122.01828002929686,\n 37.50155517264162\n ],\n [\n -121.95991516113283,\n 37.51027052249435\n ],\n [\n -121.91734313964844,\n 37.45687303762862\n ],\n [\n -121.99493408203125,\n 37.41816326969145\n ],\n [\n -122.10617065429688,\n 37.43179575348695\n ],\n [\n -122.11235046386717,\n 37.56362983491151\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-10","publicationStatus":"PW","scienceBaseUri":"576cfa1ee4b07657d1a33c6c","contributors":{"authors":[{"text":"Hartman, C. 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Varying effects of tree species identity and diversity on the richness of understory taxa","interactions":[],"lastModifiedDate":"2016-09-06T13:56:47","indexId":"70174016","displayToPublicDate":"2016-06-22T17:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Do the rich get richer? Varying effects of tree species identity and diversity on the richness of understory taxa","docAbstract":"Understory herbs and soil invertebrates play key roles in soil formation and nutrient cycling in forests. Studies suggest that diversity in the canopy and in the understory are positively associated, but these studies often confound the effects of tree species diversity with those of tree species identity and abiotic conditions. We combined extensive field sampling with structural equation modeling to evaluate the simultaneous effects of tree diversity on the species diversity of understory herbs, beetles, and earthworms. The diversity of earthworms and saproxylic beetles was directly and positively associated with tree diversity, presumably because species of both these taxa specialize on certain species of trees. Tree identity also strongly affected diversity in the understory, especially for herbs, likely as a result of interspecific differences in canopy light transmittance or litter decomposition rates. Our results suggest that changes in forest management will disproportionately affect certain understory taxa. For instance, changes in canopy diversity will affect the diversity of earthworms and saproxylic beetles more than changes in tree species composition, whereas the converse would be expected for understory herbs and detritivorous beetles. We conclude that the effects of tree diversity on understory taxa can vary from positive to negative and may affect biogeochemical cycling in temperate forests. Thus, maintaining high diversity in temperate forests can promote the diversity of multiple taxa in the understory.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1479","usgsCitation":"Champagne, J., Paine, C.E., Schoolmaster, D., Stejskal, R., Volarik, D., Šebesta, J., Trnka, F., Koutecky, T., Svarc, P., Svatek, M., Hector, A., and Matula, R., 2016, Do the rich get richer? Varying effects of tree species identity and diversity on the richness of understory taxa: Ecology, v. 97, no. 9, p. 2364-2373, https://doi.org/10.1002/ecy.1479.","productDescription":"10 p.","startPage":"2364","endPage":"2373","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074725","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470853,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://ora.ox.ac.uk/objects/uuid:703b7926-4947-4236-b4a8-97c48a6a1bfc","text":"External Repository"},{"id":324279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"9","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576ba89de4b07657d1a1766a","contributors":{"authors":[{"text":"Champagne, Juilette","contributorId":172369,"corporation":false,"usgs":false,"family":"Champagne","given":"Juilette","email":"","affiliations":[{"id":27025,"text":"1 Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":640468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paine, C. E. Timothy","contributorId":172370,"corporation":false,"usgs":false,"family":"Paine","given":"C.","email":"","middleInitial":"E. Timothy","affiliations":[{"id":27026,"text":"Biological and Environmental Sciences, University of Stirling, Stirling, FK9 4LA, UK","active":true,"usgs":false}],"preferred":false,"id":640469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":640467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stejskal, Robert","contributorId":172371,"corporation":false,"usgs":false,"family":"Stejskal","given":"Robert","email":"","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Volarik, Daniel","contributorId":172372,"corporation":false,"usgs":false,"family":"Volarik","given":"Daniel","email":"","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Šebesta, Jan","contributorId":172373,"corporation":false,"usgs":false,"family":"Šebesta","given":"Jan","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640472,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trnka, Filip","contributorId":172374,"corporation":false,"usgs":false,"family":"Trnka","given":"Filip","email":"","affiliations":[{"id":27028,"text":"Department of Ecology & Environmental Sciences, Faculty of Science, Palacký University Olomouc, Šlechtitelů 27, CZ-783 71 Olomouc, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640473,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koutecky, Tomas","contributorId":172375,"corporation":false,"usgs":false,"family":"Koutecky","given":"Tomas","email":"","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Svarc, Petr","contributorId":172376,"corporation":false,"usgs":false,"family":"Svarc","given":"Petr","email":"","affiliations":[{"id":27029,"text":"Department of Forest Protection and Wildlife Management, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640475,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Svatek, Martin","contributorId":172377,"corporation":false,"usgs":false,"family":"Svatek","given":"Martin","email":"","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640476,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hector, Andy","contributorId":102620,"corporation":false,"usgs":true,"family":"Hector","given":"Andy","email":"","affiliations":[],"preferred":false,"id":640477,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Matula, Radim","contributorId":172378,"corporation":false,"usgs":false,"family":"Matula","given":"Radim","email":"","affiliations":[{"id":27027,"text":"Department of Forest Botany, Dendrology and Geobiocoenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, 613 00 Brno, Czech