{"pageNumber":"490","pageRowStart":"12225","pageSize":"25","recordCount":40783,"records":[{"id":70170897,"text":"70170897 - 2016 - Particle size distribution of main-channel-bed sediments along the upper Mississippi River, USA","interactions":[],"lastModifiedDate":"2016-05-11T10:46:50","indexId":"70170897","displayToPublicDate":"2016-05-11T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Particle size distribution of main-channel-bed sediments along the upper Mississippi River, USA","docAbstract":"<p><span>In this study, we compared pre-lock-and-dam (ca. 1925) with a modern longitudinal survey of main-channel-bed sediments along a 740-km segment of the upper Mississippi River (UMR) between Davenport, IA, and Cairo, IL. This comparison was undertaken to gain a better understanding of how bed sediments are distributed longitudinally and to assess change since the completion of the UMR lock and dam navigation system and Missouri River dams (i.e., mid-twentieth century). The comparison of the historic and modern longitudinal bed sediment surveys showed similar bed sediment sizes and distributions along the study segment with the majority (&gt;&nbsp;90%) of bed sediment samples having a median diameter (</span><i>D</i><sub>50</sub><span>) of fine to coarse sand. The fine tail (&le;</span><i>&nbsp;D</i><sub>10</sub><span>) of the sediment size distributions was very fine to medium sand, and the coarse tail (&ge;</span><i>&nbsp;D</i><sub>90</sub><span>) of sediment-size distribution was coarse sand to gravel. Coarsest sediments in both surveys were found within or immediately downstream of bedrock-floored reaches. Statistical analysis revealed that the particle-size distributions between the survey samples were statistically identical, suggesting no overall difference in main-channel-bed sediment-size distribution between 1925 and present. This was a surprising result given the magnitude of river engineering undertaken along the study segment over the past ~&nbsp;90&nbsp;years. The absence of substantial differences in main-channel-bed-sediment size suggests that flow competencies within the highly engineered navigation channel today are similar to conditions within the less-engineered historic channel.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2016.04.012","usgsCitation":"Remo, J., Heine, R.A., and Ickes, B., 2016, Particle size distribution of main-channel-bed sediments along the upper Mississippi River, USA: Geomorphology, v. 264, p. 118-131, https://doi.org/10.1016/j.geomorph.2016.04.012.","productDescription":"14 p.","startPage":"118","endPage":"131","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070811","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":321115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River","volume":"264","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5734499ce4b0dae0d5dd68fe","contributors":{"authors":[{"text":"Remo, Jonathan","contributorId":169212,"corporation":false,"usgs":false,"family":"Remo","given":"Jonathan","affiliations":[{"id":25439,"text":"Southern Illinois University, Carbondale","active":true,"usgs":false}],"preferred":false,"id":628964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heine, Ruben A.","contributorId":169213,"corporation":false,"usgs":false,"family":"Heine","given":"Ruben","email":"","middleInitial":"A.","affiliations":[{"id":25440,"text":"Augustana College, Rock Island, IL","active":true,"usgs":false}],"preferred":false,"id":628965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":628963,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170902,"text":"70170902 - 2016 - The ecology of methane in streams and rivers: Patterns, controls, and global significance","interactions":[],"lastModifiedDate":"2016-05-11T10:34:05","indexId":"70170902","displayToPublicDate":"2016-05-11T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of methane in streams and rivers: Patterns, controls, and global significance","docAbstract":"<p><span>Streams and rivers can substantially modify organic carbon (OC) inputs from terrestrial landscapes, and much of this processing is the result of microbial respiration. While carbon dioxide (CO</span><sub><span>2</span></sub><span>) is the major end-product of ecosystem respiration, methane (CH</span><sub><span>4</span></sub><span>) is also present in many fluvial environments even though methanogenesis typically requires anoxic conditions that may be scarce in these systems. Given recent recognition of the pervasiveness of this greenhouse gas in streams and rivers, we synthesized existing research and data to identify patterns and drivers of CH</span><span><sub>4</sub>,</span><span>&nbsp;knowledge gaps, and research opportunities. This included examining the history of lotic CH</span><sub><span>4</span></sub><span>&nbsp;research, creating a database of concentrations and fluxes (MethDB) to generate a global-scale estimate of fluvial CH</span><sub><span>4</span></sub><span>&nbsp;efflux, and developing a conceptual framework and using this framework to consider how human activities may modify fluvial CH</span><sub><span>4</span></sub><span>&nbsp;dynamics. Current understanding of CH</span><sub><span>4</span></sub><span>&nbsp;in streams and rivers has been strongly influenced by goals of understanding OC processing and quantifying the contribution of CH</span><sub><span>4</span></sub><span>&nbsp;to ecosystem C fluxes. Less effort has been directed towards investigating processes that dictate in situ CH</span><sub><span>4</span></sub><span>&nbsp;production and loss. CH</span><sub><span>4</span></sub><span>&nbsp;makes a meager contribution to watershed or landscape C budgets, but streams and rivers are often significant CH</span><sub><span>4</span></sub><span>&nbsp;sources to the atmosphere across these same spatial extents. Most fluvial systems are supersaturated with CH</span><sub><span>4</span></sub><span>&nbsp;and we estimate an annual global emission of 26.8&nbsp;Tg CH</span><sub><span>4</span></sub><span>, equivalent to ~15-40% of wetland and lake effluxes, respectively. Less clear is the role of CH</span><sub><span>4</span></sub><span>&nbsp;oxidation, methanogenesis, and total anaerobic respiration to whole ecosystem production and respiration. Controls on CH</span><sub><span>4</span></sub><span>&nbsp;generation and persistence can be viewed in terms of proximate controls that influence methanogenesis (organic matter, temperature, alternative electron acceptors, nutrients) and distal geomorphic and hydrologic drivers. Multiple controls combined with its extreme redox status and low solubility result in high spatial and temporal variance of CH</span><sub><span>4</span></sub><span>&nbsp;in fluvial environments, which presents a substantial challenge for understanding its larger-scale dynamics. Further understanding of CH</span><sub><span>4</span></sub><span>&nbsp;production and consumption, anaerobic metabolism, and ecosystem energetics in streams and rivers can be achieved through more directed studies and comparison with knowledge from terrestrial, wetland, and aquatic disciplines.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-1027.1","usgsCitation":"Stanley, E.H., Casson, N.J., Christel, S.T., Crawford, J.T., Loken, L., and Oliver, S., 2016, The ecology of methane in streams and rivers: Patterns, controls, and global significance: Ecological Monographs, v. 86, no. 2, p. 146-171, https://doi.org/10.1890/15-1027.1.","productDescription":"16 p.","startPage":"146","endPage":"171","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471013,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10680/1574","text":"External Repository"},{"id":321111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-07","publicationStatus":"PW","scienceBaseUri":"5734499de4b0dae0d5dd690d","contributors":{"authors":[{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":629004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casson, Nora J.","contributorId":169271,"corporation":false,"usgs":false,"family":"Casson","given":"Nora","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christel, Samuel T.","contributorId":169272,"corporation":false,"usgs":false,"family":"Christel","given":"Samuel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":629006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, John T. 0000-0003-4440-6945 jtcrawford@usgs.gov","orcid":"https://orcid.org/0000-0003-4440-6945","contributorId":4081,"corporation":false,"usgs":true,"family":"Crawford","given":"John","email":"jtcrawford@usgs.gov","middleInitial":"T.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":629003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loken, Luke C. lloken@usgs.gov","contributorId":169218,"corporation":false,"usgs":true,"family":"Loken","given":"Luke C.","email":"lloken@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":629008,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188601,"text":"70188601 - 2016 - A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","interactions":[],"lastModifiedDate":"2017-06-16T12:23:37","indexId":"70188601","displayToPublicDate":"2016-05-11T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches","docAbstract":"The September 16, 2015 Illapel, Chile earthquake\ntriggered a large tsunami, causing both economic losses and\nfatalities. To study the coastal effects of this earthquake, and to\nunderstand how such hazards might be accurately modeled in the\nfuture, different finite fault models of the Illapel rupture are used to\ndefine the initial condition for tsunami simulation. The numerical\ncode Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE)\nis employed to model the tsunami evolution through the Pacific\nOcean. Because only a short time is available for emergency\nresponse, and since the earthquake and tsunami sources are close to\nthe coast, gaining a rapid understanding of the near-field run-up\nbehavior is highly relevant to Chile. Therefore, an analytical\nsolution of the 2 ? 1 D shallow water wave equations is considered.\nWith this solution, we show that we can quickly estimate the\nrun-up distribution along the coastline, to first order. After the\nearthquake and tsunami, field observations were measured in the\nsurrounded coastal region, where the tsunami resulted in significant\nrun-up. First, we compare the analytical and numerical solutions to\ntest the accuracy of the analytical approach and the field observations,\nimplying the analytic approach can accurately model tsunami\nrun-up after an earthquake, without sacrificing the time necessary\nfor a full numerical inversion. Then, we compare both with field\nrun-up measurements. We observe the consistency between the two\napproaches. To complete the analysis, a tsunami source inversion is\nperformed using run-up field measurements only. These inversion\nresults are compared with seismic models, and are shown to capture\nthe broad-scale details of those models, without the necessity of the\ndetailed data sets they invert.","language":"English","publisher":"SpringerLink","doi":"10.1007/s00024-016-1305-0","usgsCitation":"Fuentes, M., Riquelme, S., Hayes, G.P., Medina, M., Melgar, D., Vargas, G., Gonzalez, J., and Villalobos, A., 2016, A study of the 2015 Mw 8.3 Illapel earthquake and tsunami: Numerical and analytical approaches: Pure and Applied Geophysics, v. 173, p. 1847-1858, https://doi.org/10.1007/s00024-016-1305-0.","productDescription":"12 p. 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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-11","publicationStatus":"PW","scienceBaseUri":"5944ee18e4b062508e333618","contributors":{"authors":[{"text":"Fuentes, Mauricio","contributorId":147555,"corporation":false,"usgs":false,"family":"Fuentes","given":"Mauricio","email":"","affiliations":[{"id":16870,"text":"Department of Geophysics, University of Chile, Santiago, Chile","active":true,"usgs":false}],"preferred":false,"id":698517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riquelme, Sebastian","contributorId":193028,"corporation":false,"usgs":false,"family":"Riquelme","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":698518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 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Gabriel","contributorId":193031,"corporation":false,"usgs":false,"family":"Vargas","given":"Gabriel","email":"","affiliations":[],"preferred":false,"id":698522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gonzalez, Jose","contributorId":193032,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Jose","affiliations":[],"preferred":false,"id":698523,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villalobos, Angelo","contributorId":193033,"corporation":false,"usgs":false,"family":"Villalobos","given":"Angelo","email":"","affiliations":[],"preferred":false,"id":698524,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70170913,"text":"70170913 - 2016 - Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling","interactions":[],"lastModifiedDate":"2016-05-10T12:00:19","indexId":"70170913","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling","docAbstract":"<p><span>Climate extremes, such as drought, may have immediate and potentially prolonged effects on carbon cycling. Grasslands store approximately one-third of all terrestrial carbon and may become carbon sources during droughts. However, the magnitude and duration of drought-induced disruptions to the carbon cycle, as well as the mechanisms responsible, remain poorly understood. Over the next century, global climate models predict an increase in two types of drought: chronic but subtle &lsquo;press-droughts&rsquo;, and shorter term but extreme &lsquo;pulse-droughts&rsquo;. Much of our current understanding of the ecological impacts of drought comes from experimental rainfall manipulations. These studies have been highly valuable, but are often short term and rarely quantify carbon feedbacks. To address this knowledge gap, we used the Community Land Model 4.0 to examine the individual and interactive effects of pulse- and press-droughts on carbon cycling in a mesic grassland of the US Great Plains. A series of modeling experiments were imposed by varying drought magnitude (precipitation amount) and interannual pattern (press- vs. pulse-droughts) to examine the effects on carbon storage and cycling at annual to century timescales. We present three main findings. First, a single-year pulse-drought had immediate and prolonged effects on carbon storage due to differential sensitivities of ecosystem respiration and gross primary production. Second, short-term pulse-droughts caused greater carbon loss than chronic press-droughts when total precipitation reductions over a 20-year period were equivalent. Third, combining pulse- and press-droughts had intermediate effects on carbon loss compared to the independent drought types, except at high drought levels. Overall, these results suggest that interannual drought pattern may be as important for carbon dynamics as drought magnitude and that extreme droughts may have long-lasting carbon feedbacks in grassland ecosystems.</span></p>","language":"English","publisher":"John Wiley & Sons","doi":"10.1111/gcb.13161","usgsCitation":"Hoover, D.L., and Rogers, B.M., 2016, Not all droughts are created equal: The impacts of interannual drought pattern and magnitude on grassland carbon cycling: Global Change Biology, v. 22, no. 5, p. 1809-1820, https://doi.org/10.1111/gcb.13161.","productDescription":"12 p.","startPage":"1809","endPage":"1820","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066574","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-25","publicationStatus":"PW","scienceBaseUri":"5732f81ee4b0dae0d5dc643f","contributors":{"authors":[{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":5843,"corporation":false,"usgs":true,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":629058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogers, Brendan M.","contributorId":169247,"corporation":false,"usgs":false,"family":"Rogers","given":"Brendan","email":"","middleInitial":"M.","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":629059,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170912,"text":"70170912 - 2016 - POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:50:15","indexId":"70170912","displayToPublicDate":"2016-05-10T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"POLARIS: A 30-meter probabilistic soil series map of the contiguous United States","docAbstract":"<p><span>A new complete map of soil series probabilities has been produced for the contiguous United States at a 30&nbsp;m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30&nbsp;m) elevation data and coarse-scale (~&nbsp;2&nbsp;km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2016.03.025","usgsCitation":"Chaney, N.W., Wood, E.F., McBratney, A., Hempel, J.W., Nauman, T.W., Brungard, C.W., and Odgers, N.P., 2016, POLARIS: A 30-meter probabilistic soil series map of the contiguous United States: Geoderma, v. 274, p. 54-67, https://doi.org/10.1016/j.geoderma.2016.03.025.","productDescription":"14 p.","startPage":"54","endPage":"67","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069596","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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 \"}}]}\n","volume":"274","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5732f81fe4b0dae0d5dc6441","contributors":{"authors":[{"text":"Chaney, Nathaniel W.","contributorId":169242,"corporation":false,"usgs":false,"family":"Chaney","given":"Nathaniel","email":"","middleInitial":"W.","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":629052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Eric F woodec@usgs.gov","contributorId":169243,"corporation":false,"usgs":false,"family":"Wood","given":"Eric","email":"woodec@usgs.gov","middleInitial":"F","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":629053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McBratney, Alexander B","contributorId":169245,"corporation":false,"usgs":false,"family":"McBratney","given":"Alexander B","affiliations":[{"id":25455,"text":"Department of Environmental Sciences, Faculty of Agriculture and Environment, The University of Sydney, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":629055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hempel, Jonathan W","contributorId":169244,"corporation":false,"usgs":false,"family":"Hempel","given":"Jonathan","email":"","middleInitial":"W","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629051,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brungard, Colby W.","contributorId":99488,"corporation":false,"usgs":true,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":629056,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Odgers, Nathan P","contributorId":169246,"corporation":false,"usgs":false,"family":"Odgers","given":"Nathan","email":"","middleInitial":"P","affiliations":[{"id":25454,"text":"National Soil Survey Center, NRCS, Lincoln, Nebraska, USA","active":true,"usgs":false}],"preferred":false,"id":629057,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70171093,"text":"70171093 - 2016 - Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","interactions":[],"lastModifiedDate":"2016-09-06T14:03:13","indexId":"70171093","displayToPublicDate":"2016-05-10T09:15:00","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":"Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources","docAbstract":"<p>In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1457","usgsCitation":"Palmquist, K.A., Schlaepfer, D., Bradford, J.B., and Lauenroth, W.K., 2016, Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources: Ecology, v. 97, no. 9, p. 2342-2354, https://doi.org/10.1002/ecy.1457.","productDescription":"13 p.","startPage":"2342","endPage":"2354","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066807","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5740354de4b07e28b65e9697","contributors":{"authors":[{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629843,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, Willliam K.","contributorId":169518,"corporation":false,"usgs":false,"family":"Lauenroth","given":"Willliam","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":629845,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70171533,"text":"70171533 - 2016 - Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines","interactions":[],"lastModifiedDate":"2016-06-16T11:25:03","indexId":"70171533","displayToPublicDate":"2016-05-09T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"title":"Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines","docAbstract":"<p><span>Climate change elevates conservation concerns worldwide because it is likely to exacerbate many identified threats to animal populations. In recent decades, grassland birds have declined faster than other North American bird species, a loss thought to be due to habitat loss and fragmentation and changing agricultural practices. Climate change poses additional threats of unknown magnitude to these already declining populations. We examined how seasonal and daily weather conditions over 10&nbsp;years influenced nest survival of five species of insectivorous passerines native to the shortgrass prairie and evaluate our findings relative to future climate predictions for this region. Daily nest survival (</span><i>n&nbsp;</i><span>=</span><i>&nbsp;</i><span>870) was best predicted by a combination of daily and seasonal weather variables, age of nest, time in season and bird habitat guild. Within a season, survival rates were lower on very hot days (temperatures &ge;&nbsp;35&nbsp;&deg;C), on dry days (with a lag of 1&nbsp;day) and on stormy days (especially for those species nesting in shorter vegetation). Across years, survival rates were also lower during warmer and drier breeding seasons. Clutch sizes were larger when early spring temperatures were cool and the week prior to egg-laying was wetter and warming. Climate change is likely to exacerbate grassland bird population declines because projected climate conditions include rising temperatures, more prolonged drought and more intense storms as the hydrological cycle is altered. Under varying realistic scenarios, nest success estimates were halved compared to their current average value when models both increased the temperature (3&nbsp;&deg;C) and decreased precipitation (two additional dry days during a nesting period), thus underscoring a sense of urgency in identifying and addressing the current causes of range-wide declines.