Republic","active":true,"usgs":false}],"preferred":false,"id":640478,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70174013,"text":"70174013 - 2016 - Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin","interactions":[],"lastModifiedDate":"2018-03-15T10:26:40","indexId":"70174013","displayToPublicDate":"2016-06-22T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin","docAbstract":"Despite progress in the implementation of conservation practices, related improvements in water quality have been challenging to measure in larger river systems. In this paper we quantify these downstream effects by applying the empirical U.S. Geological Survey water-quality model SPARROW to investigate whether spatial differences in conservation intensity were statistically correlated with variations in nutrient loads. In contrast to other forms of water quality data analysis, the application of SPARROW controls for confounding factors such as hydrologic variability, multiple sources and environmental processes. A measure of conservation intensity was derived from the USDA-CEAP regional assessment of the Upper Mississippi River and used as an explanatory variable in a model of the Upper Midwest. The spatial pattern of conservation intensity was negatively correlated (p = 0.003) with the total nitrogen loads in streams in the basin. Total phosphorus loads were weakly negatively correlated with conservation (p = 0.25). Regional nitrogen reductions were estimated to range from 5 to 34% and phosphorus reductions from 1 to 10% in major river basins of the Upper Mississippi region. The statistical associations between conservation and nutrient loads are consistent with hydrological and biogeochemical processes such as denitrification. The results provide empirical evidence at the regional scale that conservation practices have had a larger statistically detectable effect on nitrogen than on phosphorus loadings in streams and rivers of the Upper Mississippi Basin.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5b03543","usgsCitation":"Garcia, A.M., Alexander, R.B., Arnold, J.G., Norfleet, L., White, M.J., Robertson, D.M., and Schwarz, G., 2016, Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin: Environmental Science & Technology, v. 50, no. 13, p. 6991-7000, https://doi.org/10.1021/acs.est.5b03543.","productDescription":"10 p.","startPage":"6991","endPage":"7000","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067273","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470859,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5b03543","text":"Publisher Index Page"},{"id":324247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"576ba89fe4b07657d1a17688","chorus":{"doi":"10.1021/acs.est.5b03543","url":"http://dx.doi.org/10.1021/acs.est.5b03543","publisher":"American Chemical Society (ACS)","authors":"García Ana María, Alexander Richard B., Arnold Jeffrey G., Norfleet Lee, White Michael J., Robertson Dale M., Schwarz Gregory","journalName":"Environmental Science & Technology","publicationDate":"7/5/2016","auditedOn":"6/23/2016","publiclyAccessibleDate":"6/21/2016"},"contributors":{"authors":[{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":640415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Jeffrey G.","contributorId":172345,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":640417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Norfleet, Lee","contributorId":172346,"corporation":false,"usgs":false,"family":"Norfleet","given":"Lee","email":"","affiliations":[{"id":24598,"text":"USDA-NRCS retired","active":true,"usgs":false}],"preferred":false,"id":640418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Michael J.","contributorId":172348,"corporation":false,"usgs":false,"family":"White","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":640425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":640419,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173781,"text":"70173781 - 2016 - Resource waves: phenological diversity enhances foraging opportunities for mobile consumers","interactions":[],"lastModifiedDate":"2016-06-22T14:42:08","indexId":"70173781","displayToPublicDate":"2016-06-22T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Resource waves: phenological diversity enhances foraging opportunities for mobile consumers","docAbstract":"Time can be a limiting constraint for consumers, particularly when resource phenology mediates foraging opportunity. Though a large body of research has explored how resource phenology influences trophic interactions, this work has focused on the topics of trophic mismatch or predator swamping, which typically occur over short periods, at small spatial extents or coarse resolutions. In contrast many consumers integrate across landscape heterogeneity in resource phenology, moving to track ephemeral food sources that propagate across space as resource waves. Here we provide a conceptual framework to advance the study of phenological diversity and resource waves. We define resource waves, review evidence of their importance in recent case studies, and demonstrate their broader ecological significance with a simulation model. We found that consumers ranging from fig wasps (Chalcidoidea) to grizzly bears (Ursus arctos) exploit resource waves, integrating across phenological diversity to make resource aggregates available for much longer than their component parts. In model simulations, phenological diversity was often more important to consumer energy gain than resource abundance per se. Current ecosystem-based management assumes that species abundance mediates the strength of trophic interactions. Our results challenge this assumption and highlight new opportunities for conservation and management. Resource waves are an emergent property of consumer–resource interactions and are broadly significant in ecology and conservation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0554.1","usgsCitation":"Armstrong, J., Takimoto, G., Schindler, D.E., Hayes, M.M., and Kauffman, M., 2016, Resource waves: phenological diversity enhances foraging opportunities for mobile consumers: Ecology, v. 97, no. 5, p. 1099-1112, https://doi.org/10.1890/15-0554.1.","productDescription":"14 