</span></p>","language":"English","publisher":"British Ornithologists' Union","publisherLocation":"Oxford","doi":"10.1111/ibi.12373","collaboration":"Reesa Conrey; Amy A. Yackel Adams; Arvind Panjabi","usgsCitation":"Conrey, R.Y., Skagen, S., Yackel, A., and Panjabi, A.O., 2016, Extremes of heat, drought and precipitation depress reproductive performance in shortgrass prairie passerines: Ibis, v. 158, no. 3, p. 614-629, https://doi.org/10.1111/ibi.12373.","productDescription":"16 p.","startPage":"614","endPage":"629","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070119","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":322103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"575158b1e4b053f0edd03c44","chorus":{"doi":"10.1111/ibi.12373","url":"http://dx.doi.org/10.1111/ibi.12373","publisher":"Wiley-Blackwell","authors":"Conrey Reesa Y., Skagen Susan K., Yackel Adams Amy A., Panjabi Arvind O.","journalName":"Ibis","publicationDate":"5/9/2016"},"contributors":{"authors":[{"text":"Conrey, Reesa Y.","contributorId":169966,"corporation":false,"usgs":false,"family":"Conrey","given":"Reesa","email":"","middleInitial":"Y.","affiliations":[{"id":16861,"text":"Colorado Parks and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":631635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skagen, Susan K. 0000-0002-6744-1244 skagens@usgs.gov","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":167829,"corporation":false,"usgs":true,"family":"Skagen","given":"Susan K.","email":"skagens@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":631634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel, Amy 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":152310,"corporation":false,"usgs":true,"family":"Yackel","given":"Amy","email":"yackela@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":631636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Panjabi, Arvind O.","contributorId":169967,"corporation":false,"usgs":false,"family":"Panjabi","given":"Arvind","email":"","middleInitial":"O.","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":631637,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70171092,"text":"70171092 - 2016 - Terrestrial nitrogen cycling in Earth system models revisited","interactions":[],"lastModifiedDate":"2016-05-20T10:14:28","indexId":"70171092","displayToPublicDate":"2016-05-09T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Terrestrial nitrogen cycling in Earth system models revisited","docAbstract":"<div class=\"t m0 x0 h4 y6 ff4 fs3 fc1 sc0 ls0 ws0\">Understanding the degree to which nitrogen (N) availability limits land carbon (C) uptake under global environmental change represents an unresolved challenge. First-generation &lsquo;C-only&rsquo;vegetation models, lacking explicit representations of N cycling,projected a substantial and increasing land C sink under rising atmospheric CO<sub>2</sub> concentrations. This prediction was questioned for not taking into account the potentially limiting effect of N availability, which is necessary for plant growth (Hungate et al.,2003). More recent global models include coupled C and N cycles in land ecosystems (C&ndash;N models) and are widely assumed to be more realistic. However, inclusion of more processes has not consistently improved their performance in capturing observed responses of the global C cycle (e.g. Wenzel et al., 2014). With the advent of a new generation of global models, including coupled C, N, and phosphorus (P) cycling, model complexity is sure to increase; but model reliability may not, unless greater attention is paid to the correspondence of model process representations ande mpirical evidence. It was in this context that the &lsquo;Nitrogen Cycle Workshop&rsquo; at Dartington Hall, Devon, UK was held on 1&ndash;5 February 2016. Organized by I. Colin Prentice and Benjamin D. Stocker (Imperial College London, UK), the workshop was funded by the European Research Council,project &lsquo;Earth system Model Bias Reduction and assessing Abrupt Climate change&rsquo; (EMBRACE). We gathered empirical ecologists and ecosystem modellers to identify key uncertainties in terrestrial C&ndash;N cycling, and to discuss processes that are missing or poorly represented in current models.</div>","language":"English","publisher":"Blackwell Science","publisherLocation":"Cambridge","doi":"10.1111/nph.13997","usgsCitation":"Stocker, B., Prentice, I.C., Cornell, S., Davies-Barnard, T., Finzi, A., Franklin, O., Janssens, I., Larmola, T., Manzoni, S., Nasholm, T., Raven, J., Rebel, K., Reed, S.C., Vicca, S., Wiltshire, A., and Zaehle, S., 2016, Terrestrial nitrogen cycling in Earth system models revisited: New Phytologist, v. 210, no. 4, p. 1165-1168, https://doi.org/10.1111/nph.13997.","startPage":"1165","endPage":"1168","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074013","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471016,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/nph.13997","text":"External Repository"},{"id":321444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"210","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5740355ee4b07e28b65e970b","contributors":{"authors":[{"text":"Stocker, Benjamin","contributorId":169502,"corporation":false,"usgs":false,"family":"Stocker","given":"Benjamin","email":"","affiliations":[{"id":25536,"text":"Imperial  College, UK","active":true,"usgs":false}],"preferred":false,"id":629828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prentice, I. Colin","contributorId":169503,"corporation":false,"usgs":false,"family":"Prentice","given":"I.","email":"","middleInitial":"Colin","affiliations":[{"id":25536,"text":"Imperial  College, UK","active":true,"usgs":false}],"preferred":false,"id":629829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cornell, Sarah","contributorId":169504,"corporation":false,"usgs":false,"family":"Cornell","given":"Sarah","email":"","affiliations":[{"id":25537,"text":"Stockholm Resilience  Centre,  Sweden","active":true,"usgs":false}],"preferred":false,"id":629830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davies-Barnard, T","contributorId":169505,"corporation":false,"usgs":false,"family":"Davies-Barnard","given":"T","email":"","affiliations":[{"id":25538,"text":"University of Exeter,  UK","active":true,"usgs":false}],"preferred":false,"id":629831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finzi, Adrien","contributorId":169506,"corporation":false,"usgs":false,"family":"Finzi","given":"Adrien","email":"","affiliations":[{"id":25539,"text":"Boston University, USA","active":true,"usgs":false}],"preferred":false,"id":629832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franklin, Oskar","contributorId":169507,"corporation":false,"usgs":false,"family":"Franklin","given":"Oskar","email":"","affiliations":[{"id":25540,"text":"IIASA, Austria","active":true,"usgs":false}],"preferred":false,"id":629833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Janssens, Ivan","contributorId":169508,"corporation":false,"usgs":false,"family":"Janssens","given":"Ivan","affiliations":[{"id":25541,"text":"University of Antwerp, Belgium","active":true,"usgs":false}],"preferred":false,"id":629834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larmola, Tuula","contributorId":169509,"corporation":false,"usgs":false,"family":"Larmola","given":"Tuula","email":"","affiliations":[{"id":25542,"text":"Natural  Resources Institute, Finland","active":true,"usgs":false}],"preferred":false,"id":629835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Manzoni, Stefano","contributorId":169513,"corporation":false,"usgs":false,"family":"Manzoni","given":"Stefano","email":"","affiliations":[{"id":25546,"text":"Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":629839,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nasholm, Torgny","contributorId":169510,"corporation":false,"usgs":false,"family":"Nasholm","given":"Torgny","email":"","affiliations":[{"id":25543,"text":"Ume˚a Plant Science Centre,  Sweden","active":true,"usgs":false}],"preferred":false,"id":629836,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Raven, John","contributorId":169511,"corporation":false,"usgs":false,"family":"Raven","given":"John","email":"","affiliations":[{"id":25544,"text":"Dundee University, UK","active":true,"usgs":false}],"preferred":false,"id":629837,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Rebel, Karin","contributorId":169512,"corporation":false,"usgs":false,"family":"Rebel","given":"Karin","email":"","affiliations":[{"id":25545,"text":"Utrecht University, Netherlands","active":true,"usgs":false}],"preferred":false,"id":629838,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":629827,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Vicca, Sara","contributorId":169514,"corporation":false,"usgs":false,"family":"Vicca","given":"Sara","email":"","affiliations":[{"id":25541,"text":"University of Antwerp, Belgium","active":true,"usgs":false}],"preferred":false,"id":629840,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wiltshire, Andy","contributorId":169515,"corporation":false,"usgs":false,"family":"Wiltshire","given":"Andy","email":"","affiliations":[{"id":25547,"text":"MetOffice,  UK","active":true,"usgs":false}],"preferred":false,"id":629841,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zaehle, Sonke 0000-0001-5602-7956","orcid":"https://orcid.org/0000-0001-5602-7956","contributorId":169516,"corporation":false,"usgs":false,"family":"Zaehle","given":"Sonke","email":"","affiliations":[{"id":25548,"text":"MPI-BGC, Germany","active":true,"usgs":false}],"preferred":false,"id":629842,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70186267,"text":"70186267 - 2016 - Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","interactions":[],"lastModifiedDate":"2017-04-03T12:50:32","indexId":"70186267","displayToPublicDate":"2016-05-09T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5361,"text":"California Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California","docAbstract":"<p><span>Archaeological investigations at prehistoric site CA-MRN-254 at the Dominican University of California in Marin County, California, revealed evidence of Native American occupation spanning the past 1,800 years. A dominant source of food for the inhabitants in the San Francisco Bay area was the intertidal, quiet-water dwelling blue mussel (</span><i>Mytilus trossulus</i><span>), although rare occurrences of the open coast-dwelling California mussel (</span><i>Mytilus californianus</i><span>) suggest that this species was also utilized sporadically. On rare occasions, cultural horizons at this site contain abundant sediment-filled casts of the smaller mussel </span><i>Modiolus</i><span> sp. These casts were formed soon after death when the shells filled with sediment and were roasted along with living bivalve shellfish for consumption. Thin sections of these mussel casts display sedimentological and microbiological constituents that shed light on the paleoenvironmental conditions when they were alive. Fine-grained sediment and pelletal muds comprising these casts suggest that the mussels were collected in a low energy, inner bay environment. The rare presence of the diatoms </span><i>Triceratium dubium</i><span> and </span><i>Thalassionema nitzschioides</i><span> indicate more normal marine (35 psu) and possibly warmer conditions than presently exist in San Francisco Bay. Radiocarbon dating of charcoal associated with the mussel casts containing these diatoms correlates with a 600-year period of warming from ca. A.D. 700–1300, known as the Medieval Climatic Anomaly. Results of this mussel cast study demonstrate that they have great potential for providing paleoenvironmental information at this and other archaeological sites.</span></p>","language":"English","publisher":"Society for California Archaeology","publisherLocation":"Chico, CA","doi":"10.1080/1947461X.2016.1176367","usgsCitation":"McGann, M., Starratt, S.W., Powell, C.L., and Bieling, D.G., 2016, Use of mussel casts from archaeological sites as paleoecological indicators: An example from CA-MRN-254, Marin County, Alta California: California Archaeology, v. 8, no. 1, p. 63-90, https://doi.org/10.1080/1947461X.2016.1176367.","productDescription":"28 p.","startPage":"63","endPage":"90","ipdsId":"IP-079316","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":339047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Rafael","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.51884460449217,\n              37.97786403627176\n            ],\n            [\n              -122.51609802246092,\n              37.97786403627176\n            ],\n            [\n              -122.51609802246092,\n              37.979555414681506\n            ],\n            [\n              -122.51884460449217,\n              37.979555414681506\n            ],\n            [\n              -122.51884460449217,\n              37.97786403627176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"58e35f7fe4b09da67997ecad","contributors":{"authors":[{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":688076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":688077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Charles L. 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,{"id":70170988,"text":"70170988 - 2016 - Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species","interactions":[],"lastModifiedDate":"2016-11-09T10:33:17","indexId":"70170988","displayToPublicDate":"2016-05-07T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":982,"text":"Behavioral Ecology and Sociobiology","active":true,"publicationSubtype":{"id":10}},"title":"Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species","docAbstract":"<p><span>For several species, refuges (such as burrows, dens, roosts, nests) are an essential resource for protection from predators and extreme environmental conditions. Refuges also serve as focal sites for social interactions, including mating, courtship, and aggression. Knowledge of refuge use patterns can therefore provide information about social structure, mating, and foraging success, as well as the robustness and health of wildlife populations, especially for species considered to be relatively solitary. In this study, we construct networks of burrow use to infer social associations in a threatened wildlife species typically considered solitary—the desert tortoise. We show that tortoise social networks are significantly different than null networks of random associations, and have moderate spatial constraints. We next use statistical models to identify major mechanisms behind individual-level variation in tortoise burrow use, popularity of burrows in desert tortoise habitat, and test for stressor-driven changes in refuge use patterns. We show that seasonal variation has a strong impact on tortoise burrow switching behavior. On the other hand, burrow age and topographical condition influence the number of tortoises visiting a burrow in desert tortoise habitat. Of three major population stressors affecting this species (translocation, drought, disease), translocation alters tortoise burrow switching behavior, with translocated animals visiting fewer unique burrows than residents. In a species that is not social, our study highlights the importance of leveraging refuge use behavior to study the presence of and mechanisms behind non-random social structure and individual-level variation. Our analysis of the impact of stressors on refuge-based social structure further emphasizes the potential of this method to detect environmental or anthropogenic disturbances.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00265-016-2136-9","usgsCitation":"Sah, P., Nussear, K.E., Esque, T., Aiello, C.M., Hudson, P., and Bansal, S., 2016, Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species: Behavioral Ecology and Sociobiology, v. 70, no. 8, p. 1277-1289, https://doi.org/10.1007/s00265-016-2136-9.","productDescription":"13 p.","startPage":"1277","endPage":"1289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068721","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471017,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/025494","text":"External Repository"},{"id":321446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-27","publicationStatus":"PW","scienceBaseUri":"5740354ae4b07e28b65e9657","contributors":{"authors":[{"text":"Sah, Pratha","contributorId":127768,"corporation":false,"usgs":false,"family":"Sah","given":"Pratha","email":"","affiliations":[{"id":7145,"text":"Department of Biology, Georgetown University, Washington DC","active":true,"usgs":false}],"preferred":false,"id":629345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nussear, Kenneth E. knussear@usgs.gov","contributorId":2695,"corporation":false,"usgs":true,"family":"Nussear","given":"Kenneth","email":"knussear@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":127766,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":629344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aiello, Christina M. 0000-0002-2399-5464 caiello@usgs.gov","orcid":"https://orcid.org/0000-0002-2399-5464","contributorId":5617,"corporation":false,"usgs":true,"family":"Aiello","given":"Christina","email":"caiello@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":629348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bansal, Shweta","contributorId":168595,"corporation":false,"usgs":false,"family":"Bansal","given":"Shweta","email":"","affiliations":[{"id":25339,"text":"Dep't of Biology, Georgetown U., Washington D.C., NIH, Bethesda, MD","active":true,"usgs":false}],"preferred":false,"id":629349,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70169357,"text":"sir20165036 - 2016 - Flood-inundation maps for the East Fork White River at Shoals, Indiana","interactions":[],"lastModifiedDate":"2016-05-18T09:55:41","indexId":"sir20165036","displayToPublicDate":"2016-05-06T14:00:00","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":"2016-5036","title":"Flood-inundation maps for the East Fork White River at Shoals, Indiana","docAbstract":"<p>Digital flood-inundation maps for a 5.9-mile reach of the East Fork White River at Shoals, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" data-mce-href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a> depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the East Fork White River at Shoals, Ind. (USGS station number 03373500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at <a href=\"http://waterdata.usgs.gov/\" data-mce-href=\"http://waterdata.usgs.gov/\">http://waterdata.usgs.gov/</a> or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at <a href=\"http://water.weather.gov/ahps/\" data-mce-href=\"http://water.weather.gov/ahps/\">http://water.weather.gov/ahps/</a>, which also forecasts flood hydrographs at this site (NWS AHPS site SHLI3). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.</p><p>Flood profiles were computed for the East Fork White River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 43.0) at USGS streamgage 03373500, East Fork White River at Shoals, Ind. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (10 ft) to the highest stage of the current stage-discharge rating curve (35 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM), derived from light detection and ranging (lidar) data, to delineate the area flooded at each water level. The areal extent of the 24-ft flood-inundation map was verified with photographs from a flood event on July 20, 2015.</p><p>The availability of these maps, along with information on the Internet regarding current stage from the USGS streamgage at East Fork White River at Shoals, Ind., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165036","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Boldt, J.A., 2016, Flood-inundation maps for the East Fork White River at Shoals, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5036, 22 p., 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Library</li>\n<li>Summary</li>\n<li>References Cited</li>\n<li>Appendix 1.