p.","startPage":"1099","endPage":"1112","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061213","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"576ba89fe4b07657d1a17693","contributors":{"authors":[{"text":"Armstrong, Jonathan B.","contributorId":98567,"corporation":false,"usgs":true,"family":"Armstrong","given":"Jonathan B.","affiliations":[],"preferred":false,"id":640406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Takimoto, Gaku","contributorId":172343,"corporation":false,"usgs":false,"family":"Takimoto","given":"Gaku","email":"","affiliations":[],"preferred":false,"id":640407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schindler, Daniel E.","contributorId":83485,"corporation":false,"usgs":true,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":640408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Matthew M.","contributorId":172344,"corporation":false,"usgs":false,"family":"Hayes","given":"Matthew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauffman, Matthew mkauffman@usgs.gov","contributorId":171443,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":638166,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175112,"text":"70175112 - 2016 - Aftershocks of the 2014 South Napa, California, Earthquake: Complex faulting on secondary faults","interactions":[],"lastModifiedDate":"2016-07-29T15:11:33","indexId":"70175112","displayToPublicDate":"2016-06-22T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Aftershocks of the 2014 South Napa, California, Earthquake: Complex faulting on secondary faults","docAbstract":"We investigate the aftershock sequence of the 2014 MW6.0 South Napa, California, earthquake. Low-magnitude aftershocks missing from the network catalog are detected by applying a matched-filter approach to continuous seismic data, with the catalog earthquakes serving as the waveform templates. We measure precise differential arrival times between events, which we use for double-difference event relocation in a 3D seismic velocity model. Most aftershocks are deeper than the mainshock slip, and most occur west of the mapped surface rupture. While the mainshock coseismic and postseismic slip appears to have occurred on the near-vertical, strike-slip West Napa fault, many of the aftershocks occur in a complex zone of secondary faulting. Earthquake locations in the main aftershock zone, near the mainshock hypocenter, delineate multiple dipping secondary faults. Composite focal mechanisms indicate strike-slip and oblique-reverse faulting on the secondary features. The secondary faults were moved towards failure by Coulomb stress changes from the mainshock slip. Clusters of aftershocks north and south of the main aftershock zone exhibit vertical strike-slip faulting more consistent with the West Napa Fault. The northern aftershocks correspond to the area of largest mainshock coseismic slip, while the main aftershock zone is adjacent to the fault area that has primarily slipped postseismically. Unlike most creeping faults, the zone of postseismic slip does not appear to contain embedded stick-slip patches that would have produced on-fault aftershocks. The lack of stick-slip patches along this portion of the fault may contribute to the low productivity of the South Napa aftershock sequence.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150169","usgsCitation":"Hardebeck, J.L., and Shelly, D.R., 2016, Aftershocks of the 2014 South Napa, California, Earthquake: Complex faulting on secondary faults: Bulletin of the Seismological Society of America, v. 106, no. 3, p. 1100-1109, https://doi.org/10.1785/0120150169.","productDescription":"9 p.","startPage":"1100","endPage":"1109","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066544","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":325841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South Napa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.44125366210936,\n 38.45789034424927\n ],\n [\n -122.37533569335936,\n 38.38795699631398\n ],\n [\n -122.35198974609375,\n 38.329807044201374\n ],\n [\n -122.34924316406251,\n 38.26406296833964\n ],\n [\n -122.32177734375,\n 38.23278669950994\n ],\n [\n -122.25173950195311,\n 38.23925875585244\n ],\n [\n -122.23663330078124,\n 38.245730236135294\n ],\n [\n -122.24899291992188,\n 38.278078995562105\n ],\n [\n -122.23114013671875,\n 38.30071455572194\n ],\n [\n -122.23526000976561,\n 38.33088431959968\n ],\n [\n -122.29843139648436,\n 38.382574703770246\n ],\n [\n -122.33276367187499,\n 38.42131826945341\n ],\n [\n -122.35198974609375,\n 38.453588708941375\n ],\n [\n -122.40554809570311,\n 38.487994609214795\n ],\n [\n -122.44674682617188,\n 38.504116723098505\n ],\n [\n -122.46322631835938,\n 38.49229419236133\n ],\n [\n -122.44125366210936,\n 38.45789034424927\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"579c7e2ae4b0589fa1ca11c0","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":643959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":643960,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171468,"text":"70171468 - 2016 - Simulated impacts of climate change on phosphorus loading to Lake Michigan","interactions":[],"lastModifiedDate":"2016-06-22T15:07:51","indexId":"70171468","displayToPublicDate":"2016-06-22T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Simulated impacts of climate change on phosphorus loading to Lake Michigan","docAbstract":"Phosphorus (P) loading to the Great Lakes has caused various types of eutrophication problems. Future climatic changes may modify this loading because climatic models project changes in future meteorological conditions, especially for the key hydrologic driver — precipitation. Therefore, the goal of this study is to project how P loading may change from the range of projected climatic changes. To project the future response in P loading, the HydroSPARROW approach was developed that links results from two spatially explicit models, the SPAtially Referenced Regression on Watershed attributes (SPARROW) transport and fate watershed model and the water-quantity Precipitation Runoff Modeling System (PRMS). PRMS was used to project changes in streamflow throughout the Lake Michigan Basin using downscaled meteorological data from eight General Circulation Models (GCMs) subjected to three greenhouse gas emission scenarios. Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.