&nbsp;Supplemental Data and Photographs</li>\n</ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-05-06","noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"572db219e4b0dae0d5d83fa7","contributors":{"authors":[{"text":"Boldt, Justin A. jboldt@usgs.gov","contributorId":167903,"corporation":false,"usgs":true,"family":"Boldt","given":"Justin A.","email":"jboldt@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":623941,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70169102,"text":"sir20155187 - 2016 - Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio","interactions":[],"lastModifiedDate":"2016-06-24T13:27:24","indexId":"sir20155187","displayToPublicDate":"2016-05-06T08:15:00","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":"2015-5187","title":"Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio","docAbstract":"<p>Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155187","collaboration":"Prepared in cooperation with the Muskingum Watershed Conservancy District","usgsCitation":"Huitger, C.A, Ostheimer, C.J., and Koltun, G.F., 2016, Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio: U.S. Geological Survey Scientific Investigations Report 2015–5187, 39 p., 2 appendixes, https://dx.doi.org/10.3133/sir20155187.","productDescription":"Report: vi, 39 p.; 5 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060945","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":320916,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-1.csv","text":"Appendix 1 - Table 1-1","size":"84.1 KB csv","description":"SIR 2015-5187"},{"id":320915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5187/sir20155187.pdf","text":"Report","size":"1.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5187"},{"id":320917,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-2.csv","text":"Appendix 1 - Table 1-2","size":"62 KB csv","description":"SIR 2015-5187"},{"id":320914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5187/coverthb.jpg"},{"id":320919,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-4.csv","text":"Appendix 1 - Table 1-4","size":"50 KB csv","description":"SIR 2015-5187"},{"id":320918,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-3.csv","text":"Appendix 1 - Table 1-3","size":"19 KB csv","description":"SIR 2015-5187"},{"id":320920,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5187/appendix/sir20155187_appendix1-table1-5.csv","text":"Appendix 1 - Table 1-5","size":"22 KB csv","description":"SIR 2015-5187"}],"country":"United States","state":"Ohio","city":"Shelby","otherGeospatial":"Black Fork Mohican River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -82.70902633666992,\n              40.83563216247778\n            ],\n            [\n              -82.70902633666992,\n              40.91934991356069\n            ],\n            [\n              -82.61959075927734,\n              40.91934991356069\n            ],\n            [\n              -82.61959075927734,\n              40.83563216247778\n            ],\n            [\n              -82.70902633666992,\n              40.83563216247778\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Ohio Water Science Center<br> 6480 Doubletree Ave<br> Columbus, OH 43229<br> <a href=\"http://oh.water.usgs.gov/\" data-mce-href=\"http://oh.water.usgs.gov/\">http://oh.water.usgs.gov/</a></p>","tableOfContents":"<ul>\n<li>Abstract&nbsp;</li>\n<li>Introduction</li>\n<li>Study Approach</li>\n<li>Step-backwater Analyses</li>\n<li>Summary</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2016-05-06","noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"572db21ae4b0dae0d5d83fb0","contributors":{"authors":[{"text":"Huitger, Carrie A. chuitger@usgs.gov","contributorId":1851,"corporation":false,"usgs":true,"family":"Huitger","given":"Carrie","email":"chuitger@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622935,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostheimer, Chad J. ostheime@usgs.gov","contributorId":140119,"corporation":false,"usgs":true,"family":"Ostheimer","given":"Chad J.","email":"ostheime@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koltun, G. 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,{"id":70169129,"text":"ofr20161047 - 2016 - An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models","interactions":[],"lastModifiedDate":"2018-03-23T14:15:49","indexId":"ofr20161047","displayToPublicDate":"2016-05-05T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1047","title":"An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models","docAbstract":"<p>The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161047","usgsCitation":"Rupp, D.E., 2016, An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models: U.S. Geological Survey Open-File Report 2016–1047, 32 p., https://dx.doi.org/10.3133/ofr20161047.","productDescription":"iv, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072786","costCenters":[{"id":565,"text":"Southeast Climate Science 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-83.232421875,\n              29.286398892934763\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Southeast Climate Science Center <br /> U.S. Department of the Interior<br /> North Carolina State University, Campus Box 7617 <br /> Raleigh, NC 27695<br />(919) 515-2229<br /> <a href=\"https://www.doi.gov/csc/southeast/\">https://www.doi.gov/csc/southeast/</a></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>1. Introduction</li>\n<li>2. Data and Methods</li>\n<li>3. Results and Discussion of Model Ranking</li>\n<li>4. Model Performance by Metric</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-05-05","noUsgsAuthors":false,"publicationDate":"2016-05-05","publicationStatus":"PW","scienceBaseUri":"572c609ae4b09acee752ef7e","contributors":{"authors":[{"text":"David E. Rupp","contributorId":167687,"corporation":false,"usgs":false,"family":"David E. Rupp","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":623130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170272,"text":"sir20165052 - 2016 - Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington","interactions":[],"lastModifiedDate":"2024-12-04T19:23:30.813809","indexId":"sir20165052","displayToPublicDate":"2016-05-05T15:00:00","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":"2016-5052","title":"Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington","docAbstract":"<p>A groundwater-flow model was developed to improve understanding of water resources on the Kitsap Peninsula. The Kitsap Peninsula is in the Puget Sound lowland of west-central Washington, is bounded by Puget Sound on the east and by Hood Canal on the west, and covers an area of about 575 square miles. The peninsula encompasses all of Kitsap County, Mason County north of Hood Canal, and part of Pierce County west of Puget Sound. The peninsula is surrounded by saltwater, and the hydrologic setting is similar to that of an island. The study area is underlain by a thick sequence of unconsolidated glacial and interglacial deposits that overlie sedimentary and volcanic bedrock units that crop out in the central part of the study area. Twelve hydrogeologic units consisting of aquifers, confining units, and an underlying bedrock unit form the basis of the groundwater-flow model.</p><p>Groundwater flow on the Kitsap Peninsula was simulated using the groundwater-flow model, MODFLOW‑NWT. The finite difference model grid comprises 536 rows, 362 columns, and 14 layers. Each model cell has a horizontal dimension of 500 by 500 feet, and the model contains a total of 1,227,772 active cells. Groundwater flow was simulated for transient conditions. Transient conditions were simulated for January 1985–December 2012 using annual stress periods for 1985–2004 and monthly stress periods for 2005–2012. During model calibration, variables were adjusted within probable ranges to minimize differences between measured and simulated groundwater levels and stream baseflows. As calibrated to transient conditions, the model has a standard deviation for heads and flows of 47.04 feet and 2.46 cubic feet per second, respectively.</p><p>Simulated inflow to the model area for the 2005–2012 period from precipitation and secondary recharge was 585,323 acre-feet per year (acre-ft/yr) (93 percent of total simulated inflow ignoring changes in storage), and simulated inflow from stream and lake leakage was 43,905 acre-ft/yr (7 percent of total simulated inflow). Simulated outflow from the model primarily was through discharge to streams, lakes, springs, seeps, and Puget Sound (594,595 acre-ft/yr; 95 percent of total simulated outflow excluding changes in storage) and through withdrawals from wells (30,761 acre-ft/yr; 5 percent of total simulated outflow excluding changes in storage).</p><p>Six scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effects on water levels and stream baseflows of potential changes in groundwater withdrawals, in consumptive use, and in recharge. These included simulations of a steady-state system, no-pumping and return flows, 15-percent increase in current withdrawals in all wells, 80-percent decrease in outdoor water to simulate effects of conservation efforts, 15-percent decrease in recharge from precipitation to simulate a drought, and particle tracking to determine flow paths.</p><p>Changes in water-level altitudes and baseflow amounts vary depending on the stress applied to the system in these various scenarios. Reducing recharge by 15 percent between 2005 and 2012 had the largest effect, with water-level altitudes declining throughout the model domain and baseflow amounts decreasing by as much as 18 percent compared to baseline conditions. Changes in pumping volumes had a smaller effect on the model. Removing all pumping and resulting return flows caused increased water-level altitudes in many areas and increased baseflow amounts of between 1 and 3 percent.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165052","collaboration":"Prepared in cooperation with Public Utility District No. 1 of Kitsap County","usgsCitation":"Frans, L.M. and Olsen, T.D., 2016, Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington (ver. 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5052, 63 p., https://dx.doi.org/10.3133/sir20165052.","productDescription":"vi, 63 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071099","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329281,"rank":3,"type":{"id":25,"text":"Version 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Cited</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-05-05","revisedDate":"2016-10-04","noUsgsAuthors":false,"publicationDate":"2016-05-05","publicationStatus":"PW","scienceBaseUri":"572c609be4b09acee752ef8e","contributors":{"authors":[{"text":"Frans, Lonna M. 0000-0002-3217-1862 lmfrans@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-1862","contributorId":1493,"corporation":false,"usgs":true,"family":"Frans","given":"Lonna","email":"lmfrans@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626717,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170856,"text":"70170856 - 2016 - Resource subsidies between stream and terrestrial ecosystems under global change","interactions":[],"lastModifiedDate":"2016-06-16T11:04:01","indexId":"70170856","displayToPublicDate":"2016-05-05T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Resource subsidies between stream and terrestrial ecosystems under global change","docAbstract":"<p><span>Streams and adjacent terrestrial ecosystems are characterized by permeable boundaries that are crossed by resource subsidies. Although the importance of these subsidies for riverine ecosystems is increasingly recognized, little is known about how they may be influenced by global environmental change. Drawing from available evidence, in this review we propose a conceptual framework to evaluate the effects of global change on the quality and spatiotemporal dynamics of stream&ndash;terrestrial subsidies. We illustrate how changes to hydrological and temperature regimes, atmospheric CO</span><span>2</span><span>&nbsp;concentration, land use and the distribution of nonindigenous species can influence subsidy fluxes by affecting the biology and ecology of donor and recipient systems and the physical characteristics of stream&ndash;riparian boundaries. Climate-driven changes in the physiology and phenology of organisms with complex life cycles will influence their development time, body size and emergence patterns, with consequences for adjacent terrestrial consumers. Also, novel species interactions can modify subsidy dynamics via complex bottom-up and top-down effects. Given the seasonality and pulsed nature of subsidies, alterations of the temporal and spatial synchrony of resource availability to consumers across ecosystems are likely to result in ecological mismatches that can scale up from individual responses, to communities, to ecosystems. Similarly, altered hydrology, temperature, CO</span><span>2</span><span>&nbsp;concentration and land use will modify the recruitment and quality of riparian vegetation, the timing of leaf abscission and the establishment of invasive riparian species. Along with morphological changes to stream&ndash;terrestrial boundaries, these will alter the use and fluxes of allochthonous subsidies associated with stream ecosystems. Future research should aim to understand how subsidy dynamics will be affected by key drivers of global change, including agricultural intensification, increasing water use and biotic homogenization. Our conceptual framework based on the match&ndash;mismatch between donor and recipient organisms may facilitate understanding of the multiple effects of global change and aid in the development of future research questions.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13182","usgsCitation":"Larsen, S., Muehlbauer, J.D., and Marti Roca, M.E., 2016, Resource subsidies between stream and terrestrial ecosystems under global change: Global Change Biology, v. 22, no. 7, p. 2489-2504, https://doi.org/10.1111/gcb.13182.","productDescription":"16 p.","startPage":"2489","endPage":"2504","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067749","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-25","publicationStatus":"PW","scienceBaseUri":"572c609ce4b09acee752ef96","contributors":{"authors":[{"text":"Larsen, Stefano","contributorId":169188,"corporation":false,"usgs":false,"family":"Larsen","given":"Stefano","email":"","affiliations":[{"id":13099,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":628833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marti Roca, Maria Eugenia","contributorId":169189,"corporation":false,"usgs":false,"family":"Marti Roca","given":"Maria","email":"","middleInitial":"Eugenia","affiliations":[{"id":25434,"text":"Centre d'Estudis Avancats de Blanes","active":true,"usgs":false}],"preferred":false,"id":628834,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170861,"text":"70170861 - 2016 - Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters","interactions":[],"lastModifiedDate":"2016-07-07T10:09:23","indexId":"70170861","displayToPublicDate":"2016-05-05T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters","docAbstract":"<div data-canvas-width=\"572.1859499999999\">\n<p>We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish <i>Pterois volitans </i>(Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities &lt;30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.</p>\n</div>","language":"English","publisher":"REABIC","doi":"10.3391/ai.2016.11.3.09","usgsCitation":"Evangelista, P.H., Young, N.E., Schofield, P., and Jarnevich, C.S., 2016, Modeling suitable habitat of invasive red lionfish <i>Pterois volitans</i> (Linnaeus, 1758) in North and South America’s coastal waters: Aquatic Invasions, v. 11, no. 3, p. 313-326, https://doi.org/10.3391/ai.2016.11.3.09.","productDescription":"14 p.","startPage":"313","endPage":"326","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064408","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471019,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2016.11.3.09","text":"Publisher Index 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,{"id":70170867,"text":"70170867 - 2016 - Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas","interactions":[],"lastModifiedDate":"2016-06-24T11:26:38","indexId":"70170867","displayToPublicDate":"2016-05-05T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas","docAbstract":"<p><span>Likelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1-year period of earthquake data and use of 10&ndash;20-km smoothing distances produced the greatest likelihood. The likelihood that the locations of January&ndash;June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple-fold benefit from smoothed seismicity models in developing short-term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.</span></p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016GL068948","usgsCitation":"Moschetti, M.P., Hoover, S.M., and Mueller, C., 2016, Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas: Geophysical Research Letters, v. 43, no. 10, p. 4913-4921, https://doi.org/10.1002/2016GL068948.","productDescription":"9 p.","startPage":"4913","endPage":"4921","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075465","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068948","text":"Publisher Index Page"},{"id":321014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.537109375,\n              33.58716733904656\n            ],\n            [\n              -97.679443359375,\n              33.61461929233378\n            ],\n            [\n              -99.38232421875,\n              36.53612263184686\n            ],\n            [\n              -99.51416015625,\n              37.00255267215955\n            ],\n            [\n              -98.41552734375,\n              37.413800350662875\n            ],\n            [\n              -97.3828125,\n              37.54457732085582\n            ],\n            [\n              -95.592041015625,\n              35.16482750605027\n            ],\n            [\n              -95.537109375,\n              33.58716733904656\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"43","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"572dc04ee4b0dae0d5d8f207","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":628864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":628865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70169399,"text":"ofr20161054 - 2016 - Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","interactions":[],"lastModifiedDate":"2016-05-04T15:49:10","indexId":"ofr20161054","displayToPublicDate":"2016-05-04T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1054","title":"Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","docAbstract":"<p>The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of &minus;40 to 60 degrees Celsius (&deg;C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer&rsquo;s specifications with bench tests, for recording data over the device&rsquo;s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.</p>\n<p>The procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer&rsquo;s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer&rsquo;s specifications. It was also observed that enabling WiFi doubles the Storm 3&rsquo;s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p.,  https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"<p>Chief, Hydrologic Instrumentation Facility<br /> U.S. Geological Survey<br /> Building 2101<br /> Stennis Space Center, MS 39529<br /> <a href=\"http://water.usgs.gov/hif/\">http://water.usgs.gov/hif/</a></p>","tableOfContents":"<ul>\n<li>Abstract&nbsp;</li>\n<li>Introduction</li>\n<li>Description of the Storm 3 Data Logger&nbsp;</li>\n<li>Methods</li>\n<li>Results</li>\n<li>Summary</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f1","contributors":{"authors":[{"text":"Kunkle, Gerald A. gkunkle@usgs.gov","contributorId":167907,"corporation":false,"usgs":true,"family":"Kunkle","given":"Gerald A.","email":"gkunkle@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":624025,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70170844,"text":"70170844 - 2016 - Hydrothermal vents and methane seeps: Rethinking the sphere of influence","interactions":[],"lastModifiedDate":"2016-05-19T10:47:06","indexId":"70170844","displayToPublicDate":"2016-05-04T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal vents and methane seeps: Rethinking the sphere of influence","docAbstract":"<p><span>Although initially viewed as oases within a barren deep ocean, hydrothermal vent and methane seep communities are now recognized to interact with surrounding ecosystems on the sea floor and in the water column, and to affect global geochemical cycles. The importance of understanding these interactions is growing as the potential rises for disturbance from oil and gas extraction, seabed mining and bottom trawling. Here we synthesize current knowledge of the nature, extent and time and space scales of vent and seep interactions with background systems. We document an expanded footprint beyond the site of local venting or seepage with respect to elemental cycling and energy flux, habitat use, trophic interactions, and connectivity. Heat and energy are released, global biogeochemical and elemental cycles are modified, and particulates are transported widely in plumes. Hard and biotic substrates produced at vents and seeps are used by &ldquo;benthic background&rdquo; fauna for attachment substrata, shelter, and access to food via grazing or through position in the current, while particulates and fluid fluxes modify planktonic microbial communities. Chemosynthetic production provides nutrition to a host of benthic and planktonic heterotrophic background species through multiple horizontal and vertical transfer pathways assisted by flow, gamete release, animal movements, and succession, but these pathways remain poorly known. Shared species, genera and families indicate that ecological and evolutionary connectivity exists among vents, seeps, organic falls and background communities in the deep sea; the genetic linkages with inactive vents and seeps and background assemblages however, are practically unstudied. The waning of venting or seepage activity generates major transitions in space and time that create links to surrounding ecosystems, often with identifiable ecotones or successional stages. The nature of all these interactions is dependent on water depth, as well as regional oceanography and biodiversity. Many ecosystem services are associated with the interactions and transitions between chemosynthetic and background ecosystems, for example carbon cycling and sequestration, fisheries production, and a host of non-market and cultural services. The quantification of the sphere of influence of vents and seeps could be beneficial to better management of deep-sea environments in the face of growing industrialization.