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dechrist@usgs.gov","orcid":"https://orcid.org/0000-0001-6108-2247","contributorId":366,"corporation":false,"usgs":true,"family":"Christiansen","given":"Daniel","email":"dechrist@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":631152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, David J","contributorId":169822,"corporation":false,"usgs":false,"family":"Lorenz","given":"David","email":"","middleInitial":"J","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":631153,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174177,"text":"70174177 - 2016 - Waterfowl populations are resilient to immediate and lagged impacts of wildfires in the boreal forest","interactions":[],"lastModifiedDate":"2016-06-28T14:47:47","indexId":"70174177","displayToPublicDate":"2016-06-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl populations are resilient to immediate and lagged impacts of wildfires in the boreal forest","docAbstract":"Summary 1. Wildfires are the principal disturbance in the boreal forest, and their size and frequency are increasing as the climate warms. Impacts of fires on boreal wildlife are largely unknown, especially for the tens of millions of waterfowl that breed in the region. This knowledge gap creates significant barriers to the integrative management of fires and waterfowl, leading to fire policies that largely disregard waterfowl. 2. Waterfowl populations across the western boreal forest of North America have been monitored annually since 1955 by the Waterfowl Breeding Population and Habitat Survey (BPOP), widely considered the most extensive wildlife survey in the world. Using these data, we examined impacts of forest fires on abundance of two waterfowl guilds – dabblers and divers. We modelled waterfowl abundance in relation to fire extent (i.e. amount of survey transect burned) and time since fire, examining both immediate and lagged fire impacts. 3. From 1955 to 2014, >1100 fires in the western boreal forest intersected BPOP survey transects, and many transects burned multiple times. Nonetheless, fires had no detectable impact on waterfowl abundance; annual transect counts of dabbler and diver pairs remained stable from the pre- to post-fire period. 4. The absence of fire impacts on waterfowl abundance extended from the years immediately following the fire to those more than a decade afterwards. Likewise, the amount of transect burned did not influence waterfowl abundance, with similar pair counts from the pre- to post-fire period for small (1–20% burned), medium (21–60%) and large (>60%) burns. 5. Policy implications. Waterfowl populations appear largely resilient to forest fires, providing initial evidence that current policies of limited fire suppression, which predominate throughout much of the boreal forest, have not been detrimental to waterfowl populations. Likewise, fire-related management actions, such as prescribed burning or targeted suppression, seem to have limited impacts on waterfowl abundance and productivity. For waterfowl managers, our results suggest that adaptive models of waterfowl harvest, which annually guide hunting quotas, do not need to emphasize fires when integrating climate change effects.