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2016.00072","usgsCitation":"Levin, L.A., Baco, A., Bowden, D., Colaco, A., Cordes, E.E., Cunha, M., Demopoulos, A.W., Gobin, J., Grupe, B., Le, J., Metaxas, A., Netburn, A., Rouse, G., Thurber, A., Tunnicliffe, V., Van Dover, C., Vanreusel, A., and Watling, L., 2016, Hydrothermal vents and methane seeps: Rethinking the sphere of influence: Frontiers in Marine Science, v. 3, art72: 23 p., https://doi.org/10.3389/fmars.2016.00072.","productDescription":"art72: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00072","text":"Publisher Index Page"},{"id":320952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f4","contributors":{"authors":[{"text":"Levin, Lisa A.","contributorId":12372,"corporation":false,"usgs":true,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baco, Amy","contributorId":120023,"corporation":false,"usgs":true,"family":"Baco","given":"Amy","email":"","affiliations":[],"preferred":false,"id":628685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, David","contributorId":10864,"corporation":false,"usgs":true,"family":"Bowden","given":"David","email":"","affiliations":[],"preferred":false,"id":628686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colaco, Ana","contributorId":169152,"corporation":false,"usgs":false,"family":"Colaco","given":"Ana","email":"","affiliations":[{"id":25423,"text":"Univ. of the Azores","active":true,"usgs":false}],"preferred":false,"id":628687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":628688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunha, Marina","contributorId":169153,"corporation":false,"usgs":false,"family":"Cunha","given":"Marina","email":"","affiliations":[{"id":25424,"text":"Univ. de Aveiro","active":true,"usgs":false}],"preferred":false,"id":628689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gobin, Judith","contributorId":169154,"corporation":false,"usgs":false,"family":"Gobin","given":"Judith","email":"","affiliations":[{"id":25425,"text":"Univ. West Indies","active":true,"usgs":false}],"preferred":false,"id":628690,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grupe, Ben","contributorId":169155,"corporation":false,"usgs":false,"family":"Grupe","given":"Ben","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628691,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Le, Jennifer","contributorId":169163,"corporation":false,"usgs":false,"family":"Le","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":628692,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metaxas, Anna","contributorId":169156,"corporation":false,"usgs":false,"family":"Metaxas","given":"Anna","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":628693,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Netburn, Amanda","contributorId":169157,"corporation":false,"usgs":false,"family":"Netburn","given":"Amanda","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628694,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rouse, Greg","contributorId":169158,"corporation":false,"usgs":false,"family":"Rouse","given":"Greg","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628695,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":628696,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tunnicliffe, Verena","contributorId":169160,"corporation":false,"usgs":false,"family":"Tunnicliffe","given":"Verena","email":"","affiliations":[{"id":25427,"text":"Univ. of Victoria","active":true,"usgs":false}],"preferred":false,"id":628697,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Dover, Cindy L.","contributorId":95341,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy L.","affiliations":[],"preferred":false,"id":628698,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vanreusel, Ann","contributorId":169161,"corporation":false,"usgs":false,"family":"Vanreusel","given":"Ann","email":"","affiliations":[{"id":25428,"text":"Ghent Univ.","active":true,"usgs":false}],"preferred":false,"id":628699,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":628714,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70170821,"text":"70170821 - 2016 - Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","interactions":[],"lastModifiedDate":"2016-07-28T10:53:13","indexId":"70170821","displayToPublicDate":"2016-05-04T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","docAbstract":"<p><span>Dune destabilization and increased mobility is a worldwide issue causing ecological, economic, and health problems for the inhabitants of areas with extensive dune fields. Dunes cover nearly a third of the Navajo Nation within the Colorado Plateau of southwestern USA. There, higher temperatures and prolonged drought beginning in 1996 have produced significant increases in dune mobility. Vegetation plays an important role in dune stabilization, but there are few studies of the plants of the aeolian surfaces of this region. We examined plant species and their attributes within a moderately vegetated dune field of the Navajo Nation to understand the types and characteristics of plants that stabilize rangeland dunes. These dunes supported a low cover of mixed grass-scrubland with fifty-two perennial and annual species including extensive occurrence of non-native annual&nbsp;</span><i>Salsola</i><span>&nbsp;spp. Perennial grass richness and shrub cover were positively associated with increased soil sand composition. Taprooted shrubs were more common on sandier substrates. Most dominant grasses had C4 photosynthesis, suggestive of higher water-use efficiencies and growth advantage in warm arid environments. Plant cover was commonly below the threshold of dune stabilization. Increasing sand movement with continued aridity will select for plants adapted to burial, deflation, and abrasion. The study indicates plants tolerant of increased sand mobility and burial but more investigation is needed to identify the plants adapted to establish and regenerate under these conditions. In addition, the role of&nbsp;</span><i>Salsola</i><span>&nbsp;spp. in promoting decline of perennial grasses and shrubs needs clarification.</span></p>","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1138157","usgsCitation":"Thomas, K.A., and Redsteer, M.H., 2016, Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA: Arid Land Research and Management, v. 30, no. 4, p. 400-411, https://doi.org/10.1080/15324982.2016.1138157.","productDescription":"12 p.","startPage":"400","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063167","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502595,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":320950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Navajo Nation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.3134765625,\n              34.56085936708387\n            ],\n            [\n              -111.3134765625,\n              38.22091976683121\n            ],\n            [\n              -107.29248046875,\n              38.22091976683121\n            ],\n            [\n              -107.29248046875,\n              34.56085936708387\n            ],\n            [\n              -111.3134765625,\n              34.56085936708387\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"572b0f1ce4b0b13d391a8407","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redsteer, Margaret H.","contributorId":9123,"corporation":false,"usgs":true,"family":"Redsteer","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":628555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70170814,"text":"70170814 - 2016 - Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","interactions":[],"lastModifiedDate":"2016-05-04T10:03:24","indexId":"70170814","displayToPublicDate":"2016-05-04T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","docAbstract":"<p><span>Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel&rsquo;s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w8050184","usgsCitation":"Snedden, G., 2016, Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain: Water, v. 8, no. 5, Article 184: 15 p., https://doi.org/10.3390/w8050184.","productDescription":"Article 184: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8050184","text":"Publisher Index Page"},{"id":320948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Houma Navigation Canal","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.74844360351562,\n              29.216904948184734\n            ],\n            [\n              -90.74844360351562,\n              29.58898286696141\n            ],\n            [\n              -90.604248046875,\n              29.58898286696141\n            ],\n            [\n              -90.604248046875,\n              29.216904948184734\n            ],\n            [\n              -90.74844360351562,\n              29.216904948184734\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572b0f19e4b0b13d391a83ec","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@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":628526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70174006,"text":"70174006 - 2016 - Spatially explicit control of invasive species using a reaction-diffusion model","interactions":[],"lastModifiedDate":"2016-09-02T09:35:37","indexId":"70174006","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit control of invasive species using a reaction-diffusion model","docAbstract":"<p>Invasive species, which can be responsible for severe economic and environmental damages, must often be managed over a wide area with limited resources, and the optimal allocation of effort in space and time can be challenging. If the spatial range of the invasive species is large, control actions might be applied only on some parcels of land, for example because of property type, accessibility, or limited human resources. Selecting the locations for control is critical and can significantly impact management efficiency. To help make decisions concerning the spatial allocation of control actions, we propose a simulation based approach, where the spatial distribution of the invader is approximated by a reaction&ndash;diffusion model. We extend the classic Fisher equation to incorporate the effect of control both in the diffusion and local growth of the invader. The modified reaction&ndash;diffusion model that we propose accounts for the effect of control, not only on the controlled locations, but on neighboring locations, which are based on the theoretical speed of the invasion front. Based on simulated examples, we show the superiority of our model compared to the state-of-the-art approach. We illustrate the use of this model for the management of Burmese pythons in the Everglades (Florida, USA). Thanks to the generality of the modified reaction&ndash;diffusion model, this framework is potentially suitable for a wide class of management problems and provides a tool for managers to predict the effects of different management strategies.