","language":"English","publisher":"British Ecological Society","publisherLocation":"London, United Kingdom","doi":"10.1111/1365-2664.12705","collaboration":"University of Alaska, Fairbanks","usgsCitation":"Lewis, T., Schmutz, J.A., Amundson, C.L., and Lindberg, M., 2016, Waterfowl populations are resilient to immediate and lagged impacts of wildfires in the boreal forest: Journal of Applied Ecology, v. 53, no. 3, 9 p., https://doi.org/10.1111/1365-2664.12705.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071371","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470863,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12705","text":"Publisher Index Page"},{"id":438609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RR1WBN","text":"USGS data release","linkHelpText":"Waterfowl Counts and Wildfire Burn Data from the Western Boreal Forest of North America, 1955-2014"},{"id":324532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324531,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1111/1365-2664.12705"}],"volume":"53","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"57739fb9e4b07657d1a90da4","chorus":{"doi":"10.1111/1365-2664.12705","url":"http://dx.doi.org/10.1111/1365-2664.12705","publisher":"Wiley-Blackwell","authors":"Lewis Tyler L., Schmutz Joel A., Amundson Courtney L., Lindberg Mark S.","journalName":"Journal of Applied Ecology","publicationDate":"6/21/2016"},"contributors":{"authors":[{"text":"Lewis, Tyler 0000-0002-4998-3031 tlewis@usgs.gov","orcid":"https://orcid.org/0000-0002-4998-3031","contributorId":169307,"corporation":false,"usgs":true,"family":"Lewis","given":"Tyler","email":"tlewis@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":641075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":641076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","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":641077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindberg, Mark S.","contributorId":89466,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":641078,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170976,"text":"sir20165061 - 2016 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015","interactions":[],"lastModifiedDate":"2016-06-22T09:37:57","indexId":"sir20165061","displayToPublicDate":"2016-06-22T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5061","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015","docAbstract":"Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 8 bridges at 7 highway crossings of the Missouri River in Kansas City, Missouri, from June 2 to 4, 2015. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches ranging from 1,640 to 1,660 feet longitudinally and extending laterally across the active channel from bank to bank during low to moderate flood flow conditions. These bathymetric surveys indicate the channel conditions at the time of the surveys and provide characteristics of scour holes that may be useful in the development of predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood flow comparison to help assess the bridges for stability and integrity issues with respect to bridge scour during floods.
\nBathymetric data were collected around every pier that was in water, except those at the edge of water or surrounded by a debris raft, and scour holes were observed at most surveyed piers. The observed scour holes at the surveyed bridges were examined with respect to shape and depth. Although exposure of parts of substructural support elements was observed at several piers, the exposure likely can be considered minimal compared to the overall substructure that remains buried in bed material at these piers.
\nThe frontal slope values determined for scour holes observed in the current (2015) study generally are similar to recommended values in the literature and values determined for scour holes in previous bathymetric surveys. Several of the structures had piers that were skewed to primary approach flow, and generally the scour hole was deeper and longer on the side of the pier with impinging flow, with some amount of deposition on the leeward side, typical of conditions observed at piers skewed to approach flow; however, at structure A7650 (site 10), the scour hole was deeper and longer on the leeward side of the pier, possibly because of a deflection and contraction of flow caused by a protrusion of the corresponding bank at the bridge.
\nPrevious bathymetric surveys exist for all the sites examined in this study. Comparisons between bathymetric surfaces from the previous surveys (in March 2010 and during the 2011 flood) and those of this study do not indicate any consistent correlation in channel-bed elevations with flow conditions. A simplified assumption of equal to lesser magnitude scour for the lower discharge in the 2015 surveys did not consistently prove to be true, particularly in respect to the depth of observed scour near the piers when compared to results collected during the 2011 flood.
\nA local spatial minimum average channel-bed elevation at structure A7650 (site 10) compared to adjacent sites may indicate this site is at or near a local feature that controls sediment deposition and scour. The average channel-bed elevation values and the distribution of channel-bed elevations imply that sediment unable to deposit near structure A7650 is flushed downstream and deposits at the next downstream site, structure A5817 (site 11).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165061","collaboration":"Prepared in cooperation with the Missouri Department of Transportation","usgsCitation":"Huizinga, R.J., 2016, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5061, 93 p., https://dx.doi.org/10.3133/sir20165061.","productDescription":"ix, 93 p.","startPage":"1","endPage":"93","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073946","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":324168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5061/sir20165061.pdf","text":"Report","size":"27.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5061"},{"id":324167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5061/coverthb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.7,\n 39.2\n ],\n [\n -94.7,\n 39\n ],\n [\n -94.3,\n 39\n ],\n [\n -94.3,\n 39.2\n ],\n [\n -94.7,\n 39.2\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
A rich legacy of geochemical data produced since the early 1960s covers the great expanse of Alaska; careful treatment of such data may provide significant and revealing geochemical maps that may be used for landscape geochemistry, mineral resource exploration, and geoenvironmental investigations over large areas. To maximize the spatial density and extent of data coverage for statewide mapping of element distributions, we compiled and integrated analyses of more than 175,000 sediment and soil samples from three major, separate sources: the U.S. Geological Survey, the National Uranium Resource Evaluation program, and the Alaska Division of Geological & Geophysical Surveys geochemical databases. Various types of heterogeneity and deficiencies in these data presented major challenges to our development of coherently integrated datasets for modeling and mapping of element distributions. Researchers from many different organizations and disparate scientific studies collected samples that were analyzed using highly variable methods throughout a time period of more than 50 years, during which many changes in analytical techniques were developed and applied. Despite these challenges, the U.S. Geological Survey has produced a new systematically integrated compilation of sediment and soil geochemical data with an average sample site density of approximately 1 locality per 10 square kilometers (km2) for the entire State of Alaska, although density varies considerably among different areas. From that compilation, we have modeled and mapped the distributions of 68 elements, thus creating an updated geochemical atlas for the State.
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\":{\"name\":\"Alaska\",\"nation\":\"USA \"}}]}","contact":"
Center Director
USGS Central Mineral and Environmental Resources Science Center
Box 25046, MS-973
Denver Federal Center
Denver, CO 80225-0046
http://minerals.cr.usgs.gov
Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process-based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.
","language":"English","publisher":"Alliance of Crop, Soil, and Environmental Science Societies","doi":"10.2136/vzj2016.01.0010","usgsCitation":"Walvoord, M.A., and Kurylyk, B.L., 2016, Hydrologic impacts of thawing permafrost—A review: Vadose Zone Journal, v. 15, no. 6, 20 p., https://doi.org/10.2136/vzj2016.01.0010.","productDescription":"20 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072731","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470869,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2016.01.0010","text":"Publisher Index Page"},{"id":324064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"576a571de4b07657d1a064db","contributors":{"authors":[{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":639756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurylyk, Barret L.","contributorId":78262,"corporation":false,"usgs":true,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":639757,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170058,"text":"sim3355 - 2016 - Changes between early development (1930–60) and recent (2005–15) groundwater-level altitudes and dissolved-solids and nitrate concentrations In and near Gaines, Terry, and Yoakum Counties, Texas","interactions":[],"lastModifiedDate":"2016-06-27T10:13:08","indexId":"sim3355","displayToPublicDate":"2016-06-21T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3355","title":"Changes between early development (1930–60) and recent (2005–15) groundwater-level altitudes and dissolved-solids and nitrate concentrations In and near Gaines, Terry, and Yoakum Counties, Texas","docAbstract":"Llano Estacado Underground Water Conservation District, Sandy Land Underground Water Conservation District, and South Plains Underground Water Conservation District manage groundwater resources in a part of west Texas near the Texas-New Mexico State line. Declining groundwater levels have raised concerns about the amount of available groundwater in the study area and the potential for water-quality changes resulting from dewatering and increased vertical groundwater movement between adjacent water-bearing units.
\nIn 2014, the U.S. Geological Survey, in cooperation with Llano Estacado Underground Water Conservation District, Sandy Land Underground Water District, and South Plains Underground Water Conservation District, began a multiphase project to develop a regional conceptual model of the hydrogeologic framework and geochemistry of the Ogallala, Edwards-Trinity, and Dockum aquifers. The Ogallala aquifer is the shallowest aquifer in the study area and is the primary source of water for agriculture and municipal supply in the area. This report describes the results of the first phase of the study, during which groundwater-level-altitude and selected water-quality data from wells in and near Gaines, Terry, and Yoakum Counties were compiled and evaluated for the Ogallala, Edwards-Trinity, and Dockum aquifers.
\nReadily available digital groundwater data for the study area (geologic, well-construction, groundwater-level-altitude, and selected water-quality data) were compiled to assess temporal and spatial changes in groundwater resources from early development (1930–60) to recent (2005–15) periods. Pertinent data were compiled from available sources for the study area and for a 5-mile buffer area around the study area to prevent gridding errors near the boundary. Geologic and well-construction data were used to determine or verify the aquifer in which each well was completed. Depending on the available data, the aquifer assignment (aquifer in which a given well was completed) was determined on the basis of the following criteria, in order of priority: (1) the screened or open interval(s) of the well, (2) the total depth of the well, or (3) the completed aquifer reported for a given well by the data source.
\nPotentiometric-surface maps were created to depict changes in groundwater-level altitudes for the Ogallala and Edwards-Trinity aquifers. In addition to comparing groundwater-level altitudes and water quality from the early development and recent periods, hydrographs of groundwater-level altitudes were created, and changes in water quality for various periods between 1930 and 2015 were evaluated. Variance maps for each groundwater-level-altitude grid were used to evaluate the spatial data coverage and to identify areas with higher uncertainty because of spatially limited data availability for some of the aquifers.
\nFor this report, existing dissolved-solids and nitrate concentration data were compiled and assessed for evidence of spatial patterns and changes over time. These data were compiled for samples collected from wells completed in the Ogallala, Edwards-Trinity, or Dockum aquifer during the early development period (1930–60) or the recent period (2005–15); temporal and spatial variations were assessed from depictions of the measured concentration values. Dissolved-solids and nitrate concentrations measured in samples from three wells completed in the Ogallala aquifer (well identifiers 11524, 11824, and 11825) for which long-term monitoring was done for various periods between 1950 and 2015 were also compiled and analyzed.
\nGroundwater-level altitudes of the Ogallala aquifer are generally higher in the northwestern part of the study area and lower in the southeastern part of the study area, varying by as much as 800 feet. Groundwater flow paths for the early development period generally trend from northwest to southeast across the study area. Compared to those for the early development period, local features in the potentiometric surface for the recent period are more pronounced, likely as a result of additional data coverage, increased groundwater withdrawals, and local flow paths that are more variable.