</p>","language":"English","publisher":"Elsevier : ScienceDirect","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2016.05.013","usgsCitation":"Bonneau, M., Johnson, F.A., and Romagosa, C., 2016, Spatially explicit control of invasive species using a reaction-diffusion model: Ecological Modelling, v. 337, p. 15-24, https://doi.org/10.1016/j.ecolmodel.2016.05.013.","productDescription":"10 p.","startPage":"15","endPage":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061162","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"337","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6bce4b07657d1a22959","contributors":{"authors":[{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":640258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":640257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":640259,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70170139,"text":"sir20165046 - 2016 - Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","interactions":[],"lastModifiedDate":"2021-10-12T17:00:16.258141","indexId":"sir20165046","displayToPublicDate":"2016-05-04T10:00:00","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":"2016-5046","title":"Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","docAbstract":"<p>The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model <i>air2water</i> was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.</p><p>The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.</p><p>The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165046","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wood, T.M., Wherry, S.A., Piccolroaz, S., and Girdner, S.F., 2016, Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099: U.S. Geological Survey Scientific Investigations Report 2016–5046, 43 p. https://doi.org/10.3133/sir20165046","productDescription":"vii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066051","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":320860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-5046 Report PDF"},{"id":320859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5046/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.18616485595703,\n              42.892567248047285\n            ],\n            [\n              -122.18616485595703,\n              42.986065036562955\n            ],\n            [\n              -122.03922271728514,\n              42.986065036562955\n            ],\n            [\n              -122.03922271728514,\n              42.892567248047285\n            ],\n            [\n              -122.18616485595703,\n              42.892567248047285\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: February 2020; Version 1.0: October 2016","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, Oregon Water Science Center<br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201<br><a href=\"http://or.water.usgs.gov\" data-mce-href=\"http://or.water.usgs.gov\">http://or.water.usgs.gov</a><br></p>","tableOfContents":"<ul>\n<li>Abstract</li>\n<li>Introduction</li>\n<li>Methods</li>\n<li>One-Dimensional Lake Temperature Modeling</li>\n<li>Results of Future Climate Scenarios</li>\n<li>Comparisons to Future-Climate Studies of Other Lakes</li>\n<li>Conclusions</li>\n<li>Summary</li>\n<li>Acknowledgments</li>\n<li>References Cited</li>\n</ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1be4b0b13d391a8403","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":626264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piccolroaz, Sebastiano","contributorId":168525,"corporation":false,"usgs":false,"family":"Piccolroaz","given":"Sebastiano","email":"","affiliations":[{"id":25322,"text":"University of Trento","active":true,"usgs":false}],"preferred":false,"id":626265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Girdner, Scott F","contributorId":168526,"corporation":false,"usgs":false,"family":"Girdner","given":"Scott","email":"","middleInitial":"F","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":626266,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70173933,"text":"70173933 - 2016 - Long-term trends in a Dimictic Lake","interactions":[],"lastModifiedDate":"2016-06-22T13:17:08","indexId":"70173933","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Long-term trends in a Dimictic Lake","docAbstract":"<p><span class=\"pb_abstract\">&nbsp;The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911&ndash;2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 &deg;C per decade before 1981 to 0.334 &deg;C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s<sup><span>&minus;1</span></sup>&nbsp;before 1994 to 3.74 m s<sup><span>&minus;1</span></sup>&nbsp;thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3&nbsp;days per century), decreasing ice cover duration (21.3&nbsp;days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3&nbsp;days per century), later fall turnover (14.6&nbsp;days per century), longer stratification duration (26.8&nbsp;days per century), and decreasing summer hypolimnetic temperatures (&minus;1.4 &deg;C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911&ndash;1980, 1981&ndash;1993, and 1994&ndash;2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Ni&ntilde;o winter of 1997&ndash;1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994&ndash;2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.</span></p>","language":"English","publisher":"Copernicus Publications","publisherLocation":"Göttingen, Germany","doi":"10.5194/hess-20-1681-2016","usgsCitation":"Robertson, D.M., Hsieh, Y., Lathrop, R.C., Wu, C.H., Magee, M., and Hamilton, D., 2016, Long-term trends in a Dimictic Lake: Hydrology and Earth System Sciences, v. 20, p. 1681-1702, https://doi.org/10.5194/hess-20-1681-2016.","productDescription":"22 p.","startPage":"1681","endPage":"1702","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065196","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":471027,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-20-1681-2016","text":"Publisher Index Page"},{"id":324224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane","otherGeospatial":"Lake Mendota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.42682266235352,\n              43.13944974967447\n            ],\n            [\n              -89.42424774169922,\n              43.14295692553958\n            ],\n            [\n              -89.41017150878906,\n              43.14195489582142\n            ],\n            [\n              -89.40845489501953,\n              43.139575009419644\n            ],\n            [\n              -89.40879821777344,\n              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,{"id":70178255,"text":"70178255 - 2016 - Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","interactions":[],"lastModifiedDate":"2016-11-09T15:29:43","indexId":"70178255","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2035,"text":"International Journal of Digital Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data","docAbstract":"<p>The goal of this study was to map rainfed and irrigated <i>rice-fallow</i> cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. <i>Rice-fallow</i> cropland areas are those areas where rice is grown during the <i>kharif</i> growing season (June–October), followed by a fallow during the <i>rabi</i> season (November–February). These cropland areas are not suitable for growing <i>rabi</i>-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (<i>Cicer arietinum</i> L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated <i>rice-fallow</i> croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (<i>kharif</i>) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left <i>fallow</i> during the second (<i>rabi</i>) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during <i>rabi</i> season. Existing irrigated or rainfed crops such as rice or wheat that were grown during <i>kharif</i> were not considered suitable for growing during the <i>rabi</i> season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable <i>rice-fallow</i> areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.</p>","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              83.97949218750001,\n              15.284185114076433\n            ],\n            [\n              82.3095703125,\n              11.996338401936226\n            ],\n            [\n              83.32031250000001,\n              7.754537346539373\n            ],\n            [\n              81.78222656250001,\n              5.266007882805485\n            ],\n            [\n              79.365234375,\n              5.747174076651375\n            ],\n            [\n              76.81640625,\n              7.406047717076271\n            ],\n            [\n              72.59765625,\n              12.382928338487396\n            ],\n            [\n              66.4013671875,\n              25.64152637306577\n            ],\n            [\n              80.4638671875,\n              29.11377539511439\n            ],\n            [\n              95.61523437500003,\n              30.34192736497245\n            ],\n            [\n              91.62597656250001,\n              20.67390526467282\n            ],\n            [\n              83.97949218750001,\n              15.284185114076433\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
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