\nFor the Edwards-Trinity aquifer potentiometric-surface map of the recent period, a general northwest to southeast flow gradient was also evident, with some subtle differences compared to the early development period. The Edwards-Trinity aquifer water-level-altitude change map between the early development and recent periods indicated similar spatial trends as in the Ogallala aquifer and indicated that groundwater-level altitudes declined over a large amount of the area for which sufficient data were available for reliably mapping changes.
\nDuring the recent period, median dissolved-solids concentrations of less than 1,000 milligrams per liter (mg/L) were predominantly measured in the western part of the study area, and median concentrations of more than 1,000 mg/L were predominantly measured in the eastern part of the study area. A general pattern of increasing nitrate concentrations from west to the northeast was evident in the study area. Nitrate concentrations measured in samples collected from 16 wells completed in the Ogallala aquifer for the recent period were equal to or greater than 10 mg/L, the primary drinking water standard for finished drinking water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3355","collaboration":"Prepared in cooperation with Llano Estacado Underground Water Conservation District, Sandy Land Underground Water Conservation District, and South Plains Underground Water Conservation District","usgsCitation":"Thomas, J.V., Teeple, A.P., Payne, J.D., and Ikard, Scott, 2016, Changes between early development (1930–60) and recent (2005–15) groundwater-level altitudes and dissolved-solids and nitrate concentrations in and near Gaines, Terry, and Yoakum Counties, Texas: U.S. Geological Survey Scientific Investigations Map 3355, 2 sheets, pamphlet, https://dx.doi.org/10.3133/sim3355.","productDescription":"2 Sheets: 32.00 x 35.00 and 32.00 x 35.00; 11 Tables; Pamphlet: vi, 13 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065525","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":321240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3355/coverthb.jpg"},{"id":321242,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3355/sim3355_sheet1.pdf","text":"Sheet 1","size":"2.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3355 Sheet 1"},{"id":321243,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3355/sim3355_sheet2.pdf","text":"Sheet 2","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3355 Sheet 2"},{"id":321244,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3355/sim3355_tables01to11.xlsx","text":"Tables 1 to 11","size":"1.13 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 3355 Tables 1 to 11"},{"id":321241,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3355/sim3355_pamphlet.pdf","text":"Pamphlet","size":"943 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3355 Pamphlet"}],"country":"United States","state":"Texas","county":"Gaines County, Terry County, Yoakum County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-102.2039,32.961],[-102.2038,32.5237],[-102.2109,32.524],[-103.0637,32.5215],[-103.0632,32.9589],[-103.0632,33.0017],[-103.0593,33.209],[-103.0559,33.3903],[-102.5954,33.3903],[-102.0774,33.3894],[-102.0782,32.9611],[-102.2039,32.961]]]},\"properties\":{\"name\":\"Gaines\",\"state\":\"TX\"}}]}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4733
Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2016.05.010","collaboration":"California State University, Sacramento, Department of Geography; State of Washington Military Department, Emergency Management Division; Binghamton University, Department of Geography","usgsCitation":"Wood, N.J., Jones, J.M., Schmidtlein, M., Schelling, J., and Frazier, T., 2016, Pedestrian flow-path modeling to support tsunami evacuation and disaster relief planning in the U.S. Pacific Northwest: International Journal of Disaster Risk Reduction, v. 18, p. 41-55, https://doi.org/10.1016/j.ijdrr.2016.05.010.","productDescription":"15 p.","startPage":"41","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072036","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2016.05.010","text":"Publisher Index Page"},{"id":324029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324014,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S2212420916300140"}],"country":"United States","state":"Washington","city":"Aberdeen, Cosmopolis, Hoquiam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.27734374999999,\n 46.807579571992385\n ],\n [\n -124.27734374999999,\n 47.10752278534248\n ],\n [\n -123.71704101562499,\n 47.10752278534248\n ],\n [\n -123.71704101562499,\n 46.807579571992385\n ],\n [\n -124.27734374999999,\n 46.807579571992385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5769059ce4b07657d19f66ac","chorus":{"doi":"10.1016/j.ijdrr.2016.05.010","url":"http://dx.doi.org/10.1016/j.ijdrr.2016.05.010","publisher":"Elsevier BV","authors":"Wood Nathan, Jones Jeanne, Schmidtlein Mathew, Schelling John, Frazier Tim","journalName":"International Journal of Disaster Risk Reduction","publicationDate":"9/2016","publiclyAccessibleDate":"6/6/2016"},"contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":639863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Jeanne M. 0000-0001-7549-9270 jmjones@usgs.gov","orcid":"https://orcid.org/0000-0001-7549-9270","contributorId":4676,"corporation":false,"usgs":true,"family":"Jones","given":"Jeanne","email":"jmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":639864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidtlein, Mathew","contributorId":31682,"corporation":false,"usgs":true,"family":"Schmidtlein","given":"Mathew","affiliations":[],"preferred":false,"id":639865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schelling, John","contributorId":49707,"corporation":false,"usgs":true,"family":"Schelling","given":"John","email":"","affiliations":[],"preferred":false,"id":639866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frazier, T.","contributorId":56453,"corporation":false,"usgs":true,"family":"Frazier","given":"T.","email":"","affiliations":[],"preferred":false,"id":639867,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173798,"text":"70173798 - 2016 - Models for ecological models: Ocean primary productivity","interactions":[],"lastModifiedDate":"2016-06-20T11:19:00","indexId":"70173798","displayToPublicDate":"2016-06-20T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5002,"text":"CHANCE","active":true,"publicationSubtype":{"id":10}},"title":"Models for ecological models: Ocean primary productivity","docAbstract":"The ocean accounts for more than 70% of planet Earth's surface, and it processes are critically important to marine and terrestrial life. Ocean ecosystems are strongly dependent on the physical state of the ocean (e.g., transports, mixing, upwelling, runoff, and ice dynamics(. As an example, consider the Coastal Gulf of Alaska (CGOA) region.
","language":"English","publisher":"American Statistical Association","doi":"10.1080/09332480.2016.1181962","usgsCitation":"Wikle, C.K., Leeds, W.B., and Hooten, M., 2016, Models for ecological models: Ocean primary productivity: CHANCE, v. 29, no. 2, p. 23-30, https://doi.org/10.1080/09332480.2016.1181962.","productDescription":"8 p.","startPage":"23","endPage":"30","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072690","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"5769059ce4b07657d19f66a7","contributors":{"authors":[{"text":"Wikle, Christopher K.","contributorId":116632,"corporation":false,"usgs":false,"family":"Wikle","given":"Christopher","email":"","middleInitial":"K.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":638550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leeds, William B.","contributorId":45563,"corporation":false,"usgs":true,"family":"Leeds","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":638551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":638378,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173954,"text":"70173954 - 2016 - State-dependent resource harvesting with lagged information about system states","interactions":[],"lastModifiedDate":"2016-06-20T09:47:59","indexId":"70173954","displayToPublicDate":"2016-06-17T15:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"State-dependent resource harvesting with lagged information about system states","docAbstract":"Markov decision processes (MDPs), which involve a temporal sequence of actions conditioned on the state of the managed system, are increasingly being applied in natural resource management. This study focuses on the modification of a traditional MDP to account for those cases in which an action must be chosen after a significant time lag in observing system state, but just prior to a new observation. In order to calculate an optimal decision policy under these conditions, possible actions must be conditioned on the previous observed system state and action taken. We show how to solve these problems when the state transition structure is known and when it is uncertain. Our focus is on the latter case, and we show how actions must be conditioned not only on the previous system state and action, but on the probabilities associated with alternative models of system dynamics. To demonstrate this framework, we calculated and simulated optimal, adaptive policies for MDPs with lagged states for the problem of deciding annual harvest regulations for mallards (Anas platyrhynchos) in the United States. In this particular example, changes in harvest policy induced by the use of lagged information about system state were sufficient to maintain expected management performance (e.g. population size, harvest) even in the face of an uncertain system state at the time of a decision.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0157373","usgsCitation":"Johnson, F.A., Fackler, P.L., Boomer, G., Zimmerman, G.S., Williams, B.K., Nichols, J.D., and Dorazio, R., 2016, State-dependent resource harvesting with lagged information about system states: PLoS ONE, v. 11, no. 6, p. 1-21, https://doi.org/10.1371/journal.pone.0157373.","productDescription":"21 p.","startPage":"1","endPage":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071587","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470874,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0157373","text":"Publisher Index Page"},{"id":323944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"576913e8e4b07657d19ff273","contributors":{"authors":[{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":639749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fackler, Paul L.","contributorId":17487,"corporation":false,"usgs":true,"family":"Fackler","given":"Paul","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":639750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G Scott","contributorId":172150,"corporation":false,"usgs":false,"family":"Boomer","given":"G Scott","affiliations":[{"id":26994,"text":"Div. of Migratory Bird Management, U.S. Fish and Wildlife Service, MD","active":true,"usgs":false}],"preferred":false,"id":639751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":639752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":639753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":140652,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":639754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":639755,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70174943,"text":"70174943 - 2016 - Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling","interactions":[],"lastModifiedDate":"2016-07-22T18:52:33","indexId":"70174943","displayToPublicDate":"2016-06-17T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling","docAbstract":"Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.
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